diff --git a/.github/workflows/build.yaml b/.github/workflows/build.yaml index 7439167..ddfbe96 100644 --- a/.github/workflows/build.yaml +++ b/.github/workflows/build.yaml @@ -15,10 +15,10 @@ jobs: runs-on: ubuntu-latest steps: - uses: actions/checkout@v4 - - name: Set up Python 3.10 + - name: Set up Python 3.11 uses: actions/setup-python@v5 with: - python-version: "3.10" + python-version: "3.11" cache: "pip" cache-dependency-path: "**/pyproject.toml" - name: Install build dependencies diff --git a/.github/workflows/test.yaml b/.github/workflows/test.yaml index 9ad5ae0..9718505 100644 --- a/.github/workflows/test.yaml +++ b/.github/workflows/test.yaml @@ -23,22 +23,18 @@ jobs: fail-fast: false matrix: include: - - os: ubuntu-latest - python: "3.10" - os: ubuntu-latest python: "3.11" - os: ubuntu-latest python: "3.12" - os: ubuntu-latest - python: "3.12" + python: "3.13" + - os: ubuntu-latest + python: "3.14" + - os: ubuntu-latest + python: "3.14" pip-flags: "--pre" name: PRE-RELEASE DEPENDENCIES - # - os: ubuntu-latest - # python: "3.13" - # - os: ubuntu-latest - # python: "3.13" - # pip-flags: "--pre" - # name: PRE-RELEASE DEPENDENCIES name: ${{ matrix.name }} Python ${{ matrix.python }} diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml index 2afc675..30ad940 100644 --- a/.pre-commit-config.yaml +++ b/.pre-commit-config.yaml @@ -11,11 +11,11 @@ repos: hooks: - id: prettier - repo: https://github.com/tox-dev/pyproject-fmt - rev: "2.2.3" + rev: "v2.16.1" hooks: - id: pyproject-fmt - repo: https://github.com/astral-sh/ruff-pre-commit - rev: v0.6.5 + rev: v0.15.0 hooks: - id: ruff types_or: [python, pyi, jupyter] @@ -23,7 +23,7 @@ repos: - id: ruff-format types_or: [python, pyi, jupyter] - repo: https://github.com/pre-commit/pre-commit-hooks - rev: v4.6.0 + rev: v6.0.0 hooks: - id: detect-private-key - id: check-ast diff --git a/.python-version b/.python-version index e4fba21..bcd75f8 100644 --- a/.python-version +++ b/.python-version @@ -1 +1 @@ -3.12 +Python 3.11.13 diff --git a/.vscode/settings.json b/.vscode/settings.json index bfcaaf2..9ce2a31 100644 --- a/.vscode/settings.json +++ b/.vscode/settings.json @@ -28,7 +28,12 @@ "notebook.cellFocusIndicator": "gutter", "notebook.lineNumbers": "on", "files.watcherExclude": { - "**/.venv/**": true + "**/.venv/**": true, + "**/__pycache__/**": true, + "**/.pytest_cache/**": true, + "**/.ruffle_cache/**": true, + "**/data/**": true, + "**/dist/**": true }, "githubPullRequests.ignoredPullRequestBranches": ["main"] } diff --git a/docs/source/example.ipynb b/docs/source/example.ipynb index 3e84497..a9e81bf 100644 --- a/docs/source/example.ipynb +++ b/docs/source/example.ipynb @@ -83,7 +83,7 @@ "outputs": [ { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -118,7 +118,7 @@ "outputs": [ { "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAABDYAAAS0CAYAAACbq4ifAAAAOnRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjEwLjMsIGh0dHBzOi8vbWF0cGxvdGxpYi5vcmcvZiW1igAAAAlwSFlzAAAPYQAAD2EBqD+naQABAABJREFUeJzs3XeYE+XaBvB7UrcXtgFLRzrSm1RBBBFBj7A06UWlyMEDiH7AAfGIC4gKIigKgoBKtXBEPSio2FDpvSlLZ4HtNe39/hg2bjbJbrLpcP+uKxdk5p13nskk2cwzb5GEEAJERERERERERAFI4esAiIiIiIiIiIjKi4kNIiIiIiIiIgpYTGwQERERERERUcBiYoOIiIiIiIiIAhYTG0REREREREQUsJjYICIiIiIiIqKAxcQGEREREREREQUsJjaIiIiIiIiIKGAxsUFEREREREREAYuJDSIiKpcLFy7gxRdfRLdu3VC5cmUEBQUhKCgIVapUQc+ePbFgwQJcuHDBYpv7778fkiSZH+fPn/dN8FRuZ8+exYgRI1C9enVotVrzuYyKinJo+7lz51q8B4o/lEoloqOj0aZNG7zwwgu4ePGi1fbfffed3e01Gg1iYmLQqlUr/POf/8TRo0dtxmCvjq1bt9qN+5FHHrEqX6NGjVKP9fjx45gxYwY6dOiAihUrQqvVIiQkBDVr1kTfvn3x5ptv4saNG6VuP3nyZDRu3BhRUVHQarVITExE27Zt8eyzz+LQoUM2t/v5558xZswYNGzYEOHh4VCpVAgLC0ODBg0wcuRI7Nmzx+Z2NWrUsDi+QHY3fNesWbPG4hjnzp3r1PbOvJd9JTs7G2+99Rb+8Y9/oGbNmggPD4darUZcXBzat2+PGTNm4I8//rDYpuTrUvTdEhwcjPj4eDRu3BiPPfYYXn31VVy/fr3MGFJSUjBjxgy0bt0aFSpUgFqtRnBwMKpXr45HH30UH374IYxGY5n1TJkyxSquVq1alfu1IaISBBERkRMKCgrE5MmThUqlEgBKfURHR1ts26VLF4v1f/31l28OopgRI0ZYxLR7925fh+S3rl+/LmJiYmye68jISIfqmDNnTpnvm6JHWFiY2LJli8X2u3fvdnh7hUIhVq9ebRWDvTo6d+5sM+bTp08LSZKsylevXt1m+YyMDDF48GCb25R8NG/e3Gp7k8kknn/+eaFQKErd9qWXXrLadu7cuQ69Ni+88ILVttWrV7coE8j88bvG3d5//32LY5wzZ45T2zvyXvald999V0RGRjr0fj506JB5u5KvS2kPjUYjpk6dKnQ6nc0YduzYIYKDg8usp2vXrqKgoMDuseh0OhEbG2tz2yNHjrj9tSO6G6lARETkoIKCAjz44IP48ccfLZaHh4ejVatWCAsLQ2pqKg4dOoSCggKYTCYfRUqesG3bNty6dcv8PDo6Gh07doRGo0FoaGi56qxevbr5rmVqair27t0LnU4HAMjJycHgwYNx+PBh1K9f3+b2ISEh6NWrFwAgLy8PP//8MzIzMwEAJpMJEyZMwGOPPYbo6OgyY/nhhx9w6NAhNG3a1GL5m2++CSGEQ8dz69YtdOjQAadOnbJYHhMTgxYtWkCr1eLKlSs4fPgwDAaDzc/IlClTsHTpUotlderUQe3atZGbm4s///wTly9fttru4MGDVnfta9asiYYNG+LEiRP4888/zctfeeUVPProo2jbtq1Dx0XkTdOmTcPixYstlqlUKrRs2RIJCQnIysrCoUOHkJ6eDgCl/q2JjY1Fly5doNfrce3aNRw8eND8HaPT6bB48WL8/vvv+PrrrxEUFGTeTq/XY8SIEcjPzzcvi46ORrt27XDjxg2LliK7d+/GG2+8gRkzZtiM4b///S9u3rxpc92aNWvw6quvlvGKEFGZfJ1ZISKiwDFmzBiLO02SJIk5c+aI/Px8i3J5eXli1apV4t5777VY7o93Udliw3ElWwO8/fbbTtdRssXGiBEjLNYfPHjQ6g7p+PHjzetLtrYoeaf50qVLIjw83KLM9u3bLcqU1upj9OjRFmUzMzOt6rO3byGEeOCBB6zuCL/11lvCYDBYlEtPTxevvfaa6Natm8XynTt3Wu3j+++/t9rPgQMHxO+//26xbPHixVYtUIr2azQarT5/ixYtstieLTYCy53aYmPdunVWn7V//OMf4sqVKxblTCaT+Oqrr0T79u3FgQMHzMtLvi5dunSx2C49PV0899xzVi2qxowZY1Fu3759Fuujo6PF9evXzetnz55tsb537952j6lv374WZdVqtfn/FStWFHq9vvwvGBEJIYTgGBtEROSQo0eP4v3337dY9uKLL2Lu3LkWd7kAIDg4GKNHj8bvv//ucP0lxz0YOXKkVZmyxgDYu3cvRowYgXr16iE0NNTcF7thw4YYMGAAFi1ahGvXrgEARo4cCUmSsHbtWos6unbtarGP7777DoDt/ux//fUXRo4cicTERKhUKquYr169ijlz5qBdu3bmvtmxsbHo3r07Vq1aBb1eb/f1yMjIwKJFi9ClSxfExsZCrVajQoUK6NixI15//XXk5uY6/NqWdPHiRfzf//0fWrdujejoaKjVasTExKBDhw54+eWXre4sFo2LUbI1wNNPP13q+SqPpk2bIikpyWLZb7/95vD2iYmJqFevnsWy4ndcbalcubL5/x9++KHF8a9evRrZ2dnmukuzY8cOfPvttxbL3nvvPUyYMAFKpdJieVRUFJ599lns2LHDYnlycrLF8w0bNqBz585W+2rWrJlV/3yNRmPxvHXr1ub9KhQKtGzZ0mJ9ZGRkqcdT3Llz51CtWjWLz8DChQsd3h4A0tLSsGjRInTr1g0JCQnQaDSIiopCgwYNMHr0aJvnOScnB2+++Sa6d+9u3iYyMhJNmjTB5MmTceLECadicEfdtsbv2Lp1K+6//35ERUVZfG8U2bNnD0aMGIE6deogLCwMQUFBqFmzJkaMGFHq92ReXh7mzp2LunXrQqvVomLFihg+fLhF6xt3EULgvffeQ+vWrREWFoaoqCj07NkT33//vUW5+fPnWxz/u+++a1WXXq9HbGysuUzlypVhMBjKjEGn0+GFF16wWNa9e3ds2bIFlSpVslguSRJ69uyJH3/8EQ0bNnT4OKOiorBgwQK8+OKLFsvff/99HD9+3Py85OepVq1aiI+PNz9v3bq1xXp7n6fU1FSLz3m9evUwePBg8/Nr167hq6++cjh+IrLD15kVIiIKDLNmzbK44xQXF1dqn2JbSruLWvIuesk7+UKUfkd548aNZY5JgGJ370u21LD3KGrBUfIuYN++fUVERITdmLdt22a1vuSjTZs24tq1a1bHuWfPHlGxYsVSt61Tp444deqUU6+/EEJs2LBBhIaGllp3bGys+Oabb8zbODIuhq3zZUtZLTaEEGL69OkWZerWrWte52yLDYVCIc6ePWtRpmQdXbp0Ed27dzc/f/nll4UQciuHWrVqWSwvbd9Dhw61WN+kSROHXpMiWVlZQqlUWpzjlJQUsWDBAjF8+HAxbNgwMWfOHPHHH3/Y3P7kyZMW2ycmJoq9e/eK/Px88dtvv4nExETzuoiICHH16lWL7e19vk6dOmWxrVKpFO+9955Tx7Zjxw67YwwUPUq2ODh48KCoUaNGqduoVCrx6quvWu2vrBYb7qx72LBhdr839Hq9GDVqVKn7kSRJzJ4922o/mZmZolWrVja3CQ8PF0899VSpr19Zim9bpUoVMXjwYLvxFT/faWlpFt8hTZs2tar7s88+s6hj1qxZDsX0zTffWO1///79Th1XWS02ihQUFIj4+Hi7cep0OlGzZk2L9/2HH34ocnNzxfnz561aZ33xxRc291OyJdXcuXPFl19+abGsX79+Th0jEVljYoOIiBzStWtXix9igwYNcroOTyY26tata3Ex27ZtW9G3b1/RoUMHUaNGDXOz46LExrJly0S/fv2s6uzcubPo16+f+XH06FEhhP0B6apUqSJ69eol2rRpY+7G8NNPP1k0NZYkSbRq1Uo88sgjonbt2hbb33fffcJkMpmP4+zZs1YJkcaNG4tHHnlENGrUyGJ5rVq1RG5ursOv/+7duy0ufAGImjVrip49e4rKlStbLA8NDRUnT54UQshJo379+okGDRpYlGnVqpX5dVq2bJlDMTiS2Ch5wVD8wqTk+yQkJMQcQ69evawGG3zuuedsvg4l69++fbvFOdXr9eLTTz81L6tUqZI4ffq0xXYlExvFL4IAiOeff97hcyOEEN9//73F9nFxcUKj0dh83z3xxBNWXcCEkAdcLP7es/W45557xM8//2y1ra3P14kTJ0SlSpXMy7Rardi2bZtTx7V3716h1Wot6g4KChJt2rQRffr0Mb+vi1+Y37hxQyQkJFhsExMTIx588EHRsGFDq2Nav369xT5L+65xd91FF73NmzcXDz/8sKhevbo5sTFhwgSLcuHh4aJ79+6iR48eIiwszGLdihUrLPYzduxYi/WSJInWrVuLzp07i6CgIKsYXElsFD2qVasmevbsaXHOAblL1bFjx8zb/vOf/7RYv2fPHou6k5KSLL6PU1JSHIrpxRdftKi3YsWKTh2TEI4nNoQQVsmcrl27Wqz/9ddfy0wyR0VFiZUrV9rdR5MmTSzKnzp1Suj1ehEXF2fx+t66dcvpYyWivzGxQUREDin5g9/ZizYhPJvYKH4xN2/ePKttr127Jj744ANx4sQJi+WOjrFhK7ExY8YMYTQazWWKWrB07NjRXEalUokffvjBXMZkMlndaS0+80fJu/4fffSRRRzz58+3WG/rjrI97dq1s9h2/Pjx5vjz8/NF7969LdaXTF6VTEq8//77Du/bXh3Fz3NqaqqYN2+e1eucnJxsLuPMrCh9+vQR2dnZVjHYSmwYjUZxzz33mJdt3LjRIpn30ksvib/++stiu5KJjZCQEIv1zo5BsnnzZoePDYAYMmSIzXp++OEHqwv3okelSpXExx9/bPG+LVLy83X06FGLesLCwsS3337r1DEJIUTnzp0t6m3fvr24cOGCRZkTJ05Y1P38889bbNO2bVuRnp5uXv/SSy9ZrE9MTLQ4ptK+a9xdd1RUlPjxxx/N600mkygsLBSnTp2yaEXWpk0bkZmZaS53/fp1UbVqVfP6mJgYUVhYKIQQ4urVq1YzTxX/njhw4IDVWDSuJjYGDx5sHushNzdXdOvWzWL9qFGjzNueP3/eIr6BAwea12VmZlokXh555BGHYyqZCGrXrp1TxySEc4mNGTNmWJRt2LChVZlLly6Jtm3b2vw8aTQakZycbHFeiys5TkfLli3tHuubb77p9LES0d84xgYREZWLcHCWCG+pXr26+f8bNmzAkiVL8NVXX+Hs2bMwGo1ISEjAsGHD7M6u4ay6devi5ZdfhkLx959SrVaLGzdu4KeffjIvCwsLw5IlS9C/f3/0798fSUlJOHr0qEVd27dvByCP7P/555+bl2s0GmzZssW8bf/+/a367hdtW5aiGUeK1/3KK6+Y4w8KCrIaM2HHjh0en9lm7dq15n748fHx+Pe//22x/p577sHEiRPLVff27dvRsmVLmzOIlKRQKPDMM8+Yn7/wwgvYvXs3APm8PvXUU07v39nPSNFMDcU1btwYhw4dQlZWFtatW2cxVseHH36IgwcPWuxv1qxZ6NKlC65fvw5AHhfg4YcfRu3atQHI474MGjQIjz32mM39Fde1a1dzPbGxsdi1axe6devm1DHdvHkTe/bsMT+XJAnr169H1apVLcrVr1/fou7inwNAHuclKirK/Pz555+3GBvl8uXL2L9/v0MxubvuqVOnokOHDubnkiRBo9Hg888/t/j86HQ6jB492vxZnjBhgsV75NatW/j5558ByGMOFR+Tol27dujXr5/5ebNmzfDEE084dLyOWrhwIVQqecLEkJAQzJs3z2L9zp07zf+vXr26xVg427Ztw9WrVwEAW7duRUFBgXnd008/Xe6YPP13puT3W8mxmz755BM0aNDA/N0ZExODnj17msfX0Ol0eP7559G6dWucP3/eqv41a9ZYPC8+tkbx/9sqS0TOYWKDiIgckpCQYPHc1o84X5o3b575R+mpU6cwZcoU9OrVC3Xq1EF4eDgeeOABrFu3zm0/lDt16mQ1ICQgvy7F95GRkYGtW7daPIonPgDgr7/+AiBf2GRlZZmX63Q6q23/97//2dy2LCkpKRZxVatWzWqwuwYNGlgMmJeVlWUxvau3de3aFbt27UJYWJjdMtWrV4eQW6BCp9PhyJEjFhfIp0+fxrPPPuvQ/kaNGoWIiAgAsBiccciQIYiLiytze1c/I0X7Lu7ll19GkyZNEB4ejqFDh6JPnz4W64sPVvrBBx/g5ZdfNp/nkSNH4vTp0/jiiy9w+vRpjB492lx2+/btVlPKlnTjxg3z/1etWmU1WKIj/vrrL6v3Xc2aNcvcruRrd++991o8V6lUVgNGOvpZcHfd999/v83lJbc5ePCg1ef50qVLNrdJSUkpNUZATnq5S3R0NKpUqVJq/ZcvX4bRaDQ/nz59uvn/er0eK1euBACsX7/evLx69erm6ZgdUfIzVPJ1cLeS9Rff/5kzZzBo0CDz4MGNGzfGuXPn8NVXX+G3336zGEz79OnTmDRpkkVdOp0OH374ofm5QqHAwIEDzc87dOiAatWqmZ/v27fPKulNRI5jYoOIiBxS/I4kIF9QFRYWemx/tkbQT01NtVt+8ODB+O233zBu3DjUqVPHoiVFfn4+du3aheHDh2Pq1Kluia/4HV1XuTLDiaPblkzo2JpVxheqV6+Ofv36oV+/fhgwYADGjh2LBQsWYN++fdi1a5fVnf3SqNVqNG7cGKtWrbJY/sknnzg0I0N4eLjN2V0mT57s0P5LfkZKznhSlnvuucdqWckZXko+T0tLM///gw8+sFg3adIki1lRxo8fb7G+ZMuF0kyYMAHnzp1zuLyrPPl+dXfd/vJd4G3NmzfHAw88YH6+cuVKpKSkWLQqGzdunMV3cVlKfoauXbvmcEscZxUUFGDXrl129//xxx9btGoaOXKkRTJ45MiRFknXr7/+2qL89u3brRLD7dq1Q5UqVVClShVUrVrV6m8aW20QlR8TG0RE5JCBAwda/EC9efNmmdM9OpP4KDm1XskfhH/88UeZ03a2atUKK1euxOnTp5Gfn49z585h8+bNFhcey5cvt2gmXd6LGns/1qtXr25RZ/369c0tCuw9/vjjDwByM+fw8HDzthERESgsLCx125JTs9pTo0YNi+cXLlywaB0CACdPnrT4YR4eHo6YmBiH6i+v+++/H1u2bMGWLVuwceNGvPvuu3juuefQokWLctdZvFsBICfJHH2dnnnmGYvz17lzZzRr1syhbUs2LT9y5AjWrVtX6jbFPyP16tWzahlS8nNQPJEBwGL6yZJ3/0u+t0s+Ly1RCMBi2s3Lly+ja9euTk8zWjRFc5ELFy441LKiZKuOI0eOWDw3GAwWU3Pa2sZbddv7Lii5TXJycpnfBUV3/YvfyQdg807+sWPH7MbkrPT0dKsuWyXrT0xMtGqlVrzVxpUrVzBkyBBz9w61Wo0xY8Y4FUenTp2sWo7MmDGj1C5xRa21nJWcnGzxvVCyRUVZn6eSywwGg8Xns2SSwmQy4fLlyxaP4n+LALkbpSNJWCKyxsQGERE5pHHjxlZ3s+fMmYMXX3zR6sdZfn6+003XS971/PHHH80/5q9du4YJEyaUuv3SpUst+qVrNBrUqlULjz/+uHl8AUC+kMzIyDA/Dw4OtqjHkfEYShMfH4927dqZn588eRLJyckWTbgB+Ufw7t27MWbMGHP/bYVCgUceecRcJisrC//617+sEkRCCOzduxdTpkzBJ5984nBcbdq0MT8vLCzE//3f/5kvGAoLC/H8889bbPPwww87dbfVXyxbtsziuVarRYUKFRza9p577kFSUhJiYmIQExPjcDcWQH69So5BMXbsWKxYscLq/GdkZOC1117Dww8/bF4mSZLVZ+ydd94xtzC4fv261fkufse8ZOuWt956y3x+TSYTli9fbrG+Vq1apR7P/PnzLZrXX7x4EV27dnWqi01cXJzFXXAhBIYOHYqLFy9alDt37pzF3fPinwMAePHFF5GZmWl+vmjRIly5csX8vHLlyg4nwzxZd8n9FL/wXbx4sc3WBzdv3sSaNWswZMgQ87L777/fPN4FAPzyyy/49NNPzc8PHz6MDRs2OB1TaWbMmGH+/szPz8ecOXMs1nfv3t1qm549e1p0kykaIwQAHnvsMVSsWNGpGDQaDebPn2+x7JtvvkFSUhKuXbtmsVwIga+//hodOnSwSkSVJiMjA9OnT7caQ2T06NFo1KiR+XnJz9PatWstksFr1641d1MB5ERwUWLy+vXr+OqrrxyOqci1a9fKtR0RAZwVhYiIHJaXl2cx40fRIzw8XHTr1k307dtXtGvXzjwifmRkpMX2pc1UIISwmJUCkKcJrFatmtUUpUWP4po2bSoAiIiICNG2bVvRp08f8cgjj1hNwRkbGysMBoN5uyVLllgdy8MPPyz69etnMQtAyZH2S5uB4Pvvv7ea0aBSpUriwQcfFI888oho3bq1xQwaxWdiOXXqlNU0kBUqVBBdu3YVffv2Fe3bt7eY0tSZmUm+/fZbi1kaAHnK2IceekgkJiZaLA8JCRHHjx+32N7Ts6I4orTpXvv27Svq1atn9T4pObuLrVlRHFHWrChCyFOJ2oohNjZW9OjRQ/Tp00e0aNHC/P5o2rSpxfbp6elW56JBgwaiZ8+eIjo62mJ58ZkohBBizZo1VvutXbu2ePjhh60+W4A880txtmYdMplMYuTIkVbHff78eYdeMyGE+Pnnn62mrQ0KCjJ/Tps2bSokSbL4TF2/ft1iOszir2HJaY8BiLVr11rss7TvGk/WXdK4ceOs6mvatKno06eP6NGjh6hbt675M1ny/TR69Gir78M2bdqILl26eGy61+rVq9uc7lWtVosjR47YrGft2rU26yrPDDpFpk6dalWfSqUS7dq1E48++qi4//77RYUKFczrDhw4YN625Hd1bGys6Nevn3j00UdF27ZtbU6hfP/995tntSpy+vRpq6mTY2NjxUMPPSRat25tVcf48ePN2y5atMhiXb9+/ewe62uvveZwWSKyj4kNIiJySkFBgXjmmWfsJhuKP6Kjoy22LeuCYOvWrUKSJJt19evXT1SuXNnqwqtIUWKjtIdSqRTr1q2z2O7KlSsiIiLCZvmYmBhzOWcSG0IIsWnTJrv1lnzs2bPHYtvvvvtOVKxY0aFtSx5PWT744AOraSJLPipUqCC+/vprq239MbFR1qNp06bi+vXrpdbhzsSGEHJyYtCgQQ7F17x5c6vtjxw5YpXcKPno2bOnyMnJsdjOZDKJJ5980qH9TpkyxWq/9qZTNhgMIikpyWJdzZo1raZsLc327dstLkRtPUp+pvbt2yeqVatW5me6+HTARcr6rvFk3cXpdDoxfPhwh85J7dq1LbbNyMgQLVq0sFk2KChIDB482KnvpJKKb1upUiXx8MMP29yXJEninXfeKfUYq1SpYrFN3bp1nYrFlpUrVzr8HXro0CHzdram5rb30Gg0Yvr06eZpbkt6//33rZIbth6dO3e2mPK1cePGFus3b95s9zgvXrxo8XdPo9GIW7duufz6Ed1tmNggIqJyOX/+vJgzZ47o0qWLqFixotBqtUKj0YjExETx4IMPildeeUWkpKRYbOPIBcGOHTtEx44dRUhIiAgJCRGtW7cWq1atEiaTye6FlxDyxeqsWbNE9+7dRa1atURkZKRQKBQiLCxMNGrUSIwbN87irl5x+/btE3369BGxsbEWLRpcSWwIIcTVq1fFvHnzRMeOHUVMTIxQqVQiKCjIfFf0pZdesnsXNCMjQ7z++uvigQceEPHx8UKtVgutVisSExNF165dxcyZM8Wvv/5aZgy2nD9/XsyYMUO0bNlSREZGCpVKJaKjo0W7du3Eiy++aJUIKBIIiY2goCBRrVo10bt3b/Hee+8JnU5XZh3uTmwUOXbsmHjuuedEu3btzOew6Pw/8sgjYsmSJSI1NdXmtllZWeLll18WrVu3FpGRkUKtVouKFSuKRx55RGzatEmYTCa7+/3uu+/EyJEjRf369UVYWJj5c9CgQQMxatQo8eOPP9rcrrTPl06nE71797a6EL948WLpL1oxN27cEMnJyaJLly4iNjZWqNVqERkZKerVqydGjhwp9u7da/N1eP3110XXrl1FbGysUKlU5s/0xIkTxdGjR23uy5HvGk/WXdKPP/4oRo8eLRo0aCDCwsKEUqkUERERonHjxmLo0KFi9erVIi0tzWq7nJwcMXv2bHHPPfcIjUYj4uPjxYABA8SxY8fK9Z1UXMn3ssFgEEuWLBHNmjUTwcHBIiIiQjz44INi165dZda1cOFCi/oWL17sVCz2ZGZmimXLlolHH31UVKtWTYSGhgqVSiViYmLEfffdJ6ZPny5+++03i21sJTYkSRJarVbExsaKhg0bij59+ogFCxaIa9eulRnDmTNnxLRp00TLli1FVFSUUCqV5s/xY489Jj788ENhNBrN5X///XeLfYeHh4u8vLxS91GyJeSbb75ZvheM6C4mCeHhCaKJiIiIiOiONX36dLz66qsA5HGLLl265PC4NkRE7qAquwgREREREdHfNm7ciJSUFJw+fRrvv/++efmTTz7JpAYReR1bbBARERERkVPuv/9+fP/99xbL6tSpg99//x2RkZE+ioqI7laBN4cbERERERH5BaVSierVq2PSpEn48ccfmdQgIp9giw0iIiIiIiIiClhssUFEREREREREAYuJDSIiIiIiIiIKWExsEBEREREREVHAYmKDiIiIiIiIiAIWExtEREREREREFLCY2CAiIiIiIiKigMXEBhEREREREREFLCY2iIiIiIiIiChgMbFBRERERERERAGLiQ0iIiIiIiIiClhMbBARERERERFRwGJig4iIiIiIiIgCFhMbRERERERERBSwmNggIiIiIiIiooDFxAYRERERERERBSwmNoiIiIiIiIgoYDGxQUREREREREQBi4kNIiIiIiIiIgpYTGwQERERERERUcBiYoOIiIiIiIiIAhYTG0REREREREQUsJjYICIiIiIiIqKAxcQGEREREREREQUsJjaIiIiIiIiIKGAxsUFEREREREREAYuJDSIiIiIiIiIKWExsEBEREREREVHAYmKDiIiIiIiIiAIWExtEREREREREFLCY2CAiIiIiIiKigMXEBhEREREREREFLCY2iIiIiIiIiChgMbFBRERERERERAGLiQ0iIiIiIiIiClhMbBARERERERFRwGJig4iIiIiIiIgCFhMbRERERERERBSwmNggIiIiIiIiooDFxAYRERERERERBSwmNoiIiIiIiIgoYDGxQUREREREREQBi4kNIiIiIiIiIgpYTGwQERERERERUcBiYoOIiIiIiIiIAhYTG0REREREREQUsJjYICIiIiIiIqKAxcQGEREREREREQUsJjaIiIiIiIiIKGAxsUFEREREREREAYuJDSIiIiIiIiIKWExsEBEREREREVHAYmKDiIiIiIiIiAIWExtEREREREREFLCY2CAiIiIiIiKigMXEBhEREREREREFLCY2iIiIiIiIiChgMbFBRERERERERAGLiQ0iIiIiIiIiClhMbBARERERERFRwGJig4iIiIiIiIgCFhMbRERERERERBSwmNggIiIiIiIiooDFxAYRERERERERBSwmNoiIiIiIiIgoYDGxQUREREREREQBi4kNIiIiIiIiIgpYTGwQERERERERUcBiYoOIiIiIiIiIAhYTG0REREREREQUsJjYICIiIiIiIqKAxcQGEREREREREQUsJjaIiIiIiIiIKGAxsUFEREREREREAYuJDSIiIiIiIiIKWExsEBEREREREVHAYmKDiIiIiIiIiAIWExtEREREREREFLCY2CAiIiIiIiKigMXEBhEREREREREFLCY2iIiIiIiIiChgMbFBRERERERERAGLiQ0iIiIiIiIiClhMbBARERERERFRwGJig4iIiIiIiIgCFhMbRERERERERBSwVL4OgIiIiMgbhMkE06UUmP48A5GbA+h0gFIJaLRQJFSCsk59SGHhvg6TiIiInMTEBhEREd2RhBAwnjgCw3f/g/HEURjPngQKC/8uIEmAEBbbSAmVoGxwL1RNW0L9QC8mOoiIiAKAJESJv+hERER01xJCAEY9YDL+fdEvSYBSDSiUkCTJtwE6QOTnQ7/rS+g++QimP8/KrTKMRscrUCgAkwA0Gqh7PgJN3yQoa9fzXMBERETkEiY2iIiI7mJCCECXLz8MhYBBb7+wJAEqLaDSAEGhkFQa7wXqAGEyQf/5ZhS8uxTIz7PZIsNpt5MiyuatETxtDhSVEt0TrAcJkwkQRYkpSX4dAiQpRUREVB5MbBAREd2FhMkI5OcABdly64zyUGmA4AhAG+Lzi2bTlUvIX/BvGI8c8MwOlEpAqULQ+H9B3ac/JIX/jL8uDDqgMA/QFwL6AtvnU1IAau3tRzCgCfL5OSMiInIXJjaIiIjuIkIIIC8LyMtwX6UKBRAWC0kb7L46naD771YULFsEGA3OdTkpJ2WTFgie+QoUcfEe35c9QgigMFc+l/oC5ytQqICQCCA4HJJC6f4AiYiIvIiJDSIioruEMOiArJvyGBqeoA0Fwip4rTWDEAKFq5ZB9+Fqr+zPTKmEFB2D0NffhSKxmnf3DUDo8oHM1PK3tLEgAWEVgJAItuAgIqKAxcQGERHRXUDkZwM5aZ7fkUIBRCZ4fPwNIQQK334dus3rPLofuxRKSOHhCF221mvJDWEyATm3gPxs91eu0gKR8ZBUavfX7WbCaAAMOkCY5C42Kg0kJSf6IyK6m5Wa2Lh8+TK2bduGM2fOoKCgHM0cySnh4eFo1aoVHnnkEYSHc3o5IiJyD5GXCeRmeG+HkiQnN9Raj+2icP17KFz9lsfqd4hCCSkmFqHLPvB4txRh1ANpVwGTwaP7QWQCpKBQz+7DSUKYgOw0iKybQF627a43aq3crSY8BoiI9asxUIiIyPNsJjYMBgPGjBmDDz74AGq1GnXr1kVwcDCbKHqQEAIZGRk4e/YsgoKC8Oqrr2LixIm+DouIiAKcyM8CctJ9sGcJiK7okZYbhv2/IW/aU26vt1yUSigbN0PI4pUeu5gWBj2QfsVNXU8cEBkPKSjMO/sqhTAZgZuXIdKuONd9SqECKlSEFFuVLTmIiO4SNr/tR48ejY8++ghvvvkmhg4diqioKC+Hdfc6f/48FixYgEmTJiEoKAhjxozxdUhERBSghC7fR0kNABBAxnWICpXdOjilyM9D/oJ/y11eTCa31VtuRiOMh/ZB/9+t0PRNcnv1wmjwblIDADJTISQJktZ3LTdEXibEpVPyTC/OMhmAm5cgMq4DifUghUW7P0AiIvIrVi02zp8/j5o1a2LFihV4+umnfRXXXU0IgcGDB+O3337DuXPn2FKGiIicJkwmIO2yPA6BL2lDIEXEua26/DfmQ//frf6R1ChOq0XY+9ugqFjZbVUKIYC0K4ChHBf3LpMAH7R4EEIANy9CpKa4r9KYREgJNfl7iojoDmbVZnLbtm0ICgrC0KFDfREPAZAkCWPHjsVff/2FAwcO+DocIiIKRDlpvk9qAEBhHkRhnluqMhw9CP3nm/0vqQEABgPyF7/k3jrzsnyU1AAAIbfc8PIY8yI1xb1JDQC4dRniyhmvH4uzhMkot1TJvA5x8wLEjRSImxchMlMh8rPlsUaIiMgmq8TGqVOn0LBhQ4SF+b5v5d2sbdu2AIDTp0/7OBIiIgo0QlcAFOb6Ooy/Zd9yy0WZbvM6QOm+bi1uZTTCuO9XGP8655bqhEEvz4DiS/oCz8zAYoe4dQW4edEzlWdch7jh5oSJmwijASLjGnDtHJBxTR7oV5cvv/66PCA3Xe6OdO0cRNYNuTUWERFZsEps5OfnIyQkxBexUDFF5yAvzz13uYiI6C6Sl+nrCCwJE1DgWqLFdCMVhh+/A4xeHGvCWUoldJ9vdk9d3pia1xE57klKlUUU5kFc/9OzO7lxESIvy7P7cJLIzwZS/7r9mS2jRYkwye+L1L/c1gqKiOhOYXP47tL6IK5ZswaSJOH8+fNO7Wju3LkO922UJAlz5851qv47DfuBEhFReQijwfZ0mL6Wn+1SVwDdF9sAf//TaDRC/9VnEHmuJXGE0eA/LW6EcDkpVfYuBMTl0/K+PExcPuU3LR5EXqbcEsPZxJHJANy6CFGQ45nAiIgCECf5LoXJZMLChQtRs2ZNBAUFoUmTJvjoo4+cricnJwdz5szBQw89hAoVKkCSJKxZs8b9ARMREXmx64BTjPpyjxchhPDfsTVKKiyAftfXrtXhb+fQ0y2AstO8d8y6AiDjunf2VQpRmCt3O3FF2mWI8swaQ0R0B/JaYmPWrFnIz8/31u7cYubMmZgxYwYefPBBvPnmm6hWrRqGDBmCjz/+2Kl6bt68iXnz5uHEiRNo2rSph6IlIiKCx++uu6SgfM3nxZWLEBl+0jWjLAoljEf2l3tzIQSQ71/dJWDQefQCWqRd8Vjd9vbny4FEhckEpLuY1CiSftXvB0UlIvIGryU2VCoVgoKCvLU7l12+fBmLFy/GxIkTsXLlSowbNw7bt29Hp06dMH36dBid6ONbqVIlXL16FSkpKVi0aJEHoyYioruZMBkB4cdjUBjK10XGePqEmwPxIJMRxuNHXNjeAJj88Bx6qHuT0OXLg2V6U2Geb1vF5KbL59kdDIX+18KHiMgH3JLY+PLLL9GpUyeEhoYiPDwcvXv3xrFjxyzK2Bpjo7CwEM8++yzi4uIQHh6Ovn374tKlSzb3cfnyZYwePRoJCQnQarVo1KgRVq9ebVHmu+++gyRJ2LRpE15++WVUqVIFQUFBeOCBB3D27Fmnjumzzz6DXq/HhAkTzMskScL48eNx6dIl/PLLLw7XpdVqUbFiRaf2T0RE5DS9zn11KVVAZDwQWxWIqQKERrtep0FfrrvLxtMn5HjcRDNoJELXforwb/YhYtcBKJu2dFvdAGC6fBEiv5yDO7qjZYSkACITgNhqQHwN+V9Xz58731vF5TrfzUWqcS+k+u0gNegAqW4bSBVrA86OTVaO/bqDEEJObDgiIh5S5XqQKtcDVBr75Rytj4joDuZyYmPdunXo3bs3wsLCsGDBAsyePRvHjx9Hx44dyxxgdOzYsXjjjTfQo0cPJCcnQ61Wo3fv3lblrl+/jnbt2uGbb77BpEmTsGTJEtxzzz0YM2YM3njjDavyycnJ+OSTTzBt2jS88MIL+PXXX/HEE084dVwHDhxAaGgoGjRoYLG8TZs25vVERER+pZxjWNgUEQ+og+QLQF0BpJAIICTK9XqNeuc3OXEEMLrpDjcAaDQw/LoHItVN3QGsCBjPnirfpu5IIEgKQKWWu7Rk3wIgIIVFA8ER5a/TUy028rPh9KiwBbkQ189DXD0LmIyQYioD0c7dQBK+auWgL3SsRY42FAiNcmxGGn2BPOAsEdFdzKXbHzk5OZg8eTLGjh2LlStXmpePGDEC9erVw/z58y2WF3fo0CGsX78eEyZMwFtvvQUAmDhxIp544gkcPnzYouzMmTNhNBpx5MgRxMTEAACefvppDB48GHPnzsVTTz2F4OBgc/mCggIcPHgQGo2c3Y6OjsY///lPHD16FI0bN3bo2K5evYqEhASrViaVKlUCAFy54t3+oERERGVy18WNJhiSSi0PcJifBUCC0IYAweFAXoZrdRv1pd99tsF0/apr+yxB94H820TZqAkUFSu7te4i4kY5B6g0uiGxYTIAt4q3gJWAiFhArQHKO9xZORJSDsnPQZnTnJYgrv0pt+BRqOTj0oY4W4Xvum84kiBSKIGoikDOLSA4ElA5cB9SX+jWVk1ERIHGpRYbO3fuREZGBgYPHoybN2+aH0qlEm3btsXu3bvtbrtjxw4AwOTJky2WT5kyxeK5EAJbt25Fnz59IISw2E/Pnj2RmZmJ/fstB+kaNWqUOakBAJ06dQIA/Pmn4/Oj5+fnQ6vVWi0vGick0AZCJSKiu4C7BhEsukAyjycl5DvjCoXcGsAV5YlRF3gzP4jCcsbsiZlftCHyvzrXfrt4ZJDKciZMpHtaQVG3NaTwChAZqc7PMOKrFg6OHG9URblc9i0n6vVQVyEiogDhUmr3zJkzAIBu3brZXB8RYb/JY0pKChQKBWrXrm2xvF69ehbPb9y4gYyMDKxcudJu64/U1FSL59WqVbN4Hh0t9ytNT3e8D2JwcDAKbfwoKSgoMK8nIiLyLx6cHcHZMQzcKRCmeS3JiUHGPSoyHpI2BCIv0z9nzClnskRcPA6h0kCKqQJExgFZN51LBPhKWccbHCEnotIuA0r13710lCo52WFve06MQkR3OZcSG6bbPzTWrVtnc3BMlcr1JnFF+xg6dChGjBhhs0yTJk0sniuVSpvlnLnTUKlSJezevRtCCIvuKFevys1hK1f2TNNVIiKicnNX8qHobra5absESAp5mkpH+vyXqhwxqp3ruuIXbLT6dIi7zqGkAKISIGmCIXLS/XeASYXt32xlypOnxBUAFFUbANEJEM4kNnyVqCvreFVqSJICiKlqsViKqQqRdhkoyLFTr9cmOiQi8ksuZR6KWlvEx8eje/fuTm1bvXp1mEwmnDt3zqKVxqlTloNtFc2YYjQand6HK5o1a4b33nsPJ06cQMOGDc3L9+7da15PRETkV8p7kViSLh/CqAc0wfIdZJUakiRB3L6YdEk5LsCk0DCIm6llF3SQskkLKKpUhyJKbtGpatcJisRq0O/4xG37kEJCy7ehwg3jJEgSUKEyJJUGojAPMOjkwShNxvIPAioprMYdcwttiHNdZMKiIUXGmd+LUoXbN5qcbY1S1D3H29RlJLzysyGKz4wTmQBJqYLIvF7666QOck98REQByqX0bs+ePREREYH58+dDr7fuM3jjxg272/bq1QsAsHTpUovlJWc5USqV6NevH7Zu3YqjR486tQ9XPProo1Cr1Vi+fLl5mRACb7/9NhITE9G+fXuP7JeIiKjcnByUs1SZN+QBCUOjAE0wRH6W6wOHAuWKUVm3gfuSNgDUDz2K4Gn/hqKyfFdcO3AEgqf92231A4Cydt3ybeiO1imSEtLt11nShkCKSoAUlQCEuTDla1kX5OUkBYc5t4FBD2hDISXUhFSxltyS6MZFiNQLzuxVHgjXFzRldGU26ORWGUWPotbGhXn2Z1ORFO797BMRBSCXbgtERERgxYoVGDZsGFq0aIFBgwYhLi4OFy5cwBdffIEOHTpg2bJlNrdt1qwZBg8ejOXLlyMzMxPt27fHt99+i7Nnz1qVTU5Oxu7du9G2bVuMGzcODRs2RFpaGvbv349vvvkGaWlprhyGTVWqVMGUKVOwaNEi6PV6tG7dGp9++in27NmDDRs22O3uYs+yZcuQkZFhnk1l+/btuHRJHrH8mWeeQWRkpNuPgYiI7jLuvLgx6oHMcs7sYY9CCakcCQpF3YbANzvcFkbBwjkoWDjHbfVZCQ2FlFCpfNu6I4FgMkBcd3zAdId4KLHhdIKhIAfizwMu7lRA8lFiQ1IoIYLC7HcpKSn1z7KHzwiJ9ExrGiKiAOJye8chQ4agcuXKSE5OxqJFi1BYWIjExER06tQJo0aNKnXb1atXIy4uDhs2bMCnn36Kbt264YsvvkDVqpb9ChMSEvDbb79h3rx52LZtG5YvX46YmBg0atQICxYscPUQ7EpOTkZ0dDTeeecdrFmzBnXq1MH69esxZMgQp+t69dVXkZKSYn6+bds2bNu2DYA8fggTG0RE5DKl2tcRlK6ciRdlvYbum/HF4yQo6zUu/4Wmv955V3kosREaKb9vPTWdrC2SAgiv4L39lRRWwfHERpkkINSFljhERHcISZQYUXP48OE4f/48fvjhB1/FRJAHTVUqlVi1ahVGjx7t63CIiChAiIzr5R9HwdPCKpTrTrnIz0d2n46BMTuKUgnNwBEIGvtMuasQGdfkrgf+QpKAuOryoJYeYEpNAW4405XERdGVoKh8j/f2Z4PITHXPgK4RcZDCfJikISLyExxCmYiI6E7iq7EDyiTJA1iWZ8vgYKjadgSc7AbqE0Yj1F17uFZHcIR7YnGX4AiPJTUAQIquKLei8BIpxg9mtguPdWnATyEAaMPYWoOI6DY3DL0dWPLz85GZmVlqmQoVKkCjKbspaE5ODnJySm9KGBcX5/R4HEREROWmCZYH2rQ30KCvBIVCcmFKSs1jg2D4xc9bkyoUUNZrBGXtemWXLY0mWJ5qt2jaXV/zcLJMUmuBijUhrp7z6H4AAHHVIPlqRpRiJIUCIqYKkHbZqVlhhBCQJAk7dv+Ajr37I4pjaxARAbDRYkOpVMJg8JM/pB6wceNGVKpUqdTHzz//7FBdr776apl1Xbx4sVxxFp0DJkWIiMgZkuTDGR9K42JMypZtIVWsDMCPL+RMJmgeH+xyNZIkASFRrsfjDtoQ8wwrHhVdCQjxcEsVbQik2Kpll/MSSaEEYqoCEXFw9H0tKRRYunYT+gx7EqPHjIEImLFniIg8y6rFRkxMDC5dumTOCN9pevbsiZ07d5ZapmnTpg7VNXz4cHTs2LHUMhUrVnQ4tuKKEiKxsbHl2p6IiO5iweFAfrb/tNrQhrp8cSwpFND8YxAK334dZU8T4QsSEB4OVacH3FNdcLg8wKQvx0uRJLnLhFd2JQFVGqDg5F4oTUaoVG6+saNUQ6rW0KVWQ54gSRIQVgEiOALIy4QxJx0w6CxubBkMBqiCQ4GQSCA4AiPGP4Ol763BJ598gjfeeAPPPvusD4+AiMg/WA0eunPnTvTo0QP79u1DixYtfBXXXW/x4sWYOXMmbty4gfBwP7zzRkREfk3oCtw/XWt5KBRAdKJbLihFYQFyRidBXL/ilwOJBj33IjQP9XVbfcKoB25egs8yORFxXp0WNTU1FQ8/+AA+XjAL1SoluCm5IQFKFaSaTfyiC0pZrl+/jpo1aqBu7RoI0mqRm5eP85cuIzvbsuvz/v370b59exiNRnz//fdo3769jyImIvIPVr8yunbtioSEBIwfP77MsSjIM44cOYLk5GT06dOHSQ0iIioXSRMEBIX5OgwgPNZtd8klbRCCX3jJ/5IaSiWUrdtD3bOPW6uVlGogwkctN7WhXn3/GI1GDBkyBPsOH8V9Q57C9u9+AiDPEueS0AhItZsHRFKjSH5BAQ4dO4m9+w/h6MnT0Omsp8Jt0aIFlixZAoPBgIEDB+LmzZs+iJSIyH9YtdgA5Cxw9+7doVar0a9fP7Ru3RohISF3ZNcUf2EymZCZmYlvvvkGX3zxBerXr49vvvkGFSpwCi8iIiofIUxA+jWY9IVQ+KIJfnAEpDD3z9pQsGIxdFs23J4awtckIDgYYWs+gSIu3u21FxQU4L2lizFxhOtjdzhMHQREV/ToTCglzZkzB/PmzbNYNuChbliTPBva8rTcUCggJdS6fRyB8/v1+vXrVt2YNRoNCgsLrcoKITBs2DBs2LABPXv2xI4dO3zzOSci8gM2ExsAcOrUKaxcuRJbt25FSkqKt+O6a7Vo0QJJSUl46qmnEB3NKbyIiMg1G9avQ4taiahdszrUKi9OhqYNBcJjPHJRKQoLkPvkYJiuXASMvh9HJPj/Xoa6+8MeqXvChAlYsWIFZkx6Cq/Meg4mk8mzF6+aYCAqwatJjf/973946KGHrAbCHDVqFFa99x6QdRPi1mV5zBEAgASTyQSTyQhJoYBSoYS5u442BFKFykBUvDw4Z4BxJrEByDP0tWnTBidOnMC8efMwe/Zsb4RJROR37CY2itPpdCgo8OHgVXeJ0NBQzoJCRERuc+jQIbRr1w6hIcHYuXk9GjesD5U3/s4EhwOh0R69U266kYq0cQOhyEyHyod35LXjJkM7eJRH6v7www/xxBNPmJ8P/kcfrFj4HwQHB3kmSRUSAYR5Jhllz6VLl9C8eXOrrhT33nsvfv31V4SE/N2FROh1cnIjPxs/fb8bf547i8qVE9GtZy9IwWHy+06lCagWGiU5m9gAgOPHj6N169bIz8/Hzp078cADbhrAlogogDiU2CAiIqLAkpWVhVatWuHMmTMAgLDQUCx+cSbGDR8Co9HooUS6BIRFA0FhHr+4vHLlCvq2aYUPqkUjQaOGWuH9i1ntyKehHf6UR+o+ceIEWrdujdzcXIvllRLisXLxfPTu3hUmk4DCHcetUAGR8fK4LF6k1+tx//334+eff7ZYHh4ejj/++AN169a1u+348ePx9ttv4/HHH8fWrVs9HarXlCexAQAbNmzA0KFDER8fjwMHDqBy5cqeDJOIyO+wIx4REdEdRgiBMWPGmJMaAJCTm4unpv0feg4Yhus3bsLo7i4cai1QoTKk4HCPJzUMBgMGDx6MfZevovu+MziXXwijt+7TKBSAJEE7abrHkhq5ubno37+/VVIDAK5eT0WfoWMx7aWFgNq1KXShUMqJqNgqXk9qAMDzzz9vldQAgFWrVpWa1CBrTzzxBJ566imkpqZi0KBBMBgMvg6JiMirmNggIiK6w7z55pvYsmWLzXU7v9uDhh2649zVm4A7xlFQqoHwGCAyAZLSO2N4zJo1Cz/88AMA4KpOjy5/nMKyi6kwCQGDyYMJDkmCVCkRIcvWQvv4EI/sQgiB8ePH4/jx43bLhIWF4clnnoUytipQIVGevcThcykBmiAgMgGIrQYpNNqr42kU+eSTT/Daa69ZLX/mmWeQlJTk9XjuBG+88QaaN2+OPXv2YObMmb4Oh4jIq7w4ihgRERF52t69ezFt2rRSyzz19NOo17yNPFhjYR6Qnw0YSm/qbkUbAgRHeH1Mg//+979YsGCBxbICk8C/z13F5zcy8W6D6qgZopVjclcrDqUSMJmgGTgC2pFPQ9Jo3VOvDe+99x7WrVtXaplVq1ahXr16AABJrQUi4+VzaTIC+kL5XJpM8vFLkvxQaeRWNUq1z8eg+PPPPzFqlPW4JG3atMGrr77qg4juDEFBQdi8eTNatmyJhQsXokOHDujbt6+vwyIi8gomNoiIiO4Qt27dQlJSEvR6vd0yHTt2xMsvvwwA8gVuUCgQFAphMgEG3d8Pk/H2hTEASHLLDLVGvkD20cXx+fPnMXz4cLvr/8jKQ3Llelj7RBJ0n3wMceWinJQob7cbSQIUCqi6PgRt0lAo69QvZ+SOOXDgAJ555plSy0yaNAkDBgywWi5JEqBUyQ+EeihC1xUUFKB///7IzMy0WB4dHY1NmzZBo3Gxe81drnbt2nj//ffx+OOPY8SIEdi/fz9q1qzp67CIiDyOiQ0iIqI7gMlkwvDhw3Hx4kW7ZeLi4vDxxx9DrVZbrZMUCrmLgg/GWnBEYWEhkpKSkJ6ebrdM7dq18c77a6CNjITm8cEwHvwDuk83wvDTbrkFw+1Ehc1ER4l1UnxFaB4bCHWvR6GI9Pz065mZmUhKSip1kMjWrVsHfIuGKVOm4MCBA1bL161bh+rVq/sgojvPP/7xD/zrX//Ca6+9hgEDBuDHH3+EVuu5VkZERP6AiQ0iIqI7wIIFC7Bjxw676yVJwocffojExEQvRuU+06ZNwx9//GF3vVarxZYtWxAZGQlAPl5V89ZQNW8NoSuE6dwZGE8fh/HMCRhPn4DIywUKCwGlEpJWC6liIpT1G0FZtwGUdRtCio33WqsUIQRGjx6Nc+fO2S1T1KIhkC9QN2zYgHfeecdq+QsvvIDevXv7IKI7V3JyMn799Vf8/PPPmDp1KpYtW+brkIiIPIqJDSIiogD33XffYdasWaWWmTNnDrp37+6liNxr48aNZV6Yvfnmm2jWrJnNdZJGC2WDxlA2aOyB6Fy3ZMkSbNu2rdQyH3zwAWrUqOGdgDzg+PHjePLJJ62Wd+nSBfPmzfNBRHc2tVqNjRs3onnz5njrrbfQqVMnDBw40NdhERF5DGdFISIiCmDXrl3DoEGDYDKZ7JZ58MEHy0x8+KtTp05h7NixpZYZNmxYmWX81S+//ILp06eXWmbGjBl45JFHvBSR++Xk5KB///7Iy8uzWJ6QkICPPvoIKhXvs3lClSpVsGHDBkiShLFjx+LUqVO+DomIyGOY2CAiIgpQBoMBgwcPxvXr1+2WSUxMxIYNG6BUKr0YmXvk5eWhf//+yMnJsVumUaNGWLFihc9n+iiPmzdvYsCAATAYDHbLdO7cGf/5z3+8GJV7CSHw9NNP48SJExbLFQoFPvroI1SqVMlHkd0devTogdmzZ9tNLhER3SmY2CAiIgpQc+bMwXfffWd3vVKpxMaNGxEXF+e9oNxo4sSJOHr0qN31oaGh2Lx5M0JD/XcWEHtMJhOGDh2KS5cu2S0THx+Pjz/+OKBbNLz77rvYsGGD1fJ58+aha9euPojo7vPvf/8b3bt3x9GjRzFhwgR5amAiojsMExtEREQBaMeOHZg/f36pZRYsWIAOHTp4KSL3ev/997FmzZpSy6xcuRINGjTwTkBuNn/+fHz99dd210uSFPAtGvbv34/JkydbLe/VqxdeeOEFH0R0d1IqldiwYQMqV66MtWvXYvXq1b4OiYjI7ZjYICIiCjAXLlzAsGHDSi3z6KOP4l//+peXInKvw4cPY8KECaWWefrppzFkyBAvReReu3btwpw5c0ot8+KLL6Jbt25eisj9MjIybE5fW7VqVaxbtw4KBX+CelN8fDw2btwIpVKJSZMm4dChQ74OiYjIrfhXhYiIKIDodDoMGDAAaWlpdsvUrFkTa9asCchxJ7KystC/f38UFBTYLdOiRQu8/vrrXozKfa5cuYLBgweXOthrz549MXPmTC9G5V5CCIwaNQp//vmnxXK1Wo1NmzYhJibGR5Hd3Tp27IhXXnkFBQUF6N+/PzIzM30dEhGR2zCxQUREFECmT5+OvXv32l2v0WiwefNmREVFeS8oNxFCYOzYsThz5ozdMpGRkdi8eTOCgoK8GJl7FA32mpqaardMlSpVsH79+oBu0fD666/j008/tVq+aNEitGvXzvsBkdnUqVPRp08fnD17FmPGjOF4G0R0xwjcv5pERER3mS1btmDp0qWlllmyZAlatmzppYjca9myZdi8eXOpZdauXYtatWp5KSL3mjVrFn744Qe761UqFTZt2oTY2FgvRuVeP//8M2bMmGG1vF+/fjbH2yDvUigUWLt2LWrUqIGtW7eW+X1CRBQomNggIiIKAGfOnMHo0aNLLTNkyBA89dRTXorIvfbu3YupU6eWWmbatGl49NFHvRSRe/33v//FggULSi2zcOFC3HfffV6KyP1u3Lhhc/rae+65B6tWrQrIrlF3oujoaGzevBkajQbTpk3Dr7/+6uuQiIhcxsQGERGRn8vPz0dSUhKys7PtlmnQoAHeeeedgLx4vHXrFgYMGAC9Xm+3TIcOHcqcBcZfnT9/HsOHDy+1zOOPP44pU6Z4JyAPKJq+9vLlyxbLtVotNm/ejMjISB9FRra0atUKr7/+OgwGAwYMGIBbt275OiQiIpcwsUFEROTnnnnmmVJnMQgJCcGWLVsQFhbmxajcw2QyYfjw4bhw4YLdMrGxsfj444+hVqu9GJl7FBYWYsCAAUhPT7dbplatWli9enVAJqWKvPzyy/jf//5ntXzZsmVo1qyZ9wOiMo0fPx6DBg3CxYsXMWzYsFIHtCUi8ndMbBAREfmxtWvXYtWqVaWWefvtt9GwYUMvReReCxcuxI4dO+yulyQJH374IapUqeLFqNxn2rRp+P333+2u12q12LJlS0C3aPj2229tTl87fPhwjBkzxgcRkSMkScLKlStRr149fPnll0hOTvZ1SERE5cbEBhERkZ86cuQIxo8fX2qZcePGYdiwYV6KyL2+//77Mqc1/fe//40HH3zQSxG518aNG7Fs2bJSyyxduhTNmzf3UkTud+XKFQwZMsRqdo1GjRph+fLlAd0K5W4QHh6OLVu2IDg4GLNnz8bu3bt9HRIRUbkwsUFEROSHsrOzkZSUhPz8fLtlmjVrFrCzGly7dg2DBg0qtfl79+7dMXv2bC9G5T6nTp3C2LFjSy0zdOhQjBs3zksRuZ/BYMCgQYOspq8NCwvDli1bEBoa6qPIyBmNGzfG22+/DZPJhMGDB+Pq1au+DomIyGlMbBAREfkZIQTGjRuHU6dO2S0TERGBLVu2ICgoyIuRuYfRaMSQIUNw7do1u2UqV66MDRs2QKlUejEy98jLy0P//v2Rk5Njt0zDhg3x9ttvB3SLhpkzZ2LPnj1Wy999913Ur1/fBxFReQ0fPhxjx47F9evXMXjwYKuZbYiI/B0TG0RERH5mxYoV2LhxY6ll3n//fdSuXdtLEbnXnDlzSm3yrlQqsXHjRsTHx3sxKveZOHEijh49and9aGhowLdo+Pzzz7Fw4UKr5RMmTMCgQYN8EBG5aunSpWjWrBm+//57/Pvf//Z1OERETlH5OgAiIiL62x9//IFnn3221DLPPvssHn/8cS9F5Lpjx47h22+/RU5ODipWrIiXX3651PLJycno2LGjl6Jzr9WrV2PNmjWlllm5ciUaNGjgnYA84K+//sKIESOslrdq1QqvvfaaDyIidwgODsbmzZvRokULvPLKK+jQoQN69+7t67CIiBzCxAYREZGfSE9PR1JSEnQ6nd0y7dq1C6jZC959911MmjSp1GMq7tFHH8XUqVM9HJVnHDp0CBMnTiy1zNNPP40hQ4Z4KSL3K5q+NiMjw2J5VFQUNm3aBK1W65vAyC3uuecevP/+++jfvz+GDRuGAwcOoHr16r4Oi4ioTOyKQkRE5CO5ubmYOnUqOnbsiM6dO6Nbt244f/683fIxMTHYtGkTNBqN94J0QWpqKiZPnuxwUqNGjRp4//33A3LciaysLCQlJaGgoMBumRYtWuD111/3YlTuN3XqVPzxxx9Wy9euXYuaNWv6ICJyt379+uGf//wn0tPTMWDAAIc/v0REvsQWG0RERD6g0+nQrl27UsdiKE6SJKxfvx5Vq1b1cGTus2HDhlIv9IvTaDTYsmULoqOjPRyVe+Tk5OC5557D7t27odPpEBwcjDNnztgtHxkZic2bNwfkYK9FNm7ciLfeestq+fTp09G3b18fRESesnDhQuzduxe//vorpk+fjiVLlvg6JCKiUjGxQURE5AMffvihw0kNQJ6B4qGHHvJgRO63f/9+h8u+8cYbaNmypQejcR+TyYTOnTvjwIEDDm+zZs0a1KpVy4NReZa96Ws7duxY5pgpFHg0Gg02btyI5s2bY+nSpejYsSOSkpJ8HRYRkV3sikJEROQDn376qcNlu3Xrhrlz53osFk9x5sI/kGZA+eyzz5w6tqlTp+Kxxx7zXEAeZm/62ri4OHz88cdQq9U+iow8qVq1ali/fj0AYMyYMTh9+rSPIyIiso+JDSIiIh9w9MI4JCQEH374IZRKpYcjcq/8/HycPHnS4fKrVq3yYDTutWPHDofLdujQAa+88ooHo/EsIQQmTJhg1bpIkiR8+OGHSExM9FFk5A29evXCzJkzkZ2djaSkJOTn5/s6JCIim5jYICIi8rK0tDRcuHDBobJ5eXnYs2ePhyNyv6NHj8JoNDpc3tHXwx84mpRSqVRYt25dQLdoWL16NdauXWu1fO7cuejevbsPIiJve/HFF9G1a1ccPnwYkyZN8nU4REQ2MbFBRETkZQcPHnSq/O7duz0TiAd9+eWXTpXv0aOHhyJxL71e7/DYKAaDARs3bvRwRJ5z6NAhmxeyPXr0wKxZs3wQEfmCUqnEhx9+iIoVK2L16tVYs2aNr0MiIrLCxAYREZGX/fTTT06VD8TpFr/66iuHy9arVw/PPvusB6Nxn5MnT6KwsNDh8j///LMHo/GczMxM9O/f32pWm8TERKxfvx4KBX9C3k0qVqyIjz76CAqFAhMmTMCRI0d8HRIRkQX+VSIiIvKyTz75xKnygwcP9lAknhMcHFxmGZVKhbFjx+Lnn38OmGlsf/31V6fKB2ICQAiBsWPH4uzZsxbLVSoVNm3ahLi4OB9FRr50//334z//+Q/y8/PRv39/ZGdn+zokIiIzTvdKRETkZY6OJyFJEhYvXoyuXbt6NB7TjVQYTx+D8dRxGE8dh+nMCYjcHMBgACQJUKshRcdA2bAJlHUbQFm3IZR1G0AKCbVb56hRo7Br1y6b69RqNcaOHYsZM2agevXqnjosj3C2a8nw4cM9FIn7mEwmfPTRRzh37hwef/xx7Nq1C1u2bLEqt2DBArRv394HEd75DAYDZs+eja1bt1qt0+l0aNq0KYYOHYpp06ZBkiQfRCibMWMGfvzxR+zYsQPjxo3DRx995NN4iIiKSEII4esgiIiI7iZ16tSxuhteUt++fTF79my0atXKIzEIvR6Gn3ZDt+0jGI8elBcqlYDJBNj7aVDU+sBkAlQqqLr1gvbRAVA2aGyz+D/+8Q+raW2TkpLw2muvoUqVKu45EC9z5NwBclLq1VdfxbPPPuv3F34TJ07E8uXLAfzdwsRkMlmUeeyxx7Bt2za/OZbx48fj7bffxuOPP24zGRBoZs2ahZdffrnMcu+88w6efPJJL0Rk361bt9CiRQtcuHABy5Ytw8SJE30aDxERwMQGERFRmYQQgMkA6HWAQQcYCgGjEUDRn1AJUKoAtQZQaQGVBlAo7V4Erl+/HsOGDbO5rl+/fpg1axaaNWvmmWPJy0Xhpg+g/2wTRGaGnKwocRHrMKUSMBqhqF0X2oEjoHqgl9Ux//TTT3j33XdRqVIljB49GnXq1HH9IHyoS5cu+OGHH+yulyQJAwcOxMyZM9G4se2Ejz/Jzs5GTEwM9Hq93TK1atXCvn37EBUV5b3AynCnJTZatGjh0Gw7jz32mNNd2Tzht99+Q8eOHQHIn/HWrVv7OCIiutuxKwoREZEdwmQCCnOAvGw5sVEakwHQFxtoUamGCA4HgkIhSZbjLAwdOhSnTp1CcnIyDAa53oYNG+LDDz9E06ZN3X0YZoZ9vyI/+d8Q6bf+TmaUN6kB3E7uAKY/zyJ//kwov/ocwdPnQJFQyVykQ4cO6NChgythu4UQJjkppdcB+kL5fAkhd7WRFIBKLSel1NpSk1JLlixBixYtYOu+0NChQzFz5kzUr1/f04fjNocPHy41qaFWq7F582a/SmrcierWretQYqNu3bpeiKZsbdq0weLFizF58mQkJSVh//79qFChgq/DIqK7WOCNaEVERORhwmSEyL4F3LoI5KSXndSwxagHctKAW5cgctLlJEkxL730EgoLC3H06FEUFhbi2LFjHktqiLxc5L/2H+RNH2+Z1HDbDuT6jIf+QM7Ix6H7YpvNC39vE0JAFOZBpF8DUs8DaVeA7JtAQTagy5cTUbp8oDAXyM0AMq8DNy8ANy9A5KZDmIxWdTZr1gwbN240X8QpFAo0b94cJ06cwLp16wIqqQGgzItpo9GIS5cueSmau9eECRPKLKNUKjFu3DgvROOYSZMmISkpCSkpKRgxYoRV9yUiIm9iVxQiIqJiRGEukJ1mvlh3G4USCI+BpCl7thB3Ml2/itx/PQlx/Yr7ExqlUD3QC8EzXoSkUnttn0WEEEB+tpysKE9SqjhtKBBeAZLS+jjy8/MRFBTkN+NOlMfYsWOxatWqUstUqVIFFy9e9FJE9v3111/o3Lkzrly5Iietbv+EVSgUiI2NxVdffYXmzZv7OMrye+CBB+wOuAsAI0eOxPvvv+/FiMqWlZWFVq1a4cyZM0hOTsaMGTN8HRIR3aXYYoOIiAhytxOReQPIuun+pAYAmIxAZipE9i25W4QXmC5fQO6k4RCpV72a1AAAw66vkDd7KoRO59X9CqMeSL8qt8xwNakByK05bl6CyMuyaoUSHBwc0EkNQB4roSwZGRl+cTc+JSUFly5dgslksjgXJpMJqampDg3q6s/mzJljd51SqcTMmTO9GI1jIiIisGXLFgQFBWHmzJmljj9DRORJZbbYyM/Px+XLl1FQUFBaMXKD8PBwVKlSBUql0tehEBHdVYTJCGRcl7uPeINKC0TGQ1J47v6C6cZ15E4cDpF2S06q+IIkQdWhK4LnLICk9PywXiIvC8i+hb8HdXUzdZB83rxwLN6g1+sRFBRUZtJi1qxZeOmll7wUlX0mkwlNmzbF0aNHrdZVqVIFZ8+ehVar9UFk7tOpUyf8+OOPVsv9sbVGcatXr8aYMWNQqVIlHDhwAAkJCb4OiYjuMnYTGz/++CPeeOMN7NixA/n5+d6O664VHx+Pxx9/HM8//zyqV6/u63CIiO54wmQE0q+55+6+M1QaICrBamBRdxA6HXKfHATT5QvmAT59RpKg6T8UQeP/5bFdCCHkbie56R7bh5lCBVSoZLNrSqD59ddfcd9999ldX79+fcyZMwcDBw70m5YpW7ZsQVJSktXy5cuXY/z48T6IyL127tyJHj16WC0/c+YM7rnnHh9E5LhRo0ZhzZo16NatG/73v/8hJycHb775Jh577LGAmCGIiAKbzcTG119/jUcffRR169bF0KFD0bp16zuiuaU/E0IgIyMD3377LdatW4fg4GDs3r0bNWrU8HVoRER3LCFMclLDWy01SlJrgcgEt/99LXh3KXQfr5Fn/fATIUtWQ3WvZ8Y/EDnp3klqFFEogQqJfttywzw9sckkz/qiVNt8j125cgWJiYlWyxs3bozZs2ejX79+fteK1FarjTultUaRmjVr4vz58+bn9913H37++WffBeSgvLw8tGvXDkeOHMG4ceOwe/dunD171m+mqCWiO5tVYqOgoADx8fHo3Lkztm7desf8kQgkFy9eRJcuXVCnTh18/fXXvg6HiOiOJXLS5EEmfSk0ClJIpNuqM544itxJw/0qqQGFAlJ8RYSt3gIpyL2Dp4r8bCDrhlvrdIhSDcQkeqTFTXkIo0HuhpObARTkWnY/kiRAEwKEhAORcZDUQeZVAwYMwObNmwEA0dHRWLFiBZKSkqDwYDcpV5VstXGntNYokp2djYEDB+LIkSPo0KED1q9fD5XKP5NoJZ08eRLNmjVDYWGheVm1atWQkpLiw6iI6G5gldj49NNP8Y9//AMnTpwIuCnL7iQrVqzAM888g2vXriE2NtbX4RAR3XGEvkAeV8MfRFd2y+whQleInLEDIK5c9t24GvZICmgeH4ygidPcVqUwGoCbF+GxMTXKEhIJKTzGN/u+TZiMwK0r8lS1jiazQiKB+GrmBMe5c+eQk5ODJk2aBETrXJPJhLi4OKSlpSE4OBjp6em8EecHcnNzMWHCBHzwwQdW627dumWeIpmIyBOs0vHfffcdateuzaSGjz3yyCMwGo02B5AiIiLXCGGSZz/xF9k3rWbcKA/9zi8gLl3wv6QGAAgTdNs+gulGqnuqE+J2Sw0ftkzJy4TQ+W5wdZGfA6QcBTKuOddCJy8TSDkKkZEKIQRq166Npk2bBkRSA5Cnd33ttdcQFRWFefPmManhJ1588UWbSQ0AOHjwoHeDIaK7jlViIz09nSMZ+4GKFSsCkKdYIyIiNyvZVN/XDDpAl+dSFUII6LZ9JHc78FcSoPtim3vqKsgFdH4wuHlWqluSUs4SuRnApZPye6dcFQjgRoo8la0/dVsqgxACIjsNwx/uhrQT+zF1+ACIrFsBdQx2CSGP91OYK3eRy88GCrKBwjzAaPCv7mU2PPbYY6hdu7bNdUxsEJGnWSU2hBB+N1DU3ajoHPjDvPFERHcSIQSQn+XrMKy5ONaH8cQRmP46698XPyYT9J9tgjC4NlirEALIy3BPTK4yGryeYBH5OcCVs3BLa5WMa0D6Vdfr8TBh1ENcPw9x9AeIk79CnD8CcfEERMpRiFN7IQ5/B3H1T4jyJnp8SQhAX1giiWGSHybT38mOghw5keWnn/H27dvj5MmT+OCDD1CvXj2LdZ9//rmPoiKiu4XTI0OtWbMGkiRZjNbsiLlz5zrcxFGSJMydO9fZ0IiIiMqmL5QvHPyNvtClC37dp5uAALgxITLTYfjxO9cqMRSWv6WCJ+Rlem1XwmQErp2DW7vg3LoMUZDrvvrcTORmQhz+HuLCcbmlji26fIhLJyEOfQeRnebdAF0hhJy00BeUnbAQJjmJpsv32+SGSqXCsGHDcOzYMXz00UeoWrUqAODYsWMQRgNMZw7CuG0FjO/OhvHtF2Bc9SKM326EuH7xzmh1Q0Q+479DXvsBk8mEhQsXombNmggKCkKTJk3w0UcfOV3P77//jkmTJqFRo0YIDQ1FtWrVMGDAAJw+fdoDURMRUal8PQtKaQrKF5swmWDY8y1g9KPuNfYoFNDv+da1OvL8rMWNLt/lVigOu3XZM0mda3/65YWlyM2AOPkL4OjrazLILTj8aQwde4qSGs52izPq5a5rfni+iiiVSgwaNAjnz5/HG2+8gW/WvgPT2pchdn4EXE8B9Dq5NUphHnD6IExbl8G0bTlEnh9/PxORX/NaYmPWrFnIz/eDvrBOmDlzJmbMmIEHH3wQb775JqpVq4YhQ4bg448/dqqeBQsWYOvWrXjggQewZMkSPPnkk/jhhx/QokULi3nYiYjIC/S+G+yxTOUciNJ06QJQ6MfHVZzJBOOJI+XeXBRdDPobF8dIcYQwGoBM9wy+akVfAOR6r+WJI4S+EOL07/IFsDMtVISAOLMPosDz58Ql+oLyj/VjNPhXqyU7FAoFJj/aA41TfgMKbl8HlEzIiNvdrlMvwbRlGZMbRFQuXktsqFQqBAUFlV3QT1y+fBmLFy/GxIkTsXLlSowbNw7bt29Hp06dMH36dBiduCv2r3/9CykpKVi6dCnGjh2LWbNmYc+ePTAYDEhOTvbgURARUXGiqO+6vzLqy3XX3HT6uAeC8Rxx7QpETjkvXvx1EEV9oef3kX3Ls8fuL9MfF7lx0fGWGiWZTBCp590ajlsJ4XpiwlDon5+FYkR2Okxfr78dpwNdbXKzYPpqnVdiI6I7i1sSG19++SU6deqE0NBQhIeHo3fv3jh27JhFGVtjbBQWFuLZZ59FXFwcwsPD0bdvX1y6dMnmPi5fvozRo0cjISEBWq0WjRo1wurVqy3KfPfdd5AkCZs2bcLLL7+MKlWqICgoCA888ADOnj3r1DF99tln0Ov1mDBhgnmZJEkYP348Ll26hF9++cXhutq3bw+NRmOxrE6dOmjUqBFOnDjhVFxEROQCd97hVKqAyHggtioQUwUIjXZPveWI0Xj6uByPm2gGjUTo2k8R/s0+ROw6AGXTlm6ru4jx7KnybWhwQwJBUgCRCUBsNSC+hvyvq+fPGy2BcjKcKx9XDVKd1pDqtAbUDtxcys+C8JNBy4UwQaSm2Fwn1WsLqfmDkFo+BKlpV0jVGsrn1LIG4MZFOZnpj0r7nAeFAyGRlg9bn28hAJOfHt9t4uivNlulSM06QzFkOhRPvQzFyFmQ2j10ewMTcC0F4vpFL0dKRIHO5cTGunXr0Lt3b4SFhWHBggWYPXs2jh8/jo4dO5Y5wOjYsWPxxhtvoEePHkhOToZarUbv3r2tyl2/fh3t2rXDN998g0mTJmHJkiW45557MGbMGLzxxhtW5ZOTk/HJJ59g2rRpeOGFF/Drr7/iiSeecOq4Dhw4gNDQUDRo0MBieZs2bczrXSGEwPXr1xEbG+tSPURE5AR3JjYi4uWLxdxMQFcAKSQCCIlyvd7yJDb+POveAVE1Ghh+3QORes19dRYnSfIMLuXhjpYRkgJQqeXZcbJvARCQwqKB4Ijy12k0QHiwNZDTXXBCIoHIOOcTFV7oUuOQjBv2z3VeFsTFkxApRwGjEVJCDSCuqnU5kxFI89MZX8r6nJuM8vgTRQ97XVb0/tsdRRj0EMd+tWpVIrXtCUX73kBhHsSezyD2f2c5PpCkgOmY4zcQiYgAwKXbOzk5OZg8eTLGjh2LlStXmpePGDEC9erVw/z58y2WF3fo0CGsX78eEyZMwFtvvQUAmDhxIp544gkcPnzYouzMmTNhNBpx5MgRxMTEAACefvppDB48GHPnzsVTTz2F4OBgc/mCggIcPHjQ3EoiOjoa//znP3H06FE0btzYoWO7evUqEhISrFqZVKpUCQBw5coVh+qxZ8OGDbh8+TLmzZvnUj1EROQEd114aoIhqdQQhbm3p46VILQhQHC469OQliNGkZfj2j5L0H0g/+1WNmoCRcXKbq0bAKBQQBSUc9wtd5xDkwG4VbyFqARExAJqDeDKcGAmE6D0UC9fo8Hx8RiUKiChpnxRHxELKLSO70dXAASFlS9Gd8qTP1e2ui+IiycApRpQqYAKlYDgMNtdMiQJIi8Ljs3J50VClP0+FkIeJLTMuvx4wOCbV6zHDVKpITXpCKErhGn7Kvk9XbK7kTAB5096L04iuiO49Nd3586dyMjIwODBg3Hz5k3zQ6lUom3btti9e7fdbXfs2AEAmDx5ssXyKVOmWDwXQmDr1q3o06cPhBAW++nZsycyMzOxf/9+i21GjRpl0fWjU6dOAIA///zT4WPLz8+HVmv9Q6BonBBXBkI9efIkJk6ciPvuuw8jRowodz1EROQkd/VHL2oWbr7LKACTEZJCYaNJvJPKE6POf+/a2iaVP2ZPjCmgDZH/1bk6yLkHxztwJqGTUFPuGpNWjpsw/tIVxWhAaRkJ6d4uUDTpCikyDuLWZeCmja4LQvjn1M6OUCjlVjfBEYAmBHZfDH8eY6PQxuepQgIktQYwGqAY9C8on/wPFMNfAGo1siznz4M8E5FfcqnFxpkzZwAA3bp1s7k+IsJ+k86UlBQoFArUrl3bYnm9evUsnt+4cQMZGRlYuXKl3dYfqamWI4RXq1bN4nl0tNxvNj093W48JQUHB6Ow0LoJZEFBgXl9eVy7dg29e/dGZGQktmzZAqVSWa56iIioHCQP3rt1V93lqUflvvE1vEP4T8yR8ZC0IRB5mUCBq7Ot+MH7KzxGvhi+egZQa/+OSa2Ruz+UlSDx5GfEGYrSfx+Js/sg1FpIFWvJrTbSrwPpJbtOSYDCa+Pku4/5PAlApZG7TUHYSbz5yfmyRaWxXnY7cSYFh8L0+06IrDRIXR6HovtgmNbOl7vdAHKLHCIiJ7j0q8J0+8tp3bp1qFixonXlbvjRUrSPoUOH2m3d0KRJE4vn9pIFzow0X6lSJezevRtCCIvuKFevyn01K1d2vmluZmYmevXqhYyMDOzZs6dcdRARkQvcddFWdBfYPKCfBEgKeTwDV7tKlCNGSRs4s44BkO8ya2xc9DjC1RYxxeuJSoCkCYbISQdyHb/5Yb9OD15kKtWw1zXDglortxxKtLxRJCXWg7hyBsjNKH17WxejPiBpgkr/3ZYjny8BQHFPCyA2EcIqsSEgacp3I8qjJAmlnsviA+QKIZ97e4kef0lE2RIdL8dX/DxmpUGYTJAUittjaxggNe0EKbYyEB4lJzYkCYip5KuoiShAuZR5KGptER8fj+7duzu1bfXq1WEymXDu3DmLVhqnTlmOkl40Y4rRaHR6H65o1qwZ3nvvPZw4cQINGzY0L9+7d695vTMKCgrQp08fnD59Gt98841FnURE5CXuuguoy4cw6gFNsHx3XKWGdLs/v8vKEaMisRqMxw9bDsDnSghNWkBRpToUUXKLR1W7TlAkVoN+xyduqR8mExSVqpRvW3dceEsSUKEyJJUGojBPvkOuDZX7+5e3CbykgFRGKwNXSJIEoQ3++462PTlpEMXv7MdVl8eDSU1xrEVKUKhrgbpLhUrAhePWicKIWEgxleVkFCRICdXl5Xl2pg+OSfRomOWmUtseQFRSAJqgv6c1Lnq/2+tS4yeJKFukkDCg1r3An0f/Po+6AogzByDVawnpvoeB7HQgOgEiJxNIv90CWwgo7m3vu8CJKCC5dNujZ8+eiIiIwPz586HXWw9wdOPGDbvb9urVCwCwdOlSi+UlZzlRKpXo168ftm7diqNHjzq1D1c8+uijUKvVWL58uXmZEAJvv/02EhMT0b6941+4RqMRAwcOxC+//ILNmzfjvvvu80TIRERUFndeBGTenrUhNArQBEPkZ7k+cChQrhiV9Rq6dWwE9UOPInjav6GoLM80oR04AsHT/u22+oHbMZeH2omBMO2RlJBuv86SNgRSVAKkqAQgzIUpXx2ZTtVVIQ7M2qIrkFszFD2KLijzssoejFIdBMmN0wa7QlKpgZjKsOpqYdADweGQqjaAVK2B3FLq6jm5NYplDbe7Gflhiw0AUNl5HwshN+RQa+XEqaSQv2fsJdz8OLEBQE5QlEhOiT2fw3RyH6R6LSC16g5cOQfTF6vl5I0kAcGhQM1GdmokIrLNpb9eERERWLFiBYYNG4YWLVpg0KBBiIuLw4ULF/DFF1+gQ4cOWLZsmc1tmzVrhsGDB2P58uXIzMxE+/bt8e233+LsWevp35KTk7F79260bdsW48aNQ8OGDZGWlob9+/fjm2++QVpamiuHYVOVKlUwZcoULFq0CHq9Hq1bt8ann36KPXv2YMOGDU6NjTF16lR8/vnn6NOnD9LS0rB+/XqL9UOHDnV3+EREZIujzfkdYdQDmdddr6c4hbJcd/0VdRu4dRDBgoVzULBwjtvqsxIeASk2vnzbuuNCzmSAuO74gOIOcUfCpSwRcTbGkSjD+cOOv9ujynlOPERKqAFx85LlwrxMiOM/ObC1gFSxhifCcg+FAlCo5Bl6LAjHp9xVafy7KwoAqXJNSE07Qhz68e+FugKIXZvsvC8lKHo8AYlj0BGRk1xOyw8ZMgSVK1dGcnIyFi1ahMLCQiQmJqJTp04YNWpUqduuXr0acXFx2LBhAz799FN069YNX3zxBapWtZyLPCEhAb/99hvmzZuHbdu2Yfny5YiJiUGjRo2wYMECVw/BruTkZERHR+Odd97BmjVrUKdOHaxfvx5Dhgxxqp6DBw8CALZv347t27dbrWdig4jIOyRJglBpLPuw+5NyXhwra9WRL5T8ZEaLUkkSlPUbW02n7vjmEoQ6yP9mTdB4vsWGpAmCCIm4PRWquytXyAOP+hEpJAKo1hDiwnHnN658D6SIWPcH5U6aYKAgB+VKtEoK7yTT3EBq3xuABHFoDwwmE1Q2BnQ1CUChUkHx0DBIibWtKyEiKoMkSozMNHz4cJw/fx4//PCDr2IiyIOmKpVKrFq1CqNHj/Z1OEREdwxRkANk3/J1GLZFxpd7sMPcZ0bCeOKI/yc3JAnaJ6dAO3B4uasQBTlAZmrZBb1FqQZiqpQ7WeMMoSsALhx1/zSf8TUgRca5t043Edf+hLh4Eg63tqpUG1JiXa+cD5eZjLfHPnHifEoSoA0LuBlfbh3bj68Wz0G/5vWhVv4d+62cfHxx/iZGLlwOKSzKdwESUUDzj46URERE3qINAXLS3H9h6CqF0qVxGjSPDUT+sUNuDMhDlEqoH+rjWh3aUPmOtasz0LhLSITXLqIlTRBEbFXgxgX3VRocAfhx6wapYi0gJALi6jkg6xYMBiOUSoXcekcIGIxGqFUqICwaUsVakKITfB2y4xRKIChM7n5iMsJgMNicVdBoNMrdoBUqQBvsvtmBvCgzOApD3/8vpmz+FvUTYhCiUSEjvxAHLl5Hw8b3YhSTGkTkApuJDWemRQ00+fn5yMzMLLVMhQoVoHFgGrqcnBzk5OSUWiYuLs6p8TiK3MnngIjIlyRJAREUDuR7oDm/K4JduzhWdXoACI8Eskv/G+dTSiVUXXtCEenCIJ243R0lJKLsqUu9QgKCwr27y8h4eUDJDDeM8aINkVs4+HnrBikiFlJELFo1boD+Xe9D/epVEB0RhsycPJy7dAWrPvsfDp46azMp4PcUCiAoDHpdIVa9txzDnxiMkOC/W25lZGbio81bMX7SZPvTvgaQmzn5+DHnUtkFiYicYPXtHxoaiuxsO1Nm3QE2btxY5tgfu3fvxv33319mXa+++ipefPHFUsv89ddfqFGjhhMRyorOQVhYmNPbEhFRGYL9LLEhKVyeZlPSaKDp2x+6j9733+4oRiM0jw10T10hUUB+ttyU35fCK0DycpcASZLkVhsKJZB2pfwVBUfISQ0/mQnFEX9euY4Xlr3v6zA8wmgSGP/Pf+GZqc8hOjoKYaGhyMrORnp6BmJiYjB+8rO+DpGIyG9Z/SW799578d577+HWrVuIifGvQaTcoWfPnti5c2epZZo2bepQXcOHD0fHjh1LLVOxYkWHYyuuaIyTe++9t1zbExGRfZJSBREaDeSm+zoUWXiFcs2GUpKm7wDotmwACv1sYE0AUCqhbNgEyvqN3VKdpFBARMYD6VfdUl+5qIPk5IAPSJIExCRChEQC1/+UW3A4vLECiKsGRMT6fUuNu5HBYMCNGzdx48ZNX4dCRBQwrAYPvXbtGhITE/Hiiy9i1qxZvorrrmYwGNC7d29cuXIFR44c8XU4RER3JCGE3JTf1zOkaELcOmij7r9bUfDaf9xWn9uo1QhbvRWKxKpll3WCyLoht9zwOgmIrQJJqfbBvi0JIeRuORnXYczNhPJ2CxKjyQSFJJmTF0alGsoKlYDwmIBqpVFchQoVkJ5uOyGp1+sDsyvKbQUFBQgOtj14cFxcHFJT/WjA3HL4888/Ubu27RlPmjZtap5FkIioPKy+/StWrIhp06Zh9uzZyMrKwujRo1G/fn1fxHbXMZlM+Omnn7Bo0SLs2rULW7du9XVIRER3LEmSICJigLSrKNd0i24JQgGEV3Brlerej0O/+2sYD+8HjD7uplGM9qkpbk9qAJCnKDXovT/9a1SCXyQ1gNutN8KigbBotG3RHCqjHo3q1EJoSDB0Oj3+unQF+4+fxP6Dh1EtKoAG1iQiInKQzbR2cnIytFotXn/9dSxatAhhYWEICQlhc0UPMplMyMrKQmFhIRITE7Fp0yb07dvX12EREd3RJKVa7s6Q6YZBGJ3euSRfHLt5MEBJkhD83IvIGfm4PNaGrwejViqhrN8YmscGeaR6SVJARFWUu6R4q/VNZDwkbYh39uWkQp0e+48dw2+Hj/k6FCIiIq+xmdiQJAnz5s3D//3f/2Hnzp04c+YM8vPzvR3bXSc8PBytWrVCu3btoAiwucmJiAKVpAm6ndzwYjNvSQIiEyCpyp6BqzwUCZUQPGch8mdNud0YxUfJDaUSUoVYBM9Z6NEBNiWFAqJCJblrkc6Tv1duJ6P8NKlBRER0tyq1I2JQUBD69HFxrnkiIiI/J2mC5bv+mamA8PCMIgqlfMffQ0mNIup2nYCZ85H/nxcASN5vuaFUQgqPROjr70ERG+/x3ZlbbhRkA1m34PZkjiYYiIgL2LEpiIiI7mRsFkBERARAUmuBCpUBrWvTrpYqOByoUNnjSY0i6q49ETz3VUChkB/eolBCio1H6FsfQFG5itd2K0kSpOAIILaqnIhwS6UKICIWiKrIpAYREZGfYmKDiIjoNkmhhBQRC0TEyS0r3EWhkruehFWAJHn3T6+6UzeEvP4epPiKchcYj5LrV7Zuj9C31kFRKdHD+7MThVIFKboSEFPl9nSsfx+3KKXlisUalUZ+H8RVgxQcwXHGiIiI/BgTG0RERCVI2hCgQqJ8YavWlr8iTTAQGS+30tAEuS9AJ6kaN0PY6i3Q/GOwvMATrTcUSiA4GEHPv4SQ+UugqBDj/n04SVJp5ERVXHUgMgEIjcKBYyeRlpFhUU5vMOD4qTO4lVMoz7JSIRFSTBVIweFeT0QRERGR89imkoiIyAZJkgBtCKANgTDo5UEpDYVIT72OyPBQq0GejSYTsnPzEBWbAKg1gCbEr7ouSEHBCJo0HapO3VCw5BWYzp8DlErXp4RVKAAhoOp4P4ImPeeV8TScJSkUQFAogFD838Kl+N///gdJkqDVaqDXG2C8/Rr88ssviKvdwLfBEhERkdP85xcXERGRn5JUakClBgAsXvAGli5ZgoT4WAQHBUEIgYLCQly5dh0LFizEM8884+NoS6dq2hKhqzbDeOwQdJ9tguG7/8nTwioUjic5lCrAaADCI6HpmwTNI49DkVDJs4G7mRACBQVemh6WiIiIPIqJDSIiIifl5OYi569cX4dRbpIkQdW4GVSNm8E0YRoMP3wD46njMB4/DMOFv+z2UzWq1NDUawhlg8ZQNm4G1X1dIKnVXo2diIiIqCQmNoiIiO5iiugK0Dw6wPz8yREj8McnmxGhUiJIoYBRCBSaBK7p9Hhl7Xr069/fh9ESERERWWNig4iIiMz0CgUOZOfbXsmZQYiIiMgPcahvIiIiIiIiIgpYTGwQERERERERUcBiYoOIiIiIiIiIAhYTG0REREREREQUsJjYICIiIiIiIqKAxcQGEREREREREQUsJjaIiIiIiIiIKGAxsUFEREREREREAYuJDSIiIiIiIiIKWExsEBEREREREVHAYmKDiIiIAAC//PIL9u3bZ3f9559/jgsXLngxIiIiIqKyMbFBREREePfdd9GhQwccOXLEbpkPPvgArVu3xuHDh70YGREREVHpmNggIiJy0JUrV3Do0CG763///XfcuHHDixG5R3p6OsaPHw8hRJllU1NTMWXKFM8HRUREROQgJjaIiIgc8Msvv6Bhw4b44osv7JZZt24dmjZtiuPHj3sxMtft3r0bRqPR4fI//PAD8vLyPBiRZ2RnZ5eaeDp//rxDyR0iIiLyL0xsEBERlcFkMqFfv37IzMwss+zVq1cxdOhQL0TlPpUrV3aqfIUKFRAcHOyhaDzj22+/RaVKlXDgwAG7ZQYPHozHH38chYWFXoyMiIiIXMXEBhERURkOHDiAq1evOlX+8uXLHozIvZo1a4aYmBiHyz/44IOQJMmDEbnXjRs30Lt3b+Tm5pZZ9tNPP8WsWbO8EBURERG5CxMbREREZYiMjHSqvCRJCA8P91A07hcUFITp06c7VFaSJLzwwgsejsi9vvjiC6daYWzZssWD0RAREZG7MbFBRERUhtq1a6Nq1aoOl2/VqhUiIiI8GJH7TZw40aFWG0lJSWjcuLEXIvKdQGqNQkRERExsEBERlUmSJMyYMcPh8s8//7wHo/GMsLCwMlttSJKE2bNneyki9+nQoYNHyxMREZFvMbFBRETkgDFjxiAxMbHMck2aNMFjjz3m+YA8YOLEiQgKCrK7vnPnzgHZWqNOnTro06ePw+WfffZZD0ZDRERE7sbEBhERkQOCgoIcGltizpw5UCgC889rWFgYkpKS7K5fuHChF6Nxrzlz5jhUrm/fvmjRooWHo3E/vV6PpUuXIiUlxW6ZRYsW4dKlS16MioiIyDskwQnbiYiIHFJQUICEhARkZWXZXF+lShWkpKQEbGIDALKyslCjRg2kp6dbLO/Vqxd27Njho6jco2/fvti+fXupZfbt2xdwiQ29Xo/+/fvj888/L7Ns9erVsXv3btSsWdMLkblfhQoVrN6bRfR6PVQqlZcjcp+CggK70yjHxcUhNTXVyxG5159//onatWvbXNe0aVMcPHjQuwER0R0lcH95EREReVlQUBBGjRpld/2MGTMCOqkBABERETh16hR69eqF6OhoVKpUCVOnTsUXX3zh69BcVlarjc6dOwdcUgMAdu7c6VBSAwBSUlLw2muveTgiIiIi7wrsX19EREReNn/+fERFRVktr1KlCiZMmOD9gDwgLi4OO3bsQFpaGq5cuYJXX331jpgppGXLlqhXr57d9QsWLPBiNO7z3XffebS8PzGZTL4OwSNMJhN+++03u+vz8vJw+PBhL0ZERBRYmNggIiJyQkhICI4ePYo2bdpAo9FAq9Wia9euOHbsWMC31rgbLF261GaS5t5770W7du18EJHr7rnnHo+W9wf79u1Dy5YtkZmZabdMs2bNsHv3bi9G5R5GoxFjxoxBly5d7JbJzc1F06ZNMXv2bLAXORGRNf4CIyIiclJiYiL27t2LwsJCFBQUYNeuXYiIiPB1WOSAHj16YPXq1QgPDwcgT2Hbrl07/P777z6OrPx69uzp1NgSjzzyiAejcb8zZ86gW7du2L9/f6nljh07hocffhh//PGHlyJzj1WrVmHNmjUOlf3Pf/6Dr7/+2rMBeUBWVhY2b95sd/3ly5fx5ZdfMmlDROXGwUOJiIgIAGBKT4Px9HGYzp2GyMkGdDpAIQEaLRQxcVDUbQBl7bqQgmwPcBhIhBDIz8+HVquFUqn0dTguGzduHN57770yy9WoUQOnTp2CRqPxQlTu8eKLL2Lu3LkOl584cSKWLVvmuYDc7JFHHnFqDJvx48dj+fLlHozIvW7evIkePXrgwIEDZZZ99tlnsXjx4jui6xsReVfgDh1NRERELhEGPQw/fw/9NztgPH4YIu2WvEKhkB/FGY2AEIAkQVGlOpTNWkHT+x9Q1m3o/cDdQJIkhISE+DoMt/m///s/rFmzBgaDodRyM2fODKikBiDPpuGMc+fOeSgSzwgNDXWqfFhYmIci8YxXXnnFoaQGALz++uvo378/2rdv7+GoiOhOw64oREREDhJCQBgNEIV5EPnZEHlZ8iM/W15mMvo6RIeYbqaicO07yBnwEPLnTofh5+//TmoAgMkEGAyWj6IGnkLAdPE89Ds+Qe7TTyDnqSHQff05RGGBbw6GAAA1a9bEyJEjSy1TpUoVDB8+3DsBuVGrVq2cKt+6dWsPReIZpY2t4Y7yvuZs15mvvvrKQ5EQ0Z2MXVGIiIhKIUwmoDAXKMwDDDpAlDErg6QA1FpAGwJoQyBJ/nMPQej1KNywCroN78mJCnfMMCEpAGGCFBWNoGlzoG7v3xddQgj5PJqMAAQACZAkQKWBpAjsLil//fUXateubXecgqVLl+KZZ57xclSuS01NRc2aNZGXl1dmWaVSiZMnTwbUAKm5ubmoVasWUlNTyyzbuHFjHDp0KKAGKn7wwQfxzTffOFx+xYoVePrppz0YERHdiQLnW5GIiMiLhEEHkX0LuHUJyEkD9AVlJzUAuYwuH7i9rchJhzDqPR9wGYxnTyH3qcHQrVspdytx17SZt18TkZmJ/FlTkPfKLIjsLPfU7QZCCAhdPkTWTYhbl4DUv4C0y0DGNSDjuvxv+lXgRgrEjRSI9GsQuRkB0/qmuJo1a6JFixY212m1Wjz11FNejsg94uPjMXHiRIfKDh06NKCSGoDcFeW5555zqOycOXMCKqkByIkNR0mShG7dunkwGiK6U7HFBhERUTFCmIDcDCA/270Vh0QCIZFeHxRPCAHdx2tQuGoZAOl2SwUPUiggRUQieM5CqJo614XAnYTJBBRkA3mZgLH0cSfsCgoDgiMgaYLcG5wHXbx4EfXq1UN+fr7F8nXr1mHo0KE+isp1jrTaCMTWGkUcabURiK01AHlGlBo1aiA9Pb3MsgMHDsTHH3/shaiI6E4TWN+MREREHiR0BUDaFfcnNQD5Ajv9KoRB5/667RAmEwqWLULhu0vlFhreaIVgMkFkZiJv+njof/7e8/uzQRTkADcvyK1mypvUAICCHCD9CkTG9YBpwVG1alWcPXsWSUlJqFWrFjp16oRdu3YFdFIDcKzVxpAhQwIyqQHIrTamTp1aaplAbK0BABEREWUeGyC31pg9e7YXIiKiOxFbbBAREQEQeVlAbtl3FN0iPAZSkGdnNhBCoGBpMvSfbfLofuySJAASgl96zWvjbgiTEci6KY+J4m6SAoiIgxTk3AwW5D6pqamoVKkSTHa6UZ05cyZgExuA3GojOjoaer1117XIyEikpaUFZGIDkFttVKtWDZmZmXbLsLUGEbnCbmLDaDTixx9/xNatW3HmzBkUFHC0c08LDw9Hy5YtkZSUhIYNA3P6PCKiQCRyM+QWFd4UVgFScLjHqi9YswK6D1Z6rH6HSBKgVCJk0dtQNW3p0V0Jg04eK8PTLStCIuVz5+UuRSTr0aMHdu7cabW8efPm2L9/vw8icq8ZM2Zg4cKFVsvfeecdPPnkkz6IyH1eeOEFJCcn211/9OhRNGrUyIsREdGdxGZiIzs7G7169cJPP/2EqlWrolWrVggODuYfcQ8SQiAjIwN79uxBdnY2Jk+ejDfeeIOvORGRh4m8THlMDV/wUMsNw8E/kPevcW6vt1wkCVJ0BYSt+QRSmGcSOcKgk7sQOTK4qzsER8jnjn+jvU6v1+Pee+/FqVOnzMsSExNx8uRJhIV5thWUt7zwwgt46623kJOTg+joaMyZMweTJ0/2dVguy8rKQoUKFWA0WicfGzZsiGPHjvkgKiK6U9hMbHTr1g379u3D5s2b0b1794Bt9haICgoKsGLFCvzrX//CvHnz2NeQiMiDhC4fyCx7ikWPiqoESa1xW3UiPw85Ix+HuHXDfTOfuEqhgLpnXwRPn+P2qoVRD9y67L2kRpHQKEhhFby7zzIIk1EeH6YwDyjMl18TSQJUWiAoBAgKd+t7zZf27NmDnTt3omPHjujRo4evwyEHzZw5E/Pnz7dYplKp8Mcff6Bp06Y+ioqI7gRWiY1jx46hcePG2LJlC/r16+eruO56zzzzDDZv3ozLly9DqVT6OhwiojuOMJmA9CveGVCzNEo1EF3JbXf/85cmQ//ZZu9f6DsgZMFbULVu77b6hBBySw1DodvqdEpURUjaEN/suxihK5Cnrs26WfZ5D4kEohIghUZ6JziiEpYuXYrFixcjPT0ddevWxYoVK9C6dWtfh0VEAc4qsfGf//wHixYtQmpqKrRara/iuuv9+uuvuO+++7Bnzx507NjR1+EQEd1xhKcGmSyPkEhIoVEuV2M8dQy54/109guFAlJ0DMI++gKSSu2WKkVepjzzia8olEBMVUg+atkqhJDHFbl1BYCTY8GHRQNx1d12LoiIiHzJ6i/x+fPnUa9ePSY1fOzee+8FAKSkpPg4EiKiO4/QF/hPUgMA8jIhDNYzITircNtHgL+28jOZIG7dgMFNU8AKg963SQ1Abu3joxiE0QBcOil3w3E2qQEAOelAylGIwjy3x+Ytwg9bJblMCHmKYoPu74fRIC8nIiK7VCUX6HQ6BAUF+SIWKiY4OBgAUFjoo+a1RER3srxsX0dgrSAbcGHMBlNmOgy7vwZsDMznNxQK6D75GOrO3V2vy1tT85alIBsiLAqS0nstH4TJCFw+7XpyzmQALp2AqNLAL7rUlEUYDcCtKxCpKUBBLiBMEJIEaEMgxVUDYqsEbgsUYQIMerlbla0khqQA1Fq56xoHrSUisuJ028k1a9ZAkiScP3/eqe3mzp3rcP9hSZIwd+5cZ0MjIiIqkzAZAZ0f3qXOz3HpDrT+y8/9O6kBACYTjIf2wZjyp0vVCJMRKMhxU1BukJfl3f2lXnBfiyOTCbhyRn5N/ZQQJpgunYI4+C1EylF5gNSiz4oQQEEuxMUTEAe/hSnlmF8fi00GvXxM+gL7LTOECdDlA/lZcguOACWMRohzR2D67X8w/fRfmP7YBZF6yddhEdEdgNOdlMJkMmHhwoWoWbMmgoKC0KRJE3z00UdO13Ps2DEkJSWhVq1aCAkJQWxsLDp37ozt27d7IGoiIipVvh+21gAAyBdo5aX775bAaK6uVEL/1eeu1eFv5zA/22vdIkRuJpB9072VGnTATf+8uBQmI8SZfcDVc2UP9CtMQGoKxKm98mw5gcCgcz7RWpgLBMrx3Sb0Oph+2wnT2v/A9PV6iP27IY78DPH7Tpi2vAnjpqUQZw/7OkwiCmBeS2zMmjUL+fn53tqdW8ycORMzZszAgw8+iDfffBPVqlXDkCFD8PHHHztVT0pKCrKzszFixAgsWbLEPIVr3759sXLlSk+ETkRE9vjzmALljM2UmQFxxT8vTK0YjTAe3u9aHf6W2BAmr7yvhBDADQ+NvZWZKo8940eEEBB/HQIybzi3YU4GxJn98sxH/syol1thlEdhnu9ndHKQKMiD6dO3IfZ9CxTc/pyYTHL8RQnBW1dg+t8GmH75EiIQErRE5Hesxtjw2I5UKqhUXtudyy5fvozFixdj4sSJWLZsGQBg7Nix6NKlC6ZPn46kpCSHp2F9+OGH8fDDD1ssmzRpElq2bInXXnsNTz75pNvjJyIia0KY/PtOp0EHIYTTU7+azpz0UECeYTx3CsJohFSOgU6FyU/Pob4QCArz7D7ys+X9eErmDSC2qufqd1ZGKpB2rXzbZt+SB1aN86PjKU4IQOdiIklXAASFuiceDxFGI0w71gA3r5beouz2OnHgOyAoBFLzLl6Jj4juHG5psfHll1+iU6dOCA0NRXh4OHr37o1jx45ZlLE1xkZhYSGeffZZxMXFITw8HH379sWlS7bvOF2+fBmjR49GQkICtFotGjVqhNWrV1uU+e677yBJEjZt2oSXX34ZVapUQVBQEB544AGcPXvWqWP67LPPoNfrMWHCBPMySZIwfvx4XLp0Cb/88otT9ZWkVCpRtWpVZGRkuFQPERE5wQ0zj5gpVUBkvHwhGFMFCI12vU5hKtddWOPp44AbpxzVDBqJ0LWfIvybfYjYdQDKpi3dVjcAQKeD6eL58m1rcMOFvaQAIhOA2GpAfA35X1fPnycTDkWcnYElrhqkOq0h1WkNqB0YGD7zpl/dLRep5wFYJ/mkem0hNX8QUsuHIDXtCqlaQ/mcltz++nm/Oh4LxVsrlBQUDoREWj6UNm4Omgxyywc/Js4dBq6lWB2r1KwzFEOmQ/HUy1CMnAWp3UN/b7P3a4gCP25ZR0R+yeUmFOvWrcOIESPQs2dPLFiwAHl5eVixYgU6duyIAwcOoEaNGna3HTt2LNavX48hQ4agffv22LVrF3r37m1V7vr162jXrh0kScKkSZMQFxeHL7/8EmPGjEFWVhamTJliUT45ORkKhQLTpk1DZmYmFi5ciCeeeAJ79+51+LgOHDiA0NBQNGjQwGJ5mzZtzOs7duzocH0AkJubi/z8fGRmZuLzzz/Hl19+iYEDBzpVBxERucCgc19dEfHyxUZuBqDSQAqJkC+i8jJcq9egs30RUwrj6ROu7bMkjQaGX/dA3akbpIqV3Vv3bcbTJ6CsUdv5Dd2RQJAUgEotD8RoMgKhUZDCouVBJ/PLORCovrBcrW2c4kwXnJBIIDIOwmSC5GjSy3R7mlG1tnzxuZEoyAWy7CRy8rIgbl0BICBVrAUpoYZcPrVEN538bCA3EwiL8nS4zisrQWcyWr7X7SU8DTpA47+zGYrDP8mzuBRLMElte0LRshvE9QsQB78HVBpAG/z3RiYjxKl9kJp28kHERBSoXEps5OTkYPLkyRg7dqzFWBEjRoxAvXr1MH/+fLtjSBw6dAjr16/HhAkT8NZbbwEAJk6ciCeeeAKHD1sOHjRz5kwYjUYcOXIEMTExAICnn34agwcPxty5c/HUU0+Zp0cFgIKCAhw8eBAajQYAEB0djX/+8584evQoGjdu7NCxXb16FQkJCVY/UCpVqgQAuHLlikP1FDd16lS88847AACFQoHHH3/c3M2FiIi8wF2zCWiCIanUEIW5ty+EJQhtCBAc7npioxwxils33HrnVveB/Ldb2agJFJ5IbCiUEOlp5dvWHd1QTAbgVvEWohIQEQuoNUC5hwMT8l1pyfnuNQ7VXvJCtzRKFZBQE0i7Kh+XwolERWGuXyQ2kHHd7ipx8YQ87alKBVSoBASH2enmIEGkX4Pkj4mNsj7nQjj2XjfqAfhnYkNk3ARSL1ouVKkhNekIoSuEafsqOWFjoyWdOP4bwMQGETnBpXarO3fuREZGBgYPHoybN2+aH0qlEm3btsXu3bvtbrtjxw4AwOTJky2Wl2x9IYTA1q1b0adPHwghLPbTs2dPZGZmYv9+y0HIRo0aZU5qAECnTvIX459/Oj69XH5+PrRa6z/sQUFB5vXOmjJlCnbu3Im1a9eiV69eMBqN0OncePeQiIjK4KZm6UUtKszTqwrAZJTvjNtoEu8c52MUhf416GOZJAnQlbPlhSe6FmhD5H/LO5BjEU92e3Am4ZVQU546NM35mzD+MpWo0Ovk94kd0r1doGjSFVJkHMSty8DNi7YLurOVlrs48j5RKOVWN8ERgCYEtrrkOFyXr2SnWy+rkABJrQGMBigG/QvKJ/8DxfAXgFqNSmyb4ZUQiejO4VKLjTNnzgAAunXrZnN9RESE3W1TUlKgUChQu7ZlM9R69epZPL9x4wYyMjKwcuVKu60/UlNTLZ5Xq1bN4nl0tNxvNj3dxhesHcHBwSgstP7RVVBQYF7vrPr166N+/foAgOHDh6NHjx7o06cP9u7d69mmq0REJPPkNYC7vsfLE6M/X9zY46XpUcsUGQ9JGwKRl+nSdLsyPzgP4THyxfDVM7dbXtx+X6o18kV+Wa+7HxyCI8TZfRBqLaSKteRWG+nXgXQbA40G4mfDfJ6E3E1DpZb/72rizdtsvfa3W5ZJwaEw/b4TIisNUpfHoeg+GKa18/+eXchfvh+IKGC4lNgw3f5yWrduHSpWrGhduRtmQSnax9ChQzFixAibZZo0aWLx3N5sJc4MIFWpUiXs3r3bqr/s1atXAQCVK7veNLd///546qmncPr0aauEDhEReYC7kg9Fd7XNY2FIgKSQZ+xw9Qd5OWKUbLQw9GtClH9cAHedQ0kBRCVA0gRD5KQDuY7f/CilUjfUYYfCwd9Uaq3ccijR8neFlFgP4soZeUyY0pRjphpPkJSq0n+35cjnSwBQ3NMCiE2EKJnYkHA7KeBnynoPFx9/Qwi5243Cznnx5/tiITZmCcpKM4/7IvZ/BxgNkJp2ghRbGQiP+juxEezhGYaI6I7jUuahqLVFfHw8unfv7tS21atXh8lkwrlz5ywu6k+dOmVRrmjGFKPR6PQ+XNGsWTO89957OHHiBBo2bGheXjQAabNmzVzeR1F3lszMTJfrIiIiB9i7OHCWLh/CqAc0wfLdcZUakiRB5JVz4MniyhGjFBltNUCfK5RNWkBRpToUUXKLR1W7TlAkVoN+xyduqR8mI6Tw8PJt6+gFfmkkCahQGZJKA1GYJ98h14beHrDRhW497np/2SAplRAqddkz++SkQRS/sx9XXR4PJjXFsRYpRd1yfC0yDrh82np5RCykmMpyMgoSpITq8vI8GwOrCgEpItajYZabQml7QFBJISf9jAb586y63bXaXhchpR8mborEVAIiY4HMm38v0xVAnDkAqV5LSPc9LHdXiU6AyMkE0m+3wJYkSPXdPBMTEd3xXOoI3LNnT0RERGD+/PnQ663/0N64ccPutr169QIALF261GL5G2+8YfFcqVSiX79+2Lp1K44ePerUPlzx6KOPQq1WY/ny5eZlQgi8/fbbSExMRPv27R2uq2RXGQDQ6/X44IMPEBwcbJE4ISIiD1Jpyi7jqMwb8mCOoVGAJhgiP8v1gUOBcsWoqNPArdO9qh96FMHT/g1F5aoAAO3AEQie9m+31Q8AyjoNyi5kizsGtpSUkG6/zpI2BFJUAqSoBCDMhSlfVRrPdysNcuAutq5Abs1Q9ChqQZSXVfZglJLCsWlhvUAKjQRCbHRpNuiB4HBIVRtAqtZAbil19ZzcGqUkTZCcIPFHKjvvYyHkZihqrZw4lRTy94y9hJs7v9PcTJIkSE06WC0Xez6H6eQ+SPVaQGrVHbhyDqYvVlskb6SGbbwZKhHdAVy67REREYEVK1Zg2LBhaNGiBQYNGoS4uDhcuHABX3zxBTp06GB31o9mzZph8ODBWL58OTIzM9G+fXt8++23OHv2rFXZ5ORk7N69G23btsW4cePQsGFDpKWlYf/+/fjmm2+QllbOkdVLUaVKFUyZMgWLFi2CXq9H69at8emnn2LPnj3YsGGD3e4utjz11FPIyspC586dkZiYiGvXrmHDhg04efIkFi9ejLAwNrcjIvIKd14EGPVApv2ZG8pHcnqqVwBQ1m1QbCBT1xUsnIOChXPcVp8VpQqKmveUb1t3JDZMBojrjg8o7hBvJATCY8xdMBx2/rDjw2aEV/CrMb+khBoQf1nOlIe8TIjjPzm2fXwNvzoeC0oV5H4kJc+OAHR5jtWhUHq0lZA7SPVaQhz8AcjJ/DvJpiuA2LXJ/vuyUTv/nMmGiPyay+05hwwZgsqVKyM5ORmLFi1CYWEhEhMT0alTJ4waNarUbVevXo24uDhs2LABn376Kbp164YvvvgCVatWtSiXkJCA3377DfPmzcO2bduwfPlyxMTEoFGjRliwYIGrh2BXcnIyoqOj8c4772DNmjWoU6cO1q9fjyFDhjhVz8CBA7Fq1SqsWLECt27dQnh4OFq2bIkFCxagb9++HoqeiIhKkhQKCHtNwP2Bunx3/ZV1y9n6wUcUNWpBUpevCb2kUPrnOfTGFKmhUXLXA3dMeWtLVIJn6i2vCpWB1AtAbiacG9VUAoJCgPhqZRf1FUmSW5S4MiCoP0zLWwZJo4Wi7ziYPnkbyM8pewyimo2g6NjHO8ER0R1FEiVGZho+fDjOnz+PH374wVcxEeRBU5VKJVatWoXRo0f7OhwiojuGyEkD8m30x/cHoVGQQiLLtWl2vwcg0t3fgtHtlEqoez+O4Cn/V+4qRE5a2YNgepUkj2Xhxu5A9ojMG0DqefdXHBoFqXId99frImHQQZz4FSjIcXALCdBoIdW/D//P3l2HN3W9cQD/nmi9UNpCcWfocC1jw23osMJgMNyZMGzDBivOcJkw3O03YMhgAwYMd3coWrc0ds/vj1BGaZMmzc1NUt7P8/TZyD25902Ttjlv3vMeprZ9BzvJ6VLSNgu1ltLDLRIbqXhSPAx/b4Nw9/LrfqdymQwGowCFXIZEvRG+dZqCVa4vyc8RIST7EaEDFyGEEOJGPHxdN7FhTQ8FM5TN2kC3fsXr7RRdltEIZeOW9p3D09e1EhuePtJNxvwCgYRoQCNCo9pUMjkQXFi884mIKVRAmVrgdy8AsS9gFATIM/hep06Q4ZsTrFglMHeZ9CvVphUpehuSGypPl+6tkRHm7YdH79VFnS6D0Kt2BZTPFwQvlRKxySn44+o93DKocGrYTGeHSQhxY+9cYkOj0WS6C0lAQABUqsz/YCQmJiIx0fInCEFBQTb14yCEEOJYTKEEV3rYt/uFI6i9wexYL69q2R66tb+KGJADMAZZ4WKQly5v32nkSnCVl/W9CBzNM4Mmlw7CGAPPUwR4dM20m4sY8hQDc8VtUV9hciVYiargmkT8OvVbdGoYCl+v/6oxNClarPnjL3w+agLkvnY0gHUGxkzVF3IluC4F2uQkqFRKGAz/NdJUKpVITk6Gt39OU0LDxftqWPIsPglT/zie7vb333/fCdEQQrKTdIkNhUIBnU6kP5QuaMOGDZn2/jh06BA+/PDDTM81c+ZMTJw40eKYe/fuoXDhwjZEaJL6HCizuAaZEEKIBZ6+rpfY8Mzi9qevyPLkhbxGKIynj4naSFRUnEPVros4DR19cgDRLpDYUHlJXh3AFCrw/O8Bj6/bmdxgQEgx0w4kboB5+mDUwt8wZNoC5A7ICX8fLyQka/A8OhYpWh16TZzl7BCzTiaHFnLkKVoSHdq2RsECBeDr64O4uHjcvnsXh48ew4OHD50dJSGEuKx0iY2QkBDs2rULRqMxW1YaNGnSBPv377c4xtqscffu3REaGmpxTJ48eayO7U2pu8OEhIRk6f6EEEIsUHmaPiV1leSG2luUybG6XRck/3tEhIAcxMsbyvrNRDkVU3qAe/kDyZarMB2KMdPSEGdcWqkGL1gWePkQSIiy/QQqTyBPUTC1l/jBOZhOb8Cj5y/xSOxNiVxAXFwcflqxMt3tQUEuum0tIYS4iHSJjZYtW2Lq1Kk4evQo6tWr54yYHCokJES0ZEHRokVRtGhRUc71ts2bN8PPzw9169Z1yPkJIeRdxhgD980FRD+BbbstOCIYGeATIMqp5FVrQlG7Hgz/HnXJqg2PQV+DeYrY0NEnJ6BNAoyGzMc6gm8gWBa25xULkyuAPEVNr+WYp4AmAYIgQBAEKBT/xWV8dZtSoTAtZciZB/APAmPUpJEQQkj2kO4vWo0aNfDee+/hs88+w71795wR0ztvz549CA8PR5cuXaBWu0nzK0IIcTNMrgB8xUko2MUvULTGk4wxeHwxDvDwNFUTuAq5HBdkaiy5eR+CiM1NGZMB/rkBOOGxqr3tavYqJubtD5b/PaBQOcxcsQHrd+3H5Zt3cP/xE9y89wB//H0MUxf/ipfKnEDhCmA5clNSgxBCSLaS7mMGmUyGvXv34qOPPkKJEiXw0UcfoVq1avDy8hJnTSzJkCAIiIuLw4EDB3DhwgW0aNECP/74o7PDIoSQ7E3tbdpuUZvknOt7+YOpxN2SUhYQCM/hY6CZkvXtVEWnUqPWL5txdftOtGzZEnPmzEGpUqVEOTVTqsFz5AZin4lyPquoPAH/YJd7X8RUnlj1v324cuVKhsd7fTXO5WImhBBCxJBh/WTBggVx6tQpbNq0CVu2bMG6deug0Wikju2d4+vri6pVq+K7775Dy5YtrdqZhRBCSNa9XpICDmglbkTp4Qt4OaZpo6J+UyhOHIbh4F6AO3mpDQDPL8ZBkTsE/fr1Q7NmzTB8+HDUqlULI0aMSLNkIquY2gs8R8ir5IaDH6/aC/DPTQkCQgghxIWYfTcREBCAfv36oV+/flLGQwghhEjKlNwIBBAlXeWGlx/glcNhk2PGGDxHTkJyfByMZ/4FRFz+YSv1oK+hbPBfw9CCBQtiy5YtWLlyJVq0aIFZs2ahXLlydl+HqT3Bc+UD4l6Itw3q23xyOvR5I4QQQkjW0AJLQggh7zzGGOCb61UTTwdOWpnM1FPDO6fDJ8dMqYTXpNmQV6nhtH4b6v4joG4flu52xhh69OiBFStWYPLkyZg8eTL0er3d12MKFRCQD/DOafe50lCogFz5JXneCCGEEGI7SmwQQgghME22macvEJDXtBWs2FReQEBeMLW3+Oc2g6k94PX9j1A0bP7qBgkm5XI5oFDA4+sJUHfsbnFoSEgI1q9fj5IlS6J58+Y4e/as3ZdnjIH55ARy5Qc8/WBXokqhAvyCgIB8pqQJIYQQQlyS8/YoI4QQQlwQkyvA/YMBnQbQxAN6rX0nVHoAXn6iNwm1FlMq4TX6e+hr14Nm9vdAUhIgOG4rWFnx9+A5ejLkBYtYFx9j6NSpE+rXr48RI0agUKFC+O677+zeFYwpVIBfILhPAJCSAKQkAQbt654jRqMRAudgMDVOl8lk4JyDyZWA2hPw9AVzRIKLEEIIIaKjxAYhhBDyFsaYqUmk2gvcoDdNjLXJrxMCBoPBtG1pagUE55DL5ZDL5aZ/y+SmHVc8fUwTZRegrNcI8verIOXHH2D4+4CpssIoUoJDJgNkMqh7DYaqQzew1O+DDYKCgrB69Wps27YNzZs3x9SpU1GjRg27Q2MymalJq5c/OOfo1eNTaOLjEByYC56eauj1BiRrNLh68zZmzp2P6iJckxBCCCHSosQGIYQQYgFTKE29N3wCwAUjfl2+FDevXEZI7mB4eqjBAaSkaPEwIgJ16n2Eth06mybTLkiWIwBe42fAcPEsdNs3wHDkT0DgAM9Cc1GZzNSU1McXqo8/gerjTyDLk9fuGNu2bYt69erh66+/xqZNmzBp0iR4eXnZfV7AlLB68vwl9u3bl+FxwQV2kCGEEEKI7SixQQghhFiJyeS48zAC0+YvzvB44dIVXDap8SZFhcpQVKgMIToS+t3bodu7EzziMQAOAYBR4FAwvG6UKXAOA+dQymSmjhUKJeTvlYWqVQcoPmgIJvL25AEBAfj555+xZ88etGzZEhMmTMAHH3wg6jUIIYQQkn1QYoMQQgh5R8kCAqHu1hvqbr3Bk5NgvHUd676fgKTLF+GvkMNTLoORc6QIAp5p9ajbszeqdAyDrFARUyWLgzVr1gy1a9fGN998g02bNmHq1Knw9fV1+HUJIYQQ4l4osUEIIYQQMC9vKN6vgsM58uCn679nOGZH2cqQFyspaVz+/v5YsmQJ/vzzT7Ru3RqjR49Go0aNJI2BEEIIIa7N9etlCSGEEPLOa9CgAXbu3Inff/8dffv2RWxsrLNDIoQQQoiLoMQGIYQQQtyCj48PfvzxR3Tv3h3t27fH779nXFlCCCGEkHcLJTYIIYQQ4lZCQ0Px+++/4/Dhw/jss88QFRXl7JAIIYQQ4kSU2CCEEEKI2/H09MT06dMxcOBAdOzYEVu2bHF2SIQQQghxEkpsEEIIIcRtVa9eHbt378aFCxcQFhaG58+fOzskQgghhEiMEhuEEEIIcWtqtRqTJk3CyJEj0a1bN6xZswacc2eHRQghhBCJUGKDEEIIIdlCxYoVsXv3bjx48AAdO3ZERESEs0MihBBCiAQosUEIIYSQbEOpVGLMmDGYMGECevXqhV9++YWqNwghhJBsjhIbhBBCCMl2ypYti927dyMmJgZt27bFgwcPnB0SIYQQQhxE4ewACCGEEEIcQS6X48svv0SrVq0wcOBAtGjRgqo3CCGEkGyIKjYIIYQQ8prBYDB7TBAECSMRT4kSJfC///0PnHOcO3fO2eEQQgghRGSU2CCEEEII4uLi0K5dO6xatcrsmM8++wyTJk1yy6oHmUyGQYMGoXTp0s4OhRBCCCEio6UohBBCiA0sVS24a0UD5xxNmzbFiRMnLI6Li4vD+PHjoVAoMGbMGImiE5enp6ezQyCEEEKIyKhigxBCCLGCVqvF559/jjlz5pgdM2bMGHzxxRcwGo0SRma/S5cuZZrUeNOyZcvcsmqDEEIIIdkTJTYIIYQQK4SFheGXX36BVqs1OyY5ORlz5szBsGHDJIzMfvfv37dpfEREBHQ6nWOCcZCkpCQMHjwYR44cMTvm888/x969eyWMihBCCCFioMQGIYQQkolnz55h27ZtVo//9ddfodFoHBiRuKpVq2bT+IoVK0KtVjsoGvEZDAY0bdoUCxcutPi8XL16Fc2bN8eOHTskjI4QQggh9qLEBiGEEJKJ+/fv27T0Ijk5Gc+fP3dgROIKCQlBy5YtrR7fp08fB0Yjvn/++QdHjx61aqwgCOjZsydOnz7t4KgIIYQQIhZKbBBCCCGZeP/996FQWN9vOzAwEIUKFXJgROIbP368VeMKFiyIzz77zLHBiMzWLV4FQcC8efMwatQot6q8IYQQQt5VlNgghBBCMuHp6YmwsDCrx/fq1QuMMQdGJL6qVataVbUxduxYqFQqCSISz/vvv2/T+EqVKmHlypWoXbs2WrRogX/++cdBkRFCCCFEDJTYIIQQQqwwbtw4yGSZ/9n08vLCV199JUFE4susaiMoKMjtqjUAoHbt2sifP7/V4zt16gQAaNWqFbZu3YoVK1Zg+PDhSEpKclSIhBBCCLEDJTYIIYQQK5QoUQLdunXLdNzgwYMRFBQkQUTiq1q1KsqUKWP2+LBhw9yuWgMA1Go1xowZY9XYAgUKoFevXq//nSNHDixfvhzNmzfHxx9/jEOHDjkqTLtFREQgNjbW7PFr167RNr2EEEKyJUpsEEIIIVYaN26cxSUmKpXKbas1Uv3www8Z3u7h4YGvv/5a4mjE06tXL6uqNswttWncuDG2b9+OzZs3Y+DAgYiPj3dEmFn266+/okCBAoiIiDA7pmnTpvj0009hMBgkjIwQQghxPEpsEEIIIVYqUaIEateubfZ4mzZt3LZaI1WrVq0wduzYNAkcDw8PHDp0yC2rNVJZU7WRO3du9OzZ0+xxPz8/LFy4EB07dkSbNm3wxx9/iB1mlly6dAm9evWyqhpjzZo1mD17tgRREUIIIdKhxAYhhBBig5kzZ2Z4O2MMM2bMkDgax/j+++8RHR2NBQsWYNOmTUhKSkLNmjWdHZbdevXqBW9vb7PHR4wYYVXy5sMPP8T//vc/7Nu3D59//jliYmLEDNNm27dvt2n8tm3bHBMIcRhaQkQIIZZRYoMQQgixQc2aNREeHp6mokEmk2HFihUoWLCgEyMTV44cOTBo0CB88sknVjVNdQdqtRo9evTI8JhKpcKIESOsPpe3tzdmz56N3r17o3379tixY4dYYdpMqVTaNN4dK290Oh1WrFhhsYHr8uXLkZycLGFU4jly5Ajq1q1r9nhkZCQ+/PBDXL16VcKoCCHEfTBOKWBCCCHEZtHR0fjpp5+gUqnQp08fi5UAxHUIgoDKlSvjwoULr2+TyWT43//+h+bNm2fpnCkpKZg4cSIeP36M2bNnS74c6Z9//kFoaKjV48eMGYMpU6Y4MCJxpaSkoEOHDvj9998zHVu3bl38/vvv8PPzkyAycZw5cwZ169aFRqPJdGxgYCBOnz6NQoUKSRCZuG7evIlSpUpleOy9997DtWvXJI6IEJKdUGKDEEIIIWlwowFISQHX6QAZA1OpAQ9Pi41T3QnnHGvXrsWWLVuQL18+jB49Gnnz5rX7vKdPn8aoUaPQp08fdOzYUbLvF+ccderUwfHjxzMd6+Hhgbt37yIkJESCyMSxatUqdO/e3erxs2bNwhdffOHAiMQ1aNAgLFq0yOrx06ZNw8iRIx0Ykfh+/PFHjBs3DomJiWbHFCtWDBs3bkTlypUljIwQkl1QYoMQQgh5h3HOIdy6DsP1yzDevArj1UsQHtwFBCHtQA9PyEuWhvy9cpCXKgNF2fchy+0+k2Op6HQ6/PDDD7h27RrmzJkjWQJh3759aNKkSabjhg0bhrlz5zo+IBF1794dq1atsnp806ZNsWfPHgdGJK4GDRrg4MGDVo/v2bMnfvnlFwdGJK41a9ZYtVU2APj7++PatWtulXgjhLgGhbMDIIQQQtxV6mcD7ljJwBPjodv7O3Tb1kGIeGS6US4HjMaM75CigfHiWRivXASMpu1C5VVrQt22CxQ1QsHkcokid20qlQrjx4/HxYsX0aNHD3Tr1g2ffvqpw18jjRo1Qq1atSxWbajVanzzzTcOjcMRbO1d4269bqpUqWJTYqNKlSoOjEZ8v/32m9Vj4+LisHPnTvTr18+BERFCsqPs0Q2MEEIIcSDOBXCtBjwpFjzuBXjkI/CXD4DIh0DkQ/CXD8CjHpuOJceB6zQuu4uBEB0FzazJiG/XECkLZ0B48vi/g+aSGm96ldQAAOPZU0geOwwJnZpCu3GVaQkLAQBUqFABu3fvxpMnT9C+fXs8evTIoddjjGHChAkWx3z66adu+Um4NZUob2rcuLGDInEMW5bZeHp6okOHDg6MRnzPnj1z6HhCCAFoKQohhBBiFjfogZQEQJMIwMY/l0wGePgAnr5gcucXSHLOoT+0F5rZU4CUZOuSGDaSFSsFr7FTIC9SXPRz24NzDhj1gF4LGLSm/xqNeP2cMhmgUAFKtelLoQYTcSeYa9eu4YsvvkDbtm3Rp08fh1VvcM4REhKC58+fpzvGGENERIRbJjY45/jwww9x+PDhTMeWKVMGly5dcrudfDp27IhNmzZlOu6rr75yu22l+/bti+XLl1s9fs+ePWjatKkDIyKEZEeU2CCEEELewg06IDHaNAEWg8oT8AlwWoJDiI6CZs73MBw9BDAGOOpP/6vlKOrPBkDd5TOnJ3S4IJgSU8nxpsSGLTx8AC8/MKWHKLEYjUbMnz8fBw8exNy5c1G0aFFRzvu2devWISwsLN3tbdq0wbZt2xxyTSkcOnQI9evXz3Tchg0b0LFjRwkiEtfly5dRvnx5i2M8PT1x//59BAcHSxSVOM6ePWv18plixYrh+vXrUCicnwwmhLgXSmwQQgghr3DOAU08kBTrgLMzwCcn4OEjaU8O48N7SBrRGzw2FhDEr9IwR1G9DrwmzgTz8JTsmqk4F4DEGFNCw9ZKm7cpVIBvIJhKnATHnTt3MGzYMDRp0gSDBg1ySGXBwoULMXbsWMTFxUGpVKJt27ZYv369W/aCSWVN1Ya7Vmukat++PbZu3Wr2uDtWa6Rq3bo1du7cmem4FStWoEePHhJERAjJbiixQQghhODVFqdxLwGjzrEXUqoBvyAwmeObbRrv3ETi8M+B5GRJkxoAAJkM8jIV4D19MZindMkNrtOYnkdB5H4fXn6mqhtm/6RZEAQsW7YMO3fuxNy5c1GyZEkRAsz4Ou46yc9IZlUb69atQ+fOnSWMSFyXLl1ChQoVMjwmk8nw9OlTt6vWSGVN1QZVaxBC7JFpYuPevXu4fv06NBqNVDG9kxhj8PX1ReXKlREQEODscAgh5J3CDTog9jnAhcwHi0GmAHLkduhSDePjB0ga1B08MSH91q1Skckgr1gV3j8sAFOpHHopzrlp+VBynOMuIlMAOfKAKcV5LA8ePMCwYcNQp04djBgxgiZ0meCcI2/evBk2l/T19UVsbKzbJ3JKly6N69evp7u9QYMGOHDggBMiEk+jRo0sPgaq1iCE2MNsYmPbtm34/vvvcfbsWaljeqcpFAo0bNgQM2fORNmyZZ0dDiGEZHvcoAdin0mX1Eglk5smyQ5IbvAUDRJ6fQL+4plDmoTahDEoW7aD1xffOuwSnHMg7gWgTXLYNV5jDMgZIlrvDc45VqxYgfXr12PWrFkoV66cKOfNrg4ePIiGDRum23Vo/fr16NSpk5OiEk9UVBRKlSqFqKio17cVLVoU169fh1KpdGJk9jt58iRq1KiR4TFfX19ER0dTco8QkmUZJjbWr1+Prl27on79+ujTpw9q1qwJb29vt16b6eoEQUBMTAz27duH+fPnIyYmBgcPHqTkBiGEOBAXjEDMU+mXaaSSK0yTZBGWN7xJs2A6dFvXOa5JaBZ4z1wCRZWaop+Xcw7EvwRSEkU/t1mMATnzginVop3yyZMnGDZsGCpUqIBRo0almcTeuHEDJUqUsKoagXNuanqr07xK1jHT8ieVp6g7vTjT0aNHMWLECNy7dw/58uXDDz/8gObNmzs7LNEIgoCNGzfixIkTaNy4cbZ6bCVLlsStW7fS3f7tt99i0qRJToiIEJJdpEtsaLVaBAcHo2nTpli7di3kcsevASZpRUZGIjQ0FEWLFsXu3budHQ4hhGRbPO4loEt2bhCevmA+4i1BNFw8i6RhvUQ7nyhkMrCcueD72zYwbx9RT82TYkyNQqXGZEBgAVF7pXDOsX79evzyyy+YPn06KlWqhKdPn6J06dKYOnUqBg4caPZ+0CSaqlaS481XH6m9AP9gwCdntklyEPcSFxeH8uXL49GjR69v69y5M9atW+fEqAgh2UG6xMbvv/+Ojz/+GJcvX6ZqASdasGABRowYgRcvXiBnzpzODocQQrIdrk02fdLvCnLkFmVpA0/RIOGzduAvnzuvr4Y5MhmULdqKuiSF63VA9GPRzmcztTdYjtyin/bFixcYMWIEChcujL///hv//PMPChQogMuXL8PPzy/NWK7VAM/vmSo0rCWTA0EFTQkOqsYlTnDp0iVcunQJjRs3RmBgoLPDIYRkA+nS9SdOnEDevHkpqeFkjRs3hsFgoB4nhBDiAFwwAglRmQ+USnykaYtSO+n37wJ//tT1khoAIAjQ/74VwsvnopzOtATlhSjnyjJtEniK+H09goODsWbNGsTGxuLEiRMAgIiICIwYMeL1GM45eMwz4NFV25IagGnp1fN7wLO7pp8FQiRWvnx5hIWFUVKDECKadImNhIQEqhBwAak7o8THxzs5EkIIyYY0idI3C7VEMAIp9i2J4ZxDu3Wtqf+Dq2IMuv9tEedcmnjA4OCtea0R/zJdI0sxvHz5Ejt37oTxVfNXQRCwa9cu3Lhxw3S9qAjTlz2SYoGIm26V3OBGA3jkYwiPrkO4fxnCo2vgLx6amgC7u9T+KJoE0+4+qV+aRNNr3YV65hBCiKtJl9jgnLv9VlnZQepz4Ig3S4QQ8i4z9SNIcHYY6Wni7fqdb7xyAcL9u649+REE6HZuBNfbNwnlnANJDtzW1RZcABxQtTF27FgkJibCz8/v9XKR58+fo3379kDcS9P2xGLQJgNP77r8+w2ekgTh4VXw83+C37toqjh5+Qh4fh/8wWXw839CuH8JPNkFf7Yzw7npedDEA/qU9ElXbjRV5WjiXzWFde3nKjOcC+CaRPCEGHBdirPDIYRkEzZnMFasWAHGGO7fv2/T/SZMmGD1Ok7GGCZMmGBraIQQQkjmdBrTRMHVGPV2VSDotm8A3KDhN4+Lhf7IQftOotMAgkGcgMSQLH6SZdGiRbhw4QJ27dqFFStW4Ouvv0bz5s3h76UGj3yU+QlsoYkH4iPFPaeIeOxz8MtHgOcP/tvBiHMA/L9JPheAl4/BrxwFj7SzkkVKgmDa0cdoZbLPoDNta+yGyQ2eFA/h1AEIK6ZA+HUyhFXhEH4aD+Pm+RBunAU3utDPNCHE7VBphgWCIGD69OkoUqQIPDw8UKFCBVG6Nk+ZMgWMMdqrnhBCnMEVqzVSZXHLUs459McPA0YXTNi8TSaH4d8j9p0j2cWWaRq04HqtqKdUKBQoWLAgQkND0b17d0yfPh27du3C0W1r4ZDFRpGPXXJiyWOfg98686qKIbPJvCnZwe9dAI90YlNZa3H+Kklh47I4weh2yQ3h6r8QVv4AfvqAaWnNm15GgP+5AcLqaeBRz5wTICHE7UmW2Bg3bhw0GhubWznZ2LFj8c0336BRo0aYP38+ChYsiLCwMKxfvz7L53z8+DGmTp0Kb29vESMlhBBiDc45YBB3AioqfdbKsvnTCCBZ/OUQDiEYYbx6Kct355zb3ixTChLExLWa9JNC0U4uuFzVBtcmg98+l7X73rsI7moJsLfpNFnv9SMYTf043IBw+Tj4X1tNjzWjZEzqbcmJELYuAo8WaZkVIeSdopDsQgoFFArJLme3iIgIzJo1C4MGDcKCBQsAAL1790a9evXw9ddfo0OHDpBnoeT3q6++Qs2aNWE0GhEZ6VpvIAghJNsTDOJ9yilXAD4BgFJtOmdKEpAUY985jQZwLoAx2z53MN68at9136Lq/BlUzdtClq8AmEyGxOG9YbxwWrTzCxEPwTUaME9P2+9s1CPzT+4zwWSAX5DpuZPJTMsBNAn2PX9STDJt3Z44sABYjmAAAH9wOfMY416A58jtMlvA8hcPMvx5ZaVqAF5+pm1rDVog5jn4o+tvJQkY+LN7YEXfly5gW3DB/PITD1/T6/JN2iTg7Yoag870GnaR5ysjPOoZ+OEd6W5nFT8AK1MD8M0BaDXg10+Dn/gDMOgh7FkJWdhXLvM6JIS4B1EqNvbs2YO6devC29sbvr6+aNGiBa5cuZJmTEY9NrRaLUaMGIGgoCD4+vqiVatWePw449LBiIgI9OrVC7lz54ZarUbZsmXxyy+/pBnz119/gTGGjRs3YsqUKcifPz88PDzQoEED3L5926bHtGPHDuj1egwcOPD1bYwxDBgwAI8fP8bx48dtOh8AHD58GJs3b8bcuXNtvi8hhBARiLmLhl8woPQwNbHUpYB5+QFeOew/bxZiNN68Zkq0iISp1DCcOAz+wkFl4ZzDeOdG1u4rRgKByQCF0tRbIiEKAAfzyQl4+mX9nFmstrFJkg0VCF5+gH8QuC1b/xrs6/MiJi4YTc1BM0piJceDP7puStYYjWC5CwNBBd4+AxD9BNxFHk86mcUlGE0NRVO/Mty5hlvfm8NJ+OXj6RIvrEYTyGq3ALTJ4Ed2gJ/9679ldFwA4iKBiDvSB0sIcWt2vwtatWoVevTogSZNmmDatGlITk7G4sWLERoainPnzqFw4cJm79u7d2+sXr0aYWFhqF27Ng4ePIgWLVqkG/f8+XPUrFkTjDEMHjwYQUFB2LNnDz7//HPEx8dj+PDhacaHh4dDJpPhq6++QlxcHKZPn46uXbvi33//tfpxnTt3Dt7e3ihdunSa26tXr/76eGhoqNXnMxqNGDJkCHr37o3y5ctbfT9CCCEiEmtLSJUnmEIJrk0yTY7BwNVegKcvkBxr37kNelPCxAbGh/dE7a+hXbkUACAv+z5kefKKdt43CQ/vA+Uq2n5HMSaqggGIevODFAb4BQJKFZDVFSWCEVwQwBy0sxwXjNYvo5IrgODCQMxTwDcXIFNbfyFtsqkKwNlinqWvUHiFP7oGyJWAQgEEhACePuaXOERGAHmKODjYLMjsdcytTFoYdIBCJU5MIuO6FPDrp9NW0iiUYBVCwXVaCP/72ZSwefv3MpNBuPgP5PmLSxswIcSt2ZXYSExMxNChQ9G7d28sW7bs9e09evRAqVKlMHXq1DS3v+nChQtYvXo1Bg4ciIULFwIABg0ahK5du+LixYtpxo4dOxZGoxGXLl1Crly5AAD9+/dHly5dMGHCBPTr1w+eb5SzpqSk4Pz581CpTL/oc+bMiWHDhuHy5ctWN+x8+vQpcudOX44ZEhICAHjy5IlV50m1ZMkSPHjwAAcOHLDpfoQQQkSU1fXsb0utjnidTOCAYASTK8CZzL7rZOG+PEUDu5dnSIkxcG0WKxxsqUCwltrL9F97+2RwAQ5rX2ZLpUpwYdP46FeJDVu4yPabPCXJ9Em/maVjrHw9MKXpfR6PigAy3CmGgackOabZqj04N/u4XpPJAS//VwkOw6vXZkbJGwf8PIgl8mn65FRAbjClClyTBFnnL8B8/METYyEc3QncfVXtzQXg6T3p4yWEuDW7/vru378fsbGx6NKlCyIjI19/yeVy1KhRA4cOHTJ73927dwMAhg4dmub2t6svOOfYsmULPv74Y3DO01ynSZMmiIuLw9mzZ9Pcp2fPnq+TGgBQt25dAMDdu3etfmwajQZqdfpPLDw8PF4ft1ZUVBS+++47fPvttwgKCrL6foQQQkTmyLm/WOvBs9IDROei5fbmMAbos1o9I/KT6B8MpvYCT44z9UmxiwNfYNa+LnwDAC9fIPpJ2v4LCpVpCY5F5hMJksukAonfPgPh9lnwxFhT1UaO3BmNcq1tga1l0JkSGdokU/wKJaAyU8XlKs9XRjJKxr1KTDJPb/BrJyH8uQHw8IasYZf/EowAoHez32mEEKezq2Lj1q1bAID69etneNzPz/xa1QcPHkAmk6FYsWJpbi9VqlSaf798+RKxsbFYtmyZ2eqPFy9epPl3wYIF0/w7Z86cAICYGOubgnl6ekKrTf8LOSUl5fVxa40bNw4BAQEYMmSI1fchhBDiAGJ9dJv6KeTrvhYMYDJTPwN7P0HNSoJE5Zql6GZxDiiVWbyzSE8ikwE5coOpPMETY+xv/Go6qQjnMHdqK8+tVJuaz+Yrmfbu+UqCP71t6gljFnedRpSZNWhPND1fHICseGUgMB94zNs9YRggc5/G9a+9ueSIc9OyG5mZ74erPF8ZyWhJU3z06yVbpt4aBrD364IF5n3VSDT51X3d7HcaIcTp7PptL7zKuq5atQp58uRJf3IRdkFJvUa3bt3Qo0ePDMdUqFAhzb/N7VbCbchqh4SE4NChQ+Ccp1mO8vTpUwBA3rzWrTm+desWli1bhrlz56ZZvpKSkgK9Xo/79+/Dz88PAQEBVsdGCCEki2zcbcQsnQbcqAdUnqaGkwolGGPibC+ZhRiZhydMk2pxPr2VV6gMWf5CYP6mDwaUNetClq8A9Lu3iXJ+cA6mtq2PyGti9LBgDAjIC6ZQgWuTTZ+Qq71fbaFpx1IMsV5fGbG270VCjGlb2FRBBU39YF4+BFKSM7+/ucoAiTEP74zft/kFguXKa0pGgYHlLmS6PTkhg7NwMA9vR4aZNYyZX2bDZKbnwPhqB6fU/hlm+o049DVnr1x5TMnfN2PXpYDfOgdWqgpYreZAQgyQMzd4YhwQ8+qDSiYDQgo7JWRCiPuyK/OQWm0RHByMhg0b2nTfQoUKQRAE3LlzJ02Vxo0babukp+6YYjQabb6GPSpWrIiffvoJ165dQ5kyZV7fntqAtGLFiladJyIiAoIgYOjQoemW3QBAkSJFMGzYMNophRBCpKDIapVABuJemrZ79c4BcAFcE29/41AgSzHKChQG5EfNT35spGrWBqqmrV7/W93Z9MFCnFiJDQCyAoWydkcxGiUyOdir8zC11+sSeK7TmBpuZoVM7rDGoQDAZHJwhSrzppP6lLTJmcD8pv8mx1vXjPLN5QDOlDMPILuSfimJQQ94+oLlzGNKDuhSwJ/eAX9yK/05GANy5ZMmXlspVBkv1eDclJ9UqvF6aZBeaz7h5qKNQwGAqT3BSlUGv5a2gSg/shMCB1ipygAY8OQOhGO7/vv9xQUkF3kfvs4JmxDipuxKbDRp0gR+fn6YOnUqPvroIyjfKit9+fKl2Z4SzZo1w5gxYzBv3rzXzUMBpJvgy+VytG/fHmvXrs2w+aela9ijdevWGDFiBBYtWoQFCxYAMFV8LFmyBPny5UPt2rWtOk+5cuWwbVv6N4Ljxo1DQkICfvzxx3TLcQghhDiImJMAox6Iey7e+VJlIUZ5ydKiJTUAQDPtO2imfSfa+dJhDPLi72XtvmLs2CEYwJ9b33fLKjbuZJMlXv5A/Evb7vPgsvV1PHKly0yUmUwOHlQAeH4faSqRkuPAr/6T6f2NggAE5IXSVZc0mEtsgAM6KyprTCPB5CImax2Ala8NfvVk2ht1KeAHN2b4utQbjbgfFY/Bg7/C3n37zFZhE0LI2+xKbPj5+WHx4sX49NNPUblyZXTu3BlBQUF4+PAhdu3ahTp16rxOCrytYsWK6NKlCxYtWoS4uDjUrl0bf/75J27fvp1ubHh4OA4dOoQaNWqgT58+KFOmDKKjo3H27FkcOHAA0dHR9jyMDOXPnx/Dhw/HjBkzoNfrUa1aNWzfvh1HjhzBmjVrrP5FGxgYiDZt2qS7PTWBk9ExQgghDiJTWNxpwenkClN/BFvvVrJM5oNciCxvATAbelWlIVdCzGU3onHwFqn37t3D5rWr8FWnFo67SI7gdLvBORMLLgT+4oHNP6+cc3DO8dW0eZi77BfIHFhJk2VMZnotW1NFkwGj0Yg/D/+Dxi0+FjkwcbFcIWChrcCP7sx0rMEoIEVvRPtlW3H1aRQmTpyISZMmSRAlISQ7sLsJRlhYGPLmzYvw8HDMmDEDWq0W+fLlQ926ddGzZ0+L9/3ll18QFBSENWvWYPv27ahfvz527dqFAgUKpBmXO3dunDx5EpMmTcLWrVuxaNEi5MqVC2XLlsW0adPsfQhmhYeHI2fOnFi6dClWrFiBEiVKYPXq1QgLC3PYNQkhhDgOYwxcobavj4IjZfFTf1ne/ICnF6Cx7pNep5LLIS9TIfNxZjDGwFWeVn+qLRlVFhM1FnDOceTIESxcuBAeHh6mJuQePkBKoujXAmOAn41bwzoY8/ACilUCv33G6vuk9kbrN2UeVvx+AHmLv4dRo0Y5MEo7qDyAFKPNDYcNBgP+PXUardp3wLJly9C9e3cHBSgOWYU6EORy8MPbTTe8lagyCgLkMhleJCSjxcJNuPo0CgDw/fffo06dOmjSpInEERNC3BHjb3VmGjp0KP766y9cvHjRWTERANHR0ciVKxe2bNmCdu3aOTscQgjJNrg22fZyfqnkyAOWxU/+kyZ9A8PhA5luk+kKPL8Nh6p+0yzfn2uTgdi3d8BwIoUaTMReDlqtFhs2bMCaNWtQrVo1DBw48HXTcq5LAR5ehegVK0EFwfxdc0t6HvMM/M75VxNi849bbzCAMYa+38/Db7sOAABkMhkOHjyIevXqSROsrQTBtK2rlckNo9GIk6fPoHm7DoiNjYOnpydOnjyZbqm2K+KJceBXT4JfPp5ma+XTD55iwV9nsfncDaTo0y6py5UrF86dO5fuQ09CCHmbG+6BRQghhNhB5WkqA7d3W1ax2dnfQN22MwyH9ooYkGMwX38o6zaw7yQqT9P2l4KLJHG8zG9vb4sXL15gyZIlOHLkCDp16oTt27en216eqTzAA/MBkY9FuabBaMTRMxdQPDQIBfxFOaXoWM48QLlQ8OcPTI9bMKbZ5pQLArR6PdbsOYT5G3bi0u37r48JgoDOnTvj3LlzGe7g53QymakKR6cxuyxFEAQwxpCUlIwlP/+CcRO/h1Zr6s+h0WjwySef4NSpU/D1de12m8zHH6x6I/CqDUyJDYMesRotOtWohQcPHmR4n6ioKHTu3Bl//fVXul5+hBDypgwTG6lbrGZHGo0GcXGW9nAHAgICoFJl/uYyMTERiYmWy0GDgoKy1Pgo9TlwpbWuhBCSHTDGwD19gWTLfwsk5+lr1+98ebmKkBUsAuHRfdftISKTQdW6A5idExTGGLhXDiAxSpy47MFkgJ1bil68eBHz5s1DbGws+vfvj2+//dbya8E/2LQ7SKx9zWsNRiPOX72B1v1GoFz5Cvj7779ddvLIPHzACpUFz18KiH4Krkk07Zgik0NjBKo3aY1rt9L3aQOAZ8+eISwsDPv373fNZpSMmXaj4YLpeTXo0iReBTB88fUo/PzbKiQnp1+CdePGDfTt2xdr1651i/eNTCYDvExJmJx+wMaNGxEaGgq9PuPEzrFjxzBq1CjMmjVLyjAJIW4mXTclPz8/xMTEOCMWSWzYsAEhISEWv44dO2bVuWbOnJnpuR49epSlOFOfA1fPvhNCiFvy9DVNSF2FTG735JgxBlX7MNdNagAA51C1bC/Oubz8XGMHD7+gLDV8FQQB//vf/9CqVSssW7YMX3/9NTZv3oyGDRtmOjllqduYZnH5S+qHJ7v/Oor6n/ZHQmISjh8/jm+++SZL55MSkyvAggpAVrA0ZIXLQ1awDHyKlMGyX361mLQ4dOgQxo8fL2GkWcBkpia0nr6mHXBefSl8cuDDho0zTGqkWr9+PRYvXixhsOKpXr06Zs+ebXHM7NmzM9xlkBBCUqXrsZH6R/bKlSsoU8a9uqxb4+nTp7hy5YrFMVWqVEHOnDkzPdfdu3dx967l7eJCQ0Ph4WF7M7iFCxdi+PDheP78OQICAmy+PyGEEMu4NgmIj3R2GCb+ucFU9m8XylM0SOjRFjzyhWntviuRyaBs1gZeX4m3jSzXa4HoCNHOZzO1N1iO3DbdJSEhAStWrMD27dvRtGlT9O7d26r3HOZwbbJpS1SdJvOxAMA5YhMSMXTidKzZuSfdmK1bt6Jt27ZZjseZZsyYgZEjR1ocs3v3bjRr1kyiiMQ1YsSI17vqZUSlUuGff/5B1apVpQtKJJxzdO7cGRs3bjQ7xs/PD2fPnkWxYsUkjIwQ4i7SJTa0Wi2Cg4PRokULrF692jW3yMrmoqOjERoaikKFCmHPnvRvOgghhIiDx710/u4anr5gPuIlsA3nTyNpRG/RzicKmQwsZwB8f9sO5u0j6ql5YgyQ5IRKUyYDAguAyaxb2nD//n3Mnz8f165dQ8+ePdG2bVsoFOK0OuOcA5oEIO4FkBxvvmpH7YVtfx5FtwFDoEnRZjjEnSePnHO0adMGO3ea31o0ICAA586dQ8GCBSWMTBw6nQ716tXDiRMnzI4pXLgwzp49a1eyzFkSEhJQtWpV3Lx50+yYSpUq4dixY1n60JAQkr2lS2wAwNq1a/Hpp5+iUaNG6NOnD2rVqgVvb2+3WLfnrgRBQHR0NPbu3Yv58+fj5cuXOHjwIMqXL+/s0AghJNvighGIeQJuNDrnb5xcAeQMydJSBks088Kh277RpRqkek1bBGX12qKfl3Nu2uXGEVugmsWAgLyZ7mDDOcc///yDhQsXQqlUYvDgwahevbpDI+Ocm7Yz1qWYqnYYA5QqQOUFJpPBYDCgYcOG+Pvvv82ew50njzExMahcuTLu379vdkzNmjXx999/W9VPzdU8evQIlSpVQlSU+f4yrVq1wvbt293yffulS5dQo0YNaDTmK5D69u2LpUuXShgVIcQdZJjYAIAtW7bg+++/x/nz5yUO6d0ml8tRv359zJo1i5IahBAigUf378LHkAQfby/RPkG3ikxu2t5VLv41uUaDhJ7tTEtSnL39K5NB2VzcJShv45ybqhW0SZkPthdjQI4Qi0uHdDodNm7ciFWrVqFq1aoYOHAg8uUTbztYez19+hQVK1bEixcvzI5x58njmTNnULt2beh0OrNjhg8fjjlz5kgYlXj27NmD5s2bWxwzffp0fP311xJFJK4VK1agZ8+eFsesWrUK3bp1kygiQog7MJvYSHXr1i3cuHHDYsMiYj/GGPz8/FClShUEBgY6OxxCCHknpKSkoE6dOtAmJ+LPrWuRM0cOKKVIbjgwqZHK+OgBkgZ9Cp6U6Lx+GzIZ5BUqw3vaQjCV5eoGe3HOgcRoh+12wzkQEx+PgCKlzVZqvHz5EkuXLsXff/+Njh07omvXrvDy8nJIPPY6ePAgGjVqZHEnPHeePC5evBgDBw60OGbz5s1o316kZrYSGzduHKZMmWL2uFwux6FDh1C3bl0JoxLP559/jl9++cXscS8vL5w6dSpb9gMkhGRNpokNQgghJLsaMGAAlixZAgAoUqgAtvyyBBXKlnZsfyml2rSThpW9GexhvH0dMQN7gGlToJBJXJYuk0H+Xll4z1wK5ind5J7rNKbqDUHkShVPP0yavQDFihdPN9m/dOkS5s2bh6ioKPTv3x+NGjVyi2UA33//Pb799luzx728vHDy5EmULVtWwqjEwTlH165dsW7dOrNj/Pz8cObMGRQvXlzCyMRhNBrRqFEjHDp0yOyYvHnz4ty5cwgODpYwMnFoNBrUrFkTFy9eNDumdOnSOHnyJHx8xO3bQwhxT5TYIIQQ8k5au3YtunbtmuY2hUKBkYP7YfzIEQAgcvUGA3xyAh4+kk16L1y4gO4ffYDNpfMjQKmAQqrJNmOQV64B7+/ngHl4SnPNN3BBMDUUTY7Hq71Ask6hAnxzgak8YTQa0aZNG4SHh6N06dLYvXs3li9fjnz58mHo0KF47733RIlfKoIgoEWLFvjjjz/MjnHnyWNiYiKqVauG69evmx3z/vvv4/jx4/D0lP51aq9nz56hUqVKePbsmdkxDRo0wN69ey1uheuqbt68iapVqyIhIcHsmK5du2LVqlVukUgkhDgWJTYIIYS8c65du4Zq1aohKSnjngxl3yuJrSt/QonCIu2coPQAfAPA5EpxzmeFuLg4VK1aFbdv30ZulQJzS+ZHs0B/CJxD5qhJgEwOMEDdvR/UYT3BFNI93oxwQQBSEkzLU4wGAKbJfEYVOUajMe3kz8MH8PIDFOo0k6Y7d+6gefPmCAkJQfPmzdG7d2+33pY9MjISlSpVwuPHj82OCQsLw+rVq91y8nj58mVUr17dYjPK3r17Y/ny5RJGJZ6///4b9evXt7ikaPz48ZgwYYJ0QYlo06ZN6Nixo8UxS5YsQb9+/SSKiBDiqiixQQgh5J2SlJSE6tWr4+rVq2bHlC9fHidOnICnSmHaRjMlCTZ/8s8Y4OELePpImtAATGX4HTt2xObNm9Pc3iE4BxZWKA4VF8RvKsoYZEWKw2vMFMiLlRT33HbinANGPaDX4tjhvyA36pEnOAgeHmoYDAYkaTS4eOU62nbsBLnaC1Cq0y0VevDgARYsWIArV66gWrVquHv3LlauXOmWk/23HT9+HB988AEMBoPZMYsXL0b//v0ljEo8K1euRI8ePSyO+e2339C9e3eJIhJXeHg4Ro8ebfY4Ywx//PEHGjduLGFU4hk6dCjmz59v9rhKpcLx48dRuXJlCaMihLgaSmwQQgh5Z3DO0aNHD6xatcrsGB8fH5w+fRqlSpX6736CYNpC06Azfem16bdSlclNyxYUatP2mkq16Nu4WmvevHkYNmxYutvbtGmDzcuXQvvrIuj37wIMhlf5miy+FZDJAEEAC8gFdYdPofqkq9OrNDIzevRohIeHZ3hMq9Wm2QKUc45jx45hwYIFkMvlGDx4MGrWrAkA+OGHHxAQEJBtPimeO3cuRowYYfa4u08e+/Tpg59++snscU9PT5w8eRLlypWTMCpxCIKA1q1b4/fffzc7JjAwEOfOnUP+/PkljEwcOp0OdevWxcmTJ82OKVKkCM6ePYscOXJIFxghxKVQYoMQQsg7Y/ny5ejbt6/FMRs2bMi09Bl4VQXwBlf55P7ff/9F3bp1odfr09xetGhRnDlz5vUbf54QD93endBuXQf+NMJUYSKTZV7JIVe8XtYhr1Qd6nadoaj1gUN3eBGTNYkNnU6HTZs2YdWqVahUqRIGDRqUbkIoCAI6dOiAsWPHuu1k/02cc3To0AFbtmwxO8adJ48ajQa1a9fG+fPnzY4pVaoUTp06BV9fX+kCE0l0dDQqV66MBw8emB1Tu3Zt/PXXX1AqXTv5mJEHDx6gUqVKiImJMTumTZs22Lp1q8v8LiaESIsSG4QQQt4J586dQ61ataDVas2OGTx4sMWSZ1cXFRWFSpUq4dGjR2luV6vVOHbsWIYTcC4IMN64AuP1KzDevAbjtYsQHj1Iv0WsWg158fcgL10O8pJloChXEbKQfI58OA5hKbERERGBX3/9FYcOHUKHDh3QrVs3eHt7mz1XVFQUOnTogK1bt7rlZP9tcXFxqFKlCu7cuWN2jDtPHm/fvo0qVaogPj7e7JjOnTtj7dq1bvn4Tp48idDQ0HRJzTd9+eWXmDlzpoRRiWfXrl1o2bKlxTEzZ87El19+KVFEhBCXwgkhhJBsLjY2lhcrVozDtOYiw69q1arxlJQUZ4eaZUajkTdr1izDx7ZkyRKbziXodPz80SM8j0rBKxTMz4WEeC4YjQ6KXFqjRo0y+xpo3bo1/+OPP7jRhsf677//8o4dO3JBEBwYtXTOnTvH1Wq1xZ+VmTNnOjvMLNuyZYvFxwaAL1q0yNlhZtn8+fMzfXzbtm1zdphZNnr0aIuPTS6X86NHjzo7TEKIEzhn8S8hhBAiEc45evbsafFT6Jw5c2LTpk1Qq9USRiau8PBw7NmzJ93tXbt2zXT5zduYUgnByxvPdAZEGTmYjy9YBjuJZDcbN25EkyZNMtw1xZzq1asjNDQUs2fPdmBk0qlYsWKmVUvffPMN/vnnH4kiEle7du0wfPhwi2OGDx+O06dPSxOQyAYNGpTpUrrPPvsMd+/elSgicU2aNAn16tUze9xoNKJTp054+fKlhFERQlxB9n+XQggh5J02d+5cbNu2zeKYVatWoVChQhJFJL5Dhw7h22+/TXd76dKlsWTJErcsq3cUnU4n+jkHDx6Ms2fPuu1k/229e/fGp59+ava4u08ep02b9roJbEZ0Oh06dOhgsZ+Dq2KMYfny5ShRooTZMXFxcfjkk0+QkpIiYWTiUCgUWLduHXLnzm12TEREBLp16waj2Ds/EUJcGiU2CCGEZFvHjh3DyJEjLY4ZNWoUWrRoIVFE4nv27Bm6dOkC4a2eGF5eXti8eTN8fHycFJlrefjwIUaOHJlpkisrGGNYvHgxvv32W7ed7L8p9fGULVvW7JiIiAh07drVLSePKpUKGzduRK5cucyOuX//Pj777LN0TYLdgZ+fHzZv3gwPDw+zY86dO2dxFxxXFhISgnXr1lmsrNq3bx+mTJkiYVSEEGejxAYhhJBsKTIyEp06dYLBYDA75oMPPsDkyZMljEpcBoMBXbp0wfPnz9MdW7p0KcqUKeOEqFwH5xzHjx9H165dMWbMGLRr1w6dOnVyyLX8/Pwwd+5c9OnTxy0n+2/z9vbGpk2bLDZP3b9/P77//nsJoxJPgQIFsHr1aovVTDt37nTbRpsVKlTAokWLLI5ZsmQJ1q5dK1FE4vroo48wadIki2MmTJiAAwcOSBQRIcTZKLFBCCEk2xEEAd26dcPjx4/NjgkODsb69euhULjHNqUZGT9+PP766690t/ft2xfdunWTPiAXodfrsW7dOjRv3hw7duxAeHg4Vq9ebXH5gRgqVKiAVq1aZZtPikuXLo3ly5dbHDNx4kTs379foojE1bRpU4wdO9bimNGjR+PIkSMSRSSunj17omfPnhbH9O3bF9euXZMoInGNHj0azZo1M3ucc46wsDBERERIGBUhxFkosUEIISTbmTp1Kvbu3Wv2uEwmw7p16xASEiJhVOLavXs3pk6dmu72SpUq4ccff3RCRM4XFRWFH374Ac2aNUNsbCw2b96M8PBwFChQQLIYevXqhYcPH2abT4q7dOmCAQMGmD3OOUfXrl3ddvI4YcIE1K9f3+xxo9GIzp0748WLFxJGJZ4FCxagfPnyZo8nJSXhk08+QVJSkoRRiUMmk2HVqlUWf75fvnyJzp07W9wClxCSPVBigxBCSLZy8OBBjB8/3uKYiRMnWpzMuLqHDx9m2NzR398fmzZtsri2Pju6evUq+vXrh969e6NixYrYt28fBgwYYHEZhSPNmzcP4eHhbjvZf9ucOXNQpUoVs8fdefIol8uxdu1a5MmTx+yYJ0+eICwszC2XGKX22vH19TU75urVq+jfv79b9hPJlSsXNm7cCKVSaXbM0aNHM63MIYS4P0psEEIIyTaePHmSYSPNNzVt2hRjxoyRMCpx6XQ6dOzYEdHR0emO/frrryhWrJgTopKeIAjYs2cP2rRpg3nz5mHo0KHYtm0bmjVrZtN2rY7g5eWFhQsXom/fvm452X+bWq3Gpk2b4O/vb3aMO08ec+fOjfXr11t83fz5559u24+nZMmS+Pnnny2OWb16dabLjlxVzZo1MWPGDItjZsyYgZ07d0oUESHEGSixQQghJFtIbaRpqWQ8f/78WLVqldMnvvb4+uuv8e+//6a7/YsvvkDbtm2dEJG0kpKSsGTJEjRu3Bjnzp3DTz/9hCVLlljcwcMZSpUqhR49erjtZP9tRYoUwW+//WZxjDtPHuvVq5dpb5RJkyZh3759EkUkrg4dOmDIkCEWxwwdOhRnz56VKCJxDR06FO3bt7c4pkePHrh3755EERFCpOa+7+wIIYSQN4wbNw6HDx82e1yhUGDjxo0IDAyUMCpxbdq0CfPmzUt3e+3atREeHu6EiKTz6NEjjBo1Cu3bt4efnx92796NMWPGuPTz2bFjR6SkpLjtZP9trVu3xldffWVxjDtPHkeOHImWLVuaPZ7aT8RSU2JXNnPmTFSvXt3sca1Wiw4dOiA2Nla6oETCGMPPP/+M4sWLmx0TGxuLDh06QKvVShgZIUQqlNgghBDi9n7//XdMmzbN4pgZM2agVq1aEkUkvlu3buHzzz9Pd3uuXLmwYcMGi2vM3dmJEyfQtWtXfPPNN2jVqhX27NmDsLAwqFQqZ4dmlRkzZmDhwoVuO9l/29SpUxEaGmr2eOrkMSUlRcKoxCGTyfDbb7+hUKFCZsekbiPtjkuMVCoVNm7ciJw5c5odc/fuXfTq1cst+22k9hhSq9Vmx5w5cwZffPGFhFERQqRCiQ1CCCFu7f79++jevbvFMe3bt8ewYcMkikh8Go0Gn3zyCRISEtLczhjDmjVrkD9/fidF5hh6vR7r169H06ZNsXXrVkydOhVr165F7dq1wRhzdng2UavVWLp0Kfr16+eWk/23KZVKrF+/HkFBQWbHuPPkMSAgINNmlMeOHcPo0aMljEo8hQoVwqpVqyyO2bZtG+bOnStNQCKrWLEiFixYYHHMokWLsH79eokiIoRIhRIbhBBC3JZWq0XHjh0RExNjdkzx4sXx888/u92E+E1DhgzBxYsX090+btw4NGnSxAkROUZ0dDTCw8PRrFkzREVFYfPmzZg+fbrFT9DdQeHChTF06NBMl3G4i3z58mHt2rUWf6YWL16MdevWSRiVeKpXr47Zs2dbHDNr1ixs375dmoBE1qJFC4waNcrimJEjR+LYsWMSRSSuzz//PNNkd+/evXH9+nWJIiKESIESG4QQQtzWV199hVOnTpk9bs1uDq7ut99+y3BHgwYNGmS6ra27uHbtGgYMGICePXuifPny2LdvHwYNGgQfHx9nhyaali1bwsfHJ9t8UtywYcNMX399+vRx28njoEGD0LFjR4tjPvvsM9y9e1eiiMQ1efJk1KtXz+xxg8GATp06ITIyUsKoxMEYw6JFiyw2FE5KSsInn3yCpKQkCSMjhDgSJTYIIYS4pQ0bNmRacrxgwQJUrFhRmoAc4NKlSxgwYEC620NCQrBmzRrI5XInRCUOzjn27t2Ltm3bYs6cORg0aBB27NiBFi1auPWuNZZ8//33WL16tdtO9t82btw4NGrUyOxxd548Msbw008/oWTJkmbHxMXF4ZNPPnHLJUYKhQLr1q1D7ty5zY55/PgxunXrZnH7bFfl7e2NzZs3W0yOXrlyBQMHDnTLfiKEkPSy5zsHQggh2dqNGzfQu3dvi2O6d++eYbNNd5GQkIAOHTpAo9GkuV0ul2PDhg0WJySuLDk5GUuXLkWjRo1w+vRpLFu2DMuWLUO5cuUcfu2UlBQ8ePDA7PH79+879PoKhQLLly/H4MGD3XKy/za5XI41a9YgX758Zse48+TR19cXmzdvhqenp9kx586dw/Dhw6ULSkQhISFYt26dxUTi3r17M90G11W99957WL58ucUxK1euzLAijhDifiixQQghxK0kJyfjk08+QWJiotkxZcuWxaJFi9y2rwbnHH369MGNGzfSHZs6dSrq1q3rhKjs8/jxY4wePRpt27aFj48Pdu/ejbFjx1psQimmc+fOoUCBAhb7PpQqVQr9+/d36CfUISEhGDNmDIYMGeKWk/23BQUFYcOGDRarh9x58li+fHksWrTI4pilS5dizZo1EkUkro8++giTJk2yOGb8+PH4888/JYpIXJ07d8bAgQMtjhk8eDDOnz8vTUCEEIdhPDv8VSWEEPLO6NmzJ1asWGH2uLe3N06dOoXSpUtLF5TIFi5ciMGDB6e7/eOPP8b27dslWapx7tw5VK5cGfny5cPjx4+zfJ5///0X8+fPh9FoxODBg52ys4nRaESBAgXw9OlTq8YvXboUffv2dWhM33//PfLkyZNp5ZG7mDlzJr7++muzx9VqNU6cOOG2S8N69eqFX3/91exxLy8vnDp1CmXKlJEwKnEIgoCWLVtiz549ZscEBwfj3LlzyJs3r4SRiUOr1aJOnTo4c+aM2THFixfH6dOn3bofEyHvOkpsEEIIcWnHjh3D33//DZ1OB7Vanek2i2vXrkWXLl0kik58p06dQp06daDX69PcXrhwYZw9exY5c+aUJA57EhsGgwFbt27Fr7/+irJly2Lw4MEoXLiwYwK1wsmTJ1GjRg2rx7do0QK///67AyMyTSbbt2+P8ePHu+1k/02cc7Rt2xY7duwwO6ZYsWI4c+aMW04ek5OTUbNmTVy6dMnsmDJlyuDkyZPw9vaWMDJxREVFoVKlSnj06JHZMXXr1sXBgwehUCgkjEwc9+7dQ+XKlREbG2t2TPv27bFp0ya3rfQj5F1HS1EIIYS4rMmTJyM0NBRjxozBhAkTMk1qDBgwwK2TGtHR0ejQoUO6pIZKpcKmTZskS2pkVXR0NKZPn44mTZrgxYsX2LhxI2bOnOnUpAYAm79vUnyfZTIZli9fji+++AJxcXEOv56jMcawYsUKFClSxOyYO3fu4PPPP3fLJTheXl7YvHkzfH19zY65evUq+vfv75aPL1euXNiwYYPFpMWRI0cwduxYCaMST5EiRfDbb79ZHLNlyxbMmzdPoogIIWKjxAYhhBCXdOPGDYwfP97qSUKVKlUwZ84cB0flOIIgoEePHhk2t5wzZw6qVq3qhKisc/36dQwcOBA9e/ZEmTJlsH//fgwePNjiJFBKxYsXtym5YmmnDzEFBgZiypQpbjsZfluOHDmwadMmqFQqs2PcefJYsmTJTHuFrF69OtOGla6qVq1amDFjhsUx06dPx86dOyWKSFytWrWyuFwKMG0hfuLECYkiIoSIiRIbhBBCXNKKFSusnuylTqjUarWDo3KcmTNnZrj8oXPnzhlu+epsnHPs27cP7dq1w6xZszBgwADs2LEDLVu2dLntWhljVn/SXKRIEUmrfmrVqoXq1au77WT/bVWqVMGPP/5ocYw7Tx47dOiAIUOGWBwzdOhQnD17VqKIxDVs2DC0b9/e4pgePXo4fAchR5kyZQpCQ0PNHjcYDOjYsSOioqIkjIoQIgbqsUEIIcQlNWnSBPv27bNq7I4dO9CqVSsHRySugwcP4vDhw6hWrRq8vb3RsGFDGI3GNGNKlSqFU6dOOaXywVyPjeTkZKxevRobN25EvXr10K9fPwQHB0sen610Oh1KlSqV6YTs559/Rq9evaQJ6hXOOcLCwjBs2DDUrFlT0ms7Aucc3bp1w9q1a82OKVCgAM6dO4dcuXJJGJk4dDod6tati5MnT5odU7RoUZw5cwY5cuSQLjCRxMXFoWrVqrh9+7bZMVWrVsXRo0fdMpkcERGBSpUq4eXLl2bHNGvWDL///rvLJWkJIebRTyshhBCXwznHuXPnrB7v4eHhwGjEt2LFCjRo0AATJ05Ey5Yt0bRp03RJDU9Pz0zX9EspIiICY8eORdu2beHp6Yldu3bh22+/dYukBmDqU5JZ1UbhwoXx6aefShTRfxhjWLJkCcaMGZMtPilmjGHp0qUWdyZ69OgRPv30U4duresoKpUKGzdutNiL5e7du+jZs6dbLjHy9/fPtALu9OnT+PLLLyWMSjz58uXD2rVrLTYJ3bNnD3744QcJoyKE2IsSG4QQQlzO06dPLX6a9raVK1c6MBrxTZs2Lc2/tVptujGLFy9GuXLlpArJLJ1Oh+7du+PLL79E06ZN8ccff+DTTz91y09qu3fvbvET9LFjx0KpVEoX0Bv8/f0xe/Zs9OnTxy0n+2/z8fHB5s2b4eXlZXZM6uTx+fPnOHv2LKKjoyWM0D6FChXCqlWrLI7Zvn272/b9qVixIhYsWGBxzMKFC7FhwwaJIhJXw4YNMWHCBItjvvvuOxw6dEiagAghdqPEBiGEEJdjS7UGAJu3I3WmuLg4XL9+3eKYXr16oUePHhJFlJ7BYMD+/fsBABqNBhMnTsT69etRt25dt94KUaVSoXfv3hke8/DwcOr3HDBNJps1a5ZtPikuU6YMli5danHMuHHjkD9/flSpUgW5c+fGtGnT3Cax06JFC4waNcrimG+++QbHjh2TKCJxff755+jevbvFMb1798aNGzckikhc48aNQ+PGjc0eFwQBXbp0wdOnTyWMihCSVZTYIIQQ4nK2bdtm0/hmzZo5KBLxXbhwIdMxlnaVcKSYmBjMmDEDTZo0eb0kwt/f3+IWnu5mypQpCAkJSXf73LlznVat8abevXvjzp072eaT4m7duqFPnz4WxxgMhtf/HTVqFLZu3SpFaKKYPHky6tWrZ/Z4ajNKWyrQXAVjDIsWLULZsmXNjklMTMQnn3yC5ORkCSMTh0wmw+rVq5EvXz6zY54/f44uXbq8fo0SQlwXNQ8lhBDickqVKoWbN29aNbZmzZrYtWsXAgICHByVOObNm4dhw4ZlOu7EiROoUaOGBBGZttadN28eHj58iD59+qBFixa4ePFihs1Ds4PExEQMHDgQhw8fRq5cuTBu3Di0bdvW2WG9lpSUhNatW2PVqlUZJmHcTUpKCmrVqoXz589bNb5OnTo4evSoY4MS0dOnT1GpUiU8f/7c7JhGjRphxIgRuHPnDooWLYqmTZu6TWPKa9euoVq1akhKSjI7pn79+vDx8QHnHLVq1cJXX33lEolCa/zzzz+oV69euj5Hbxo9ejSmTp0qYVSEEFtRYoMQQojLqVSpUqaTIG9vbwwePBjjx4+Hp6enNIGJoEePHlb1BNm6datDJ9ucc/z5559YvHgxcuTIgaFDh+L9999/fdzcrihEGteuXcPXX3+N7du3Q6FQODscu925cweVKlVCQkJCpmPVajUSEhLcZmIMAIcOHULDhg2tXkbTqFEjbNiwwWIDUleybt06hIWFWT2+bt26OHToEORyuQOjEs+sWbPw1VdfWRzzv//9D0FBQRAEAaVKlXKbZDoh7wr3SBUTQghxC5wL4LoU8OR48MRo8IQo01diNHhyHLhOAy6Y/1QslaVeB76+vhg3bhwePHiA8PBwt0pqAMDevXszHZMnTx40bNjQIdfXaDT46aef0LhxYxw7dgyLFi3Czz///Dqp0alTJ6hUKlSvXh2AaTcUlUoFHx8f/PTTTw6JiaRXunRphIWF4bvvvnN2KKIoWrQoqlSpYtVYrVabaR8aV/PRRx9h0qRJVo/fv38/Zs2a5cCIxNWlSxcMGDDA6vFHjhzB9u3bHReQyL744gu0adPG4pg2bdqgZs2aqF27NooWLYqNGzdKExwhxCqU2CCEEGIXbjSAJ8WAR0UAkY+AuOdAUgygSQBSEk1fmgQgKRaIewFEPQaPemxKdhj0GZ5z+PDh6Zq6yWQyDB48GA8ePMDkyZORK1cuCR5dxrjRAB4bCf7yCXjkU/C4KHALZcyv78e5xXJ1AGjXrh3+/fdf0bd5ffLkCcaNG4fWrVtDpVLh999/x3fffYfcuXOnGXf16lXo9fo0a8r1ej2SkpJw7949UWMiloWFhSEuLg67du1ydih2u3z5Mv766y+rx1u7bMWVjB492qZ+P0uXLnWr7WDnzJljdXIKADZt2uTAaMTFGMOvv/6KokWLmh3z5lKVuLg4dOnSBXfv3pUiPEKIFWgpCiGEkCzhOo0pYaHT2HcipRrw9ANUnul23Dhx4gRWrFiBokWL4rPPPkNwcLB918oirtWAXz4J/vAW+KPbwLNHwNuVJ3IFEFIIrGAJsEIlwcpUBVOmbwIql8vTlaszxtCxY0eMHTsW5cuXFzX206dPY968eUhJScGgQYPwwQcfWNzZZMWKFejZs2e629VqNe7cuWOx0Z6r4pwDBh2g1wIGLaBLAQQDkPoWiMlMr8PXXx5gMtcooU9JSUGrVq2wfPlyFCpUyNnhZNnmzZvRoUMHq8cPHToUP/74owMjcoyoqChUqFABT548sWr8/fv33ep5vXfvHkqXLp3hFtVvK1WqlNtV3pw9exa1a9e26vEBwIgRIzB79mwHR0UIsQYlNgghhNiEC0YgMRrQitwFX+kB+OYCk7tOPwH+7BGEE/vBz/wF6HWATJ4+ofG21DFqT7AaDSCr0RAsV57Xh9/usdGgQQPMnz8fpUuXFi1ug8GA7du345dffkGpUqUwZMgQi59Evn3f9957D3fu3Elz+5AhQzBv3jzRYpQCFwQg5VW1kDHj6qCMMcDDB/D2B1N6OCo8q929excDBw7Ezp07nbZjjr1u3bqFkiVLWj2+WLFiuH37tgMjcgy9Xo9q1apZtfsRYNoBKrMlEK5kx44dVsfLGEN8fDx8fHwcG5TIli5div79+1s1tlatWm67nS8h2Q0lNgghhFiNa5OBhCiAW9cgz3YM8A0A1N4WqwocjScnQtj5K/j5fwCZDLCyIWA6TAZwAaxmY8iahYGpTZPk/fv3Y9++fejYsSOqVasmWtyxsbH4+eefsXv3brRq1Qo9e/aEn5+fzed5u2rD3ao1OOem5VCJMQDsfJujVAN+wWBKtSixZdWOHTtw8OBBt6xiSNWlSxesX7/eqrFyudwtt9g8efKkTbsZjR8/HhMmTHBcQCIbMGAAlixZYvX4Y8eOoVatWg6MSHwvXrxAkSJFrNrC1svLC/Hx8W7TJJWQ7Ix6bBBCCMkU5xw8KRaIf+nApAYAcFPiJDHaaWvPhSunYZw5AvzC8Vc32PF4X32v+L/7YZz9JYQ7VwCYdkSYMWOGaEmNW7duYciQIfj0009RvHhx7Nu3D8OGDctSUgMAunXrhvz587/+d9++fd0nqaHXAlGPTFVF9iY1ANPylahHpp4wTvwsKLU3ijv1LXjb6tWrMXbsWHh4ZF4F466fu9nah+aff/5xUCSOYc2uNm9yx2qGJUuWWJXUAIDk5GS3rCwiJDsyW7GRkJCArVu3YtOmTbh+/To0GjvXUBOLGGPw9fVFzZo10aFDBzRp0oSyv4QQl2D69DsW0MRLe2G1F+AbKFnlBuccwu7V4Ed2AYz9139BLK/OKWvWFbJ6H9t9Os45Dh48iMWLF8Pf3x9DhgxBxYoV7Y/zlSlTpmDcuHFgjOHRo0dukdjgyXGm5JujKFRAzrxOWy6l1+vRpk0bzJkzx6ZlHa7m2bNnmDVrFhYtWmR2Apk7d248e/ZM4sjs9+TJExQoUMDqbV+9vb2RmJjo4KjEs3PnTrRu3drq8XXq1MHRo0cdGJH4unbtirVr11o9ft26dejcubMDIyKEWCPDxMbLly/RoEEDXL58GXXq1EHNmjXh7e3csuDsThAExMTEYN++fbhx4wa6du2K3377jZIbhBCn40mxQHKccy7u4QP4BDj87w/nHMLW5eCnDjr0OqlYg/aQN7K+keKbNBoN1q5di3Xr1iE0NBQDBgxIt7OJGAwGAxo3boxq1aph2rRpop9fbDwxBkiMcvyF5AogIL/TkhsRERH47LPPsGPHDnh5eTklBrG8fPkSkydPxsKFC9MkAmQyGQ4ePIh69eo5MbqsGzNmDH744Qerx0dFRSEgIMCBEYlHEASMGTPG6t8JwcHBme4E5WpmzJiBkSNHWj0+LCwMa9ascWBEhBBrZJjYqF27Nu7evYsDBw6gXLlyzojrncU5x4YNG9CtWzeMHDkSU6dOdXZIhJB3GNdpTFu0OpNvLjAPxzafM+5eDX74d4de422y5t0g+6BlutufPn2KsLAwHDhwIE1y++nTp1i8eDFOnDiBsLAwdO7c2aqSflvoNRrcOXQYEWfO4cn5S9DExIDJZPDPlxf5KldEwZrVkb96FZf7oIMnxQIJkdJdUK4EcuV32s4pBw4cwIYNG7B8+XIYDAZMmjQJgwcPdtquQfZ69uwZvvzyS1y8eBFFixbFjBkzMqxI4dpkU5I1Jdm0G5MgmCqhVJ6Ahzfg5ev0/jypVqxYgXHjxiEiIiLTsTqdDkqlUoKoxLN3715MnDgRx48ftziuRIkSuHnzpkRRiePZs2eoVq0aHj9+bNX4vHnzWvU8E0IcK11i4/r16yhdujS2bt2Ktm3bOiuud97QoUOxZcsWPHr0CDIZtUIhhEiPCwIQ8yTzXUAcjgEBjiv/F66ehrBypkPObRFjkA+YBFawxOubNBoNqlWrhrt37+LXX39Fp06dcObMGcyfPx/JyckYOHAg6tWrJ/rELf7JU/zz4yKc/Ok3aOPjIVPIwY3C6z4HTC4HOAcXBASWLI7ag/uj6ufdoXCBHTq4TgNEO2FSofI0LUtx0iR64sSJyJEjB1atWoXLly9jzZo1aN++vVNicaTXjWCjnwHapMzvoPIEcuYxJUSdnODQarX49ddf8cMPP+Dhw4cZjgkMDMTLlw5cPuVAqcvhJk6ciCNHjmQ4ZtmyZejTp4/EkdkvIiIC3bt3x8GDmVfx5cmTB0+fPpUgKkKIJekSGzNnzsT48eMRGRkJT09PZ8X1zjty5Ag++OADnDp1ClWrVnV2OISQdxCPj7RuIiEFpQfgHyz6RIUnJ8I4cwSgSRS/p0ZmmAwICIZ8+HQwpQqcczRt2hR//vknjEYjChcujDJlyqBEiRIYMmQIihUrJnoInHOcW7UOO4ePhCFZA8FoRRLr1XMQXPo9dPxtKfJWrCB6XNbiXAAiHwJGJ+2e4RcM5pW1Bq322rt3L9q0aYOUlBQApt0qFi1a5JRYHIUb9MCL+6YeP7by9AVyF3H6bjaAqSLj559/xsiRI9P001AoFPjrr79Qp04dJ0Ynjv3796Nnz56vKxcYYxg0aBDmz5/v5Mjsc+TIEUyePBn79+83O6ZBgwY4cOCAhFERQjKSLrHx5ZdfYteuXbh+/bqzYiIwlRznzZsXO3fuxMcf299kjhBCbMH1WiDWxRr3+QWBqcXtKWBcvwD8wjEH7/RiAWNgdVtC3rwrvvjiCyxduvR1M0Vvb2/s2rXLYX0GjAYDtg0YhrMr1mSpWapMLgcH0HHFUrzf+ROHxJgZHh8JJMc65doATN+3wEKS99sYO3Ysli1bhsjI/5bfVKtWDSdPnpQ0Dkfi2mQg4oZ9SSsmA/KVAvN07FI2a+n1esyaNQtHjx5F8eLF8e233yJXrlzpxnHBCOh1pmo5uRxQqMHcpHr36dOnOHfuHBo0aAC1OoOkEhcAg/7V7xtu+hliclPvGhdYQmTO8ePHMWzYMJw6dSrN7V5eXnjw4AECAwOdFBkhJFW6v8R6vR4qFygtfdel/jHQ6/VOjoQQ8k7S2LalnyQ0CaadUkTCX0SAn3dyt37OwY/uwqIrj7Bo0SJotdrXh5KSkvDDDz84JLHBOcfWfkNwbtX613HYKrW6Y0P3PpApFCj/SRsRI8wcN+qdm9QATN+3xGjAX9reFoIgwMPDA3K5HMZXz0NUlASNUyXCdSnA4+v2L4PjAhBxAzz/e2Ae3uIEZwelUolRo0aZPc6T48FfPAAiI9ImW2UK8KACYMEFXeJxWBISEoKQkJD0B4wGwKADjObe1zLTrkMKFeCCSZxatWrh5MmT2LlzJ2bOnImIiAjUqlUL8+fPR86cOZ0dHiEEgM2/OVasWAHGGO7fv2/T/SZMmGB1CTFjDBMmTLA1NEIIISLggtF1lqC8SZ9iKk0XiXB8n2u8geYcXldPoly5cqhatSoqVKiAMmXKoGTJkrh27drriauYTv30G86tXCfa8ptNPfsh6s49Uc5ltWSJtx82R5Ng+pmR0A8//IArV67gq6++Qv78+SGTyRAZGWmq4ODcNIHUJpt+jrXJgD7FeVVJNuJcAJ7eFq+3z6vzSf0c2YLrtRCunwC/chR4+Tj9cyUYgOf3wS/9DeH2WXBnLb3KCs5NjV61SRaSGgDAAYMWSEnIZJxztWrVCocPH8adO3ewevXqdEkNnhAD4eQ+CHvXwLjnNwgHN4Hfu2rqWUUIcSgXeEfnugRBwPTp01GkSBF4eHigQoUKWLdunc3n+euvv8AYy/DrxIkTDoicEELskOKCSY1UKeJUknBtCvjpQ6ZdFZyNc3QrnhunTp7EqVOncOHCBVy5cgU3btzAgwcPRN/2O/bhI+z6crR4J+QcgsGAzb36p9my05E4587bgjgd7pQKJz8/P4SHh+PatWsYM2YMtFotHt+7Y4pFpzFNDo0G03/1WtPt2mTXT3DEPDPFLyaDDohyzV0ruFYDfvUfICEm9RZzI03/iXkGfu24qEleh0lNahh0tt1Pm2xaruJGeFwkjLt+hbAqHPzMQfC7l4B7V8FvnIWw5zcIK3+AcPk4MtiMkhAiEskSG+PGjYNGI/IfKgcbO3YsvvnmGzRq1Ajz589HwYIFERYWhvXr12fpfEOHDsWqVavSfBUvXlzkqAkhxE66ZGdHYJ5WnNj41VOmNeyuIiEG/O4VSS7117Q5MIr82AWDEQ+O/YtbeyVqoKdNcq0JusZ51SM+Pj6YPGkSEqOe4/2y78H8xBimJEdKomsk9DLABSMQ7aDdJWKfg9s6wXYwbtSD3zwJ6LSw+Ly9TZMAfuu061cBWFx6kgldsgvsyGUdHvkEwuYFwMNX29py/l81XOrvqeR48MPbIRzZQckNQhxEsm5XCoUCCoW0zbXsERERgVmzZmHQoEFYsGABAKB3796oV68evv76a3To0MHmT9Hq1q2LTz5xToM1QgixBufctSb8bxOM4IJgdyM9/vA2IJO7zhtnJgMe3QGKl3foZVLi43F25VoIBvEfN5PLcXzRMpRq1lj0c6ejT3H8NWxh0InyuswynQYKa/sucm5KDHn4uF6zxvgoxyas4l4CufI57vy2evEw6xVyiTGm6pZcecWNSSyc2/9zqk8B1K7dU4QnJ0D430+ALsW6pX2Xj4P75gCr9KGjQyPknSPKX+A9e/agbt268Pb2hq+vL1q0aIErV9J+8pRRjw2tVosRI0YgKCgIvr6+aNWqFR4/fpzhNSIiItCrVy/kzp0barUaZcuWxS+//JJmTOqSj40bN2LKlCnInz8/PDw80KBBA9y+fdumx7Rjxw7o9XoMHDjw9W2MMQwYMACPHz/G8ePHbTpfqoSEBBgMbrQ2khDybhEMsOmTQ0vkClNTxcACQK78gLdIDdZE+NSVP7JzDb+nN2Tdv4J81ELIJ6+EfNQCyBp3smOiyCE8vpP1eKx0/fc/YEjJfLLxwVfD8MWV0/heG42p+lgU+SA00/twoxE39/4JTUysCJFmQq/NfExmcuYFgosAuYsBQYUBXzt3NTCIEFNWCIL5T8WVHoCXv+mLvfGWj1u4jzMl2NAANUceoFB5oHgVoEhF0++YzMRHZj5GIpxz8Of3MzzGKnwIWbXmab6QI3f6c5i5v0sw9/qSyf97Tb755eGbwTkMrlWZlQF+6RiQkpwmqcHeqwpZ5y8g6/s9ZL3GQ/ZxbyBXnv/uc+pP085jhBBR2Z3YWLVqFVq0aAEfHx9MmzYN3377La5evYrQ0NBMG4z27t0bc+fORePGjREeHg6lUokWLVqkG/f8+XPUrFkTBw4cwODBg/Hjjz+iePHi+PzzzzF37tx048PDw7Ft2zZ89dVXGD16NE6cOIGuXbva9LjOnTsHb29vlC5dOs3t1atXf33cVj179oSfnx88PDzw0Ucf4fTp0zafgxBCHErMag2/YNPEKikO0KWAefkBXjnsP6+diQ1uNAJPH9gXg4cXWFA+CCf/hPD7SoBzyOq3BauVxWoFzoFHtiXgs+Lx6bOQKZWZjlN4eOD67r2Ie5jxhw1mcY6IcxeyGJ21lxDhk2DA9DpKiALiXwJcAPPOYZpgZZWzJirmfh5kCtMOE+Y+RdZrRWseKwaeWklijVz5wIIKmBKxLx4CMU+tmwAbdK7TeDPuhcXXDNckQLhz7vUXkmLTD0qKBXeVJrpv4tz8YxOEV41tX32lvn4FM8+Liy0fehM3GsAvn0j7c+QXAFn9DoBPDvB/fge/dxWsQAnI6rX7b4xBB37zvOTxEpLd2bU2JDExEUOHDkXv3r2xbNmy17f36NEDpUqVwtSpU9Pc/qYLFy5g9erVGDhwIBYuXAgAGDRoELp27YqLFy+mGTt27FgYjUZcunTp9X7f/fv3R5cuXTBhwgT069cPnp6er8enpKTg/Pnzr7etzZkzJ4YNG4bLly+jXLlyVj22p0+fInfu3OmqTFK3sHry5IlV5wEAlUqF9u3bo3nz5ggMDMTVq1cxc+ZM1K1bF8eOHUOlSpWsPhchhDiUWEszVJ5gCiW4NulV/wEGrvYCPH3t36LT3hiTE0yfBNojLgrG2V+8fkMrKJSQf9wDLKRw1utd4mPAObd6B7GsiDhzDoIV24gf/H4aAKBgrerIWbig1ednMhmenr+I4vXF36L2NS6IMyFPiDRVMchkgIe35SSANZw1YTZmNPFjgNrTVEUiV2VcScQF0xcTtzltlumtLOVnMiBHblM/joibr/oZ2PCpvk5j+j3kZDwu0vS8mE086YDYF5n/vouLBLz8xA/QXmafE562mkOpNv3XXALDaAAyz8U6R8SdDPo+MdPOProU8Me3wLgAlK5qqup4A79xFihbQ7pYCXkH2FWxsX//fsTGxqJLly6vtxmLjIyEXC5HjRo1cOjQIbP33b17NwBTQ803DR8+PM2/OefYsmULPv74Y3DO01ynSZMmiIuLw9mzZ9Pcp2fPnq+TGoCptwUA3L171+rHptFooFar093u4eHx+ri1ateujc2bN6NXr15o1aoVRo0ahRMnToAxhtGjRexMTwghdhNxGQoAvN6qlAOC0dSDgNlZLGhvabIYVSnCG5NrxsBKmRLU/PYl+87r4J0AkiJtKPXPAiaXIzk6JvOB9hCzyiCoEFhQYTC1N7gmwb4moM4qmc/o+6H2NL1GM6sicaGKDVi7rbHKE0wmN32/C5YDK14FKPy+9UvdXKViw6C3/P33DYCsShOwKk3Ailc2Jd7exhi4Ky4psvZ1JVeYlqYYDeYTOK70Gn0LT85gN6T4KPC/tgGe3pB3HQnZh+3Bo55COLgp7bgkV9nViZDsw66KjVu3bgEA6tevn+FxPz/zGeQHDx5AJpOhWLFiaW4vVapUmn+/fPkSsbGxWLZsmdnqjxcvXqT5d8GCaT9dSt1jOibG+jdbnp6e0GrTvyFIebU2+c0KkawoXrw4Wrduja1bt8JoNIq+nR8hhLgc0SoRXKjhoVwBWceBkJWsAOGfPeAXjtl3PnuTPpme3/HfO6c10MyKmKfgcoVpiZSHj2nHEGuXQ7zNVRpxypWmZSja5LSvJyZz+X4F1jFNdJlcCR4bYepVEFwYyFMUuHfeioouF3meLLxeeORjICUJXDCCBRcCy5nH1Dj5bkbLvFzk8WSF4tUHiG7bbyKD773aE6zyh4BeC+HPjUCuPJBVqQ9ZvbYQ9q5+465u/LwR4qLsSmyk7le/atUq5MmTJ91xMXZBSb1Gt27d0KNHjwzHVKhQIc2/zSUJbNleKSQkBIcOHUpXFvz0qWkbsrx57e9CXaBAAeh0OiQlJVlMAhFCiHREerOV+qloauUGGMBkpu0J7Z1c2fuGUJW+Gi9LPLwg7/4VWNEyEA5shnBgs/3ndHCS2y9vCCJv3HLY+bnRCO/AXA47PwBxkz/6FODVB94sRx5wT7+sJzacNcF8O2Ehk5l+Rjze2k3Cw9v02N6sWHB0Is0W1r5n1Gv/e28W89T0iX7OPGBqL3ClOvMtoeUuskOfQgnTayaD96ZP/uu3w/VaMP+gjJfPcA6mcMF1Gtb8jmYy03MhGM3317D2XE7CfHOkf/byFQfzzwV+7wr47QvAvStAlfpA4TJv3JEBvgFShkrIO8Gu3+6p1RbBwcFo2LChTfctVKgQBEHAnTt30lRp3LhxI8241B1TjEajzdewR8WKFfHTTz/h2rVrKFPmv19G//777+vj9rp79y48PDzg4+Nj97kIIUQUYr3p12lMJdIqT8DTD1AowRgTp9GdvTF6+QJKlX1LUlRqyPtPBMtTAMKN8+AvIsAq1AKS4sHvXMn8/hnJGeTQ/hoAkL9KJdw/egyC3nI5fuHQ2ggsWQzegaadQko1b4xcxYvg9C+rLN6PCwLyVa4oVrgZY8z+6gOVF+DpY9qiEfivaag9O5s4a4KpUKVtpmrQp61aUHmavl86TdrbZXJTEsRVKNTWPa+C0dT01S/QtOOSXguoPMANOtNjzIzavopbsbCceTLe1cTTF6zAe+BxLwGjASzw1W4viWaqjjPYLcXpGMt8O22lldUachdM3KQKKQL4+AOJbywriYs09djIVwysXC0g4NXzE/3svzGcg5WpJm2shLwD7PqL1qRJE/j5+WHq1KnQZ9CM7OXLl2bv26xZMwDAvHnz0tz+9i4ncrkc7du3x5YtW3D58mWbrmGP1q1bQ6lUYtGiRa9v45xjyZIlyJcvH2rXrm31uTKK8cKFC9i5cycaN24MmSu9sSCEvNsyWsedVXEvTW9avXMAKk9wTbz9jUMBu2NkMhmQr4h9MXj7geUpAACQlaoIedgwyMOGQdagfVaDAitYwr6YrJC/epVMkxoAUKVnN7RbOh+5ipm+Tx98ORTtls7P9H4yhRwhFcvbHacljDHTbjv2EIymibRvoGmCzBh4YgyQGJ31cypFqgSy1dsJFS6YqjJSv1I/UjYa0vYrEPNnXQSMMdNyIGu8fAgeHwn45gIC8poaAqc2ErVE5WHqz+EKfHKmr6oBTE00BQEspBhYobKm353P7oE/upZ+rF8gmIeX42PNCkuvL8ZMCQtrth12sdfpm5hMBla+NtJUa0U9BT+0BUiIBavVHKz4++APrkPYv+6/MWovsKLWbWZACLGeXR97+fn5YfHixfj0009RuXJldO7cGUFBQXj48CF27dqFOnXqYMGCBRnet2LFiujSpQsWLVqEuLg41K5dG3/++Sdu306/3V14eDgOHTqEGjVqoE+fPihTpgyio6Nx9uxZHDhwANHRdrwRMSN//vwYPnw4ZsyYAb1ej2rVqmH79u04cuQI1qxZY1NPjE6dOsHT0xO1a9dGcHAwrl69imXLlsHLywvh4eGix04IIVkmk4u3Ft+oB+Ke23+et4nwyTgrUBz84e2s77AS8xKGUZ3tjuM/HCxfURHPl7FSzRrDw98PKXGWK2e2fD4QWz4faNO5ZQoFyrVrDbUUVYhKNaDLZMmBJQYtEPVIvHiA//oFSI3JTN8Pc598p2TQ4FAmd81Pwv0CrWvgKhiB5/eycP4g2+/jIIwxIHdh8AdvVXjpteC3z1h3jtyFxQ9MLHIlgBRkuNSGc+ueZ7nSpZeiAAArWxP86ikgPvr1301+/TT49dPm7xP6MZirLIkiJBux+6cqLCwMefPmRXh4OGbMmAGtVot8+fKhbt266Nmzp8X7/vLLLwgKCsKaNWuwfft21K9fH7t27UKBAgXSjMudOzdOnjyJSZMmYevWrVi0aBFy5cqFsmXLYtq0afY+BLPCw8ORM2dOLF26FCtWrECJEiWwevVqhIWF2XSeNm3aYM2aNZg9ezbi4+MRFBSEdu3aYfz48ShevLiDoieEENsxxsDfLm13JXIFmAh9AVihUuBHdokQkEg4BytU0uGXUXp4oHqfnjgyZwG4tbtQWEkwGFBzQG9Rz2mWyhNIcvDuK7ZQqh2+jMgihdo0WTToIAiC5UpQJgfU3q45YfTJCbzMZAlDVjFmSpy4ksACQNQTIDEWNu9IFRAC+LtOoiYdxgCVh3XLg8yxtzJLAkzlAVmr3hB2LAMSYsxWDQkwlcmz2i0gK1VZ0hgJeVcw/lZHzaFDh+Kvv/7CxYsXnRUTARAdHY1cuXJhy5YtaNeunbPDIYS8Q7gmwb6SfEfy8gfzzmH3abhBD+OUAYAm0f6YxBAYAvmXsyWZHCdHRWN22arQxMSamrmKQCaX472Pm6HrxlWSPAbOOfDygeWmg1LyDwbzdIEm4AYd7t68jqKFC0Gv179umq5SqRAZFQW/gECovHxdM6nxCo97Cby4L/6Jc+UDC7C/8bvYuEEPfuMkkGzD9p/+QWDFK7vOshpL9ClZ2/VE7e06jV6twFOSEPvnNrAbZ+CjVkJvNP1ulTEGhVyG24l6lOzUF6zQe06OlJDsy31+YxBCCJGGh/erRnU2foIoBWvX4GeCKZRgNRuC/7XTJbbAlNVpKtkn/l65AtBu2Xysbt9VlPMxmQwqHx+0WThHssfAGAP38gcSoyS5nuVgZKK9Lu2mUKFVxzD4eHmiScMG8Pf3Q3JyMi5evoLt/9uF27dvo6C3CyRgLPELBBKirVuqYC2VJ5AzRLzziYgplMB7NcEfXgWiHkN4VUn1ZtWNIAhgjJmWL+QuDJavhCiVa5JQegBgmVYB/ldp9GpHH3dI2ryBeXjjin9hNBndC+0rlUSp3AHwUCgQlaTBzou3UbBiNeweSUkNQhzpnUtsaDQaxMVZzooHBARApcq8WVFiYiISEy1/2hcUFGRTPw5CCHE2xmTgnj6AJoO1+c6k8hR1XbKsRkMY/9oh2vmyTKECq1RX0kuWadUC9b/9Bgcn27eck8lkkCkV+HT7OvgES1wW7+XnGokNLz+Xm2T+e+o0/j1lfo2/K2OMgecpCjy+lrVP+t8mVwB5Szh3qVAmmFwOVqQ8dLmLYEy/HujfrjkKhgRDIZdDpzfg5sMIrNl3BOHLV7pnbwalGpArkZwQh4SYSOQODgaANMumbt6+g/fKVXCLvhqWJOv0WPVv+p2xClaUPhZC3jXpfjuqVCqkpLjo2moRbNiwIdPeH4cOHcKHH36Y6blmzpyJiRMnWhxz7949FC5c2IYITTQa05pEtdpJzTlmj60AAQAASURBVMgIIe82D1/XS2yIXOrPcgSC1WkO/s/uzHdTcCBZ445O2dmgwbejIFcqsf+778Hkcpt7bsgUcig9PdF9xwYUCbV+pzCxMJkc3CeXc5MbMjngndN518+mmEIJnv894PEN+/r9KFRAvlJgztqxxkaCTIFZq7di1uqtAACVUgHdq12MgoKCMM0dkxqpZDI8i4pBqVJl8OEHocgbEgIvT0/ExcfjyrXrYDI5zp8/7+woCSFuLN1vyEKFCuHBgweIj4+Hn5+LlytmQZMmTbB//36LY95//32rztW9e3eEhoZaHJMnTx6rY3tT6ta2BQsWzNL9CSHEHkyhNJX627Lu25HU3mAq8RvJyZp0gvHqKSAmUvolKTIZkLcIWGhzaa/7CmMMH43+CoVDa2HTZ/0Q++gxAJZpkkemkEMwGFG8UX20WzIPfnmdWOLvnQNISTTtcuIM/sHu0efADTGFCrxgWSDqMRCbhd2V/AKBwALuWeHwis6KrZndjcFgwIGDf6W73dr33oQQYk663/atW7fG0KFDsWXLlkwrG9xRSEgIQkLEeRNWtGhRFC3qmO351q5di+LFi6NcOdrnmhDiJF7+gDbZtG2rMzEZ4BPgmFMrVZB3GgTj4vEOOb/li8sg7zQIzNIOFhIoUrcOhl86iXOr1uPY/CV4eeMmAMD4VoJDzhjAgBKNG6DWwL4o0biB08v7GWPgOXIDkQ+lv7iHL5jaW/rrvkOYTAYEFQT3zWVKbiREA+DQ6w2QyWWQy2QQBAEGoxEq5avta71zAjlzg3n6OjV2Qggh0kqX2ChYsCBat26NwYMHIygoCM2bN7e8bRgRlUajwZw5c7By5UrMmSNdIzZCCHkbY+zVhOKZcwPxDXTo5J8VKgVZq88g7FzhsGtkRNZpEFiQa+zSoPLyQo1+vVC9b0/0bf8Jjm//H3IzOdRg4OBIBMczwYjJy5ei8+e9nB1uGkyhAs+RR9rXqdLDtbfazGaYhzeQpyh4UEF0/6QNShUugFJFC8FDrYZOr8et+w9x5vJ1rNv2Pyg8PJ0dLiGEECfIsD5v7dq1aN26NT7++GPky5cPNWrUgLe3N02yHUgQBERHR+Pw4cNITEzE2LFjMWzYMGeHRQh5xzGl2pTcSHBSHwPvHGBqx09UZLWbAjothD/WOfxaACD7pD9kFWpJci1bMMZg8PfDFa7HFZ6+UkeZw98JUWWOefiA++cG4rKwZMFWSg8gZ4jLNQx9FzC5Arv+PobV22MyPL5OoZQ4IkIIIa4iw8SGl5cX9u7di2PHjmHTpk24fv06Xrx4IXVs7xTGGPz8/PDNN9+gQ4cOKFWqlLNDIoQQAK8mjZwDidHSXtjLT/SGoZbIPmwNqD1NlRsMgCBuzw3OZBA4hzJsqEsmNdwd8/QFl8lMlRsOagb7LDYBeUoVpaQGIYQQ4mLMdlSSyWQIDQ3NtDkmIYSQ7I95+oIzJl3lhncOMC/pqwNktRqDFSwB44aFwIsIAOJNkFn+ohh/7hGaRKXgI9HOSt7E1N7ggYWA+Bem/jCinVgGnYc/Pu3WH7/++isKFCgg3rkJIYQQYjf6yIEQQohVmIcPkCMEkDuw3FsmB/xzOyWpkYrlKwL50HCw+m0BuQKm8g07KNWQtfgU8gGT8O2PizBlyhQ8e+bkviXZGJMrTK9T/9yvnj87efgAgQWh9s+FJUuWoE+fPtDpdPaflxBCCCGiocQGIYQQqzGlCsgZYtoxRWwePkBAXods62orplBA3rgj5GOXQNaiG5DzVaNIxkyVK2ZwJgNSjwfng6zN55CPWwJZ3RZgMhm8vb0xf/589OnTBwZD9tvK0VUwxky7YgQWAnLmBd7YvUQQhHTfe845dPo3eorI5KadeIIKg+XI83rL0OLFi6Nv374YNWqUJI+DEEIIIdZx3829CSGEOAVjDPDOAe7hDWgSgJREO3oaMMDDG/D0BVOoRI1TDMzLB6xuC7A6zYAHN8Af3cbD43/DcP8G8vl4Qik3fT6gMwp4EJeEnOWrIrhSDbBCJYH8xTJsul26dGl06dIF48ePx5QpU6R+SO8Uxhig9gLUXuCCABi0WLl8KVSMI1+e3PDy8oRer0d8YiKuXL+Jjl27o0DR4oBcabZhert27XD06FFs2bIF7du3l/gREUIIISQjlNgghBCSJUyuBHwCwL1zmPoZpCQBBh3ATU03BUGA8KoBJ5PJIE/dspUxQKEG1J6A2sehW7mKhclkQJHSYEVK49+nyeg8ahYAQM4YOADhVWLn77+/QZ7QDzI9X1hYGAYOHIjdu3ejefPmjgydvMJkMkDlid8PHsHWrVszHNO0QzerEmzh4eFo1aoV3n//fRQvXlzsUAkhhBBiI0psEEIIsQtjMtMyEg8fAMCvP/+EbZs2oGC+vPDwUIMxBo0mBU9fvED12nUxctTobLN9uNGO3Tdmz56NVq1aoVy5cihYsKCIURFHU6lUWL58OXr16oWdO3fC09PxWxITQgghxDxKbBBCCBFVcooW/9t7IMNjJctVzDZJDXt5eHhgyZIl6Nu3L3bu3AmVyvWW4hDzChQogC+//BLDhw/H0qVLnR0OIYQQ8k5z/fpfQgghJJsqWrQo+vfvj5EjRzo7FJIFTZs2RXBwMFauXOnsUAghhJB3GiU2CCGEECdq06YNFAoFNm3a5OxQSBZMmDABmzdvxpUrV5wdCiGEEPLOosQGIYQQ4mQ//PADfv31V9y8edPZoRAbyeVyLFu2DEOGDEFiYqKzwyGEEELeSZTYIIQQQpxMqVRi2bJlGDRoEDQajbPDITbKkycPxo8fj4EDB4Lb0VCWEEIIIVlDiQ1CCCHEBeTPnx9ff/01hg4d6uxQSBbUq1cPZcqUwZIlS5wdCiGEEPLOocQGIYQQ4iIaN26MvHnzYsWKFc4OhWTByJEj8eeff+L06dPODoUQQgh5p1BigxBCCHEh3333HbZt24ZLly45OxRiI5lMhmXLlmHkyJGIiYlxdjiEEELIO4MSG4QQQogLkcvlWL58OYYNG4aEhARnh0NsFBAQgPDwcPTr14/6bRBCCCESocQGIYQQ4mKCg4MxadIkakbppqpXr44PPvgAs2bNcnYohBBCyDuBEhuEEEKICwoNDUWFChWwaNEiZ4dCsmDQoEE4f/48jh496uxQCCGEkGyPEhuEEEKIi/rqq6/w119/4dSpU84OhdiIMYbFixfju+++w4sXL5wdDiGEEJKtUWKDEEIIcVGMMSxbtgzffPMNoqOjnR0OsZGvry/mzp2LPn36wGg0OjscQgghJNuixAYhhBDiwnLmzInp06ejb9++EATB2eEQG1WoUAFt2rTB5MmTnR0KIYQQkm1RYoMQQghxcVWrVkX9+vUxY8YMZ4dCsqBnz554/Pgx9u/f7+xQCCGEkGyJEhuEEEJEZWmLUtq+NOsGDBiAy5cv4/Dhw84OhWTBvHnzMH36dERERDg7FEIIISTbocQGIYQQUSQlJaFVq1YYPXq02TELFy5EaGgoIiMjJYwse2CMYdGiRZgwYQKeP3/u7HCIjby8vLBw4UL06dMHer3e2eEQQggh2QolNgghhIjis88+w//+979Mx/3zzz9o1aqVBBFlP76+vpg3bx569+5NzSizQBAExMbGmj0eFxfn0OuXLFkSPXv2xJgxYxx6HUIIIeRdQ4kNQgghdouPj8eOHTusHn/8+HHcvXvXgRE5xtGjR/Hzzz+bPb5gwQKcP3/eoTGUK1cOHTp0wIQJExx6nezm/PnzKFCgAA4ePGh2TN26dTF48GCHNmnt0KEDdDqdTT8vhBBCCLGMEhuEEELslpSUZHN5vbttX7pt2zZ89NFHFhtAbtq0CaGhoQ7vg9G9e3c8f/4cf/zxh0Ovk10kJSWhfv36ePLkicVxnHMsXLjQ4U1aZ8yYgcWLF7tlco8QQghxRZTYIIQQYreQkBAUKlTI6vGenp6oUKGCAyMS3+jRo2EwGDIdl5SUJEk1xY8//oiZM2fi0aNHDr+Wu9u/fz9iYmKsHr9+/XoHRgOoVCosXboU/fv3R0pKikOvRQghhLwLKLFBCCFEFIMHD7Z6bN++faFSqRwYjbji4+Nx48YNq8efPHkSnHMHRmRKDi1evBh9+/alZpSZ0Gq1No3X6XQOiuQ/hQoVwrBhw/Dll186/FqEEEJIdkeJDUIIIaIYMGAAgoKCMh3n4eGBb775RoKIxOPn54eCBQtaPb58+fJgjDkwIpMSJUqgd+/eGDVqlGjntFSV4uhkjaPUqlXLpvG1a9d2UCRptWjRAn5+fli7dq0k1yOEEEKyK0psEEIIEYW3tzdGjhyZ6bh+/fohJCREgojE1bVrV6vHhoWFOTCStNq3bw9BELB161a7zhMbG4u2bdti3bp1Zsd8/vnnmDhxotslOAoWLIhPPvnEqrGMMQwbNszBEf1n8uTJWLt2La5duybZNd0R5xznz5+3uHTn1KlTbvfaJIQQIg5KbBBCCBHNgAED4OPjY/a4QqFwu2qNVF988YXFx5YqJCQEffr0kSCi/0ybNg3Lli3D7du3s3R/zjmaNGmC7du3W9xGNj4+HhMmTMCUKVOyGqrTfPfdd1aN69ChA8qVK+fgaP6jUCiwfPlyDBkyBElJSZJd151wzjFmzBhUqlQJGo3G7LjatWujb9++tBUyIYS8gyixQQghRDTe3t747LPPzB5v3LixW1ZrAEBgYCCGDBmS6bjRo0fDw8NDgoj+o1KpsGzZMgwYMMDixM+c8+fP4+TJk1aPX7p0qdt9Ml6+fPlMqzYYY/j2228liug/ISEhGDt2LAYPHux231cp7Nq1C+Hh4VaN/emnn/Dbb785OCJCCCGuhhIbhBBCRPX9999n2BhUJpNh9uzZTohIPF988YXFpEWuXLkkr9ZIVbBgQXzxxRcYMWKEzfe9d++eTeOfPHnilrt5ZFa10aRJE0mrNd700UcfoXjx4vjpp5+ccn1XtnPnToeOJ9Kw1L9Hq9VSUo8QYhdKbBBCCBGVv78//vzzT/j6+r6+zcPDAxs2bECpUqWcGJn9AgMD0aFDB7PHBw0aJHm1xpuaNWuGwMBArFq1yqb7Va1a1abx5cqVg6enp033cQXly5dH+fLlzR7/4YcfJIwmvdGjR2PPnj04d+6cU+NwNd7e3jaNt2bJmKt58uSJxWV6MTExGDduHOLj4yWMSjxz585FlSpVzB6/fv06ihcvjrNnz0oYFSEkO6HEBiGEENGFhoYiPj4ep0+fxtGjR5GcnGx180ZXN23atAx3PFEqlRg9erQTIkpr4sSJ2LRpE65cuWL1fQoWLIiGDRtaPb53795ZCc0lzJs3L8Pnr3LlyqhYsaL0Ab1BJpNh+fLl+PLLLxEXF2fz/RMTE5GQkGD2+PPnz+0Jz2nq1avn0PHO9vjxY3zwwQeYN2+e2TEGgwFTpkxBgwYNsvTacKbVq1djxIgRSExMtDju7t27+Oijj/D06VOJIhPXkydPzB6LioqyedtpQohtKLFBCCHEYapUqYI6depIsvWpVEJCQrB48eI0j0kul2Pr1q1OrdZ4M5Zly5Zh6NChmU4k3jR+/HirxjmjOaqYPvzwQ6xYseJ1RRFjDLVq1cLx48edHJlJrly5MGXKFPTr18+m0vwdO3YgMDAQDx8+NDumevXqGD58uNuV/H/88cd47733rBobEhKCbt26OTgicS1btgx37tyxauzp06exefNmB0ckLlt6nsTHx2PHjh0OjEZ8Op0OnTp1QqdOncyOOXnyJPLkyYNjx45JGBkh7xZKbBBCCCE26tevHyIjIzF16lTMmjULcXFxaNmypbPDei1Pnjz47rvvMGjQIKsnsaGhoVZVbTijOarYunfvjri4OCQkJECv1+PYsWMZ9oVxllq1aqFmzZqYO3euVeNv3ryJ9u3bW/WJ8I8//oiFCxfaGaG05HK51bvajBo1yu2WSR09etSm8UeOHHFQJI5ha6WQu1UWjR07Fhs3bsx0XGxsLBo3bozY2FjHB0XIO4gSG4QQQkTHOQc36sENOtOXUQ/OBWeHJaqAgACMHj0aX3zxhc09AKRQr149lC5dGkuXLrX6PhMmTLB4PGfOnG5drfEmxhh8fHwgl8udHUqGhg0bhpMnT1pVSbJ161abtji1ZhLmajp27Jhp1Ya7VhPZ2nvI2uoVV1GzZk2bxteoUcNBkYiPc45NmzZZPT4pKQl79uxxYESEvLsosUEIIcRu3GgA1ySAJ0SCRz8BIh8C0U+AmKemr+gnQOQj8OgI8PhI8OR4cKPe2WFneyNHjsSBAwdw5swZq8bXqVMHJUqUMHt8wIABbl+t4S4YY1iyZAnGjh2LyMhIi2Mt7TaREVuSIK7CmqqNkSNHul21BgC0adPG6rGMMXz88ceOC8YB+vfvb/XY4sWL29Tvx9kYYzb//Nk6nhBiHUpsEEIIyRLOObhOAx73AoiOABKjgZQkwFLCwmgAtElAUgwQ/QQ89jm4Ntnt1vxzTRL40wfgj26DP74N/uwhuFbj7LDSkclkWLZsGb7++mvExMRYdZ/vv/8+w9tVKhXGjRsnZnhOwQXB9LpNSTQl4zQJ4ClJ4Aa9y70O/f39MXv2bPTp0weCYL7iqU6dOjadt3bt2vaG5hQdO3ZMs9vSm1QqFfr16ydxROJo3Lix1VUKHTp0QNmyZR0ckbgqV66MVq1aWTX222+/hUKhcHBE4rL1569WrVoOioSQdxvjrvZXnBBCiMvjei2QEGlKVIhBJgd8coGpXfPTVp6cCH75BPjjO8CTe0CCmSSBfyBYviJAgRJgZau7zOM5efIkZs6ciQ0bNljVyHXEiBFp+jsolUrs3bsXH330kQOjdAzOOaDTACkJgC7FcuKNMUDpAai8AC8/MJlrLFP56aef8OzZM7OJJUEQULlyZVy4cCHTcykUCty6dQuFCxcWOUppLFq0CIMGDUp3+9ixY80m5dzBH3/8gWbNmlkcwxjDxYsXUa5cOYmiEs/Zs2ctbvcKmKo1rl275naJjWPHjlmd3Pj444+xc+dOB0dEyLuJEhuEEEKsxrkAJMUBmnjHXEDtDfgEgMlco6CQR9yDcOYQcO00kNojJLM/m0xmGqtQgpWvBVb5Q7DgfI4PNhPz58+HTqfDl19+icuXL2Ps2LEWdx949uwZfvvtNwQHB6Nbt25QKpUSRms/Lgim12lybNYTcB4+gFcOMJVzl99wzvH555+jW7duqF+/foZjtm3bhnbt2mV6rj59+mDZsmVihyipOXPmYPLkyYiNjYWvry+GDBni1kkNwPQc16hRA6dOnTI7pmPHjtiwYYOEUYmrUaNGOHDggNnjv/32G7p37y5hROJp0qQJ9u3bl+m406dPZ5rgIYRkDSU2CCGEWIUb9EDcC0Bw8PpgJgP8g8GUasdexwKuSYKwfwNw5V9AJgMsLAOw6NV9WdX6YPXagKmc+Jg4R7du3ZA3b16sXr0aBoMBN27cQEBAgNNichSuTQbingOCSL0kPP0A30CnJtySkpLQunVrrFy5Ennz5k133JqqDXev1sjudu/ejRYtWpg9funSJbes1kh18uRJs0tufH19ER0d7XbVGqmsqdqgag1CHMtiYkOv1+PgwYO4fv06NBrXWzucnTDG4Ovri5o1a6JSpUpWlQoTQohUuF5rSmpIubOJfzCYSvqlHPzWRQi7fwM0yeI9XsYA35yQteoFVsB8c05H0mg06NSpE3bv3g2j0QhfX1/s2LHDLZeXmMMFwbREyhEVRTIFkCO3U16Tqa5fv44vv/wSO3bsyHACmFnVRteuXbF69WpHhkjswDlHYGAgoqOj0x0rWbIkbty44YSoxFWqVCncvHkz3e3ffvstJk2a5ISIxFOjRg2cPHnS7HGq1iDEscwmNmbPno0pU6YgOjoaHh4e8PLyosm2AwmCgISEBBgMBhQrVgxLly5FgwYNnB0WIYSAG3RA7LPMl2A4gn9uSZcBCCf2gh/aakpEiP14GQM4wFr0gKyCtM3joqKiUKNGDTx48CBNR/7x48eb3eKVcw6DVgsmk0GuVLr8ewAuGE277xi0jr2Qf24wz4wbWEph3bp1uHDhAsLDw9MdEwQBQUFBGU6MAeDu3bsoUqSIo0Mkdjh27Bjq1q2bplmsWq3GtWvXssVzFxcXhwoVKuDhw4evbwsLC8OaNWucGJU4Dh48aPa9+3vvvYdr165JHBEh75YMExvTp0/HN998g379+qF///54//33Xf4NTXag1+tx6NAhhIeH4/jx49izZw8+/PBDZ4dFCHmHvZ4sSlmpkQYDAkLA5I7v7yD8sxv8sPmeE2JizT6FrGKoJNcCAK1Wi++++w7r1q3D06dPXyc3GjRo8HrNu2A04tKuvbj0+x+49+8pPL16A8KrcWofbxSsXBFFalZD9bAOyP9+eclit4bpdRoBGHTSXNDJyY1BgwahWbNmaNmyJQBTP5Tg4GDIZDKzzTU//PBDHDp0SOpQRccFI6DVmBrCcm5KGKo8ALWXyzR7tdfNmzcxevRo3Lp1CxUrVsT06dORJ08eZ4clqsuXL+Py5cto3LhxtloOV7JkSdy6dSvd7Xv27EHTpk2dEBEh7450iY2EhAQEBwdjwIABmD17trPieqelpKTgo48+glKpxOHDh50dDiHkHcbjXwLaZOcGoVCblgA4MMEunD8CvkfaEn3ZJwPBSrwv6TUTExMRHh6OlStX4vHjx8ibNy8e3L+PQ/OXYP/MeYh78gwyheJ1QiNdzK+OFalZDa0mj0Pphs5fxsI5NyU19CnSXjhnXjC1l7TXfEWr1eLjjz/GsmXLcOTIEQwcOBC7du3CBx98AAD47rvvMG3aNOh0OjDG8MEHH+DPP/+EXO6eE3/OBSAxBoh9AaQkmh+o9gJy5HapBsTk3ZKYmIg6derg4sWLAAAvLy/MmTMHffv2dXJkhGR/6RIb69atQ1hYGO7du0fNpZxoxYoV6NWr1+s3noQQIjWuTQbiXzo7DBOfnGCefg45NY9+DuGnSeJtXWstDy/I+k4E83bM47IkOTkZP/zwA36aMQuDy1bBo3MXbVp6w2QycEFAaJ/P0H7m9/D0k/4xpOJJMUBClPQXlsmBwIJOqxK4ceMGPvzwQ2i1WsTExGDKlCkYM2bM6+OCIOD58+fIlSsXVCqVU2IUA0+OB57fBQwWtul9m0wB5C4M5pPTcYERYkFKSgpiY2ORO7djk/KEkP+kS2dfvHgRhQoVoqSGk9WrVw+cc1y+fNnZoRBC3kGmJoxOmCyakxgD7oDEA+cChN9XZH3XE3toUyDsXSv9dWH6FDGsXn20Z96IuHDZ5n4i/NX3659fVmJajfqIe/rMEWFmHodB57zXqWAE4iOdcumHDx+iQ4cOiIyMRExMDACkq/CUyWQICQlx26QG5xz8xQMg4oZtSQ3AtHPT09vgz+6+fq0SF8K5aXmjILz6/+y3QaOHhwfy5MlDSQ1CJJQusZGUlARfX+etGyUmfq8+/UpMtFBySQghjpKS6MS+GmZoEkQ/JT93BIi465zHygXgxjnwG+ckv/Stw/9gQYsOMOr0EIxZ3xKVGwW8uH0Hsz5sjsQoJyQY4l5If803pSSYKpsk1rJlS1y/fj1NI9g3mzG6O8458Oyu/c9vQhTw5JZbJTd4cgKEh1ch3DoN4foJCLfOQHh8wymvM9EZDaaljZp40+/zlIT//l+f4np/cwghbiXDBYiWsosrVqwAYwz379+36UITJkywOmvJGDPbpf1dQRleQoizcM4ds12mvVISTGvtRcK5AH5sj2jnyxLGIBzfK+klk6KjsbR9NwgGgygTPsFgROSde1jTd5gI0VmP61Ok76uRkaRYyS956tQpTJ06FYULF4aHh2nXoOjoaOh0r5qncm6aRKZ+uduEMSoCSMx4ZxebaeKBlw/EOZcD8f+zd9bhUVxdGH9nduPEHUmw4q7FHYq7BocWKFqhTkvbr0XaUkrxFgvu7haKF3fXJESJ++7O/f4YEgjZmazMzu6k9/c88/Vj7t07ZzI7s3PPPec9iTHg7pwFuXUSiHnG64mkJgBJMUDUI5DrYeDuXwBJlejvIiecjndeZKcDOn3RNwTQZL/qk6H4CA6SkQoS9QQk4iFI/AtFOdYoFCVDlZVE4DgOs2fPRpkyZeDo6IgaNWpg/fr1Jo93+fJldOvWDV5eXnB2dka1atUwb948CS2mUCgUCdBk8S+itgYh0gqZPr4NpCZKN54pEAJEPQGJCZftkBsmTkVGYpKkL9ucTocr23bh4qZtko1ZKOnJ8h1LjJwMEGNTJczEwcEBn376Ke7du4fZs2cjKCgI8fHxuHnjOpCT9XoSmbvlThjl1pExAZKVBiRGSTtoSjyIrXxf3oIQwkdkPLzEC6Tye/V3To4HuXsOJOapXOaZj05rXASgTmObEYOFQAgBCb8P3b5V4Fb+BG77YnC7/gK36Q9wa2aCuxwGkplubTMplCKNbI6Nb775BpmZmXIdThK+/vprfP7552jXrh3+/PNPBAUFYdCgQdiwYYPRYx06dAiNGjVCbGwspk2bhj/++ANdunRBRESEBSynUCgUMxCrOmBtMqWzjbt0HGBswL/PsCCXw2Q5VPjV67iwbrNZ6SeCMAy2fPylZcZ+C8Lp+DB2WyHTOpNme3t7TJw4EQ8fPsRfixehZsVygDYbeifGOg3v5MjJstkVcUIIYKlJe8wTSSO+pIJEPgCiHhnam//f57dB4hSQesTp+O+csRBOUZEbRKcFd3QTuN3LgGd3UeD+S0sGOXcA3LpfZXViUyj/NdSyHUithlot2+HMJjIyEr/99hvGjx+P+fPnAwBGjx6NFi1aYOrUqejbt6/BZdNSUlIwdOhQdO7cGVu2bAFLS5BRKBRbRpNtbQuE0eaAEGJ2uh7RaYEnt21jVZBwIPevAR2HWPxQJxb8BVatAqe1gPOBECRFRuHm/kOo0aWj9OO/SY6NLZRkpQOuPlY7vB3LYMSgfoZ11r66v+0dLWeQqWSlWe7a6jR82lAxL8uMbwIkOQ6IemjaZ5/efFUtykZ18cyNsON0/HfVzga/p29ACAF3bDPw4NqrHUK/KQTIyQS3cynY3h+C8Q6UzUYK5b+CJDPs/fv3o1mzZnBxcYGrqys6d+6MW7du5eujT2MjOzsbH330EXx9feHq6opu3boJRjBERkZi5MiR8Pf3h4ODA6pWrYrly5fn6xMWFgaGYbBp0yb89NNPKFmyJBwdHdGmTRs8fGjcD8fOnTuh0Wjw4Ycf5u1jGAbjxo1DREQEzp49a/BY69atQ0xMDH766SewLIv09HRwNN+OQqHYIITjpEtDUakBdz/ApxTgXRJwkaL0IpEmnD7uhXmVUBydwfYeB3b8DLBT54P9cAaY5t0BmOhwyUgFSbPsqr8mOxvn1mwwyKnR/rMp+P7eZSzUJWExSUGFFk0NOgarUuH036Hmmlo4UjjfPIsDfmUA/3KAb2nzHBM6jfWiAcQmkHaOgLM7v70ZnaTNts20lGQjykt7BADB1YHydYEytfhnTGEkWVls9i2EUkqYGi3B1u+Ub4OH/9u9+Koxtgqn0z/JZ1Wvv5Nvbo56HDSaHNuP2nh0A3hwFW9GaTCV6oEd8DHYD/4HduR3YLuOBrwD8rRvuMPr+egkCoUiKWY7NlavXo3OnTujWLFimDVrFqZNm4bbt2+jadOmhQqMjh49GnPnzkX79u0xc+ZM2NnZoXPnzgX6xcTE4N1338WRI0cwYcIE/PHHHyhfvjxGjRqFuXPnFug/c+ZMbN++HZ9++im+/PJLnDt3DiEhIUad15UrV+Di4oLKlSvn29+gQYO8dkM5cuQI3NzcEBkZiYoVK6JYsWJwc3PDuHHjkJVlA8JnFAqFkotWwmgNNz9+YpWeDORkgXF2A5w9zB9XAhtJtJlh3A5OgE8gyNWTIEc2ASBgm3QCU7el6WOaa1MhRF6/CW2WYX87O0dH3NhzAInPjQub5nQ6PDxtuOPfZKQQDc0tFZsSBxAOjIsHP8Ey2aYc820yBZ0GelNPWDWgtheeGGqtZK8YGQaKFnuXAONbii/rGvuc1+QwxLGUlWYzE0qSnSHqyCGZqeAeXcnbCorUEiAuAkSvGKcNIPT94l6lmeRuuf04fY42iRzZFoS7fgp4c+HWzQts675AMQ+Q03tAntwGU+odsC168e2EAxJigBgFpBJRKArDrNyQtLQ0TJo0CaNHj8bSpUvz9g8bNgwVK1bEzz//nG//m1y7dg1r1qzBhx9+iAULFgAAxo8fj5CQEFy/fj1f36+//ho6nQ43btyAt7c3AGDs2LEYOHAgpk+fjjFjxsDJySmvf1ZWFq5evZpXu93T0xOTJ0/GzZs3Ua1aNYPOLSoqCv7+/gWiTAID+dCxFy9eGDQOADx48ABarRbdu3fHqFGjMGPGDISFheHPP/9EUlKSWYKkFAqFIilSvUTaO4FR24Fkp7+qsMKAODgDTq5ARpJ5Y0sh1Bgbwa8cmhqdkpIIbul3ryeNKjWYdv0BfwNWjfXBsCCxEWDKVzft8wbw/NJV/gXcgInd3h9mAgDKNm4I79LBRh0nPT4BSS+i4FHcgqHWUkRspMbzUQwsCzi6iDsBDEGbbZ30Dr0TSIZ3vmmzAZV9/olXLjoNP8myBZ0ZgJ+gGzJJZ1jAw5/XWYm8z18zQ6NlCOE1RhycCu9raeIjwUd4CXznNDl8hInYM4pwQGIM4GPic8dSECJyLd9qs3Pg/yvkCNHmAGo7Sc2TCpIQA0S/HTXD8NFbOVkgEQ/AEA6oXA/IeiOqimHB3TwLVYBxz1YKhSKOWb9mhw8fRlJSEgYOHIj4+Pi8TaVSoWHDhjh+/LjgZ/ft2wcAmDRpUr79U6ZMyfdvQgi2bt2Krl27ghCS7zgdOnRAcnIyLl++nO8zI0aMyHNqAECzZs0AAI8fPzb43DIzM+Hg4FBgf25ZNWOEUNPS0pCRkYGhQ4di3rx56NWrF+bNm4cxY8Zgw4YNePDggcFjUSgUikWRKpxe9cpvnickSQBOB4ZlJZhISbDiaq6AIuHe+Dzz2iHx9K5p4zEMb5MFefksHCqZtK5ePrXwaqRUq+6+wWB8S4NxcAHJTDWvzLG1UlH0TXwdnPiV8cIcQLaUFmuos8reCQyr4v/eQdXAlK8LlK5peKqblFFpZkAK0xJx9QJbtwOYuh3AlK/DO94KwADZNqY3Axh+f6rUvINZpxV24NiCDpIA5KWe6j0pL0HCtgNOLlCFfAa2ZW+Ql1G8DkfeBzneuU6hUCTFrDec3Al569at9ba7ubkJfvbZs2dgWRblypXLt79ixYr5/h0XF4ekpCQsXbpUMPojNjZ/zmRQUFC+f3t68j92iYmGl/VzcnJCdnbBH7/c1JE3I0QMGQsABg4cmG//oEGDsGTJEpw9exbvvPOOweNRKBSKxbBklLaZgp95SDGplapyh0oNpstwMGWqgLtwFOT2BTNssmzItU4jX8i65Y8l0Rc1MQpEpeZTpByL8eKVplRxkNAks1HZ8Wko2Rn5nYgMq2eSaCtGw4j7mu/HqOxAkiJBNNmAX2kgoCzw5GrhUVg2korC26nfFhIfAWSlg3A6MH7BYDwDAE4H8vha/o4MXyFIoierhBj4N1a/WkC0ZcFqMfSlnzk4ganTEtBkgzu6CfAOAFu3NdgWPcEdXPO6ny2mglEoCscsx0auAObq1asREBBQcHAJVoZyjzF48GAMGzZMb58aNWrk+7dQtRJj8ioDAwNx/PjxAur7UVG8d7Z48eIGj1W8eHHcunUL/v75hZ/8/PwAGOdwoVAoFIsilfMhd5KeG7kBhk+34DjzV+CksFGtFo0CNwgHJ7C9x4EJrgju5G6QU3vMtMmy4db2TvKlSdg7WzrU39yL9wpNFvDKB8N4BIA4uZnu2JDq3jEXluVtcXTJv9/RhT+3fA40G7EZ4FfuDUGT/frdLDGKd1R4BoBxcAaxcyi8EoeNpN7wz0aB7/GL14L3RJMNxt2XT+N7GwIwKhusOGjIvcCw/N+A0wnoaxgxlpVgHJwKXr0S5cG4e4M8uQXy8Brw5BZQtzVQukr+fg7OcplJofxnMOtpmBtt4efnh7Zt2xr12eDgYHAch0ePHuWL0rh3716+frkVU3Q6ndHHMIdatWrh77//xp07d1ClyuuH0fnz5/PaDaVu3bo4fPhwnnhoLrk6Hb6+vtIYTaFQKOYi1UtkTiafM2/vBDi5AWo7MAwDYqg4oBhSTEycXWHWpM7OAeyQqWB8S4A8ugm8jAZTuR5IRirw7F7hn38bwr2yyXIEVK5ocCRF+WaN4V+hPFx9+Uoh1Tp3gG/5sji9zLCKJ/4VLRyFyKrEJ0OFYe8MOBV7nf6TKxpqTpqCoRNzqVHZ5dcs0GryRy3YO/H3TE7mW9EMjPVs1oddwfRfvXA6XvTVzYevuKThtU2INsewUrH2NqCvAYBxdgPR59RwcgVTqhJfClanBZOrn5GmbxGMAM7C0dHWg0Ghzkc7A6M1bOk7+jbFy/COxDdTupLjeY2NEuXAVGsEeL1a1EyIft2HYcAEV5LXVgrlP4BZb4cdOnSAm5sbfv75Z2j0vCzFxQmrPXfsyNe4nzdvXr79b1c5UalU6N27N7Zu3YqbN28adQxz6N69O+zs7LBw4cK8fYQQLF68GCVKlEDjxo0NHqtfP762/LJly/Lt//vvv6FWq9GyZUtJbKZQKBSz0ZvHbSLJcfxLq4sHYO8EkplivnAoII2NAUHmlbV1LgbGtwQAgClXDWyP9/mtScHKXgZBCJiAoML7mUFQ3doG920ycgiG/D0fvuXKAADaT52MIX/PN+iz3mWC4SSSiioJhk6CheB0fBi8qw8/QWYYkLREIC3BejaZytv3A+H4qIzcLXduqdPmT8NQC4iKWgmGVfFVlAwh7jlISjzg6g14FQcyUl8LiYrBqmxHiNK7uH4nrTYH4DgwgeXABFfln53RT0DC7xTsa+cAuNvg4hjDiD+nGYZ3yBGucMFYKX+TJIZxKgaUr5H/Or6MAjm+FUhNAtOoE5jyNUGe3QV3+I1CAQRgqjaU32AKpYhjVsSGm5sbFi1ahCFDhqBOnToYMGAAfH198fz5c+zduxdNmjTB/Pn6X4Rq1aqFgQMHYuHChUhOTkbjxo1x9OhRPHz4sEDfmTNn4vjx42jYsCHef/99VKlSBQkJCbh8+TKOHDmChAQzXkQEKFmyJKZMmYJffvkFGo0G9evXx44dO3Dy5EmsXbtWMN1FH7Vr18bIkSOxfPlyaLVatGjRAmFhYdi8eTO+/PJLo9JaKBQKxaJI+RKp0wDJMdKNl4sENjIBweYlMiS/hG7GGLPtyId/KWnHewu/d8rBLcAfKdGFX5NVI8Zh1YhxRh+DVatQtYMM0ZV2jqanjAB8ZMZL40rZivNqomYNWBXAqAAi4KjLSs33z7w0DlucMBbzABKjC+0GTgfEPDF+fBePAtXurAWjsgPxKQnEhSNfZIMmG+ThJcPG8C9tM+dTALW9cAQUIYYJ9TIq247YAMDWaAbuQX7tE3L3Isjdi3r7EzBgylUD42qg2C2FQjEYsxPzBg0ahOLFi2PmzJn45ZdfkJ2djRIlSqBZs2YYMWKE6GeXL18OX19frF27Fjt27EDr1q2xd+9elCqV/+XO398f//77L3744Qds27YNCxcuhLe3N6pWrYpZs2aZewqCzJw5E56enliyZAlWrlyJd955B2vWrMGgQYOMHmvx4sUICgrCihUrsH37dgQHB+P3338vUAWGQqFQrAnDMCBvh7bbEgwrzYuuhw/g4AhkW7YSicF4+oGxcKlQlmXRcvz72P3dz7zWiQXgtDo0HzvSImPnw1rREULYOVhvgskwfL5+VhoK0x3RvRLN1aoc4MDaiNbEm7j7GebYMBUP/8L7yAgTUBrkZQTAmeBmVdvzqTi2CvtKQ8McUWQ7G3S+vQXjVxJMi54gYdsK7avVcXiclIZ3hvewvGEUyn8QhrylqDlp0iSEhYXh+vXr1rKJAiAhIQHe3t7YunUrevXqZW1zKBTKfwiSlgBkphbe0RrYO/NCehLAHVwHcuWk9csJMgyYZl1NT2MxguToGHwVXBW6HOkV+Vm1CqUb1MNnpw9LPvbbEEKA2CfWv3a5uPmCydXpsBYcxwtnEh04QsC+4WjRarVQq9WIf5mAAcNGYPjI0Rg8eLAVjRWGRD0U0JMwE8diYEpVln5cMyFJsSAP9K/u60Or1QEsC7tqTcG4WPk7VxiE8A43I+9TQggYOweb0UMxBO7+Fd65oafaiUbHwU7F4sCtxwhZsRvrtmxDp06drGAlhVK0sUF3PYVCoVCsiqNlRSzNwqmYZEMxdVrYyMSYAVOzqSxHcg/wR/efvrXY+CGL51ps7DdhGOa14KfVYWzjnmFZwNEF67ftwosYXn9Mq9UhLT0d5y9ewsDho1CifCUcPX4CK1assLKxIvgGS59+wDCAfxlpx5QIxsMPTMUGhZ4zx3HgOIKXySno8flMEH1VUmyN3Oo8Bgo+50YUbd6xy3C9FRuBrVAb7IhvwLToBXgHIocj0Oo4xKdlYvmZ66jz8wp0WbgFyZnZtn3/USgKxgZrRFmWzMxMJCcni/bx8vKCvX3h4W9paWlIS0sT7ePr62uUHgeFQqFYG0Ztx5dNLEytXm5YtaQvu4xvCaBEOeDF48JFBy0FwwIVa4MpJt8kve1H43F5yw48v3gFnM4MAdW36DL9K5SoXlWy8QrF2R1It4Fy6c5uYGwkrYMAWLZyFfoOGAio1RgxZAjWrFlToN+xY8fw5MkTlClje5N9Rm0H4l8GiCqouWYyvsEWT/UyB8bNB6jREoiPAIl5mvfs1ep0ULEsGIbBg/AX+HPjLqzZfwyp6Zk4ceIEWrVqZVW7DYJhAcdi/Dlpc6AvXUqj0cDOzg5Xb9zAL7/Pw8Yt21CjbgNUqqSsyiGMnQMvClq1IdYvX45Ro0bp7bdz507Ex8fDx8dHZgsplKJNgV9ihmHyPKZFkY0bNyIwMFB0O3PmjEFj/frrr4WOFR5umjhZ7jVgbeRliUKh/MewxdVAJ1fJdQzYFt2t59TItaGp5VNQ8h1PpcKHOzfAM6gkWLUEjneGQYPB/fHel5+YP5Yxh1Wp+VLCVoUBnD2sbMNrLly4gDp16kCt5tetRo4U1jtZtWqVXGYZDVPME/ArbdYYeZnWPiUlS1+zJIydA18JpWZrMBXqgwmuiqV7wjBuxny0+OAzVOk7Bou27EVqOl/Sdvny5Va22AgYBrB35H9X7J14JzXD4nlEJC5cuoxVa9ejfrNWqNekJTZu4bUqVq5caV2bzaRv375wcXHR26bRaLBu3TqZLaJQij4FNDamT5+OBQsWIDY21naVls0gKioKt27dEu1Tt25deHoWrlb8+PFjPH78WLRP06ZN4eho/CrBrVu3UK1aNRw/fpyWg6VQKLJDCAGSovXmC1sFVgV4FQdjYEizMegOrgOu/GMVBwfTvDvYJtbJtU6Oisbcdt0RffsuiAnnTnh9fzR9fzgGLfodrBWiEwnHAfHPzCvdaw6uPmBcPKxzbD2MGzcOkyZNQuXKvJYEx3EoV64cnj59WqBvcHAwHj9+bNMLKCQtia9+whknQKnRapGVlY1s90D4lq1oGeNkYMGCBZgwYYLeNicnJ0RFRcHd3VZSsoznq6++wowZM/S2BQQEIDw8PM9Jp0RGjBgh6KCpWbMmrl69Kqs9FEpRp4Bj4/jx42jdujXOnz+PBg0aWMuu/zyzZs3C999/j7i4OEGPL4VCoVgSos0BEqOsbQaPu7/FQslJTha4pdOBtCT5nBsMC/gWBzv8KzBWTFfUZGdj7w+zcHDmHDAsA05buIOAgIAAyAHwvHQAjj15YHE7Re3JzgASX8h/YDtHwKuEzSwCZWZmolevXti/f3++/T/88AO+++47vZ85cuQI2rRpI4d5JkN0Wr4kamq8eD9CoOM4sAyDrQePYcpPc/DBuPGYPn26PIZagISEBBQvXhzZ2frTApcsWYIPPvhAZquk48GDB6hQoYJg+549e9C5s7wRbVJy8uRJNG/eXLD98uXLqF27towWUShFmwJu+ubNm8Pf3x9ffPEFMjIyrGHTf55Hjx5h3rx56NKlC3VqUCgUq8Go7QFbWI12crVofjxj7wi211i+NKEck1SGBRycwPb8wKpODQCwc3BAj5++xTdXT6PRsBCoHXh9KVad/2/BgYB7lRufAYKLyMEGpOH404dWX3VkHJwBl8KjLCWFVQEe/jbj1ACA7du3662iNmzYMEE7lSBiyKjUYALKAGVqAd4leL2GtyK3MrOycPbKDfy8aDlKt+yG/pO/QlRsPFauXAnOQqWN5cDLyws9evQQbFfC9RPjnXfeQdOmwsLJikq30UPTpk1Rvnx5wXalXz8KxdYoELEBAP/88w86duyI4OBgDBkyBI0aNYKLi4tN/YAXNTiOQ0JCAg4dOoTVq1fDy8sLYWFhCAwMtLZpFArlPwwhBEiOsZ6QqMoO8AywSArK25Bn98BtnMenNVgqcoNhAXsHsCGfgPEvZZljmEFGUhLuHT+J55euIOLaTWQkJYNVqXD6yiU8TklELDhEQ5dP/m/SpEn4448/rGYz8Op7mhIHZKZY/mAMC3iX5B1/NkT37t2xevVquLkV1B1p27Ytjh49WmC/o6MjoqKi4OHhIYOF0kEIAXQagBDcvXsP1WrVFnRgHD16FK1bt5bZQuk4dOgQOnToINh++/btvNQjJbJixQpBLRg7OztERkbC19f2NVKE+Omnn/DNN9/obfPy8sKLFy/g4OAgs1UUStFEr2MDAM6fP4/ffvsNe/fupZEbMuLv748+ffrg66+/pk4NCoViExCO450bcuttsGreqSF16UcRSMQjcJv+BHKypS8Fy7CAiyvYgVPA+BSXdmwL87///Q/Tpk3T2+bt7Y3IyEirv5wTQoC0l0B6kuUOwqr49BMbc2o8e/YM3377raAg6Lp16xASEqK3bfHixRgzZowlzbM49evXx8WLF/W2hYSE6K0MoxR0Oh1Kly6NiIgIve1Tp07F7NmzZbZKOtLS0hAQEID09HS97b///jumTJkir1ESEhERgaCgIEEdo02bNqFv374yW0WhFE0EHRu5ZGRkICIigjo3LAzDMHBzc0NQUBAtD0uhUGwO3rkRC2hlitxQqXldDZX8wnEkLRncgbXAg2uSjKfjOKhYFqjeCGzbfmAcnSUZV07Cw8MRHBws+HK+efNm9OnTR2ar9EOy0nlHnESOKZ1Ox/8uOxYD3HxldbQZyg8//IBmzZoJlv/MzMxEYGCg3nL3DRo0wPnz5y1tokVZuHAhxo8fr7fN0dER0dHRihbZnDZtGv73v//pbfP390d4eDjs7Oxktko6Ro4cKZiWUaNGDVy9elXRUePvvfceDh48KNj2ti4OhUIxjUIdGxQKhUKhAAAhHJCWCGSlWfZA9k6Aq7dVJ5CEEJDbF0AObwAy03m9CSN/LrU6DmoVi4jkNMy+FoEF+09YyFp56NChAw4dOqS3rVOnTti7d6/MFglDOB2fmmLGd1Wr00GtUiEmLh6bDoRh0tQvJLRQOjiOQ/v27XHo0CHRCifjxo3D4sWL9bbdvHkTVatWtZSJFicxMRGBgYGCIptKj0p59OiRqFbDrl270LVrVxktkpbCRDYvXbqEOnXqyGiRtGzatAn9+/fX28ayLJ49e4aSJUvKbBWFUvSw3RpfFAqFQrEpGIYF4+oNuPsBrAqSe8UZli+f6e5n9VVxhmHAVm0AdsIsMN1GAcXLvG4UsI0AyNG9rioS9uQFeq4+iHK/rMfCA//gypUrFrbasowYMUKw7cCBA4iMjJTRGnEYVgXGIwDwCQKc3Q0WhdVqtdC9uoYXr97A4PGfILheC3z9w0+CofLW5sSJE2jevHmhZVvFrp/SRQw9PT3Rs2dPwXaln1+5cuVEJ/5KP7/CRDaVLiLarVs3eHrqFzjmOA6hoaEyW0ShFE1oxAaFQqFQjIZwHK6cDkP5kgEo5uIMjuOMTqPLFftjGBaMowtQzNPqDg0xyMtokIhHQPQzkBdPgMQ4QKcFwABqNeAVgNAj/+DozQc4/SwaTxNT831+woQJ+PPPP61jvARkZWUhMDAQSUlJettnzJiBL76wzagGwnFAdjovgqvJeiWGm//1h2NYbNq+Cxev3sCRk2dw/fbdfO2rVq3C0KFDZbTaMIYPH47vv/8ewcHBov0IIahevTpu3bpVoM3Pzw8RERGKTmc4fPgw2rdvL9h+69YtVKlSRUaLpGXVqlUYPny43ja1Wo3IyEj4+fnJa5SE/Pzzz/j666/1tnl6euLFixdwdLRcdSxLM3HiRMyfP19vW/ny5XH//n1Fp9tQKLYAjdigUCgUitEwLIvRkz9FYLV6+ODjL3D73gOjx3gRE4uPp/2I31ZsAOPmY9NODQBgvAPA1mwCtsMgqEZ8DdXHc6GaOh+qqX9C9dHvUA37HC8qNcbaqw8KODUAXsBRKFReCTg6OmLQoEGC7StWrBDU4LA2DMuCcXLlv2feJQH/soBfWcCvDL/5l4PKvyw2HTyBOUuWF3BqALa5apycnIzExMRCnRoAH4UkFLURGxuLffv2SW2erLRu3RqlSglXGlJ6VEOfPn1QrFgxvW1arRZr166V2SJpGTp0qGDUUWJiInbu3CmzRdIiFjH18OFDnDp1SkZrKJSiCXVsUCgUCsVorl27hitXriAjIxPL1m5EzZbvoW7brtA4eQBOboCdA5+ywar4FBNWBagdACdXwNUH8CyO7WHnMe+vFVi8dKlgqUalMXToUMFVt4SEBOzatUtmi6RFqCwjANy/fx9nzpyR0RrTYRiGd3awKn57dc3EJh8nTpzAo0eP5DLRIMRy9/UxePBgqNX6BXmVPvFXqVSCEQ0AEBoaCo1GI59BEuPi4iJ6rZcvX26zjkVDKFmypGjEjdK/n7Vr10bNmjUF25V+fhSKLUAdGxQKhUIxGn0vYU1btIR9MXcwxTzBeASA8S7Jbz6l+P96BoAp5gXG0QWM2g6DBg2CnZ0dHj9+jJMnT1rhLKSnVKlSoi/ntrjqbwx16tRB9erVBduV/nLesWNH+Pv7C7avXLlSPmMMYPv27aLaEm/j7++Pzp07623bu3cvYmJipDLNKog5NmJjYxVffULM8Xbz5k1cunRJRmukR8xxeujQIYSHh8tojbSIRUwBvJMyLc3CwtwUShGHOjYoFAqFYhQ5OTlYs2ZNgf1iL2368PHxQffu3QEof8L/JmJ/h0OHDiEiIkJGa6SlsJfzjRs32qzIpiHY2dlhyJAhgu2rVq3KExe1Nnfu3EFwcDCcnJyM+pzQ9dNqtXrvayVRtmxZtGzZUrBd6Y63xo0bo0KFCoLtSn+OduvWDV5eXnrbCCGKF9kMCQkR1LFJT0/H5s2bZbaIQilaUMcGhUKhUIxi9+7dePnyZb59NWvWRO3atY0eK3eStWXLFqSkpEhin7Xp3r17kVbAF0tnSEtLw5YtW2S2SFrEHDfh4eE4duyYjNYIs3LlStEVbiE6deokKDKp9HQGQPz67dmzB7GxsTJaIy2FORbXr1+PzMxMGS2SFgcHB4SEhAi227KOjyH4+PigW7dugu1Kd7xRKNaGOjYoFAqFYhT6VgVNmWABQPv27VG8eHFkZGRg06ZN5ppmEyhZZNMQfH190bVrV8F2pa8aV6lSBQ0bNhRst4Xz02q1uHz5MurVq2f0Z8WiUm7fvo0LFy6Ya55V6d27N1xdXfW2FYWoFDGRzaSkJOzYsUNegyRGzHHz6NEjxactip3fyZMn8eCB8ULcFAqFhzo2KBQKhWIwL168wIEDB/Lts7OzE53Ii6FWq/NKaBal1arCFPBPnz4tozXSI+bI+ueff2xOZNNYxK7f9u3bkZiYKKM1BTlw4ADee+89k8tDip2f0u/Doi6yWbx4cbz33nuC7Uq/frVr10atWrUE25V+fh06dEBgYKBgu63p+FAoSoI6NigUCoViMKGhoQUqmHTv3h0+Pj4mj5k7yTpz5gzu3i1YZlOJ1KlTBzVq1BBst4VVf3N47733EBAQINiu9JfzAQMGCGpXZGdnY/369TJblJ/Vq1dj8ODBJn++atWqaNCggd42paczAOKOm1u3buHixYsyWiM9Yud35MgRPH/+XEZrpKcwkc3U1ILltJXCm858fdiSjg+FojSoY4NCoVAoBkEI0btaZqxo6NtUqFABTZo0AaD8CXEuRV0Bv7CX85UrVyr65dzd3R29evUSbLfmqnFcXBwIIaLVWwxBKOomOTkZ27dvN2tsa9OoUSNUrFhRsF3pjsWuXbvC29tbbxshBKtWrZLZImkJCQmBvb293raMjAzFi2yK/TZERkbi8OHDMlpDoRQdqGODQqFQKAZx9uxZ3L9/P9++wMBA0fKmhpI7yQoNDYVWqzV7PFugMAX8oiyyGRERgaNHj8pojfSIpdtcvHgRN27ckNGa16xdu9asaI1cBgwYAEdHR71tSp/4/9dFNleuXFkgsk5JeHt7i4psKv37WbFiRTRu3FiwXennR6FYC+rYoFAoFIpB6HvZGjZsmGCFDGPo27cvnJ2dERUVhYMHD5o9ni1Q1EU2K1WqhEaNGgm2K/38WrZsidKlSwu2WyNqgxCCffv2oWPHjmaP5e7ujt69e+ttO3bsGJ49e2b2MazJ0KFDoVKp9LYlJycrXmRTzPH2+PFj/PPPPzJaIz1i53f69OkCTnalIeZ427lzJxISEmS0hkIpGlDHBoVCoVAKJT09HRs3biyw39w0lFxcXV3Rt29fAMoXh3sTsZfzoqCAL3b9d+zYoeiXc5ZlMXz4cMH2NWvWICcnRz6DAFy+fBk1a9YUjAQyFqHrVxTSGQIDA0VFNpXueCusxLbSn6O5FbOEUHraYr9+/eDs7Ky3LScnB+vWrZPZIgpF+VDHBoVCoVAKZcuWLQU0IZo0aYIKFSpIdoxcJ8CuXbsQHx8v2bjWpKgr4Pfv39+mRTbNZdiwYYJtcXFx2Lt3r4zW8JNVqZyJANCqVSsEBwcLHkvJ6QyAuGPx6NGjio9KEfsubN68GSkpKTJaIy0qlUr0/lO6yKabmxv69Okj2K50xxuFYg2oY4NCoVAohWIJ0dC3adasGcqVKweNRoO1a9dKOra1KOoK+IW9nCt91bh06dJo06aNYLuc55eVlYVHjx6hSpUqko0pFpXy9OlTnDhxQrJjWYMuXboIVmwqClEpgwYNEhTZzMzMxKZNm2S2SFrEIqZevHiBQ4cOyWeMBRBzvF25cgVXr16VzxhKkScrKwspKSkmb1lZWdY+hUKhjg0KhUKhiPLo0aMCExxnZ2f069dP0uO8Kfi3fPlyEEIkHd9aFKaAf+TIERmtkR6x87t06RKuX78uozXSI3Z++/btQ3R0tCx27NixAz169JB8XLFVcaWvGtvb2xd5kc3u3bsLtiv9+lWoUAFNmzYVbFf6+TVv3hxly5YVbFe6Y5hiO2RlZcHbyRnu7u4mb2XKlLF55wZ1bFAoFApFFH3pEn379oWrq6vkxxo6dCgYhsH169dx5coVyce3BkVdAb9FixYoU6aMYLvSX8579uwJNzc3vW06nQ6rV6+WxY6NGzdiwIABko9bpkwZtG7dWm/b1q1bkZycLPkx5UTMMfXkyRPFR6WIrfqfPXsWd+/eldEa6SlMZFPJaYuFVe9Zs2YNsrOzZbSIUlTJyclBBgiGoRjeh6vR2zAUQ3R0tOy6UsZCHRsUCoVCEUSn0+kN15Y6DSWXUqVK5ZWPVfqE/02oyKZtvwyJ4ezsjIEDBwq2r1ixwuLRReHh4XB1dYW7u7tFxhf6fmZmZuoVDVYSNWvWRJ06dQTble54a9euHUqUKCHYrvTz69u3L1xcXPS2aTQaxYtsDhs2DAzD6G1LSEjA7t27ZbaIUpRxYhg4s8ZvTgLfUVuDOjYoFAqFIsjRo0cRHh6eb1+5cuXQvHlzix0zd5K1bt06mw97NJSiroAv9nIeHx+PPXv2yGyRtIg5pu7cuYPz589b9PirVq0STRkxl169eglGpSh9YgyIRzVs2bKlSItshoaGQqvVymiRtLxZMUsfSv9+lipVCu3atRNsV/r5UWwL1oxNCSjFTgqFQqFYAX0vVcOHDxecxEpB9+7d4enpicTEROzatctix5GToi6yGRwcbDMim5agQYMGoqKdljw/juMQFhaGVq1aWewYzs7Ogmku586dw507dyx2bDkYOHCgqMim0qNSxCKmoqOjcfDgQfmMsQBijsWrV68qPm1R7PwOHDiAyMhIGa2hFGXUDGPypgSoY4NCoVAoeklMTMT27dvz7WMYxqIrxwDg6OiIQYMGAfjvpKNcvnwZ165dk9Ea6RFbFd+3bx+ioqJktEZaCsuFX79+PTIyMixy7JMnT6Jp06ZgWcu+soldP6U7pry8vNCzZ0/BdqWf3zvvvINmzZoJtiv9OdqsWTOUL19esF3p169Hjx7w8PDQ28ZxnGw6PpSij5oxfVMC1LFBoVAoFL2sX7++gHBZu3btUKpUKYsfO3eSdejQoQKpMEqlqCvg9+jRQ1ADoii8nA8ZMgQqlUpvW2pqKrZt22aR465cuVJ0RV4qGjRogMqVK+ttCw0NhUajsbgNlkTMMXX27FnFR6WInd/u3bsRFxcnozXSwjCM6D2wdu1aRYtsvunM14ccOj6U/wYMw5i8KQHq2KBQKBSKXvRNtMVWdaWkdu3aqFGjBgghCA0NleWYlqYwkc1Fixbh3XffxeTJk/H48WP5DJMIJycnUZFNpZfw9ff3R+fOnQXb33//fbi6umLYsGF4+vSpJMdMTU3Fy5cvUbp0aUnGE0MsKiUmJgYHDhywuA2WpG3btihZsqRgu77qT0qiMJHNtWvXymyRtBQmsqn0tEUxx9T9+/dx5swZGa2hFFVoxAaFQqFQ/nPcuHEDFy9ezLfPw8MD3bt3l+X4b06yitJqldjLeU5ODs6fP4958+ahSZMmikzdEHN83bt3D+fOnZPRGukRO7+srCykpaUhNDQUXbt2RXp6utnH27RpE/r162f2OIYiFpWi9Iiioi6yWaxYMdHvitKfoyVLlsyrmKUPpX8/69ati+rVqwu2K/38KLaBykR9DRWN2KBQKBSKUtH3EjVo0CA4OjrKZkNISAjs7Ozw6NEjnDx5UrbjWpKgoCDRl9dcoqOjMX36dMsbJDH16tVD1apVBduV/nJev359ODg4FNrv5s2b2LJli9nH27p1K3r16mX2OIYSEBCATp066W3bvXs3YmNjZbPFEhQmsrl//375jLEAYqv+169fL9IimwcPHlS0yGZhOj4bN26UxFlK+W9Dq6JQKBQK5T9FTk6OXj0EudJQcvH19UXXrl0BKH9CnMuMGTNw/fp1g/reuHHDwtZID8Mwot+TDRs2KPblXKPRoEWLFgbn8t+7d8+s4927dw9BQUGCZYIthdD102q1ik9nKF++vGipaqU/Z5o2bSoqsql0EdHciln64DhO8WmLgwcPhlqt1tuWlpYmibOU8t+GpqJQKBQK5T9BYmIiHj16hF27diE+Pj5fW/Xq1VGnTh3ZbcqdZG3atAmpqamyH19KEhMTMWPGDIP7KzUsXuzl3JIim5Zmy5YtePjwocH9hcqLGsrKlStFV3AtRefOneHr66u3Tek6KUDRF9kUO79169YhKytLRoukpTCRTaV/P9905utD6Y4pivVhwZi8KQHq2KBQKBQK1qxZgxIlSqB8+fIYPHhwgfaRI0daRRW7Q4cOCAwMREZGBjZv3iz78aUkPDzcKOdM8eLFLWiN5fDz80OXLl0E28eOHQs/Pz+MGTMGz58/l9Ey84iOjjaqf2BgoMnH0mq1uHjxIho0aGDyGKZiZ2eHIUOG6G27efMmLl26JLNF0tKnTx8UK1ZMb5tWq8W3336Lbdu2KTayaOjQoYKlgRMTE7Fz506ZLZIWsYiwhw8f4vTp0zJaIz1ijql//vnHKOcqhfI2NGKDQqFQKEUarVaLMWPGIDMzEwAKhNqzLItu3bpZwzSo1eq8SZbSV6v8/PyMcg4p1bEBiL+cZ2RkIC4uDkuXLkWXLl0UM4EsV66cUf3NuX6HDh1Chw4drFZiT+z6Kf0+LExkc/HixejduzdKlCiBHTt2yGeYRBR1kc3cillCKP372bFjRwQEBAi2K716D8W6qBiYKB5qbcsNgzo2KBQK5T9OXFwcMjIyBNs5jkPz5s1x7do1Ga16Te4k6/Tp07h//75VbJCCgIAAjB8/3uD+5qz4W5tGjRoZJDR748YNbNiwQQaLzKdr165o166dwf3NcWysXr1ab+SUXFSrVg3169fX27Z+/fo8J6hSMUQvKDk5GUOGDMGzZ89ksEhaxM7v0KFDCA8Pl9EaaSks3WbTpk1IS0uT0SJpedOZr49Vq1ZBp9PJaBGlKMEypm9KgDo2KBQK5T+Ot7d3oX0iIyMxbdo0GawpSKVKldCoUSMAyl+tmjlzpsGTY39/fwtbYxl0Oh3atGljcC6/uSKbcsEwDNavX4+GDRsa1N9Ux0Z8fDy0Wq3oqq0cCE0ek5KSFBnJ8Ca3bt0yKBomLS0N//zzjwwWSUu3bt3g5eWlt40QoniRzdyKWfpIT0/H7NmzERYWplidIjHHTUREBI4cOSKjNZSiBE1FoVAoFEqRxt7eHj4+PoX2S0pKsrwxAuSuQCp9tcrFxQW7d+8WDYXPxcnJSQaLpGfXrl1GVXQREhq1Rby9vXHkyBHRUP9c/Pz8DB739u3bePToEQBg7dq1CAkJMdlGqRg4cKBg1I2S0xkePHiAcePGGSwyqcToBgcHB1GRzR9++AEBAQEYMmQI7t69K6Nl0lCYyOaPP/6IVq1aoUyZMoosFV65cmW8++67gu1Kvv8o1sWUNJTcTQlQxwaFQqFQDFpdHjdunAyW6Kdfv35wcnLCixcvcOjQIavZIQUODg5Yt24dxo4dK9qvUqVKMlkkLZGRkUb1V1rKTbFixQp1ThUrVgwqlcrgMefPn4969eqhVq1aWLJkCVq2bCmBpebh4eGBnj176m07cuSIooRf32T16tXgOM7g/kIVYmwdsXSUnJwcxMTEYM2aNWjXrp0iK8EYkk4UERGBPn36FLnz27p1Kz755BMsXbpUMRpFFNuAMWNTAtSxQaFQKJRCV5d//fVXDBw4UCZrCuLm5oY+ffoAUL44HACoVCosXLgQY8aM0dvu5+cnqHFg65QuXdqo/koUSbW3t8e6devQqVMnve3vv/++UeOVL18eSUlJuHbtGu7fv4/q1auja9euRldikRqhkHhCCEaOHIkpU6bgyJEjiiqx6eDgYFR/pTnecqlSpYpBTpmIiAgsWLBABoukJTY21qB0otjYWJw6dUoGi6Slf//+glF7Wq0Wc+bMwZgxY1ChQgVERUXJbB1FqdCIDQqFQqEUeYRWMFUqFVauXIlPPvlEZosKkruCtXPnTsTHx1vZGvNhGAaLFy/Ghx9+mK88o5+fH86dO2dFy8yjc+fOaNOmjcH9lejYAPh7Y8+ePRg9enReOo1arcb48eMxZ84co8YqW7ZsnmaATqdDZGQkHj58KKgjIBetW7dGUFCQ3rajR4/ijz/+QLt27fDFF1/IbJnptG/fXrAcqj6U+v3s3bu3wZEKSktHuXfvHkaNGmWwQ02JArBubm6iZbNzefHiRaHRfxRKLioT9TVoVRQKhUKhKAZ9K0NqtRrbtm3DsGHDrGBRQZo3b44yZcpAo9Fg3bp11jZHMhYsWICXL19iy5YtOH/+PKKjo1GmTBlrm2UyuSKb9erVM6i/UieOAH+uf/31F7Kzs5GRkYHs7GzMnz/f6HFKlCiBYsWKAeDvuzp16uDcuXMGCftaEpVKhQ4dOhTab/bs2YqpWFS/fn18+eWXBvdX4vfz8uXL2Lt3r8H9laRzA/AaE8ZECVn7PjKF69evIywszKC+Z8+etawxlCIDTUWhUCgUSpFn0qRJ+f7Nsix2796Nbt26WcmigrAsmxcav2DBAowfPx7+/v4243gxBw8PD/Tu3RsNGjQwKLza1vH19cWxY8cMitywdvUPKWBZFk5OToVGAghNxgIDA0EIgVqtRtOmTXHq1Cm4u7tbwlSj2LZtm8GViG7evGlZYyTkxx9/xLfffmtQXyVqbERERBjVX2npNsZE3ADKOz8A+PLLLw2OuHn58qVRujEU5ZGeno5p06ahcePGKF++PMqWLZtvMxQVw5i8KQFluWgpFAqFYhHat2+PxYsXY9asWShWrBjmzZtnEwKGbxIXF5dXvu/+/ft5K8QnTpywplkWg2RnAtHPQaKfAVHPQZJiAY0GYBjAzgGMTyAQEAQmMBjwKwlGbd20hbdxdXXF3r17MWjQIGzbtk1vHycnJ6M1D5QAIQTIyQQ0WYAmm/8vx1fzIQB/DdUOgJ0DYOcIf19vpKamokOHDti5c6dNrKDrdDp89tln0Gg0BvW3BZsNhWEYfP/99/Dx8Sng1H0TOzs7o0RgbYXg4GCj+istKqVVq1aYMWOGwf2Vdn4cx2Hfvn0G9w8ICDDa2UNRFqNHj8aJEycwZMgQBAYGmrwAwsK0qAalfLuU8ytEoVAoFNMgBCBc3sQqD4YFWBU/yQIwZswYQTFLa3P58mU0bdoUmZmZBdqUuBonBCEEiHwM7nIYcOciwHGvrg/DX8M3+0Y/Ba6f5ifK9g5gajYFU7sFGG9/+Q0XwMHBAZs2bUKXLl1w4MCBAu2DBw+2glWWg+g0QEYKkJFc4Hrl70heOT2yACRDDeBq2AFUrd8IsJGJtE6nyytBawhKvA8nTpwIb29vDB48WG80TdWqVa1glfnUrFkTw4YNw6pVqwzqr7SJf7t27TB69Gj8/fffBvVX2neTZVm4uroiNTXVoP5KOz+K8ezfvx979+5FkyZNzBqHYRiTnCKMQpJRlOKAoVAoFIoxEMKvFGelAZkp/H9zMvNv2el8W2YqkJPFT6JtlMzMTL1ODaDovNSR5/fBLfsB3OrZr50awGvH1Nu8eb1yskEuHge39Fvo1s8FeRkjj9EGoFKpsG/fPgwdOjRvVZFlWQwZMgRLly61snXSQDgOJDkWiHsGpCeKOzUEqFq+NJAYBcQ/B9FkSW+kkdjb26NUqVIG91fa5DiXQYMG6Z0g29nZYdmyZVawSBrmz5+P9u3bG9RXic/QxYsXG1R9iGVZeHh4WN4gifnggw8M7qvUe49iOJ6envDy8jJ7HJUZmxJgiAHqOzqdDtnZ2XLY85+FYRg4OjoWidxqCoViRTiOXwXWGRY+XgBWzYfHq2wvoG/NmjUYMWJEXjpKLuPHjzdJsNFWIDnZIGHbQC6F8dEZ5pbOZFiAZcC07AWmXmswNhSirNVqkZCQAC8vL0WlLohBsjOA5JiCEVHm4uIJFPOy6nvBrl270L1790L7MQyDnJwcRV/TmzdvYty4cYiOjsY777yDhQsXGl262NbIycnB0KFDsXHjRtF+9+7dQ4UKFWSySjoIIfjmm2/w888/C/ZxcHBAVpb1HYXGkpGRgdatW+P8+fOF9h0yZAhCQ0NlsIpiLdasWYOdO3di1apVcHZ2NvrzKSkpcHd3x3pPPzgzxr8TZBAOAxNjkZycDDc3N6M/LxeCv0DPnj3D0qVLsWXLFjx48EBRNcqVilqtRoMGDdCvXz+MGjUqTyGdQqFQCoUQQJvzKrTdDDgtkK0F1PaAnWNemootMHjwYHh5eaFPnz75ojeUvFpF4qPAbZwHpCa+2iHBby3hAB1Ajm4GuXcFbJ8PwTi5mD+uBKjVavj5+VnbDEkghABpCXyEhiVITwSy00E8i4OxkqOxW7duWLFiBUaPHg2dTthx4+zsrGinBgBUq1YNJ0+etLYZkmJvb4+1a9fCy8sLixYt0tuHYRjBkr62DsMw+Omnn+Dl5YVPP/1Ub59q1arJbJU0ODs748iRI+jduzcOHTok2pcuihZ9fvvtNzx69Aj+/v4oXbp0gVLgly9fNmgcUyucKOUbpvdX6N69e2jVqhUyMzPRq1cvfPrpp3BxcaE3jgXhOA6JiYk4ePAgpk6dim3btmHv3r3UuUGhUAqHcEB2hrQrxtocPurDwYXX4bAROnXqhMOHD6Njx455+cf6StUqARL9HNy6OUBOtjQODX1EPga3ejbYkE/AuNjeKgun0+HFrTt4dvEKIm/cQnZqGliVCm6B/giuWxvB9evAPcB2NENyIYQAKXF8Kpcl0eYALyNAvEtazbkxfPhweHl5oV+/foLRu2+/ZFNsB5VKhQULFkCj0ehNuWnRogUcHR2tYJl0fPLJJ8jIyChQ6UatVmPx4sVWssp8ihUrht27dxcadaPEVBuKcfTo0UOScVQAVCZM51UKiW8okIpCCEHFihVhZ2eH48ePF5mVFSVx9uxZdOjQAQMGDCgy+ccUCsVCEA7ISjcpp99gHIvZlHMDAK5fv4569epBo9Fg8+bN6NOnj7VNMgryMhpc6CwgO8uy1w7gU1N8AsAOngrG0fgQVkuQEhOLU3+tRNiCv5ASzeuBqOzsQAjJy8bhXqUcVWzVHC0njkGNrh2hspGoAJL60nKRGvpQ2QHeJcFY8T48ceIE3nvvPb1h/dWrV8f169etYJXlIBzHX+OMVxpFmlcOSIbho9kcXQBnN6CYJxgTQrutwSeffIJ58+blpfO1bt0aBw8eVHy0TS6HDx/GRx99hJcvX6JcuXJYtmwZKlasaG2zzEan02HIkCFYv3693vbw8HCULFlSZqsoSiI3FWWLpz9cTEhPTec49EmMsflUlAKOjYsXL6J+/fo4cuSIQfXnKZbhm2++wcKFCxEdHQ17e3trm0OhUGwRQvgXbktPjAGbdG48fvwY1y5fQvem9YCUeJDUBH7yAfDlUF29ADdvMD6lbKoUKtFqwP39A5AUL8+1A3jnRoVaUPWybtUbjuNwcslybPnkK2izc/jJYyGwKhU4nQ6l6tTEiNClKF61sgyWCkOy0oGkKPkP7OACeARYNXr23LlzaNasWQGdm/379+O9996zklXSQjiOF3FNMlA3hVUBHgGAZ4BN6dkIwXEcoqKi4OPjUyRLLRdVCCHo06dPgdLZX375pajGCKVocenSJdy5cwcAX7Wpdu3aBn0u17Gx1ct0x0bvBAU6Nn766Sf88ssviI+PLzIeXCWS62A6deqU2aV9KBRKESU7w3SRUGNhWN65YSMpiUSrAXl+GyTmyavqIAyAt2MlX+1jWTD+ZcAEVbEJBwd3fCvIucMoaK/lYXq8D7ZyPdmPCwCZyclY3Gsw7h07YdLnWbUKAIMBf/6C5mNHSWucgRBOB8Q/l14o1FDc/cE4uVrn2K+4efMmRo0ahTt37sDT0xPLly8vMgthJCsNiH782kFqDHaOQEBZMI62oWdDKZqcPXsW8+bNg6OjIyZMmIC6deta2ySKDMTGxmLAgAEICwvLSz1KSkpCq1atsGHDBvj6+op+PtexscMrwGTHRo+EaJt3bBTwXMTHx6N48eLUqWFlckusxcfHW9kSCoVik2g18jk1AD6yQJMN2Fs/F5skx4G7f4HXpshzDuhzErzax3EgUY9A4iPBVqwPxl38BcCSkMgnVnNqAAA5sBYkqILsehuZycn4rUUnvLh52+QxOC3vTFg37iNkpaWj/aeTpDLPcFLirefUAICUOBB7J6vpbQC8GKMhlRqUBklLBKIeweR7U5MFhN8BKV4ejIuHlKZZHJKV/kqnieMrYjkVA2NXBKI5COHvV53mlY4RAcDwUTZqO95hrzAaNWqERo0aWdsMisxMnDgRqampuHXrFipX5qMWb9++jWHDhmHSpEmCaUpvwzL8ZiymfMYaFPhl1Ol01KlhA+QKcYmpkFMolP8ohAA5mYX3kxptNv8yaMWUFPLyBbi752HS5EOTBe7mKbCVGoLxtk4lFe74Fv3BJXKRnQVy/hCY1vJpkhBCsKT3ELy4eRucRL9p26Z+A58ywajTu/BSpFJBtDlAVqpsx9NvBAdkJAGuPta1o4hBMlKAqIdSjAS8eAhSogIYZ9td1QReRR8lxoDEPAXSkwq2e/qD8SsNuFq35LBJEMI7MzTZ+tP9dBreEaWy48ub21iaJYXyNgcOHMCRI0fynBoAUKVKFSxYsADt27c3eJyiXhXFaFflypUrwTAMnj59atTnpk+fbvCDkWEYTJ8+3VjTKBQK5b+BNgdWmxmbEqItESQ1Edw9E50ar0cBd+88r8chMyT+BRD+0HIVUAwyggO5ehJEkyPbIU8uXYG7R8Mkc2oAABgGa96fiJTYOOnGLIyMZPmOJUZGCohc2iyGwHFAThaQmcpXiclM5R2v1oxsMQKi0wLRj6QcEYh+zI9ro5D0ZJDrYSCPr+p1agAAEmNB7p0HuXMGxIrPfaMhBMhO57+Dhd0nOg2vU6WV73koJYRwIM/vQXdgNXTrf4Nu7Wzoti0Ed/00SLYVFj8oFoPjOL3Vp+zs7MAZoFWVi4phTN6UgPJisGSE4zjMnj0bZcqUgaOjI2rUqGFwqM+bDB8+HAzDCG6RkZEWsJ5CoRRJCLHuS5hOI5/g5RsQTsenn0jhEyAAd/8iv2IpI+TyP7YR+pydBXLnkiyHSomNw+aPvpR+YEKQlZKKrZ9+Lf3Y+g7HcZYv7WoohOMnY9YmdwKZlcpHcxGO30c4/hmVlcZvtu7giHsOSO2E0GmA+HBpx5QIkpoIcvcsUKhz89XDNj0F5PYZkJyC1XBsjtzvpLHfuZxMxTk3SPgDcGtmg9uzHHhyG0iMBZJfAtHPQE7tArfyf+DO7jdIoJli+7Ru3RqTJ0/Gixcv8vZFRkbio48+MkrjiDFjUwKyvWF98803yMxUlvfw66+/xueff4527drhzz//RFBQEAYNGoQNGzYYNc6YMWOwevXqfFtoaCicnZ1RpUoVlChRwkJnQKFQihycziqOhXxoZdT2eAWJevRqMieRZyMrDeSFlKu0hRyRcCA3zlj/2gEAw4BcPyXLoU7/vQrabMus9nI6HS6s24zkV+ViLUp2unUjbd4m0wZSYrLSCncIcDq+HLWNOjeIJhtIfWmZwVPiZY2MMgSSnQHy4MIrwWVDv88EyMkCuX9Bdmew0ZgTKZSTKb2Dy0KQRzfA7VkGpCa92qEv3UYLciUM3KF11LlRBJg/fz5SUlJQunRplCtXDuXKlUOZMmWQkpKCP//80+BxWDAmb0pANjENtVqtKO2OyMhI/Pbbbxg/fjzmz58PABg9ejRatGiBqVOnom/fvlCpDMvJ0yf0c+rUKWRkZCAkJERy2ykUShHGFl68dBo+L1kmCCEWcUKQqEcgJd6RJ388IfaV2KkNQAgQ9QyE4yxanpLT6RC2YKlFX6oJITj99yp0+uYzix0DgFVTsPSiyQIhxDraB4TwQpMGO+kI79xwcrWZqkp5JFs4lSklDvC2ncUrEv0EMCkljPDOtMRomzqffHCc+YLammxePNWGIfFR4A6vN9zR+vgGyIXDYBp2sKxhFItSqlQpXL58GUeOHMHdu3cBAJUrV0bbtm2NGkfF8JuxmPIZayDJG83+/fvRrFkzuLi4wNXVFZ07d8atW7fy9dGnsZGdnY2PPvoIvr6+cHV1Rbdu3RAREaH3GJGRkRg5ciT8/f3h4OCAqlWrYvny5fn6hIWFgWEYbNq0CT/99BNKliwJR0dHtGnTBg8fGicKtXPnTmg0Gnz44Yd5+xiGwbhx4xAREYGzZ88aNd7brFu3DgzDYNCgQWaNQ6FQ/mNwZjg2GBZwcAGc3PhJhp2JFU44nbyr1ynxBomlsnU7QNWkV74NXoHCH8jJBJLlqTxFop6aN4CjM9je48COnwF26nywH84A07w7TA4Q1WqABMtGOkTduYfkF9EG9W3/2RR8f+8yFuqSsJikoEKLpgZ9jnAcbuw9aI6ZhqGRIAzfszjgVwbwLwf4ljZPADRXHNEacLqCq+IqO74ctJMbvzm4vJV2ZeUUOiGM0drxCACCqwPl6wJlagHeJaUd38IQnRaIj4BYpAYTVAVs/U5g63cC9JStJTFPLWeguQh9v1gV4OxecHPUUzaZ076KZrFduGv/FPz99SsFtscYsKN/ADt8GpgmXfIJopJrJ0FsxbFOMRmGYdCuXTtMnDgREydONNqpART9VBSz3ZKrV6/GsGHD0KFDB8yaNQsZGRlYtGgRmjZtiitXrqB06dKCnx09ejTWrFmDQYMGoXHjxjh27Bg6d+5coF9MTAzeffddMAyDCRMmwNfXF/v378eoUaOQkpKCKVOm5Os/c+ZMsCyLTz/9FMnJyZg9ezZCQkKMKk925coVuLi45FOfBYAGDRrktTdtatiL19toNBps2rQJjRs3Fv37UCgUSj5yS9eZioMzP9nQZPEvPXYOAIhpq9GEyLb6SlITYWgpEZKRAhJ+9/WOtESR3gxIWgIYDxnKv0Y/5//mpl4/ByfAJxDk6kkgIw1Mo/fANukELj0F5NJxk4Yk0c/A+Ig4fszk+aUrBve1c3TEjT0HULtXV3iXDjbqOOFXr4PT6cAaGEVpLISYeI+8Ta7uBAC4eIBx8QDRaUwXJdVkA2p78+0ylrcnkAzDP1sIef1sUdsD9k58Cs+bn1Pb20zUBtHpeG0QQ/AuAcarOEhWGhAbDbCsYZU0NFkgnA6MLVTdeBkp/vxx9wV8g8TtTU8GyUixvYovYtpTHMdHGOWiUvPfQ6FFAl0OwFq/rLk+SGY68OBa/mgpJxewXUYCDAtydh+YEuXA1mwGLicb5MJhvo9WA3L/MphqtEyskpg3bx4++OADODo6Yt68eaJ9J00yrPw5wzBgTXgGK6UyklmOjbS0NEyaNAmjR4/G0qVL8/YPGzYMFStWxM8//5xv/5tcu3YNa9aswYcffogFCxYAAMaPH4+QkBBcv349X9+vv/4aOp0ON27cgLe3NwBg7NixGDhwIKZPn44xY8bAyckpr39WVhauXr0Ke3v+B9/T0xOTJ0/GzZs3Ua1aNYPOLSoqCv7+/gUuZGAg/xL4pniLsRw8eBAvX76kaSgUCkU+WDX/Iq7VvH4BVNkBagcTHRscZJNpSk+CwfngmmyQxGgDU3YIkC5TpYvUJPP0NVISwS397vVKnUoNpl1/wN+AVWN9MOzr/GwLEXnjNlR2dtBpCo8s2PvDTABA2cYNjXZsaLOyEff4CfzfKW+SnYVCCCTRdkmN5//uLMuvhqvtzYt8spbeQYFIEeaVaCjh7ztCXjlc3jo3wvEbYwOTfMDwktkMC3j48/oSkfdfC6QacxzHYqbZKCFEzMmrtgdTpgYQ9QjwKcE7qoRISwRs0bEheI++Fd2Um0Yp5AjR6YCCxSdsAvL8XsH7PiAYjKMzyONbILfOgUQ+gqp8DTDVG712bIDX5QB1bCiK33//HSEhIXB0dMTvv/8u2I9hGIMdG6yJjg1TPmMNzHJsHD58GElJSRg4cCDi41+H86pUKjRs2BDHjwuvIu3btw9AQQ/TlClTsG7durx/E0KwdetW9OvXD4SQfMfp0KEDNmzYgMuXL6NJkyZ5+0eMGJHn1ACAZs2aAQAeP35ssGMjMzMTDg4Fc8gdHR3z2k1l3bp1sLOzQ79+/Uweg0Kh/BcxYxKUq6WQ74WcvAoXNywaQjJbjD2SMSHsbj5QvduNn4QkRoN7eEU0BF4ucT+i1Zg3ic133Rgw5avz//fpXb3dC4VhLC4Cm50qldiroceyEFIKvvoG562Gk9zyqKZiDSFafd9hwvGTd3snPsUN4Cdf+spN2pIAq6GOIXsnMKyKj64JqgbGzp5/bsQ9B9LFIsJyj2MjqQ0i9ztTpgaQlQ7y4gEYHzENDcs/N0zDwO+V6pWDX6cVuf429B19m6x0/tn95n2U8erZ5x0AuHuDCa4EAGAcXfhIv9z7MNMGKilRjOLJkyd6/785sAy/mfI5JWCWY+PBgwcA+BI0+nBzE/boPnv2DCzLoly5cvn2V6xYMd+/4+LikJSUhKVLlwpGf8TGxub7d1BQUL5/e3p6AgASEw34AXqFk5MTsvUouWdlZeW1m0JaWhp27tyJDh065EWfUCgUimEo5JdFagwskUpinwGZaeA4HdiAsmC8S4DR6UAeXBQZW6a/qVQinSo1mC7DwZSpAu7CUZDbF0wciEhnkwCMKtdpZnlYS4qTS/kdSYwCUakBZw9+FT8rLX+6hnGGSWeXWTCv9HoIP4liWf7f9k5ATsZbXW3FZhjx5+MnkYzKDiQpkq+k4lcaCCgLPLlqsxVfCiB0v3uXANy8QR5cepWu+OoPY+8E5GQVPD9bKFltKupXC5a2JgZsKCp1QedgzHNwN86Ard4YqpDPQDQ5IDotGJUa+b7kNi6KSjGO3EyG4ODgvHmuIbAqBqwJXor/RMQG98oLvXr1agQEBBQcXIIXjdxjDB48GMOGDdPbp0aNGvn+LVSthBixUhAYGIjjx48XUB2PiooCABQvXtzgsd5kx44dtBoKhUKRn9xVw3wvpUwhIbxiyPcjxzg4g7y9SqWHN7U1uJwsqDz9wbi4C58dw/CrWjLA2DmAMKx5q+wOTmB7jwMTXBHcyd0gp/aYPhYhFq9s41E8ULYyg+6BBd9BJEPKFzpNFvBqwZvxCABxcjPdsWGNF02GKbhirFLxk2athg/514F3bOibSNnSpNhQfRJN9ut3wcQo/tw9A/jnkp1Dfv0Gc45jaewcoS86j3FwBsOqwFRskG8/W7EBuAeXgKQ3RYYt/9wwCUPuBYblv5OcTlyE25a+o2/BePjq/T0jJ3dCdyUMKOYBaHLA9psEkpLw+rvJsICnn4yWUqRmypQpqF69OkaNGgWdTofmzZvj7NmzcHZ2xp49e9CyZUuDxmFZEx0bNuNIF8csz0NutIWfn5/RyqzBwcHgOA6PHj3KF6Vx7969fP1yK6bodDqT1F9NpVatWvj7779x584dVKlSJW9/rgBprVq1TBp37dq1KFasGLp16yaFmRQK5b8Ew/AvKKZMjrlXobe5wmmsih/P1GoPcorhFfMAogtxvji7gS1dHSQpBtBqwPiXBgCQlJfCnyGEH1sOzBXptHMAO2QqGN8SII9uAi+jwVSuB5KRCjy7V/jn34YQMD6mOegNJahuLXAGlpYs36wx/CuUh6svXymkWucO8C1fFqeXhRb6WbcA/7zPWQKGYUHMEX4FAHtnwKkYvwIO8FUZAMPFK/VhrQmz2iH/c4Pj+Hsp99nC6Et7A6/pY0urfnaOBZ00+uB0QOpLwM0H8CnFr/bbO/IpcoXpdDCszTgCGK9APqrtLUhCFJ8WldsvuCoYOwdwz2690jd6cxAW8LDBCTLDFi7ObGdgtIbKRgU2AKBEWcDVo4A+EtOgPZCWBDAsmGqNwDAsuItHX3cgHNiqDeW0lCIxW7ZsweDBgwEAu3fvxtOnT3H37l2sXr0aX3/9NU6fPm3QOLm+aWOxpUe3GGa5JTt06AA3Nzf8/PPP0OgRB4uLE64P3rFjRwAooPI6d+7cfP9WqVTo3bs3tm7dips3bxp1DHPo3r077OzssHDhwrx9hBAsXrwYJUqUQOPGjY0eMy4uDkeOHEHPnj3h7CwizEShUChCmONQyM7gX/xyV1M12aaF5DKsrL9yjCEv0pocgHBgSlQAU64WYO8E7sUDkKc3xMd2l6EiCgAmINi8aA3nYmB8+dx3plw1sD3e57cmBSuJGUxAUOF9zCC4Xh2DvydNRg7BkL/nw7dcGQBA+6mTMeTv+YV+jlWpUK6xDC/sppZGzoXT8Q4BVx9+gswwvJhjmhnlQK01YVa/NfHL1dggHP93UtvxkRtvRzLYSuTCKxiGMVzUM+45SEo84OoNeBUHMlJfC4mK4VjMdqoJFPPUf75ZaUBi9Ost1zmQEv/W7wMD+JQA8/b1txXUIvcDw/AOC8IVUiaZsemUDYZhwVRvggIRk26eYBp1BtO0KwCAO7oR5C6fgkkYho/WCCgtr7EUSYmPj8/Ljti3bx/69u2LChUqYOTIkbhxQ/w9501yIzZM2YxlwYIFKF26NBwdHdGwYUP8+++/Bn1uw4YNYBgGPXr0MPqYZt29bm5uWLRoEYYMGYI6depgwIAB8PX1xfPnz7F37140adIE8+frfzGpVasWBg4ciIULFyI5ORmNGzfG0aNH8fDhwwJ9Z86ciePHj6Nhw4Z4//33UaVKFSQkJODy5cs4cuQIEhKkrxNesmRJTJkyBb/88gs0Gg3q16+PHTt24OTJk1i7dq1guosYGzduhFarpWkoFArFdFhVIS9mIhDOjHz+t2yQEcbBGfD0BxJjIZg2o8kCd+esMaMCHn6ypaKY7URIfgndjDHS2AIAxdzBOFu2UoOrrw+qtG+Nu0fCCo3cWDViHFaNGGf0MTidDu8OG2SqiYZj52jevaPNBl6GS2cPq7ZeCVGGxYVrN1G/5hti7DqN4HOJEAImN0rM1nD3Bd6IVhCE0wExJoj3yeQ4NQSGYYCA0iBPCy4Svgm5HibwlCVg/IyrWCQreZoS+gRuiWFCvXa2U45YCKbquyAPrgLxUXnOcnJko95rpuM4gGFh17K37TjYKCbh7++P27dvIzAwEAcOHMCiRYsAABkZGUbNSVUsA5UJTgqVkakoGzduxMcff4zFixejYcOGmDt3Ljp06IB79+7Bz094serp06f49NNP8wp/GIvZiWSDBg3C0aNHUaJECfzyyy+YPHkyNmzYgFq1amHEiBGin12+fDkmTZqEAwcO4LPPPoNGo8HevXsL9PP398e///6LESNGYNu2bZgwYQL++OMPJCQkYNasWeaegiAzZ87Ezz//jIMHD2L8+PF4+vQp1qxZg0GDTHuJWrt2rUlpOxQKhZKHLYTJWmHFji1ZCdKq1ROwJSsW3k0iGOdigG8J2ILgI2FY6IIqyXKslhM+MDgdxRTciwegeucOFhs/DwfTBMMthlg5TgtCCMGsWbOwau166Ap5Fmm1vI7BqrXr8TQq1jYnjMU8LbdCr1LLl+pmKD6lTE4lYUpWBGNrZV7fhGF4wVMTIAAfiSgW9WEjMHb2YLuMKjS9UaPTIUerQ4/FWxHDmBlxRrE6I0aMQL9+/VCtWjUwDJM3lzx//jwqVTL895wBA4YxYXv17pKSkpJv01doAwDmzJmD999/HyNGjECVKlWwePFiODs7Y/ny5YK26XQ6hISE4Pvvv0fZsmWN+Ou8cX7kLUXNSZMmISwsDNevXzdpQIo0JCQkwNvbG1u3bkWvXr2sbQ6FQrElstLFxc8sCcMAjq5WmaRwj6+CRD2WZrCAslCVqyXNWAbCXT0Jsn+NrMcUYsqVGGS5+2L48OFo3LixxVbzOJ0Osxq1QfiVa+C00js4hixbgCYjh0g+7tsQQviIC2NKD1sS75JgzE2PMRKtVotJkyahTJky+PTTT/nvjE7Lpyu8eh5xHAf2VfWNU2fOYd6ixdi8bQemT5+O7777TlZ7DYWkvgSiJXquvElAOTCuXtKPayZEpwN5dBlILjyVO/d67rpwC93HfaqMVX9NtlHaURqtFhkZmXD3K27xSlFSQrQakFvnQG6cAVL4yPVckduMHA1WnbuJeccv4kFsIn755Rd8+umnVraYYi5btmxBeHg4+vbti5IlSwIAVq1aBQ8PD3Tv3l30sykpKXB3d8fld8rCVWX89zxVx6HOg4LPye+++w7Tp0/Pty8nJwfOzs7YsmVLvnSSYcOGISkpCTt37tR7jO+++w7Xr1/H9u3bMXz4cCQlJWHHjh1G2Wm7iWQUCoVC0Y+dA5BtJceG2sFqK69McDVe6T09GaZHbzCAizvY0tUK7yoxTJUGIEc28Xog1oJhAP8g/LlpCR48eIDQ0FB89913aNWqFYYMGVKgXLq5sCoVRoQuxY81GoEvlyHRuGoVKrVpicYjBks2phgMw4A4ewApsYX2tThqB9mdGmlpaRg+fDj69OmDAQMGvG5QqV9VmuAATovZM2fi9p07uHTlKm7feV2laOXKlZg2bVqe08OmKOYFuCQUFMo0a0xPm3RqAACjUgHv1AWiHoPEPNXrrNNotbBTq3HvWSR+/Hsdtp84h6gBo+DlZZvnlA87Bz764u1Sw2+h0WhgZ2eH02fPYeykj3H9xg3Y29uWDowYjNoOTM1mIDWaAlFPsH7JApw4dgxxaRk4cvcpUrNeX9fly5fjk08+UYZjiiJInz598v07KSlJsGKoECwL06qivHrlCg8Ph5vb68gtB4eCUU7x8fHQ6XTw9/fPt9/f3x93794t0B8ATp06hWXLluHq1atG25bPTn07jSmLqjQyMzMRHR0tuuXkGPbSmZaWVuhYOhNDcIvyNaBQKGbCqgDWCn5phrGqACCjUoOt1hQ6ZzdwnInPyGIeYKs1BWMFgTjG3gFMnRbWDcknBEzDdgCAd955Bz/++CMOHTqEd999F9988w26d++OtWvXIiOjkBKWRhBQqQIGLfpdsvFYtQqufn4YunyhvC/qTsVsoxSki4esh4uOjkavXr0wadKk/E6NN2FZQG0Px2JuWL1uQz6nBsDnTZ84cUIGa42HYRjAv6x06T0OzoB/GWnGshAMw4IpXh5MzdZgytXmBW0dnBGTkIS7T8Ox5egptPjgM1TrPxYbD/+DnJwcrFu3ztpmG47aDnBy41NT9NyzWdnZWLV2Peo2aYFW73XBvfv3sWePGeWzrQjDMGCKl0W5Tv2w9NRVbL96P59TAwDu3LljsHAjxTaZNWsWNm7cmPfvfv36wdvbGyVLljQqyyK3KoopG8Dra7656XNsGEtqaiqGDBmCv/76Cz4+5lU4K3C3Ozk5ITOzkPJVCmbjxo0IDAwU3c6cOWPQWL/++muhY4WHmyYWlvtSSaunUCiUAjCMdXL+7Z2tnifPqO2x/Nw9/G/lJmh1OmgMSm9gADBgSlUCW70FL2RoJZimXfi8e2v8HRkWKFMFTOV6+XazLIs2bdogNDQUoaGhyMzMRJ8+ffD+++/j9OnTkjjam4wain5/vNLEMuPcc50aH4fthUdxM0voGgnDsICblcUg7Z0Mr+QhAXfu3MHAgQPxxx9/oHnz5oX2DwkJgZ2dfu0Nsdxqa8OoVECJiib/bXPvEeJYDChRyXrCrkbCsCwYr0CwFRuArdESX6w7iKr9xmLwtF9w6uqtfH1XrFhhJStNJNcR7+TKX1cHF3z27feo26QF/Eu/g/fHT8Llq9fyuivu/N6iQYMGqFKlimC7Ld9/lMJZvHgxSpUqBQA4fPgwDh8+jP379+O9994zKs0oVzzUlM1QfHx8oFKpEBMTk29/TExMXmWXN3n06BGePn2Krl27Qq1WQ61WIzQ0FLt27YJarcajR48MPnYBjY1ly5bhgw8+QFRUlKhqqVKJiorCrVu3RPvUrVsXnp6ehY71+PFjPH4snpfZtGlTODoaHzK6detW9OnTBw8fPkS5cuWM/jyFQvkPoM3hyyzKgdreZGE2qalfvz4uXryICqWK48PeHTGic2u4ODmC4zgQMFCp2NdlGFkVGL9gMIHlwDi7WtfwV5Bn98CtmyP/ge3swX7wAxi3wn/fAODBgwdYtWoVzp49i9atW2Po0KF5L1amcm7DFiwZNBJ2hIA1QUi1Soc2GLp8oexOjVwIIUBStDTVhYyGAXyDwMgkIPzPP//gf//7H0JDQ/W+jArRu3dvbNu2rcB+JycnREVFwd3dXUozJYW/vjHAy4jCS7m+QqfTIUerxeez/0SngcPRsWNHC1tpOcLCwtCqVSvB9qtXr6JmzZoyWiQta9euxeDB+tPXWJZFREQEAgOt82yRgl9//RVTp07V2+bm5oaoqCi6YKpQnJyccP/+fZQqVQqTJ09GVlYWlixZgvv376Nhw4ZITEwU/XyuxsbtauXhakJlz1SdDlVuPkRycnK+VBQhGjZsiAYNGuDPP/8EwOv1BAUFYcKECfjiiy/y9c3KyipQFfWbb75Bamoq/vjjD1SoUMHgNLECjo3cOrk///wzPvvsM4MGoUgLx3Ho2rUrXrx4gStXrljbHAqFYssYKZRmEiq1TURrAMCNGzdQo0aNfPsc7O1QvWwQ6lQsh88/noLSpUsDdg5ginkALu42uXqqO7wRuHhM1mMyXUaArf6u0Z/T6XQ4fvw4QkNDkZycjP79+6NHjx4mvSCvWLEC40aOxLtwQAXwE/RX8TR6+7MqFTidDu7FA9D9p+/QaNggq+eJE50WiH+eV2pRNtz8ZKtKsWHDBmzZsgUrV65EsWLGRTHs3bsXXbp00du2ZMkSfPDBB1KYaFGIJgdIiQOSYt8Qaua/dzqdDizLVwqIfZmAReu2YunG7YiKjUefPn2wefNm6xluJhzH4Z133hFctJs8eTLmzp0rr1ESkpmZicDAQCQnJ+ttnzVrlqLnPtHR0ShZsqRgGvzq1asFHTsU26Z48eLYsmULGjdujIoVK+J///sf+vbti3v37qF+/fpISREvZ5zr2LhT3XTHRuUbhjs2Nm7ciGHDhmHJkiVo0KAB5s6di02bNuHu3bvw9/fH0KFDUaJECcyYMUPv500VDy2QiuLj44MxY8bgyy+/xJw5cwr1AFGk5cmTJxg1ahT2799fwKNFoVAoBbBzACwpJGhDTg1Af7hwdo4GF+8+wsGr91C6aQewQZXBBpYF4+plk04NAGDb9AUq1YFc5V+ZFj1McmoAgEqlQtu2bfNSVdLT09GnTx988MEHOHPmjFGpKitWrEA2gBPIxmqk4wJyEA0dNHrEYD1KFEetnl3x4a6NmPH8DhoPD7G6UwPgtV7gVULee8LFUxanBiEEs2fPxsmTJ7FhwwajnRoA0KFDB8FVb6WE+zN29mC8SwBlawFBVQG/0oCnP+Dhh9tRLzHyix9Qo8tAlGjaGd//+ReiYuMBALt27cLLly+tars5sCyL4cOHC7avWbPGYB06W8TJyUlYJwZ8uoaSNe4CAgLQuXNnwXal3H+UgvTq1QuDBg1Cu3bt8PLly7zIsCtXrqB8+fIGj8OqGJM3Y+jfvz9+/fVXfPvtt6hVqxauXr2KAwcO5AmKPn/+HFFRUUaNaQgFIjYA3mP74YcfYunSpVCr1ahUqRJcXFxs4oWiqMJxHBISEvDgwQM4OTlhwYIFGDFihLXNolAoSkGrAXIyodNpoTLBG68XO0c+BcVGnv05OTkoUaIE4uPj9bbrKztmyxCdDtyelcBty4q6MS17gm30nuTj3r9/H6tWrcK5c+fQpk0bDBkyRDRV5cGDB6hQoYJg+8a/lqFJw4ZgVCq4+fuimLe35DZLCcnJAhJfWD5yw8UDKOZt8XcwrVaLKVOmoFSpUvjss8/MOt4XX3yBWbNm6W27ffs2KleubPLY1iYlJQWBgYGCArvz5s3DxIkTZbZKOp4/f47SpUsLTvC3bNmC3r17y2yVdPz7779o2LChYPuZM2fQqFEjGS2Slh07dqBnz56C7U+ePOGjGimKQqPR4I8//kB4eDiGDx+O2rVrAwB+//13uLq6YvTo0aKfz43YeFingskRG+Uv3zc4YsNa6HVs5PLixQts374dd+/elVQhnVIQhmHg5uaGhg0bonPnziatklAolP829+/fw6WzpzCwb5+8UnbGQPAqfoBR8eKkNhbtsH37dvTq1UuwXYkvbIRwIGcPgPyzGwQEjFSrhQwL2DuA6TgY7FtioVKj0+lw7NgxhIaGIiUlBf3790fPnj3h5JRfk+Xrr7/Gzz//rHeMgIAAhIeHQ61WVhV6os3hNTf0lMw0HwZw8wHjbHlNivT0dAwbNgy9e/fGwIEDzR7v3r17qFSpkt62qVOnYvbs2WYfw5oMGzYMoaGhettq1aql+DTi9u3b4/Dhw3rbOnfurNgKIgAflVStWjXcvn1bb/vo0aPx119/yWyVdGg0GpQsWRKxsfpLUyttAYAiDbmOjUd1K5rs2Ch36Z6yHRsUCoVCUQ65q6Q1a1THuNEjMTRkIJwcHZGTo4GdnVp0BZYQgodPnuGdylX4UrI2EqXxJt26dcPu3bv1trVu3RpHjx6V2SLpIHGRuDfnK5R3dQBHCFSsiWVFGZaPIHinJtiOg8G4yPsCkpycjE2bNmH79u0oVaoUhg8fjnfffRccxyE4OBiRkZF6P/fZZ58JrvDbOoQQIC0BJD0ROp0OaikipuwcAXc/WSr4xMTEYOjQofjqq6/QokULycZt3Lgxzp49W2C/v78/wsPDjXa82hInTpxAy5YtBdsvX76ct6KqRNavX49BgwbpbWNZFuHh4ShevLjMVknHb7/9JlhJwtXVFVFRUXBxcZHZKun45JNPMGeOfoHq4OBgPH78GKypvzEUq7F69WosWbIEjx8/xtmzZxEcHIy5c+eiTJky6N69u+hncx0bT+pVgqvaBMeGVocyF+/avGODfqspFAqlCKDVarFq1SoAwLXrNzB20kcIKFMB/YeOwNwFCxETpyd9g2Hzqp3o7J0xbsonIDbq1IiOjsa+ffsE20eOHCmjNdJz72Uqqs9ejfe3/YObMby2lUZnRIoD8+rnvHQlsH0ngO09TnanBgC4u7vj/fffx759+/DJJ59gz549aNeuHUaPHi3o1ACg6NRLhmHAuHrj3L1w7Nh/GDqdTlC8Twjtq7LF2TrCl5T1KiGLU+Pu3bsYOHAg5s6dK6lTAxC+J2NiYnDgwAFJjyU3zZs3R9myZQXbla5l0KNHD3h4eOht4zgOq1evltcgiRk8eLBgymZqaqreqj5KQux5+uzZMxw/flxGayhSsGjRInz88cfo2LEjkpKS8n5jPDw8jBP0ZfhXPGM3meTAzIY6NigUCqUIcPDgQURHR+fbl5KSgk1bt2P6TzPh7OUHOLvn35xc+RKuanuo7exRv359nD9/3kpnIM7q1asFJ4tubm6iOcVKYOXKldByBCsv3UPdP7ei0cLtWH7xLu7EJkInFlipUgEBQWAatgM79n9QDZgMpnx1m9DEqlChAn766SccPHgQT548EezXqFEjwbQFJfHHwsXo9/5EBNVtjh/nzMejZ88N+yDD4N9rt9Ci5yBMm7sUjLO7LNfv5MmTmDRpEtatW2cRzYt+/foVSEfKRekTf4ZhRCePa9euRXZ2towWSYuTk5NoSpLSRTb9/f0FK/cA/PkpmWrVqqF+/fqC7Uq///6L/Pnnn/jrr7/w9ddf53PK1atXDzdu3DB4HLnEQ60FdWxQKBRKEUDsRax3794GhQ6OGDHCJl94CCGi5zdgwACTSo/aCm9G2+RyISIO43eeQvW5mzGPKQ12yGdguo8G03komM7DwfR4H+yoaWA/+ROqEV+DbdULjKevlc5AnOTkZL0pCbkoOVojl4SEhLyydFExsfhhzny8824b3IxNBzyLA67evAioszvg7AG4eAIeAYBPMOBXFsmMI06eu4DVq1dDo9FY3N6NGzdi7ty52LZtGwICAixyDDc3N/Tt21dv2+7duxEXF2eR48rFsGHDBB1QCQkJ2LVrl8wWSYvYfXn//n3Re1oJiJ1fWFiYYMlbpSB2flu3bkVSUpJ8xlDM5smTJ3rT2xwcHJCenm7wOIyKNXlTAsqwkkKhUCiCxMXFCWpPAIanaVSoUAERERE2JxZ9/vx53L17V7Bd6Wko+qJtcmFZFoOGDQdTshzYKvXB1mgCtkYjsJXrgfErCUaqCjgWZN26dYIlItVqNdauXYsZM2YgIiJCZsukQ9851qlTB9Vr1ATj4AzGxROMqw8YN18wbj5gXL3BOBYDo7YDwzBo3749ihcvjpiYGOzfv99idhJC8OuvvyIsLAwbN260uFC50ORKq9VizZo1Fj22pSlVqhTatWsn2G6LTmJjqFevHqpVqybYrvTz69SpE/z8/ATbV65cKZ8xFmDgwIFwdNRfCj4rKwsbN26U2SKKOZQpUwZXr14tsP/AgQPGRdyZkoeSl49i+1DHBoVCoSictWvXCq7yli5d2qjc+V69emHr1q1SmSYJYtEalStXRoMGDWS0RnrEzu+9995TtEgfIH5+gwYNwtGjR1G3bl18+eWX6NmzJzZs2IDMzEwZLTQffZM8YyJR1Go1hg4dKjiWFOh0OkyaNAlarRYLFy6UpQKNmBbFihUrFJ3OAIhf44MHD4rqytg6haXbbNiwwaiVYlvDzs4OQ4YMEWxfuXKl0Vo5toSHh4doiqbS023+a3z88ccYP348Nm7cCEII/v33X/z000/48ssv8dlnnxk8Do3YoFAoFIrNUliaxvDhw41SP+/Xrx82b94shWmSkJGRgQ0bNgi2jxw50ib0JEylsGgbpadpXL16VbT05YgRI6BSqdC+fXusXr0aK1asQEpKCnr37o2xY8fi3LlzNj/5vXbtGi5fvpxvn729vWBVCSFyr/WePXsESzWaSnp6OgYMGIBGjRrhiy++kO2eYVkWw4cP19t248YNXLp0SRY7LEVhIptCJWGVwuDBgwUdYGlpaTbnBDcWsedreHg4jh07JqM10iMWzfjvv/8Klryl2B6jR4/GrFmz8M033yAjIwODBg3CokWL8Mcff2DAgAEGj0MdGxQKhUKxWS5fviwoHMUwjOCkQghXV1f4+PiIij3KydatW5Gamqq3TaVSYfDgwTJbJC1i0Tbe3t7o2rWrzBZJi1j0QdmyZdG8efN8+zw8PPDBBx9g3759mDJlCnbu3Il27dph5syZNrv6re8ce/ToAS8vL6PGqVChApo0aSJ5mkZMTAx69eqF8ePHG+1skQIxLQqlpzM4OjqK/k2VHpXi5+dXpEU2q1atKhrxp/TvZ+vWrREUFCTYrvTz+6+g1WoRGhqKtm3b4sGDB0hLS0N0dDQiIiIwatQo4wajqSgUCoVCsVXEXkxat26N4OBgo8ccPny4zeQXi51f586dLSZ8KAeFRduEhITAwcFBRoukJScnB2vXrhVsLyyaqFKlSpgxYwYOHjyI2rVr4/PPP0ePHj1sKlUlJydHrxPCVN2X3M9JVXXi3r17GDhwIObMmYOWLVuaPZ4pBAUFoW3btnrb1q1bh6ysLJktkhaxVf8HDx7g9OnTMlojPWLnd+LECTx69EhGa6RH7F7dtm0bEhMTZbRGWliWxbBhwwTbQ0NDZRErppiHWq3G2LFj856Vzs7OovowYjCsiREbRkT+WhNlWEmhUCiUAmRlZYlOHE2dXDVr1gynT58Gx3GmmiYJT548wfHjxwXblZ6mIRZtAyhfFHX37t14+fKl3jaGYURfuN9EpVKhQ4cOWLNmDVauXInk5GT06tUL48aNw/nz5626Iq7vHEuWLCk4kS+Mvn37wtnZGbdu3cLFixfNsu3UqVOYMGEC1q5di6pVq5o1lrkI3atJSUl51WSUSt26dVG9enXBdqWvinfs2BH+/v6C7bbiBDeVAQMGCIpsZmdni6ZCKgGxqM3Y2FiLihVTpKNBgwaiaZ2GwqgYE1NRaMQGhUKhUCzIzp07BUu2ubu7iwqHicEwDFq1amX1/GKxF2Y/Pz907txZPmMsgNiEp3bt2qhZs6aM1kiPWDRK27ZtRUOkhfDw8MCYMWOwf/9+TJ48GTt27EC7du0wa9Ysq6Sq6LuGQ4cOhcrEajWurq55JVLNCfPfvHkz5syZg+3btyMwMNDkcaRCTItC6RP/wkQ2N27ciLS0NBktkpbCRDZXrVqlaJFNd3d39OrVS7Bd6d/PsmXLikZrKT2d6L/Chx9+iE8++QTz58/H2bNncf369XybwbCM6ZsCoI4NCoVCUShiLyQDBw6Ek5OTyWMPHToUq1atMvnz5sJxnKhjY/DgwbCzs5PPIImxVLSNrfDixQscOHBAsF2K83szVaVWrVr4/PPP0bNnT2zcuFGW9IYXL17oXe00N5Io92+zfv16o1NuCCH47bffcPToUWzatMni5VwNxcnJCQMHDtTbdvjwYTx//lxmi6RFTGQzPT0dW7ZskdkiaSlMZPPo0aMyWiM9Ys+jCxcu4ObNmzJaIz1i57d3717ExMTIaA3FFAYMGIAnT55g0qRJaNKkCWrVqoXatWvn/ddQ+IgN0zYlQB0bFAqFokDCw8Nx+PBhwXZzJ1elSpVCamqqYESIpTl27JjoZEfpaShi0TamVNSwNUJDQwVTmTw8PNCjRw/JjvVmqsry5cuRmJiInj17WjxVZfXq1QXOsVmzZihfvrxZ4zZr1gzlypVDcnKyUWkaOp0OkydPRnZ2NhYtWiRLOVdjEJpcEUIUXz3E19dXVOhX6aviVapUQcOGDQXblR7V0KpVK1E9KqWfX+/eveHq6qq3TWqxYoplePLkSYHt8ePHef81FFoVhUKhUCg2R2hoqOCErWrVqqhfv77Zxxg4cKDV8ovFXiTr16+PatWqyWiN9IidnykVNWwJQojo+Q0cOFAwp91cPD09MXbsWOzfvx+TJk3C9u3b0b59e8yePRsvXryQ7DhCwq9SRKK8mdpg6IQ4IyMDAwcORIMGDfDVV1/ZZAnkunXrCt63K1assLqmj7mIXfuTJ0/iwYMHMlojPWLnt337dsWLbIppUaxevVrRIpvOzs6iJUGVXr3nv0BwcLDoZjC0KgqFQqFQbInCJo4jRoyQZGLTvXt3qwj7JSUlYdu2bYLtSo/WCA8Px6FDhwTblX5+Z86cwf379wXb5UqzqVy5MmbOnIn9+/ejRo0amDp1Knr16oVNmzaZnapy9uzZAufo4uKCPn36mDVuLkOHDgXDMDh69CiePXsm2jc2NjYvQsWWyx8zDCN47R8/foyTJ0/KbJG0vPfee6JVmpQustm/f3/B9Mbs7GysX79eZoukRUzMOC4uDnv37pXRGukR+12RQqyYYnnu3buHCRMmoE2bNmjTpg0mTJiAe/fuGTUGjdigUCgUik1x8uRJwRJ7KpVKssmNo6Mjypcvj1u3bkkynqFs2LBBcOLp6OgomKuvFMSibUqUKIF27drJbJG0iDndqlWrhrp168poDV8q77333sPatWuxbNkyJCQkoGfPnvjwww/x77//mrRSqS+Son///pJpWpQqVQrt27cHIURU6+b+/fsYMGAA5syZg1atWklybEsipkWh9HB/tVqNoUOHCrYXBZHN3r17C7Yr/fqVKVMGrVu3FmxX+vm9++67qFSpkmC70tOlijpbt25FtWrVcOnSJdSsWRM1a9bE5cuXUa1aNWzdutXwgVgWUJmw0XKvFAqFQrEEYi8gXbp0ES3NZywjRoyQ/YVO7Px69uwpWF1BCRQWbTNs2DCTK2rYAunp6di4caNg+8iRI62aJvFmqsrEiROxdetWtGvXzqhUFaFzlDrSJne8lStX6k3TOH36NMaPH481a9ZYvZyroYhpUWzevBmpqakyWyQtYt+ByMhIHDlyREZrpEfs/C5evChavloJiJ3f3r17ER0dLaM10lJY9R5TxIop8vHZZ5/hyy+/xNmzZzFnzhzMmTMHZ86cwVdffYXPPvvM4HEYhjF5UwLUsUGhUCgKIjU1FZs3bxZsl3pyVadOHVy7dk22/OJbt27hwoULgu1KrxYiFm0DKD8NZcuWLYKlLdVqtU2lSlSuXBmzZs3CgQMHUL16dXz66afo2bNnoakq+s7xnXfeQZMmTSS1r3v37vD09MSTJ09w4sSJAjb89ttv2LZtG4oXLy7pcS2N0Hc8IyMDmzZtktkaaalUqRIaNWok2K70VfGWLVuidOnSgu1Kj2ro1asX3Nzc9LbpdDrFi2wOGTJE0HGenJyM7du3y2wRxVCioqL0RoQNHjwYUVFRBo9DU1EoFAqFYjNs2rQJGRkZetv8/PzQqVMnSY/HMAw6d+6Mffv2STquEGIvxkFBQaKhwkpAbGIjRUUNayN2/bp27QpfX18ZrTEMtVqNjh07Yt26dVi+fDlevnyJHj164MMPP8SFCxcKpKroO0epdG3exNHRMa86Tu4xCSGYM2cODh8+jI0bNwpWOrBlOnbsKKhFofSJPyDunNyxYwcSEhJktEZaDBHZzMnJkc8giSlMZHP58uWKFtkMDAxEx44dBduV7pgqyrRs2VKvDtGpU6fQrFkzwwcyJQ0ld1MAyrCSQqFQKADEXzyGDBkCOzs7yY8ZEhIiy0qVRqPB6tWrBduHDx8OViF5nvooLNpG6dEojx49KhBZ8CZKiEbx9PTEuHHjcODAAUyYMAFbtmxB+/bt8csvvyAqKkrvObIsK6qtYA6534ktW7YgISEBU6ZMQWZmJhYvXmyRe10O1Go1hgwZorftzJkzRovh2RpiIps5OTlYt26dzBZJy/DhwwWdePHx8YoX2RR7Dt+5cwf//vuvjNZIj9hz2BCxYop16NatGz7//HNMmDABa9aswZo1azBhwgR88cUX6NmzJ3bt2pW3icGwjMmbEmCIkl2PFAqF8h/i3r17ouJfN2/etFiuff/+/fHHH3+Iqv6by86dO9GjRw/B9kePHqFs2bIWO76lWbZsGUaPHq23zcXFBdHR0ZKJT1qDadOm4X//+5/eNn9/f0RERAgKR9oyWq0Whw8fxurVq3H58uUCE++OHTtaLKKJEIJatWrh+vXrqFevHiZPnmxT6TymcufOHVSpUkVv2+eff46ZM2fKbJG0DB06VNBJW6dOHVy6dElmi6Slbdu2OHr0qN62Ll26YPfu3TJbJB2EEFSrVg23b9/W2/7BBx9gyZIlMlslHTk5OShRogTi4+P1tn///ff49ttvZbaKUhiGLuowDKNXpDglJQXu7u6IH9kWbvbGO8VTcjTwWX4EycnJgulatoByl74oFArlP4ZYucAGDRpYVEBwyJAhFo/aEAtDb9WqlaKdGoB4tI2UFTWsgU6nE/1+Dh06VJFODeB1qsrq1av1iluKheabC8Mw6Nu3LwBetLQoODUAXt/k3Xff1dsWGhoKrVYrs0XSIrYqfvnyZVy7dk1Ga6RH7Pz2799fpEU2N2zYIJgOqgTs7e1FnyMrVqzQK1ZMsS4cxxm0FVZ5iYqHUigUCsXqaLVa0bKPlk5jeO+993DgwAGL5RdHR0eLhjArIY1BjHv37uH06dOC7Uo/v6NHjyIiIkKwXennB/Dn+HblFEdHRyxevDgvVUVqHjx4gIMHD0KtVuPOnTu4c+eO5MewFkLfiaioKBw8eFBma6SlRYsWKFOmjGC70rUMevXqBXd3d71tOp1ONKVQCQwePFhQZDMlJQXbtm2T2SJpEXtfePr0qWhKIcX2MMrRRjU2KBQKhWJtDh06JDhxcnR0FBU8kwK1Wo26detaLL94zZo1gisNrq6u6N27t0WOKxdi0QyWqKghN2LRNu+++y4qV64sozWWQd9k9P3338ehQ4dQtWpVfPzxx+jVqxe2bNmC7Oxss4935swZfPjhh9iwYQO6desGQPx7pDTEtCiUPvEvTGRzzZo1ihbZdHJyKtIimwEBAaJC3Er/flavXh1169YVbFf6+RVF2rRpg8jIyAL7z58/j1q1ahk+EMMCrAkbowyXgTKspFAolP84YhNHsdUzKRkxYoRFXngIIaLjDhgwAM7OzpIfVw4iIyNx9uxZ0etniYoacpKYmIgdO3YItitdFBXgz1FfKcQRI0ZArVajU6dOWL9+Pf7++2/Exsaie/fumDBhAi5evGjSBG/r1q345ZdfsG3bNpQoUSLvb1gU0jRycXd3F3RY7tq1S1ADQCkMGzZM8L5++fKlonUoAPH7+u7duzh//ryM1kiP2PkdO3YMT58+lc8YCyB2flu2bEFycrKM1lAKw9HRETVq1MDGjRsB8Kkp06dPR7NmzYyrhmeKUyN3UwDKsJJCoVD+w8THx4sqXcs1caxUqRKePXsmeX7xv//+KyjUBigzjUGn02HkyJEIDg5G48aNERsbq7efJStqyMX69esFIxScnJzQv39/mS2SHn3nWKtWLdSuXTvfPi8vL3z44Yc4cOAAxo0bh02bNqF9+/b49ddfDdYdmDt3Lg4ePIhNmzbllXPt0KEDAgMDER0djQMHDkhzUjaA0LNLo9Fg7dq1MlsjLcHBwWjTpo1gu9JXxevXry8oAAsov3Rv586dRctTKz16auDAgXBwcNDblpmZiU2bNslsEUWMvXv34ocffsDIkSMxaNAgNG3aFH/99Rf27NmDuXPnGj4QdWxQKBQKRW44jsPWrVvRtWtXtGnTBhqNRm+/4OBgtGrVSja7evXqpXfl2hzEXvArVaokKDJoy3z//fdYsWJFoUJeHTp0QIkSJWSyyjKITWD69Olj0wrqhqLvHAtzuFWtWhWzZ8/G/v37UaVKFXz88cfo3bu3YKqKTqfDlClTkJqaiiVLluQr56pWq/McYEqfML5JixYtULp0ab1tSk9nAMSdzvv37y+g2aIkGIYRPT+li2za2dkJliUGeMeGkkU2PT09RauQFaXnTFFh/PjxmDRpEjZs2ICLFy9i8+bNaN++vXGDqFSmbwqAOjYoFArFBpk5cyb69OmDPXv24Pr164L9hg8fbnAZMCno379/XiikFGRkZGD9+vWC7UpN0xA7pzdJS0vTW2lDKVy/fl20dKUSo23eRt852tvbIyQkxKDP56aqrFu3Dn/99RdiYmLQvXt3TJw4EZcuXQIhBJmZmQgJCUGdOnUwbdo0vd/53L/l7t27ERcXZ/6J2QAsywp+R65fv44rV67IbJG09OjRQzBNkOO4Ii2ymZqaiq1bt8pskbSIPb+ePXuG48ePy2iN9Ig5ps6dO1ekxIqVTmJiInr37o1FixZhyZIl6NevH9q3b4+FCxcaNxDDmL4pAOrYoFAoFBsjOjoa33zzjUF9c0tByoWbmxu8vLwkyy/evn07UlJS9LapVCrRFTNbhRCCZ8+eGdT35MmT+PHHHy1skeUQi7YpXbo0WrRoIaM1lkHfOXbr1g3e3t5Gj+Xl5YXx48fjwIEDGDNmDDZs2ICWLVuidu3a6N27t2haUsWKFdG4cWNotVqLl16WEzEtCqWnazg5OWHQoEGC7StWrFB0VIq/vz+6dOki2K7061etWjXUr19fsF3p59emTRuULFlSsF3p51eUqFatGmJiYnDlyhW8//77WLNmDZYtW4Zp06ahc+fOhg9EU1EoFAqFIie3b982+GW3T58+yMzMtLBF+Rk+fLho6VljEHtx6tixIwIDAyU5jpwwDANPT0+D+y9ZskRRkxutVott27bh+++/x99//y3Yb8SIEbJGE1mCnJwcvU4EKXRtqlWrhjFjxoBlWUycOBHbtm1Dnz59sHXrVkHNktwVZKVPiN9ETIti7dq1yMrKktkiaRFb9b937x7Onj0rozXSI3Z+x48fx5MnT2S0RnrEzm/r1q1ISkqSzxiJUalUotV7QkNDBdNgKfIyduxY/PPPP/nKSPfv3x/Xrl0zrsISTUWhUCgUipwUpsvwJnfv3pV9VaV58+b4559/zMovfvnyJa5evYqjR48K9lFyNY3ixYsb3JdhGMWk26SlpaFu3bro3bs3pk+fjrS0NL39GIbBsGHDZLZOGnJycvDLL7+gV69eGDhwYIHqHMWLFzc+r1kPZ8+exdixY7FmzRqMHz8e69evx5IlSxAdHV0gVSWXfv36wcnJCTdu3BBNAVIaQpPHxMREUeFkJVCvXj1UrVpVsL1Tp04oVaoUvvjiC0VOkjt16gQ/Pz/BdqWLbA4YMEBQZDMrK0vS1ExrIObYiImJKVJixUpm2rRpeQsFbzp7S5YsicOHDxs+EAMTU1EkPiELQR0bFAqFYmMYG6Vw69YtC1miH5Zl0bJlS4SFhRn92eTkZAwcOBABAQEFKkq8iY+Pj3HhlTaGMY6Nli1bWs4QiZk6daqo5ksuzZo1Q3BwsAwWSc8XX3yBzz77DNu3b8e2bdsKtA8dOlRQV8BQtm/fjlmzZuWVc83F29s7X6rK+vXr0b59e/z222+Ijo6Gm5tbXvpZUQoT79mzp6AWhdJFDAsT2UxOTkZERARmzZqFkJAQxQlS/hdENnv16iXYrvTvZ7ly5URTBovSc0bJcByHH3/8ESVKlECxYsXw+PFjALzDY9myZQaPw6hUJm9KgDo2KBQKxcYwZlIMGO8IkYJhw4YZnY5CCMGIESOwYcMGaLVa0b6DBw+Gvb29OSZaFbEVzDfx8fHB/PnzLWyNdJw8edKgftevX8eFCxcsbI1lKKzqz+PHj81aWf/jjz+wb98+bN68WbRiTLVq1fDrr79i3759qFixIqZMmYI+ffqgXLlyAIB169YpPk0jFycnJwwcOFBv26FDhxAeHi6zRdLStm1bg6Ky9u3bZ/A9ZkuIpWs8f/4cx44dk9Ea6RE7v3///Vf2xQWpETu/3bt3C5Yrp8jH//73P6xcuRKzZ8/O925UrVo10ZTQAjAm6mswynAZKMNKCoVC+Q/h6ekpGPr6NoGBgZgwYYKFLSpIUFAQkpKSkJycbPBnYmNjDS4V6+vrq2gNAUMmMaVKlcLJkydFxdtsDUOrcSQlJWHKlCmKvIaFpYJt2rQJvXv3NnpcjuPw8ccfIzk5GUuXLs1XzlUMOzs7dOnSBRs2bMCSJUvg4eEBJycnJCUl4ffff1fk31gfQpMrQghCQ0NltkY6UlNT0b59e4Ov0927dy1skfRUrVoVDRo0EGz/+uuv8dNPPym2yk3r1q0RFBQk2N6uXTvUrFkTv/76q+yaV1LQp08fFCtWTG+bVqvF2rVrZbaI8jahoaFYunQpQkJC8kUM1qxZ07hnBq2KQqFQKBQ5YRgGLi4uhfbz8vLCjh074OHhYXmj9DBgwACj8osfPXpkcN+vv/4aR44cMcUsm6Awx1TlypVx+vRpVKpUSSaLpMHf39/gvmfOnCmgT6EEDImYOnbsmFFlenPLudasWRPffvutyZoq3t7emDRpEr788ksAvPBshw4dMGfOHMTExJg0pq1Qv359QS0KJYulLl261Khro1arLWiN5SgsquGbb75BnTp1MHnyZBmtkgaVSiWqGRQVFYXr169j6tSpGDdunOK+qy4uLujfv79g+7Jly/DixYsiEyGmRCIjI1G+fPkC+zmOM07glYqHUigUCkVuClvNLVmyJE6dOiW6SmZpevToYXAEBgC4uroaNf4ff/xhrEk2g5ggW6VKlXDy5EmUKlVKPoMkwtg0KWOvuS1gSGpXYGCgQc5HAIiPj0evXr0watQoyQRVc0ukPn/+HIsWLUKFChUwefJk9OnTB9u2bTNOJd9GYBhGcHL86NEj/PPPP8jIyJDZKvOJiIgwqr8SK0EBvKPbkPTBefPmYc+ePTJYJC1du3Y1qN+qVatw9epVyxpjAcQcU7du3UKJEiVQsmRJzJgxQ0arKLlUqVJFb5rali1bRPXKCkDLvVIoFApFbsQ0GsqVK4fTp0+jcuXKMlpUECcnJ5QpUwa3b982qL+xL+xKXh1q2LAh3n333QL7S5UqhQsXLsDb29sKVpmPMdewf//+cHR0tKA1lqEw5429vT1WrFhhUCnbhw8fol+/fpg1axbatm0rlYkICgpC27ZtQQjB+vXr86WqvHjxAt26dcPkyZNx5coVRa0eDx48WDBioW3btnBxcUH79u3x8OFDmS0zHWNFdI11HtoKGzduLFQ7KZd//vnHwtZIS0pKCnr06GFwf0N/E22Jxo0bo0KFCqJ9Xr58ia+++so4TQeKJHz77beYMGECZs2aBY7jsG3bNrz//vv46aef8O233xo+EHVsUCgUCkVupk2bpnd/QEAAzp49K5rvKycjR440WDXd29vbYF0BgM8dVTJnzpzBp59+iuDgYJQoUQITJkzAo0ePBHOZlYCvr69B/cqXL4958+ZZ2BrL4OPjI9hWrFgx7N+/Hx06dCh0nPPnz2Ps2LEIDQ1FjRo1pDQRwOtyyCtWrMirOuHt7Y0JEybgwIEDGDVqFNasWYMOHTrg999/V4QAoL+/v2A1pNxJ8+HDh9GzZ09kZ2fLaZrJjB07ttAJ45so0bERExODKVOmGFz9RGlpU4sXL8aLFy+sbYZFyc7OFn32vcnixYstbA3lbbp3747du3fjyJEjcHFxwbfffos7d+5g9+7daNeuneEDUccGhUKhUOSmb9+++eqWA7z69a1btwyeXMpB3bp1cfXqVYNyPBmGMfjFKSgoCN9995255lkVhmHwyy+/4OnTp4iIiMCff/5plGPHFjGkzGmtWrVw6tQpgyvD2BpCq84+Pj44fvw4WrduXegYO3bswM8//4ytW7daTBy2R48e8PDwwOPHj/WGKNeoUQO//fYb9u7di/Lly2PSpEno27cvtm/fbrOpKklJSUhMTCy0382bN3Hnzh0ZLDIfR0dH7Nmzx6DIDWOekbbEgQMHjIqwCwgIsKA10mOMPhSgTOfUV199hTNnzhjUV0kRU0WJZs2a4fDhw4iNjUVGRgZOnTqF9u3bGzeIijVRY0MZLgNlWEmhUCj/QX744QdkZ2fj4sWLePbsGW7cuAEvLy9rm5UPhmHQsWNH7N+/36D+hkzsy5Urh7CwMNFSmNaEEA7kZTTIo5sg966A3L8K8vgWSGKcosL+TcHT01O0vUWLFggLCzNKZNTW0Kdb4+7ujlOnTqFevXqFfv7PP//E7t27sXnzZri7u1vCRAD8hHnQoEEAgOXLl0On0+H48eMFFPLt7OzQtWtXbNiwAYsWLUJERAS6du2al6piS0yePNngNIWoqCgLWyMd77zzDk6fPi0ojpqLvb29QSlOtoaxWjpKm/iXKFHCqP5K00nJzMzEkiVLDO6vRO0kyiuKeFUUhhT1tzAKhUKhWJTY2FhMnDgRGzZswPnz5/HgwQMMGTJEb9/y5cuLrn7VrFkTBw8etLmJMUmMA7l+GuT5AyDmOaARWPG2dwQCg8EEVwRTozEYV3FHgNJISUmBh4eHXgdO06ZNcfjwYUXqarxN9erVcfPmTQB8+smVK1f0KtK/CcdxmDp1KlxdXfHdd9+ZXPnEGC5evIj69etDrVbD19cXUVFRKFmyJMLDwwv97PXr17Fq1SrcvHkTHTt2xKBBg6waZZOdnQ0XF5dCy+3mcunSJdSpU8fCVklLQkIC3nvvPVy4cEFve/HixREZGSmzVeaTnJyMKlWqGJyusWnTJvTt29fCVklHUlISqlSpYrAzLTk52WYd8/rIzs426rldv359/Pvvvxa0iCI1KSkpcHd3R8Ks8XBzEq/apvfzmdnw+nyBzX+3lecWplAoFKVCCMDpAG0OkJMJZKUBmamvt+x0QJMN6LR8X4VACMHNmzdRrlw5dOrUCX/++adg3/r164u2nThxwmacGoQQkIc3oNvwB7jF34CcPQhEPBR2agBAThbw7B7Iyd3gFnwJ3dbFIM/vy2e0hXFzc8OPP/5YYH/9+vVx/PjxIuHUAIAbN25gz549WLFiBZKTkws4NZKSkvK92GdlZWHw4MGoVq0apk+fbnGnBiEE69atw0cffQSAT58xNoIhN1Vlz549KFeuHCZNmoR+/fphx44dVklVMaSixpsobVUc4Et0Hz9+XLDM89SpU2W2SBrc3d2xcuXKQstc56K0a+fh4YGdO3caJPpsZ2enuIgGBwcHo0qPKy3ihvIGVGODQqFQKGZBCO+wyErlnRk5mbxzg9MBhHu96bSAJot3cGSm8P04w1YvrUFmZiaaNWuGOnXq4M6dO3jy5AkSExNFNQV+++03vekolSpVwokTJywaum8MJDUR3KY/wW2eDzx9FdpPDBPG4/sSfntwDdza36DbuQwkM90yxsrM119/jQsXLqB///7o1KkTNm/ejH///VewmoXNQAh/j+VkAhkpQFoCkPoSSE0A0pP4e1OTnXedO3fujOHDh+tNDZg5cybat2+PK1eu4OXLl+jVqxeGDx8uWjJRSi5duoSQkBCcOnWqQJuxk443U1UWLlyI58+fo2vXrpgyZYqsZSsZhjG4HC7LsorVcHFxccHVq1fzabWo1Wp88cUXmDJlivUMM5N27drhwIEDBk3qlTgxrl+/Pk6dOlWoZo69vb0s0VpS89dffxmcBqU0xxTlDRjW9M1IFixYgNKlS8PR0RENGzYUjfL566+/0KxZM3h6esLT0xNt27Y1KSpINBXlxYsX2LZtG+7evYvMzEyjB6cYDsMwcHV1xbvvvovOnTsrWjWfQqG8ghDegaExs2ypSg3YO5n0w2JJCCEYO3YsNm7ciOTk5Lz9H3/8MX777TfBz929exe9e/fGw4cPoVar0adPH/z1119Gr9haCu7GWZCD6wGtxjhnhhgMCzg6ge08DMw7yq72ojgIx0fSZKUDnGHlKGHvBDi4AOqCTjidTofy5cvj6dOnCAwMROnSpbFo0SJZq/hkZ2ejVatWOHv2bIG27t27Y8eOHWYf49q1a3mpKp06dUJISIjFhYuTkpLQrl07XLx4UbSft7c34uPjLWqLHGRkZCAxMRGBgYGK1NbQx+XLl9GhQwfR65ORkQEnJycZrZKO8PBwtG7dWlBAs1SpUnj+/LnMVknDjh07MGDAgEIrDk2cOFGxVa+KGnfu3MGyZcvw66+/ivbLS0X5/WPTU1E+mmNwKsrGjRsxdOhQLF68GA0bNsTcuXOxefNm3Lt3T69TOiQkBE2aNEHjxo3h6OiIWbNmYfv27bh165ZRGjd6HRscx+HDDz/E0qVLoVarUalSJbi4uCjSA6kUOI5DYmIi7t+/D0dHRyxcuFC2lR8KhWIBOB2QnQkQqSIuGH6ypWeiZW2+/fZbLFiwAAkJCQCAhQsXYty4cVa2yngIISAndoCcPWChIzAACJi2/cHWL7yyhjXhOA4Jz8ORlZIKhmXh5u8HV1+FVWsg5HV0BkxM7VI7AC7uAPu6GsyuXbswePBgpKamAgDKli2Ly5cvyx5tlJ6ejr59+xYQ7h03bhwWLlwo2XE0Gg3279+PtWvXghCCkJAQdOrUyWIVflJTU9GjRw8cO3ZMsI+/vz+io6MtcnyK+dy/fx8NGjTI5/DORckT/1zi4+NRo0YNvelfc+fOxeTJk61glTSEhYWhW7duec83fRS2eEGxLOnp6diwYQOWLVuGc+fOoUqVKnmaUELkOTbmfmK6Y2PKbwgPD8/n2HBwcNCbgtawYUPUr18f8+fPB8C/U5QqVQoTJ07EF198UejxdDodPD09MX/+fAwdOtRgO/XGjU6cOBF//fUXfv31V4wYMaJQFXSKdDx58gQ//PADRo0aBWdnZ/Tv39/aJlEoFGPRafl0EkkhQE4GwDkAdg42pVD9ww8/wN/fH9OmTUNKSgrKlCljbZNMgoRtAzl3yJJH4P/3yEZwhAPboK0Fj2U8aS9f4uzKdbi2cy+eX76KnPSMfO1u/n4o06gBGg7uj5rdOkFly6VrOR2fXqI1UytCmw0kxwHOboCDMwBgxowZ+V76nzx5gtatW+P8+fOypuO4uLhg586dGD58ONatW5e3X+pSmnZ2dujWrRu6deuGuLg4rF+/Hl27dkXlypUxfPhwySNVXF1dsW/fPoSEhGDr1q16+xQVLZe3IYTjHeLZGXykHyF8tJe9Ix9BZO+oiEXGChUq4OrVq6hevTrS0tLy9tvZ2WHTpk1WtEwafHx8cPPmTbRq1QrXr18HwEdeT5o0SdFODQBo2bIlwsLC0KJFi3zX7k26d+8us1UUADh9+jSWLVuGTZs2ITMzEx999BGWL19ulD5KXvlWY3n1mVKlSuXb/d1332H69On59uXk5ODSpUv48ssv8/axLIu2bdvqjTLUR0ZGBjQajdGVAAv8AsfHx2PJkiWYMWMGPv74Y6MGo5hPmTJlsGzZMsTGxmLmzJnUsUGhKA2LODXeQJsNgAB2jjbl3Bg/fjx8fX0xcOBAlPByA4l5CpKW9EqzgAB2DmBc3AFXL8DF3eZezrkLxyzs1MgPOboZXDF3sFWExVTlIiMpCTu+/B6nl68Gp9WAcPqjG1JiYnF9935c27EHrn6+6DL9SzQbM9L2Quh1Gl43Q6o0IhAgIxnQafEsLhG3b98GwE+uvby84O7ujrp160Kj0ciuM2JnZ4fVq1fD09MTCxYsAMC/EFoKX19fTJo0CZMmTcK1a9ewcuVK3Lp1C507d8agQYMkS1VxcHDAxo0b0bdvX2zfvr1Ae0hIiCTHsRWIJhtIjuWdaHm6Sm8+I1/dkyo7EA8/wM0XjA1G771J6dKlkZSUhGnTpuHChQsoU6YMZsyYYZAApxLw8vLCtWvX8Pz5c0RHR6NWrVo2k05pLnXq1MG///6L2rVrF0hLKV++PJo3b24ly/57xMbGYuXKlVi+fDmSk5MxcOBAhIWFoVGjRhg5cqRxTg3glRCoCY6NV7/z+iI23iY+Ph46na6AELy/v3+BcuRCfP755yhevDjatjVuAajAL/DOnTtBCMHw4cONGogiHSzLYuTIkejTpw8ePXqEcuXKWdskCoViCJzOsk6NXLQ5/CqenfHhhJaCEIK+bZqgbdh2eOjiQB7H8Y6X3GxHhgGJexV+7OQKBJYD/IJswsFB4qNAjm2R/7j714AEVQBTzHqCqbcOHsGqYWORGv8SxIAym7l9UmPjsP7Dj3Fxw1YMD10C7+AgS5tqGDotLwhqiapC2em4fv40CCHo06cPBgwYgDZt2sDDw0P6YxkBy7L4888/kZCQgH379qF///78RDkzjf97sCwfbeLgLOn9VrNmTfz+++/IycnB/v37MX78eACQLFVFpVJh69at6NWrVz7NkEaNGhVYIVQqhBAgMQp4+QIF06X0fId1GuBlJJAQBeIbBLj52MQzVAiVSoWff/7Z2mZYlKCgIAQF2cjzT0IqV66MmzdvIiQkBFevXoVKpUKrVq30OhopliM4OBh9+vTBH3/8gXbt2pm/kGBqhZNXn3Fzc7N4udeZM2diw4YNCAsLMzo6r4Bj4/79+yhTpoxi1aaLCg0aNAAAPHjwgDo2KBQlQAgfPiwXmixeVNQUz7vEkOxMkMdXgaRYeLz5q/Lm5PLN/5+ZyvePfQaUrwPGyXpiyYTjwO1eYZ3yupoccPtWg+073iqTk9PLQrH6/YlgGAaEMy264dGZc5hRrwU+Or4XJapVkdhCIyGEr3RiwWvZtV0rpMRF56Wl2AoMw2Bt6CrgZSTIywiQ2wWrpYBVgXgGgPEpCcZRunvO3t4e3bt3R/fu3REXF4d169ahS5cuqFq1KoYPH44aNWqYPDbDMNi+fTuePHmCQ4cOoXbt2nnvR0qH6DRA5H3TfjcIB8Q+BdISQQLLgbGB3wHKKwh5VensjecQq7KpCEtDKV++PM6fP29tM/7TBAcH49SpUwgKCkJwcLDxERpvw6pMjNgw/DM+Pj5QqVSIiYnJtz8mJqbQVMlff/0VM2fOxJEjR0z67SjgssnMzFSsUnFRwtmZf2myZEgphUKREG22hKHvBpKTaZ0J+RuQ9BSQ62FAUpzxH05LArkeBpJiveoG5PIJIPqZ/NcO4I/56AZw74rsh76wYQtWj54AEGKyUwMAOK0OGYlJmNOyE+KfPJXOQFPITJWnPHJGik2VYSaEgCRGg9w5DRL9iE//0genA16+ALl3HtyLByAWOAdfX19MnjwZBw8exNChQ7FixQp06NAB8+bNM6uKSZkyZTBmzJgi5NTQAuF3zXeGZyQDkffNuoflhHA6kJeR4O6eB3f9OLirR8HdOAHu8TWQtESIFGq0fXKroGWl8Vt2+utNAeXbKbbJ3bt3sWbNGkRFRaF+/fqoW7cufv/9dwAwbUGEVb3W2TBmM8KxYW9vj7p16+Lo0aN5+ziOw9GjR9GoUSPBz82ePRs//vgjDhw4gHr16hl/btDj2ADE/1ArV64EwzB4+vSpUQeaPn26wReAYZgiE2ZoKrYcWkihUN6CcMKTCUvC6fjQZCtBstL5lWGtBqZVnSAApwO5c5bX45AZQjiQ8/LpauiFYcDJbEP802cIHTlesvE4nQ6ZySlYPvh9cNaaYGlz5EkDAwAQIL1gtQdrQAgBefEA5PktAydNr+7TuOcgDy+BaC33/KhVqxZ+//137N69G8HBwRg/fjz69++PXbt2QaPRf9yXL1/izp07hQ/Oca9KaWfz/1XQhJEQAkQ9NL8MeC5ZaUDcM2nGshCE48BF3ge5egzk8TU+XSw7k79+Wem8w+3OWZBbp0ASFVjtRpvz2nkh5CTPc3qkW31BwhwI4UAiH4G7/S+4m+dAHt8E0Zgp0kwRpUmTJli+fDn+z955h0VxvHH8u3tH7yAqgmIXe1cs2CMC9hZLxB5r7Ikajb1rorHmZ+ya2I0N0BjFiAWxd8WCghQVkV6u7Pz+WCAgd8f1gvN5nn2UndmZd27rvPOW+Ph4jB07FocPH4ZUKsX48ePx+++/48MHFRaWGEb9TQWmTZuG33//Hbt378aTJ08wbtw4ZGRk5Gf8DAwMLBRcdOXKlfjpp5+wY8cOVKxYEQkJCUhISJAbwFYeRhbxy7jgOA6rVq1CpUqVYGlpiXr16mH//v1qtfX8+XMMGDAAHh4esLa2hpeXFxYtWkQtMiiUkoCmmRc0wUAfFIQQkBe3AYkEaqfSzIPjQJ7f1MkKskKingCpSfrt83MIAeKiQN7F6Kk7gj3Dx0Oq5euGk0jw6up1hG74TavtKk22ah8/GiPJMahSMQ/yLgpIVPPayUoDibrLZ+LQIXmuKgcPHsTGjRsRFRWFrl27Ytq0afkZJfJYsmQJfHx85Cs3pGJ+Ypidxk8ixdn8v3mr5BKx8U8aUxN56yItt0mMRNn2OUQqAYmMAOJeKLhncs9ZVhrIi9sg8S/1Jp/GiHP4a1BZOAl/rRrCSlADiDgH3J1/we1dAe7EVpCLR0Eu/QXuzF5wOxeDCzsBYuj3aQnH1tYWo0ePxtWrV/Ho0SM0atQIc+fORbly5ZRvRB1rDTUyqXz99ddYs2YN5s2bhwYNGuDu3bs4c+ZMfkDR6OjoQumSt2zZApFIhL59+8LNzS1/W7NmjUr96k2xMXfuXGRlqXDjGwFz5szBzJkz8dVXX2HDhg2oUKECBg0ahAMHDqjUTkxMDJo1a4bw8HBMnDgR69atQ4sWLTB//nwMHDhQR9JTKBS9QIjBlAt8/1LDrFa+e81nntBUqZFHdgbI20jttKUk3K2LfBBWQ8OwIHcu6aWr55euIPJiGDiJbq6ZoAUrIM7Rs/USJzWMxZQ+Y+rIgGSkAO+iNGskM5WPdaMnPndV2bFjR76ryvv373HixAl8/PgRfn5+iI6O/u9AQgBRNv+bcxLZjXNSPiW2EbjoyYNwUuBDdPEV1eH9a6Nz5SAcB/L8Vu67QoXj3j4DefdaN0JpE4lIPcsbwpmU5QbJSAV3dBPItRAgXYYCTSICeRgO7uBakNhX+hfwC6RmzZr4+eefERsbi4MHDyp/YF6MDXU2FZk4cSLevHmDnJwcXL9+Hc2bN88vu3jxInbt2pX/9+vX/PPr801VDw695SUTCoV6T4OmCbGxsfj5558xYcIEbNy4EQAwatQotG3bFt9//z369esHgZLaq7179yI5ORmXL19G7dq1AQDffvstOI7Dnj178OnTJzg5OelsLBQKRYdwUmhtcq8uEhFgrr/YSHnm71on/hWIezUwAt2/KwjHAa+fGMeqGeFAXjzQS1cXN20FKxSCk8iZHGpIZnIybh85juaD9Ziq3FAKhpwswMreIEEBCSEgb5VLm1dsWwlRgJMbGHPVos9rSoMGDbBu3TqIRCIEBwejf//+ePv2LQDgzZs36NChA65evcoHs5eIclNdK4FUDIgZvT4TlSbto+6eORIRr6iyMVyWpSK8f82PWQ1I9GPAwRWMpY12ZdIWhKhmqVHk+Fx3KiPKbiYLIsoGd/J3IDkRCr91CAdIxOBObwfbezwYV3e9yVjSkUqlePPmDSpWrAiWZZGTk4MTJ06A4zi0b98evXv3Vr4xluE3VVHnGAOglaWqkJAQ+Pj4wMbGBnZ2dggICMCjR48K1ZEVYyMnJwdTp06Fq6sr7Ozs0L179/yX2ufExsZixIgRKFOmDCwsLFC7dm3s2LGjUJ2LFy+CYRgcOnQIS5cuhYeHBywtLdGxY0e8ePFCpTGdOHECYrEY48ePz9/HMAzGjRuHt2/f4tq1a0q3lZqaCgBF8vm6ubmBZdkSk/eaQvki0cRagmEBCxt+cmRlB5ipObHQt8VGygd+UqeIclXBNOgIxrs72BY9AHuX4tvlJHwqQ32Q9C43Noj6sIOmgZ3yC9gfNoGdsALMVwP4TDXqkPYJJEu3MSKy09Nx99gppZQa1o6OGHd8P5ZFP8aGrPdY9uYReiz5qdj4TwzL4tquP7QlsnJo4gpmZQ84ufGbyitSxHDuKJmpit1vrO3BVGkEpk5bMLV8wJSrpkABQ0CS4nQipjKYm5ujZ8+esLa2LhR74+XLl2jRogVSU1Jkr4oLzQFL2wLPzwITRGONu5GihC+8lR2Yak2LbKioRIaAVDWCOOsIQohcqwumXjuwTf0LbXAs83mt/1KEGyOK7n2BWYFr055/z8uyDpTkGL3VBrl7CUzFWmAHTgM7bjkE41cC5Sr/V6FiTbBfTwU7ZinYwT+A8WoM7t9jhhO4hHH//n2UL18e1apVQ/369RETE4MmTZpgxIgRGD16NGrWrIkbN24o3yDLqmmxYQTWrUqgsZR79+5FQEAAbG1t8wN/PH78GK1bty42wOioUaOwbt06dO7cGStWrICZmRkCAgKK1Hv37h28vb3xzz//YOLEifj1119RtWpVjBw5EuvWrStSf8WKFfjrr78wY8YMzJ49G+Hh4Rg8eLBK47pz5w5sbGxQs2bNQvvzInLfuaN8FPt27doBAEaOHIm7d+8iJiYGBw8exJYtWzBp0iTY2BipNppCoRSPJh/PFtb8C0OcDUgl/Ie5Oqs3nFSvH0ck5UPxq9SsAPiUULwCpBAMSIp+MqSQBM3N78m7GJDQYyBn/wRE2WCbtAdTv7X6Db7T7Uf827sPwEmVu16tHOxRtmYNXN66C4emzAIhBH5zvkfbCd8qPI5wHF5fv6U/k3iigXJBaMHfg5rIaiDFBkl5D0DOPSg0A1OpAWBlBxL/Asj4BMa1ApjSFeU3aOCAjenp6flpJe3s7FC6dGm4uroiLi4OIaeOFz3AzIK3yMhbNZflimTI2EcyIBynnHWRKAsk/uV/W57FQ7YSik9tx+7QhNRE3n1IDiQrDdzLO/kbMpI/rwF8iNF/7CVlkef+xjD8c4Vhc9/tYl7hLcuCiBDjVMDlQqRSkIfhgEAI8vopkJZcuIK9C1jfIYCZOcjlk0BWBti2vQFzS5BEwylLSxI//PADWrVqhXv37qFjx47w9fVFzZo18enTJ3z69AkBAQH48ccflW9QTzE2DIVG9r7p6emYNGkSRo0aha1bt+bvHzp0KGrUqIFly5YV2l+Qe/fuYd++fRg/fjw2bdoEAJgwYQIGDx5cJJjUnDlzIJVK8eDBA7i48Kt+Y8eOxcCBA7FgwQKMGTOmUIra7Oxs3L17N98SwsnJCZMnT8bDhw9Rp04dpcYWHx+PMmXKFFmdcnNzAwDExSl/w3bp0gWLFy/GsmXLcPLkyULjWrJkidLtUCgUI0TdjxJWyE/+JeL/PsAFZvxkS514AYTozyQ+Pbn4yeDbZyAAGDtnwNJayYYJkP5JQ+GUJDGe//01+Kgk5w/zY7O0BuPVGCjlBrXdkhgG5EM8mIo1i6+rJm9u3QHDskqlhvz0NhYLajbJr2tmYYH+v65E+QZ1iz02Oy0NiVGv4Vq5ksYyFwvh1FNMMCxvsp+dzk841LW0kUgAQ1iSZ6RA7rVm7QBGaMYrID/GgqR/AuNYBihVXn5MDlEWiFSiFzcwWYjFYkyaNAmVK1dGhQoV4O7ujnLlysHayip3sv7ZWIUW/HlXlAlHIuKt4Iwly5xISZcpqQRILxCTwiU3MOCneNn1PzuWSMRghGaqy6dlyMc48Mo3OdepWAQkv1f8DJZKgJREwOlzaw4Dw3EKXIoY/tokhJefEN66SN7vkKf4MEbePOXjX938BwDAlPUE7J3zi5nazcEIBODuhYE8ug6SmgRBt1Fg67YCeRwBpk1PAwlecoiIiMCVK1dQs2ZNLF++HBs3bsSuXbtgZsbf47NmzULbtm2Vb5Bh1YstZgzxyJRAozvp3LlzSE5OxsCBAwvlJxcIBGjevDlCQ0PlHhscHAwAmDRpUqH9U6ZMwZ9//pn/NyEER48eRf/+/UEIKdSPr68vDhw4gNu3b6NVq1b5+4cPH17IvcPHxwcA8OrVK6UVG1lZWbCwKPq1YmlpmV+uChUrVkSbNm3Qp08fuLi4ICgoCMuWLUPZsmUxceJEldqiUChGhLqrvXlmfYU+jkjuy0PBx6B8QdSTQx10mVZTJQsPDRBpJ9gkO2YxGGtbAAD38DrI3cvqNcQwOg+AmRr/DqxAAKkSio2Clh0Mw6BOgC8A4Mk/F5XqKyX+nf4UG+pg48BPqPIUG/ruX1MUTZLzFKWWtvzY7PgFIUZoBiIQ8pMtmW1m8S4dBsDJyQnz588vWkAIijzbWAF/vxAOsLTjn6UcB4izio6NcABjJCuN6ri+2TiAMbcCyUxVPpaMRAQYgWKDt9ZQ8F6ycwbb2Je3yEj5APL6oWwrG0MEBi4ORfc94fh7ydzqv/uJk8p/txlDnCc58NaZrFwZGYdSfL08S4603IUJx1IgD67oQcKSDyEkP0bl5/8C/JxbpTTr6lpffAkWG8+f88HjOnToILPc3t5e7rFv3rwBy7KoUqVKof01atQo9PeHDx+QnJyMrVu3yrX+eP/+faG/K1SoUOjvvMCcnz4pvxJoZWWFHBmR3bOzs/PLleXAgQP49ttvERkZCQ8PDwBA7969wXEcZs6ciYEDB+ZbolAoFIpa6NNPV6d96cuFQTsfk9yx38DY2INp/hWYWk1AIu8Az5R3VSzcmG4/cJV1QymI0NwcQ3f/D7U6d8CFX7fg5oEjyvWlo+CkRVDncjG34lf805P+myQDuRY8nJqN6hlF92BmKkhiDJhS5cHUbMmbk3McmOJ8pI3S11+GTHlyMiwgyQbEHH9Oza1lW3cYC+r8vo5l+X9VchUykvEreMaSxLe8JQAnBVPaE4xTWYCTgry6p1I7xgmTGy+L8MoMluX/NreSrZA0ktMlE3lKULkUsI7SMIYVhadx48ZYuXIlFi5ciO3bt6NSpUrYuHFjfpzJDRs2KL1oD4BX9KqR4cRoFMTFoJFiI09DtHfvXpQtW7Zo41rIgpLXxzfffIOhQ4fKrFOvXuGASvKylaji8+vm5obQ0FAQQgq5o+Tl3FUlZ/DmzZvRsGHDfKVGHt27d8euXbtw584ddOrUSen2KBSKEaGOcQXw3yS2kHkfI3uFUik59GhuLTRX6DutEfoyydXWimbM8/yzxfb6FmzdluDUUWwQAGa6XWW1sLVR6T1o5eCAccf/RPV2Pji9YDlOL1yu9LGWdrbqiKg66lz3ecoMu88WFOxceGWHKivEhvJyEJopnHSQ2EiQ92/4CRUnBVO9GYhIhkXD520aHUyR77B896OCVk7EooAlR4Fr3FjcUADVJxMW1mCs7UFysoBMGSk2tdWPrlB0PcX9F9CfiHPAOLjKtxYSGOF1qei6EuQGWpSIeTcTKfj7UN67zZiu0c+xtFGsoEpJBAOAsXPk34N2jnxBciJgpad3QAln+fLl8PPzw86dO+Hi4oLQ0FCMHDkyPwHFp0+fcOrUKeUbZBj1rjljvk4LoNEXZJ61RenSpVWemHt6eoLjOLx8+bKQlcazZ88K1cvLmCKVSvU6+W/QoAG2bduGJ0+eoFatWvn784JbNWjQQOm23r17JzOda170b4m+VrYoFIr2YViAqBGngZPw5qkCIa8oyPsolxX9X1k59IWNI5BZzMqonQtgZZMfDJVxKgNiaQO8LyZApo2jtqRUjJ2jZiuBlWuDqdUUePsSYBgwjdsDAMh72Zm9ioVwgK2j+vIogXvd2kpbUljY2GDG5bNwr1MLD0POIeFpJJp83Qdp7z/gWeglhccyLIuyNWsorKM11JnEibILT/Ct7fl2MlNUX2VkDeQbb+2g0G2LKVsZRJTNX5suHmAYBpy8+BoAP351szJpGalUioiICAQFBeHmzZtYNn8uGtarU1i5IRXzz00zy1x3E7Zo3ANWYFx+4RbKxhrKxSl3wTBZBWsNhjGa88jYOoMkvy9aYGUHprwX7+YglYAplbvoJy++ko6fi2qh6LrichVvee92RpbbaQGMRRElA6ZiTZCwE0DZimAcS/HvdACMpxfg4ALy+DpI/dZg6vsAUimYmk0BANyDq2BqNDKk6CWGpk2b4s2bN3j69Clq1KgBW1tbXLx4EX/88QeysrLw1VdfFfF2UEgJd0XR6Inv6+sLe3t7LFu2rFCKrjw+fJCfdsrPzw8AsH79+kL7P89yIhAI0KdPHxw9ehQPHz5UqQ9N6NGjB8zMzLB58+b8fYQQ/Pbbb3B3d0fLli2Vbqt69eq4c+cOIiMjC+3fv38/WJYtYnFCoVBMCE0mNjmZvHIjbzVHnKOePzHD6lWbztg5oTirEqZ0BbBVGoKxzP0QKlcNbJWGxbUM2BZVAusCpqynZqb3melgXN3BdOgLpmM/QCgEdzUE5LIKKyeyZNIhFRo3ULqubSkXuNfhlfp1/L7CqAM7MerATgTMm1nssWVqVIO5Cu6aGsEwqt+DnIRXIOZtedeBOEd1ZZeBrBwYm2LuE3NLMOWqgSlXHQDART8CkuQFn2QAO+diU/nqkqSkJOzfvx+BgYHo2rUrzpw5g+7duyM4OBiNmjUvKpsoKzeWRK5yg5MUjf0jNIcxwQjNlLdIE5oDtk4gEhGQ+lH5TsytDHoeC1HKQ/Z7SSICOA6MWxUwnrUBcyuQhCiQmCefVWQAe5f8d4hRwTDyr6+8GBuE469NoRmviJMXI8XIrtOCMLaOgGdNMDWbgm3fF4wDb+XGNmwLtn1fIOUjuLP7AIkYjE93wMoG3L9/Ae9jwFQpPtA0RTlsbGzQuHFj2NryVjCWlpYYOXIkJk6cqJpSAyjx6V41Wmqwt7fHli1bMGTIEDRq1AgDBgyAq6sroqOjERQUhFatWmHjxo0yj23QoAEGDhyIzZs3IyUlBS1btsT58+fx4sWLInVXrFiB0NBQNG/eHKNHj0atWrWQlJSE27dv459//kFSUpKMHjTDw8MDU6ZMwerVqyEWi9G0aVMcP34cYWFh+OOPP+S6u8ji+++/R0hICHx8fDBx4kS4uLjg9OnTCAkJwahRo1Rya6FQKEaGJqsthNNOIE59r/g4lwOi7itUDJCXd0BequqSQcC4ehRfTRuUKa/Z8QlvwO1cqh1ZAORwBN+MGosmTZvCx8cHTZs2zQ9WrS2cK5RH6WpV8P7Fq2KVOh/fRGMsIz9OljxYgQD1uvmpK6J6CM0BkQaWj6kaLJAYykzesQwQFyk3owSJfqxCYwSMi57uu7weCcGDBw8QHByMy5cvw9bWFr6+vli5cmV+9rn/KjO8f/fnlnGiLABFrVYIIXw8EWN0YbB1BlJkWDF8jkQEvLilevt2zsXX0ROMmTmIczngYxwKKcLFOSBKjY0oTlFsaITm8lMKS8XKpYIWmBm9iT/bqB24v7ZAeuGQ7ApRj8FFFX7eMN5+RpGZpyTx/PlznDhxAq9fvwbDMKhcuTJ69OiBypUrq9YQzYqimEGDBqFcuXJYsWIFVq9ejZycHLi7u8PHxwfDhw9XeOyOHTvg6uqKP/74A8ePH0eHDh0QFBSE8uULf3CWKVMGERERWLRoEY4dO4bNmzfDxcUFtWvXxsqVKzUdglxWrFgBJycn/O9//8OuXbtQrVo17Nu3D4MGDVKpnTZt2uDq1atYsGABNm/ejI8fP6JSpUpYunQpfvjhBx1JT6FQ9IIxmOfpOVUcY2YOUsoD+PAW2ot8lrs6p6esDIyFFeBcBkh6p5f+FAvDwKJidfw5fT0iIiJw6dIl/PzzzxCLxWjQoAF8fHzQsmVLhQG5leuGQfvvxuDg5OKtLtSF4zj4jFH87tc65pbKp9LUJgIzg5mRMwIBUNoTJOGV5o1Z2+vFUiojIwMXLlxAUFAQoqKiULduXfj7+2PatGmFMtkVgWH4tMrZ6cUq5MRiCVJSU+Hk5gGBMU4YHUorp9hQCwawd9VR2+rBuFUB+ZSgRlpths9c5FhaJ3JpBVbAW4txGihVzQyRK1o1mLKeYDr0Bzl/CMq87088fYueY9voXrAviOXLl2PevHngOA6lS5cGIQQfPnzAzJkzsWzZMsyYMUP5xkq4KwpDPoskNmnSJFy8eBH37983lEwU8GaZLi4uOHr0KHr37m1ocSgUiiJyMtSIHq5FrOz1vupDcrJA7p5X44NVHgyYeu3A2Gg2eVcFLvwsSOhfMIaw9Ey3EWDrNC+0TyKR4P79+wgLC8PVq1eRmpqK6tWrw8fHBz4+PihTpozK/WSlpOBHz9rISk3TehYMVihAnYAuGH98v1bbLRZCeKsLrV2LSmLjqFmqWA0hhAOJvAFkZ0Dta5hhwNTwBqNq/AclefXqFYKCgnDhwgUAQMeOHeHv76/6KiOQa+GWJXMiKRZLYGYmROilMASOGovft21Dly5dNBVfJ5C450BGsvYbdiwDxrVC8fX0DElN5K9TJZ83EokUWYSBfbPOYIzYTQMAP6bsdJVc2DiOA8MwYCxsjDRgr2zI6yfg/j0GZKQWSgErzR1PlkiCVX+HY9nZa7h48V+0aUOVG9ogNDQUnTp1wk8//YTJkyfnx2xMSkrCunXrsGzZMly4cKHY3zs1NRUODg5IOrsX9jaqP+9TMzLh7DsEKSkpGi+y6BKq2DBSqGKDQjEhpDL8u/WF0Nxgk6uM109hFf+s+IpKwJSvCcajulbaUhaSmQ5uww/6nxB/jqU12O9WFWu6SwhBZGQkwsLCcPnyZbx79y7fQtLHxweVKlVSyr8+4s9D2DF4lLakz8fcxhoLn96Ck4e71tsuluwMICtVf/0xLL/6bmCrACLKBnlxExCLoIpyQ8pxYFkWbMV6fEYKLSESiXD58mUEBQXh4cOHqFy5Mvz9/dGhQwfY2GgpVgIn5V0ApBK8inqFlJQUXL56HVu2bceTp/zzqH///jh48KB2+tMyRCIG3jzQ7nNHaA541gFjpIEoSfonkOe35LtuABBLJDATChF68z7m7jyKq9cjjCdeiCII91+8rGIQi8UghGDVrxsxd/5CPQinXQjHAdHPwD2OQPTDO8jOyEB8ajoO3HyC/TeeID2HP7/Dhg3Dzp07DSxtyeDrr7+Go6Mj/ve//8ks//bbb5GWlob9+xUvKOQpNj79vU9txYZT52+MXrFhoHDehiMrKwspKYrTZjk7Oys2i8wlPT0d6enpCuu4urqqFI+DQqGYIHnBlQwxQRYaxpQ1OjoaI0ZNxK4ls1GOKH4OFotrBcC9mnYEUwHG2hao1RR4FKFZhhSNhGDBNGyjlD8ywzCoUaMGatSogVGjeMVEbGwswsLC8PPPP+PVq1dwcnJCq1at4OPjgzp16oCVEfCr6cB+uHX4OO6fDOY/VLXEgI0/G0apAfAZJ3IyNTMLVwVrB4MrNQCAMbcEqjYBefMAyFROsSORSpGUkoozj6IxrH5HjWWIj49HSEgIzp49i/T0dPj4+GDYsGGoU6eObiamrCBfmTtn8QocOHCgSJXjx48jKSkJzs7GE3MiD0ZoBlKmMhD/XEsNMoBbFaNVagAAY+sE1G8PJCWAvHtdJH2tWCLFkfOXsfnwaVy9zwcRvXnzJpo2bWoAaVWEYQELG15pIxHlv0sIABACiUQKgYBFjkiEvX8ewK+bf8OTp88QOHwkKlQwPgsbRTAsC1SsCUHFmjj9MhWTZk6SWe/QoUNYv3497Oz041pakomIiMDevXvllg8ZMgSBgYHKN8gK1Qt6b6gMYCpSREqBQFCi048ePHiw2NgfoaGhaNeuXbFtrVmzBgsXKta4RkVFoWLFiipIyJOXZYYqRSgUE4BhAHNrIDtNv/2aWxkkUvXdu3cxbdo0bN++HR6VKiHx4Q3YfYoGwMBMqOwziwFAAPfqYMp7GWxljvXpBu7pLUBiCMUGA1hagWn2ldotuLu7Y8CAARgwYAAA3trvypUr2LdvHx49egRLS0s0b94cPj4+aNy4MczNzcEwDEbs+x2/ftUDURE3QaSajz1g/iy0HDZY43bUhmF415C0RN33ZWbJx/UwEvKUG/j4lp80SkTIv79yEYklMBMKkC0SY+fxEPy0cSdsHRwxZNxklb8zOI7DjRs3EBQUhIiICJQuXRr+/v747bffZKa21yUjRoyQqdgQiUT4888/MXHiRL3KoyyMrSNI2cqABjFSOI4DKxAA5aqDsbTVonS6gWEFQCl3MKXcQbLSAVEWvpswAQ8eP8HjqGgkJhdWzO3YscM0FBtAbppdC95yhpMCUjEYQnD27FnEJyTg9t172PPngUILq7t378ZPP/1kQKE1Y9CgQZgxYwZEoqJWOJmZmTh8+DBGjBhhAMlKFu/evVM4j6xUqRISElRMCc2q8b1lBIp8ZSjiirJ06VKsXr0aiYmJEApNQzujCvHx8Xj06JHCOo0bN1bq5fzq1Su8eqX4pdS6dWu1ItvnaaovX76MVq1aqXw8hUIxAOIcPn2kPmAF/CqRnl82Z8+exa+//oq9e/fCxYVP/TZ37lwc+2M3ts6agJb1auabFMsmd8JlZQemSgMwRhDFn7v9L8jZPw3SN9tnHJjqDXTWfmZmJq5fv45Lly7h1q1bIISgYcOG8PHxQaN69XFg9Hd4cCqEv45UjLnBgYBlWfRZtQRfTf9ORyNQEV27pLACwK6U0aa+I4QD0pJAMlKArFSIsrJw9do1PHr5GjcfPcPx0KtITf/Pbe7s2bPo3Llzse0mJyfj7NmzCA4Oxrt379C0aVMEBASgadOmBl2AkUqlqFSpEmJiYoqUNWzYELdv3zaAVMpDstJ45YYCFw1ZcByHh5EvUa5Ra7i6m9aqf0FWrVqFmTNlBzN2cHBAfHw8rPSVOloHTJ48GevXr5dZVrlyZTx//lymVZ2p0L9/fxw+fFhmWatWrXD58mU9S1TyYFkWCQkJKF1adiDdd+/eoVy5cpBKFVsM57uihB6Bva0arijpmXBq39foXVGKKDbyJtT//PMPOnbU3ESRoh5z587F5s2bkZCQoJRbDIVCMQII4VMQKpPmTRMYBrC01Xv6re3bt+PChQvYvn17vsJWKpWiYsWKePv2LQCgUY0qGNmtE9o1rotq5ctBUPCjzcKaz3xS2hOwczYa/2lCOHB/rgViXujPJYVhgZqNIeih/VgXihCLxbhz5w7CwsJw7do1ZGZkoCoRQvpvODiRCIQrXrnBgYAFgyRI8dyjFG5HvzaacwkAyErjA/ppG5bNVWqYliVlixYtEB4eLrPs66+/lmnxQAjBo0ePEBQUhEuXLsHGxga+vr7w8/MzuhT18+bNw+LFi2WW3blzBw0aNNCvQCpCOCmQFM9nS1HgzigSi2FuZoZ3iUn4efs+rNu9H8uXr1AtI4KRER8fj/Lly8udlP3xxx8qZyI0Ju7evYuGDRvKLb948SLatm2rR4m0S0hICPz9/eWWP3v2DNWr6zd2VkmDZVksWbIEtrayrbLS0tIwb9485RUb/x6Dva3q8Y5S0zPg1La36Sk2CCGoUaMGzMzMEBoaKldDRNEdV69eRZcuXTBgwABs3brV0OJQKBRVIIRPPamrLCkMA1jY6nXFmBCC+fPnIysrCytXriy0wnT27Fm52QecHOwR9fwZ/xIUmoERGG8EeJKRCm7PSiA1CdBi3AmZMCxQxgPsoOlgLAzr0sBxHJ48eYLQkDO49edhCJ68gDCbXz1mc61uGIaBWCwCC155EQcJHkGM15CAA/Dvv0YYAV+LlhsEACMQArbOJqfUAIDff/8d3377rcwyCwsLxMXFwdnZGZmZmfnpWF++fIk6deogICAArVu3hoWF8aalfPXqFapUqSKzbNKkSfj111/1LJF6EI4D0pP+U8yJcwBCIJJI8CjyJSLuPcLZy+E4dSEsfxJTq1YtPHz40LgUiyrSrVs3nD59WmZZp06dcO7cOT1LpF0aNWqEO3fuyCwLDAzE7t279SyR9pBKpahQoQLi4uJkls+aNQvLly/Xs1Qli4oVKyp1f0dFRSksz1dsXDquvmKjTU/TU2wAvIatffv2yMrKQq9evdCiRQvY2NiY9IPT2OE4DklJSTh79iz+/vtvtGjRAkFBQXI1dBQKxYghhP8oleTwftDaUkKwAt7qQY+WGiKRCGPGjEGTJk0wYcKEIuUDBgyQm31g4MCB+PNPw7h4qANJTQK3bw2Q+kl3lhsMC7iWAztwKh+81MjgOA63z4fi36N/IfLqdaR/SoallRXevE/Ai5RP+AApMj/LvmG0EfClYj6tpppKxrxYVxfDb+Grbj1Nxsf4c1JTU1G2bFlkZWXJLO/Xr19+toYOHTrA398fVatW1bOUmtG+fXtcvHixyH4XFxfExcWZtOXrtWvX0LJlS7nl4eHhaN68udxyY+fYsWPo06ePzDKGYRAVFQVPT089S6U9NmzYgEmTZAfZtLa2Rnx8vFFPFIvjxx9/lKu8KFeuHKKjo2m8QCMgX7Fx5ZT6io1W3UxTsQEAb968we+//44jR44gMjIScqpRtIhQKETz5s3Rv39/jBgxgio1KBQTJzM9De+io1ChQnkwgGYKDjNLPjCZHidXKSkpGDJkCEaOHIkePXoUKU9KSoKbm5vM4GEAcO7cOXTq1EnXYmoVkp4C7vAmIOGNbjqoWBNs7zFgLEzHb/zDhw+YPXs2tm/fLrPc2toaCQkJxhkBP8+CKjtDqaxFEokELMtCJBZj36Gj+HnTb0jLyMKbN29M+uM8MDBQbmT9KlWq4O7duyb9zbFnzx4MHTpUZtmRI0fkTpxNAUIIatWqhadPn8osHzNmDH777Tc9S6U9RCIR3N3dkZgoO/DvwoULMW/ePD1LpT0+fvyIcuXKyX1P/v777/lZrkyRyMhI1KhRQ255cHAw/Pz89CgRRRb5io1rweorNlr4m65ioyAcxyE7W08B8b5QGIaBpaUltYqhUEoQO3fuxPjx4zFu9Eh8N/ZbVKroCbFYDDMzFVwyhOZ8Slc9BxiLiYnB8OHDsWzZMjRr1kxmnU2bNsnNOlChQgVERUWZZGA0wklBrp8DuXSC90PQ1HqDYQGhEEyn/mDqtzbJ53xxH+c9evTAlClT0Lx5c+MM9kcIb8EhygIkYplxcKLfxiL85i2EXYvAvkNHkVwgg8GZM2fg6+urT4m1RkJCAn755ResXr1abp179+6hXr16epRKu2RkZMDNzQ1paUUzU/n7+yMoKMgAUmkPRUE27e3tER8fD2tr1QMCGgtTp07FunXrZJZVqlQJL168MMl3SR6Kgmy2bNkSV65c0bNE2sXHx0duoNC+ffvKHTuleC5cuICJEyciPDy8iEIhJSUFLVu2xJYtW4p1B81XbISHqK/Y8PYrGYoNCoVCoahOwZc9wzDo1KEdBvTtgxbNmqJG9WpyPtQY3uVEINS7hUYe9+7dw9SpU7Ft2zZUrlxZbr3GjRvLzTowb968YtNhGzskMQ6pf+2AbWIMJFIOQoFqH9YSjgPLMGCrNwT71ddgHAyfAUYT+vXrhyNHjsgsq1evHgYNGoTr168jJycHderUgY+PD1q1aqX3FKBKQQivsMr7BGJZtGrtg6tXr8qs3r9/f7kuV8YGx3G4efMmgoODcf36dbi6usLX1xc//vgjoqOjZR4zZcoUrF27Vs+SapfRo0dj27ZtRfazLIuYmBijC3qqCsUF2dy3bx8GDzZgumUNuX//PurXry+3/MKFC2jfvr0eJdIuZ86cUWi18OTJE3h5eelRIu2yY8cOjBw5UmaZmZkZ4uLiUKpUKT1LVTLo3r072rdvj6lTp8osX79+PUJDQ/HXX38pbCdfsXHjnPqKjaZfGb1iw3TVnxQKhWLEPH/+vNAKBiEE586HYuS4iajVuDn+vnydz2xiYfPfZmUHWNsDljaAmYVBlBp///03Zs2ahcOHDytUaty/f19hKsVhw4bpQDr9wpQqh3kPP8Dr5wNYf/UBUrILWCvICiJZYN+HjCysuHgHlVf9ib9tKpq8UgMARowYIbfs/v376NWrF44dO4aTJ09i0KBBeP36NcaPH48uXbpgwoQJOHjwoNwgc3qHKaBAFAgBhsXw4cPlVj9+/DiSkpL0KKBqJCcn49ChQxg2bBj8/f1x8uRJdO7cGadPn8aePXswePBguRMPgJ8Yy7PGMRXkXZ8cx2HPnj16lka7uLm5KZwY79ixQ4/SaJ969eqhcePGcsuNMoaPCnz11Vdwd3eXW75r1y79CaMD+vXrBxsb2ZNlsVhsUrG2jI179+7JDdAOAJ07d8atW7eUbo9hWTCsQI3NNFQG1GKDQqFQdMCcOXOwbNkymWVubm6Ijo6GMDfrhLGwc+dOnDt3Dtu3by/WnUCR6XD79u1x4cIFHUioX3JycuDu7o6PHz8CAMqVLYvXt8IhSIwFEt6AfErkg8QyDGBmDsa5DFDWEyhbAbVbt8fTZ88AlBxT3OIi4M+ePVvmNU8IwatXrxAWFoawsDDExcWhTJky8PHxgY+PD6pVq2YU7jmpqalwc3NDZmamzPINGzbIdb3SN4QQPH78GMHBwbh06RIsLS3RuXNn+Pv7y51AvXnzBpUqVZIbM+3o0aPo3bu3LsXWKYQQ1KxZE89y77uCVK9eHU+fPjWK60xd/vrrL4XnJyoqChUrVtSfQFpGkWujlZUV4uPj4eDgoGeptIcpfhOowvDhw+UqaBo0aCA3MwxFMZaWlnj48KHcgM4vXrxA3bp15QaHziPPYiP59gXYqxFPKTU9HY6NOlCLDQqFQvnSkEqlClO4DR061Kg+YPLSuT569Aj79u0rVqkhEomwb98+ueWKVr5NiVOnTuUrNQBg0DffwKycJ9h6LcF2HgjB199B8M0MCAZPh6D/d2A79QdbpznYUm4YVuA3OHHihNzAeKaEQCBAYGCg3PLdu3fLNJVnGAZVqlTBsGHDsH37doSEhGDFihWwt7fHxo0b4e/vj6+//hrr16/HnTt35Jrb6xp7e3v07dtXbrmhV42zsrIQHByMCRMmoEuXLti2bRsaNGiAI0eO4PDhwxg9erTCVWFPT0907NhRbrmhx6cpDMPItdqIjIzEtWvX9CyRdgkICFBozm/KaUMBPouWvLTCWVlZOHTokJ4l0i6KrBjj4+Nx9uxZ/QmjAxRZ9N29e5cqNtTE3d0dDx8+lFt+//59uLm5Kd8gI+CtFVXdGNMInk0VGxQKhaJlzp07h9jYWLnlxjTxF4lEGDVqFEqVKoU1a9YoFaDt9OnTcifqdnZ2Jp2BoCCfT/RUOW9DhgzJ/y1Lkimuot8gLi4Of//9t1LtlC1bFv369cP69esREhKCrVu3olq1ajh8+DC6d++Onj17YtmyZQgLC9Nr8HJFH+e3b9/GvXv39CYLALx+/RqbN29G7969MWDAAERGRmLKlCk4e/Ys1q5di6+++kruZFAWisYXHByM+Ph4bYhtMIYMGSI3e42pu2uYm5tjyJAhcst37twJjtNRmmo94OzsjJ49e8otN3XFW7Vq1eDj4yO33NTH17p1a4Vpok19fIbC398fP/30k8z3YFZWFubPn4+uXbsq36BAoP5mAlBXFAqFQtEyiiKgt2rVSm70cH2TkpKCwMBADB8+XOEH5ed07dpVbpaB0aNHY+vWrVqS0HDExsaiQoUK+ROF5s2bIzw8XKU2Cv5OJckUt3Xr1nKj+GvL7SY7OxsREREICwvDjRs3IJFIUL9+ffj4+KBly5Y6M4UlhKBq1ap49eqVzPLJkyfLdcHSBmKxGFevXkVQUBDu3r0LT09PBAQEoFOnTlpJx5qVlQU3NzekFMj4UpCVK1fihx9+0LgfQyLv+WRra4uEhAS5sQBMgQcPHijMXnP+/Hl06NBBjxJpl7///lth9qHHjx+jZs2aepRIu+zcuVOucrEkBNlcunQp5s6dK7PM2dkZcXFxKiliKcC7d+/QqFEjCAQCTJw4MT+17tOnT7Fp0yZIpVLcvn0bZcqUUdhOvivKg6uwt1PDFSUtHY51Wxq9KwoIhUKhULRGYmIiMTc3J8hNFPr5tm3bNkOLSAghJCYmhnTs2JGEh4erdFxcXBxhWVbu+K5evaojifXL8uXLC43rt99+U7mNI0eOFGrj9u3bOpBU/2zfvl3u+Tc3NyeJiYla71MsFpNbt26RtWvXkn79+pEuXbqQSZMmkcOHD5OEhASt9rV48WK543NxcSE5OTla7e/du3dk165dZMCAAcTf358sWbKE3Llzh3Acp9V+8hg7dqzc8dWoUUNn/eqLo0ePyh3frl27DC2exjRp0kTu+AYPHmxo8TRCIpEQDw8PueP7/vvvDS2iRqSlpREbGxu541u3bp2hRdSImJgYwjCM3PEdOnTI0CKaJK9fvyZ+fn6EZVnCMAxhGIawLEv8/PzIq1evlGojJSWFACDJD8MJ9+ahylvyw3ACgKSkpOh4tJpBLTYoFApFi2zYsAGTJk2SWWZtbY2EhATY2dnpWarC3L9/H1OmTMHvv/+OKlWqqHTsqlWrMHPmTJllXl5eePz4sUkH6AP4VXsvLy9ERkYC4IN3JSQkqBy4TiQSwd3dPd9t57vvvsP69eu1Lq++SUtLQ9myZeUG2Vy/fj2+++47ncpACEFkZGR+QNL379/D3d09PyBppUqV1L4OY2Ji4OnpKTfI5pEjRzRyt+I4Drdv30ZQUBDCw8Ph4uICPz8/+Pr66mW19saNG2jWrJnc8qtXr6JFixY6l0NXfH7fFaRt27a4ePGi/oXSIps3b8aECRNklqn7rDIm5s6di6VLl8osK1u2LGJiYowqRpWqjBgxQq5bRr169XD37l2Tfod26dJFbrwQPz8/BAcH61miksOnT5/w4sULEEJQrVo1lVKp51tsPI5Q32KjVjOjt9igMTYoFApFiyjyI+3Xr5/BlRrnzp3DzJkzcejQIZWVGoQQhX7qw4cPN+kPsjyuXr2ar9QAgD59+qg1UTA3N8fgwYPz//7jjz+Qk5OjFRkNiZ2dHfr37y+3XB+xDBiGQY0aNTBq1Cjs3r0bISEhWLBgAczNzbFmzRr4+/tj0KBB2Lx5Mx48eKBS7IHy5cujU6dOcsvVGV9KSgqOHDmCESNGwN/fH8eOHUOnTp1w6tQp7Nu3D4MHD9abCXqTJk1Qu3ZtueWm7gtvbm6Ob775RmbZv//+i5cvX+pZIu2iKMhmdnY2Dhw4oGeJtIuiIJsJCQk4c+aM/oTRAcWlzTZ1l0VF4zt79qzC+GMUxTg5OaFp06Zo1qyZSkqNwjAabMYPVWxQKBSKligu8rehg4bu2rULO3bswLFjx9SaRIWHh8tMpQjwGTMUBbYzJT6f2Cn6UCuOguc8KSkJJ0+eVLstY0LRtWyoCPgeHh4YOHAgNm/ejJCQEGzcuBHly5fH3r170bVrV/Tu3RurVq3CtWvXIBKJFLal6JyfOXNGbsrbPAghePLkCdasWYNu3bph1KhRSEpKwqJFi3DmzBksW7YMrVq1MsjKs6LsIQBw4MABZGRk6FEi7aPo+pSXktJUcHJyQq9eveSWm7piqmrVqmjTpo3cclMPAtuqVStUq1ZNbrmpn7/u3bvLnXRzHIc9e/boWSJKIVhG/c0EoK4oFAqFoiUmT54s19WgSpUqeP78uUEsGgghWLRoEVJTU7F69WqlMp/IYvTo0di2bZvMsq5du+LUqVOaiGkUZGRkoGzZskhPTwcAVKxYES9fvlT7NwOAxo0b4/bt2wBKjilunimsvNVvY3S7ycjIwPXr1xEWFoZbt26BEIJGjRrBx8cH3t7ehYJzZmdnw83NDcnJyTLbWr58OWbNmlVoX1ZWFi5evIjg4GBERkbCy8sL/v7+aNu2LSwtLXU5NJXJc92RSCQyy/fs2WPyisomTZrg1q1bRfaXL18eUVFRcrOnmALnzp1D586d5ZY/evQItWrV0qNE2mX37t1yLTeEQiHi4uLg6uqqX6G0yLJlyzBnzhyZZU5OToiLizO6Z4YqfPfdd9i4caPMsqpVqyIyMrJEWHeaEvmuKM9uq++KUqMRdUWhUCiUL4GcnBzs27dPbvmwYcMM8iIXi8UYPXo0nJyc8PPPP6s9Qc/IyMDBgwfllmti1WBMHDlyJF+pAQBDhw7VSKkBFP5tSoopLsMwClfFjdHtxsbGBh06dMD8+fNx8uRJHDt2DAEBAbh79y6GDRsGf39/TJ8+HcePH0d6ejoGDRokt62dO3eCEILo6Gj89ttv6NOnDwYMGICnT59i4sSJOHPmDH799Vf4+voa5QSldOnSClMEmvqqOCDfaiMmJgbnz5/XszTapUOHDihfvrzcclNf9e/bt6/cLEASiUThu9YUCAwMlPte+fTpk8lb9il6N7x48UJuVi2KHmAAMIwam6EFVw6q2KBQKBQtcOrUKSQlJcksYxgGQ4cO1bNEvIa+b9++CAgIkBvQVFmOHj2KtLQ0mWWlSpVCQECARu0bC59P6BT5eyvLwIEDYW5uDqBkmeIGBgbKVdaZgtuNmZkZmjVrhhkzZuDIkSM4ffo0RowYgYSEBEyZMkWhO01kZCS8vb2xaNEilC5dGjt37sSJEycwdepU1KhRwyRWIxVNPi5evCg35a2poCgWhalP/AUCgcJn0969eyEWi/UnkJaxsbHB119/Lbc8T7Foqnh4eCi0uDF1xWLDhg1Rv359ueWmPj6ThmHV30wA05CSQqFQjBxFH8pfffWVwtU1XRAbG4vevXtj9uzZCv2xlUXR+IYMGZI/cTdlXr58iUuXLuX/3aFDB1SsWFHjdp2dnQudA1P/KM+jfPnyCj/OTW3yyLIsateujbFjx2Lfvn24cuUKvLy85NavXbs2tm3bht69exu1aa48/Pz8UKZMGbnlph6LwtnZGT179pRZ9tdff+HTp0/6FUjLKFJsvHv3DiEhIfoTRgcoUrw9ePAg373PVFFk5fj3338jJiZGj9Jol+Is+g4dOlTIMpKiR6hig0KhUCiKiI2NVRipXd9uGg8ePMCQIUPw22+/wdvbW+P2Xr16pTBFoqGDomqLzydy2jxvBX+j58+flxhTXEXn3lTdbvLSsS5ZskRhvT179qBXr1745ZdfcOPGDbnxKowVMzMzhXE0du3aBalUqkeJtI+8ezgnJwf79+/XszTapXLlymjbtq3cclNTLH5Oy5YtUb16dbnlpr7q3717dzg7O8ssI4SYvGXf4MGDYWZmJrMsIyMDR44c0bNEFABquqHkbiYAVWxQKBSKhuzdu1duOklHR0f06NFDb7L8888/+OGHH3Do0CFUrVpVK20qWrlt3Lgx6tatq5V+DIlUKi00Tnt7e61YuuTRqVMneHh45P9t6pOOPHr06FEiIuCnpqbi2LFjGDlyJPz8/HDo0CG0a9cOFy5ckJu5RCqVwtfXF3Xq1MHJkyfRq1cv9OjRA4sXL8bFixeRlZWl51GojiLFVExMDC5cuKBHabRPx44dC913BSkJ96Ai5evp06fx/v17PUqjXYpb9f/zzz+RnZ2tR4m0i4WFRaF04J+za9cuk7bsK1WqFLp37y633NQVU6YKw7Bqb6aAaUhJoVAoRgohROELevDgwXoLHrh7925s27ZN7XSusvh8wv85JSVo6Pnz5/H27dv8vwcMGABra2uttS8QCArFWTl48GCJMMW1tLRUKsimsUEIwbNnz/DLL7+ge/fuGD58ON6/f4/58+fj7NmzWLFiBXx8fODm5oZu3brJbWf//v3o3LkzFi9ejFOnTuHQoUPo2LEjrl+/jsGDByMgIAAzZ87E6dOnjdL1oVatWmjevLncclOf/CuKRXHz5k08ePBAvwJpmT59+sDOzk5mWUkPspmcnIzjx4/rVyAtU1yQzcuXL+tRGu2jaHxhYWF4/vy5HqWhAKAWGxQKhUKRz9WrVxW+nPXhppGXzvXu3bv4448/YGVlpbW2L1y4INfX18LCAgMHDtRaX4bkc+WULhQ2BSdYJckUV9E1bkxuN9nZ2Th79iwmTZoEX19fbNy4EbVq1cKhQ4dw9OhRjB07FhUqVChynKJr4dKlS3jx4kX+3xYWFmjZsiVmzpyJY8eO4eTJkxg0aBBev36N8ePHw8/PDxMnTsTBgwcRFxenk3GqiqLzd+zYMaNUyKiColgUpq64KS7I5o4dO4xSsags5cqVQ5cuXeSWm/r5K+lBNn19feHm5ia33NTj+Jgm6sbXMA2VgWlISaFQKEaKog+PevXqoVGjRjrtXywWY8yYMbC3t8fatWshEAi02r6iD8devXrJdUMwJZKSkgqt/NWsWRPNmjXTej9Vq1ZFmzZt8v829Y/WPBo1aoR69erJLTfk5CMmJgb/+9//0LdvX/Tr1w8PHz7E+PHjcfbsWWzYsAFdunQp1qKqS5cuKFu2rNxyRR/nAoEA9evXx8SJE7F//34EBwdj6tSpyMrKwty5c+Hn54dhw4Zh+/bteP78uUEmoQMGDJD7G+Tk5ODAgQN6lki7VKlSpdB9V5C9e/dCJBLpWSLtokgx9ejRI9y8eVOP0mgfReM7d+4coqOj9SiN9lGkOD18+LDcbGSmgFAoRGBgoNzy3bt3m3wcH5ODBg+lUCgUiizS09Nx6NAhueXDhw/XadrH1NRU9OvXD76+vpgyZYrW2//06ROOHTsmt7ykBA3dv38/cnJy8v8eMWKEzs5bwY/YsLCwQqv9pkpxvvD6dLuRSCS4fPkyZs+eDV9fXyxYsAClSpXCjh07cOrUKUyfPh1eXl4qnV+hUKgwyKYqH+cMw6BKlSoYNmwYduzYgZCQECxfvhz29vbYsGED/P39MWDAAKxfvx537tzRy0e/g4MD+vTpI7fc1FfFAfmTx8TERAQFBelZGu3SokUL1KhRQ265qZ+/bt26leggm4MGDVIYZPPw4cN6lki7KHo3xMbG4ty5c3qUhlLSXVEYYso2ahQKhWJAdu3aJfelLRQKERcXB1dXV530HRsbi2HDhmHRokVo0aKFTvrYsmULxo8fL7OsfPnyiIqK0rqFiCFo0qQJbt26BYBfYX/79q3CFXpNyMjIQNmyZfMn+nPmzCk2+4YpkJiYiHLlykEsFsss37lzp0KXAE37PnPmDEJCQpCUlIQWLVogICAADRs2lOufrypPnjxBrVq15JafOXMGvr6+WukrOTkZV69eRVhYGO7fvw8zMzM0a9YMbdq0QdOmTWFhYaGVfgpy4cIFdOzYUW75gwcPUKdOHa33qy8+v+8K0rVrV5w6dcoAUmmPlStXYtasWTLLHBwcEB8fr1UXRX0zefJkrF+/XmZZ5cqV8fz5c63d64agX79+cl0TW7dujbCwMD1LpF1atWqFq1evyizr378/Dh48qGeJvjxSU1Ph4OCAlOgXsLeXHZdH8fFpcKhQFSkpKUad3tx0nwIUCoViYBSthHXv3l1nSo28dK6bN2/WmVIDUDy+oUOHlgilxoMHD/KVGgAQEBCgM6UGUNQnviSk1AT4CPiKgmxq0+2GEII7d+5gyZIl8Pf3x6RJk8BxHNauXYuQkBDMmzcPjRs31upEp2bNmgpTJ2tzVdzR0RH+/v5Yvnw5goKCsH//frRu3Rr//vsvvv76a3Tt2hVz5szBmTNnkJqaqpU+27Vrh4oVK8otN/VVf0WxKEJCQpCQkKBnibTLkCFD5F7vKSkpJTrI5qtXr0x+4q9ofJcvX0ZkZKQepdE+isZ3/PhxJCUl6VGaLxyWVX9TkU2bNqFixYqwtLRE8+bNERERobD+4cOH4eXlBUtLS9StWxfBwcGqj49QKBQKRWWeP39OAMjdTp06pZN+z58/T3x9fcn79+910n4eDx48UDi+Fy9e6LR/fTFlypRC4/rrr7903ufly5cL9RkSEqLzPvXB6dOnFV4zkZGRaredmppKjh07RkaOHEk6d+5MfvjhB/Lvv/8SkUikxREoZuvWrXLHZmFhQT5+/KgXOcRiMbl58yZZu3Yt6devH+nSpQuZPHkyOXLkCElISFC73fnz58sdn6urq15/a13w+X1XcFu1apWhxdOYgIAAueP76quvDC2exjRs2FDu+IYOHWpo8TRCLBYTNzc3ueObPXu2oUXUiJSUFGJtbS13fBs2bDC0iCWelJQUAoCkvI0iJDVR5S3lbRR/fEqKUv0dOHCAmJubkx07dpBHjx6R0aNHE0dHR/Lu3TuZ9a9cuUIEAgFZtWoVefz4MZk7dy4xMzMjDx48UGmcVLFBoVAoajBnzhy5L+myZcsSsVis9T737NlDvv76a5KRkaH1tj9n2rRpcsfXtm1bnfevD3JyckipUqX0PnnjOI5Ur149v9/+/fvrvE99UNzH+Y8//qhSe8+ePSO//PIL6d69O+nduzfZvHkzef36tY6kL56UlBRiZWUld3wbN240iFwcx5GnT5+S33//nQQGBpIuXbqQkSNHkl27dpFXr14RjuOUaicqKkqhYkofSj9d8vl9V3Dz8vJS+ncyVo4cOSL33DEMQ968eWNoETVi/fr1csdnbW1NUlNTDS2iRsyaNUvu+MqVK0ckEomhRdSIwMBAueNr1KiRocUr8eQrNuJeE5KepPKWEvdaJcVGs2bNyIQJE/L/lkqlpFy5cmT58uUy6/fv358EBAQU2te8eXMyZswYlcZJXVEoFApFRaRSKXbv3i23PDAwEEKhUGv9EUKwZMkS3Lp1C3/88Qesra211rYsxGIx9u7dK7e8pAQNPX36NBITE/P/HjJkiNwgbtrk82CbJcUUV9Mgmzk5Ofj7778xZcoUdO7cGevXr4eXlxcOHDiAo0ePYty4cfD09NSF6Ephb2+Pvn37yi03VJYbhmFQo0YNjBo1Crt370ZISAgWLFgAc3NzrF69GgEBARg8eDA2b96MBw8egOM4me1UrFgRHTp0kNuPqbujKApy+/TpU1y/fl3PEmmXbt26oVSpUjLLCCEK31mmwKBBg2Bubi6zLDMzU2Egb1NA0Xs1Li4Of//9tx6l0T6Ksr/cvn0b9+7d06M0Xy6p6RlITUtXfUvP4I9PTS20FQy8nodIJMKtW7fQqVOn/H0sy6JTp064du2aTLmuXbtWqD7ApwuWV18uKqlBKBQK5Qvm7du3ZPHixWTw4MEKVzafPHmitT5FIhH59ttvyS+//KK1Novjr7/+kjs2W1tbkp6erjdZdEnXrl0LjU1Vk0dNiI2NJSzLljhT3CdPnii8N86cOVOofkxMDPnf//5H+vbtS7p27UpWr15NHj16ZLSr5xcuXFA4vnv37hlaRJkkJiaSEydOkBkzZhA/Pz/Sq1cvsmrVKnLt2jWSk5OTX2/fvn1yxyYQCEh8fLwBR6E5n993BbfRo0cbWjyNmTx5stzzV6lSJSKVSg0tokb069dP7vhatmxpaPE0plWrVnLH169fP0OLpxEcx5HKlSvLHd/kyZMNLWKJJisri5QtW1bh+6u4zdbWtsi++fPnF+krNjaWACBXr14ttP/7778nzZo1kymfmZkZ+fPPPwvt27RpEyldurRK46SKDQqFQlGCCxcuEKFQWOyDv0WLFlrrMzU1lfTs2ZMcPnxYa20qQ7du3eSOb+TIkXqVRVfExcUVmuA0bdpU7zL4+/uXSFPcFi1ayL1++vbtS65cuUJ+/PFH4uvrS4YNG0YOHTpEkpOTDS22UkilUlKpUiW54+vSpQv59ddfSVRUlKFFVUh6ejo5f/48WbBgAenevTvp1q0bmTdvHjl16hSxt7eXO77Vq1cbWnSNKXjfFdzs7Oz04uanS+7evavw/RQaGmpoETUiODhY4fiePn1qaBE1Ytu2bXLHZm5uThITEw0tokYsXrxY7vhcXFwKKVkp2icrK4ukpKSovSUnJxfZl52dXaQfqtigUCgUI0YkEhFXV1elNNqbN2/WSp+xsbGkU6dO5MqVK1ppT1ni4+OJQCCQOz59y6MrVq5cqZPzpgqHDx8uJMPdu3f1LoMu+P333+VePwzDkJkzZ5KIiAiTXT1euHBhsc8BhmFMKiClSCQi4eHhZPXq1QoVNzVr1jRaaxpl+fy+K7jt2bPH0OJpTKNGjeSOb8iQIYYWTyMkEglxd3eXO76ZM2caWkSNSE1NVRhkc/369YYWUSOio6MJwzByx3fkyBFDi0jRAjk5OUQgEBSJyxQYGEi6d+8u85jy5cuTtWvXFto3b948Uq9ePZX6pjE2KBQKpRhevnyJDx8+KFV3x44dSE5O1qi/R48e4ZtvvsGmTZvQsmVLjdpSlX379smNg1CjRg2dppfVF4SQQvEQLC0tMXDgQL3L0a1bN7i4uOT/beoxDPLo168fLCwsZJYRQlCuXDlUq1ZNq+lY9cnQoUOLrUMIwaxZs0wmboOZmRmaN2+OGTNmYP/+/XLrPXnyBCdPntSjZNrn8/uuICXhHlQUy+DIkSNaSxFsCAQCAQIDA+WW79mzBxKJRI8SaRc7Ozv069dPbrmh4vhoi/LlyxeJo1AQUx8fhcfc3ByNGzfG+fPn8/dxHIfz58/L/YZs0aJFofoAcO7cOZW/OU3zq4JCoVD0yMePH5Wue/PmTWzevFntvi5cuIDp06fjwIEDqF69utrtqMPnE/7PGT58OBiG0aNEuiE8PBzPnj3L/7tXr15wdHTUuxwWFhYYPHhw/t/79u2DSCTSuxzaID09HSdOnMC3336L/v37o0qVKnLrTpkyBU5OTujQoQPu3LmjRym1w6lTp5S6DziOw7///qsHibRLs2bNULNmTbnls2bNgp+fHwIDA7F161Y8efIEhBA9SqgZn993BQkNDcWrV6/0LJF2GThwoNwgm1lZWRg4cCBmzpyJJ0+e6Fky7aAoyGZ8fLzJB9lUNL67d+/i7t27+hNGByhSvJ05cwZxcXF6lIaiK6ZNm4bff/8du3fvxpMnTzBu3DhkZGTkX9+BgYGYPXt2fv3JkyfjzJkz+Pnnn/H06VMsWLAAN2/exMSJE1XrWCX7DgqFQvkCefnypVJuKHmbukHM9u7dS/r37693P+/MzEzyxx9/kPnz58sdE8uyJDY2Vq9y6YpRo0YVGtvff/9tMFk+94k3JVPc58+fk3Xr1pHu3buTXr16kY0bN5JXr14RQggJDQ1V6l5xd3eXm9feGHn9+rVSsXbytilTphhaZLVYvXq13DHZ29uTjIwM8u7dO3L06FEyZcoU4ufnR/r27Ut+/vlnEhERoZN019pEUSyKefPmGVo8jenfv79S1+fu3bsNLapatG7dWu6Y+vTpY2jxNILjOFKlShW545s0aZKhRdSIrKws4ujoKHd88tKBUkyPDRs2kAoVKhBzc3PSrFkzEh4enl/Wtm1bMnTo0EL1Dx06RKpXr07Mzc1J7dq1SVBQkMp9MoSYkJqdQqFQDEBWVpZKKVb9/PwQHBysdH1CCJYtW4Z3795h7dq1EAgE6oipFvfv30eHDh2KtUrx9/dHUFCQnqTSHRkZGXBzc0NaWhoAoEKFCnj16pVef/PPadTYy+KkAAEAAElEQVSoUb7lQkBAAE6fPm0wWRQhEolw6dIlBAUF4dGjR6hatSoCAgLQvn37IvfH8+fPUbduXZmp4D5n8+bNGDdunK7E1irr1q3D1KlTla6/fPlyzJo1S4cS6YaEhAR4eHjIdUsbN24cmjZtit69e8PBwQEAkJaWhmvXriEsLAx3794Fy7Jo0qQJfHx80Lx5c1hZWelzCMVS8L4rSIUKFRAVFWWyrlIAEBISAn9//2LrWVpa4vXr1yhTpowepNIeO3fulLvyb2Zmhri4OLmpb02BJUuW4KeffpJZ5uzsjLi4OLnufqbAhAkT5Fq2Vq9eHU+fPi0R1qEU/WO6T20KhULRE1ZWViq5KowdO1bpuhKJBOPGjYOVlRV+/fVXvU6wOY5Dnz59lHK1UWQ+akocPXo0X6kB8PESDKnUAAqbHoeEhBiVKW5cXBy2bduG/v37o3fv3rh9+zZGjRqFs2fPYvPmzQgICCii1MjJyUH79u2VUmoAvBLEVLCxsVGpfrly5XQkiW4pW7YsAgIC5JZv2bIFI0aMgLu7O86ePQuAjw/QuXNnLF68GKdOncKhQ4fQoUMHhIeHY/DgwfD398fMmTMRFBSkcRwibSDP5D86OhoXLlzQszTaQyQSYc2aNUrVzc7OxoMHD3Qskfbp16+f3HtRLBZj3759hZ7zpsbQoUPlTuyTkpIwY8YM7Ny502TjpShyt4mMjMS1a9f0KA2lRKGRjQmFQqF8IZQvX14p094JEyYo3WZqairp1asXOXTokA4ll8+bN2+UNqkfMmQIkUgkBpFTUzIyMsizZ89IZmYmadeuXaFxvXz50tDikcTERGJubp4v04oVKwwmi0QiIVevXiVz5swhvr6+ZOjQoeTgwYPk06dPSrexZ88elVy3fvrpJ90NSMvExMQQOzs7pcdmSDcnTfnrr7+UGqOzs7NSaSglEgm5e/cu2bBhAxkwYADp0qULmTBhAjlw4IBB3Nw+v+8KboMGDdK7PNpi+/btKt1/Bw8eNLTIajF8+HC5Y8rLvNG+fXty69YtQ4uqFp07dy723Nna2pLz588bWlSV4TiO1KlTR+64SkpaeYr+oRYbFAqFogRCobDYOj/++CM2bNigVHvx8fHo3bs3pk2bpjAKui559+6d0nX37t2LI0eO6FAa3ZCcnIymTZuiRo0aKFOmDC5evJhf1q5dO1SuXNlwwuXi4uKCHj165P+9Y8cOvQZjTEpKwv79+xEYGIhu3brhzJkz6N69O4KDg7Fr1y70799fJYslVVdK3dzcVJTYcHh4eGDz5s1Km0mbqsUGIURpq4WkpCSlgsAKBALUr18fEydOxP79+xEcHIwpU6YgMzMTc+fOhZ+fH4YPH44dO3bg+fPnOr8HPr/vCnLs2DGjsCpRhzwLGmUx1WtU0ap/3rUTGhqKbt26qfSuMxaUsZJMT0/HgAEDkJKSogeJtAfDMArHt2fPHvTo0QPz589HfHy8HiWjmDpUsUGhUChKYGdnp7B87dq1WLp0qVITnkePHmHw4MHYuHEjWrdurS0RVaZs2bIq1T98+LCOJNEdly9fxuPHjwEUnXC7ubkhKSnJEGIVoeBHXmRkJDp06AAbGxvUrl0bb9++1WpfhBDcv38fy5cvR0BAAMaPH4/s7GysWrUKwcHBWLhwIZo1a6Z2jIE6deqoVN/UJlbffPMN9u/fDzMzs2LrmtrY8jh79qzSSloAarlPMQyDqlWr5iszQkJCsGzZMtjZ2WH9+vXw9/fHgAEDsH79ety9e1duvA9NkDe5ys7Oxtdff43Ro0fjzJkzJpX1RdUMT6akWCyIh4cHLC0ti60XFxdncu+uvNSYyvDhwwfcv39fxxJpn2+++UbugpFYLMbJkyexaNEiNGzY0KjcMylGjiHNRSgUCsVU2Lhxo1yzye3btyvdzoULF0jnzp2NIhOESCRSyWT58wjWpkBQUJDCMXl6ehpFtpdHjx4RW1tbmTJu3LhR4/bT09PJiRMnyJgxY4ivry+ZPn06uXDhAsnJydGC9EUZPHiw0tdVRESETmTQNWfPniVWVlYKzeE5jjO0mGoxdOhQlZ4NZ86c0Ykcnz59IkFBQWTWrFkkICCA9OzZkyxbtoyEhYWR7OxsjduXSCTE3d292PEtXbpUC6PRD7du3SICgUDpc6fvLFzaICcnh1SoUEHpMZpaJpHjx49/Ee5En7uGytsGDhxoaFEpJkLxttUUCoVCwYQJE3D48GH8+++/+fsYhsHatWuVDqz5559/4vjx4zh27JjKQQh1gZmZGUqXLo33798rVX/o0KE6lkj7FLca+ebNG1y6dAkDBgzQk0RFWblypcLMGeoGN3358iWCg4PzXQo6duyIH374QS/uN9u2bUNGRgaOHz9ebF1TXTHu3LkzLly4gHbt2skMlFqtWjWTjeyvShYoQHfn0NHREf7+/vkZPrKyshAREYGLFy9izZo1kEgkqF+/Ptq0aYMWLVrA3t5epfYFAgF8fHxw4MABhfXmzp2LsWPHwtnZWe2x6ItGjRph1apVmD59erF1raysVD7XxsCxY8cQHR2tdH1TG2Nx1+PnmFpWG4C3AL18+bJSde/evatbYSglBqrYoFAoFCW5ePEiTpw4gcOHD8PGxgYLFy5Uyp2DEIIVK1YgLi4O+/fvN3gWjoLY2dkppdiYOXMm2rdvrweJtEtxrgA2NjYGH1dxJv/KThpFIhHCwsIQHByMhw8fonLlyggICMAff/yh9w97S0tLHD58GGPGjMGOHTsU1jXFj/I8vL29cenSJbRu3RpisTh/v7m5Of78808DSqYZffv2xZYtW5Sury+XGysrK7Rt2xZt27YFwGeVunfvHsLCwrBjxw6kpaWhevXq8PHxgY+PD0qXLq2wvS1btig1iSSEIDIyEt7e3loZh66ZNm0a7OzsMHbsWHAcJ7eeqaYMVTUbiKm5hBmLYlFXSCQSzJw5ExKJRKn66enpOpaIUlJgCDEhx0EKhUIxMSQSCb777jtUrVoV06ZNM7oV3Bo1aiAyMlJhnaVLl2L27NlGJ7sycBwHc3Nzmf75jo6OOH36NFq1amUAyf5j0qRJCpUbERERaNq0qcyy+Ph4hISE4OzZs8jIyICPjw8CAgJQu3ZtozhfhBDMnDkTq1evllnu4OBgskEaC5KamorJkyfj2bNnqFq1KtasWVPspNrYmTJlCn799ddi6wkEAojFYqO53p49e4awsDBcvnwZ79+/h4eHR76io2LFivlyZmdno3z58khMTFSq7Tt37qBBgwY6lF77HD16FAMHDiykdCtIuXLlEBsbq2epNOfKlSsqxac6cuQI+vTpo0OJtEtISEi+lZIypKamFhsHzJiIjY2Fh4eH0vWbN2+O8PBwHUpEKSlQiw0KhUIhBOCk/MbvAMAADAuwAoBh+K0YOI7DoEGDsHnzZjg7OyM9PR1Dhw7F119/jf79++t0COqiyCWGYRhs2bIFY8aM0aNE2oVlWdjZ2RWZPLu5ueHs2bOoW7euYQQrwC+//ILU1FTs3r1bZnnB1UapVIqbN28iKCgIN27cQOnSpeHv74/ffvsNTk5O+hJZaRiGwapVq5CdnS1TeTNt2jQDSKV97O3tsXPnTkOLoVXWrl0LS0tLrFy5UmE9S0tLo1BqAPz15uXlBS8vL4wePRoA8PbtW4SFhWHVqlV4/fo1nJ2d0apVK9SvX19ppQZgeqviANCnTx+EhITA19dXpnJ34MCBBpBKc1q1aoXAwEDs2bNHqfqmdu78/Pwwbtw4paymLC0tTUqpAQBOTk5gWVahNVFBTM3ihmJADBngg0KhUAwGJyVElEVIZiohGcnFbCmEZKcTIhEToiAY4NmzZ4m1tTVp2LAhefXqFfnqq6/IpUuX9Dgo1dm0aZPcwIcHDhwwtHhawdnZudDYKlasSF69emVosQohlUrJ9OnTZZ6L9+/fkwMHDpDAwEDSpUsX8tNPP5Hw8HAikUgMLbZKrFmzhjg4OBCWZYm9vT1ZvXq1oUXSDxzHPztE2fwzR5RNiFik8FliTKxZs0ZhYD9nZ2dDi6gSiYmJ5MSJE2T69OnE0tJSqeCFAoGASKVSQ4uuNqdOnSJmZmaFxlS/fn2Te4YUJCsri/Tq1Uup8xcVFWVocVVGKpWSadOmFTs2BwcHQ4uqFlOnTlU6OOqECRMMLS7FRCjWFSUzMxMxMTHIyspSSWFCUQ2GYWBnZwdPT0+j8r+nUEocHAeIswCpcr6dRWBYwMwCEJgVseJo27YtLl26BIFAAHt7e1y5cgU1a9bUgtC6gxCCVq1a4dq1a/n7GIbB77//jpEjRxpQMu3Rvn17XLx4EQDg7OyMx48fG2VcB0IIVq1aVSiQKMMw6NevH3x9feHn52dyK49fLIQDRFmAKBuQinmrMFmwQv55YmENCIzXiHbnzp1ygyT37dvX5NJp5hEcHIyuXbsWm87VVF02CpKZmYnFixfj3bt38Pf3R9++fQ0tksZIJBKMHTsW27dvV1gvKytLqdSwxgYhBCtXrsTs2bPl1ildujTevXunR6m0Q0ZGBrp164bQ0NBi686bNw8LFy7Ug1QUU0euYuP69etYs2YNgoKCqFJDj5QpUwZ9+vTB3Llz6QcshaJNCAEkIkCcrZ32WCFgYcUrOgDExcWhSZMmiI+PB8AHuRs0aBC2bdumnf50zIEDB/DXX3/B3t4eS5YsMcqJvzKQXNNWhmXz92VlZWHixInIzMzE+vXr4erqaijx5JKZmYkLFy4gKCgI586dw8uXLwEANWvWxOPHjw0sHUVpOCmQnQ7kZIFfbFQBoTlgacsrOoyQjRs34rvvviu0z8nJCS9evDCJbCHyOHLkCAYPHgyRSCS3jr29Pfbs2YPWrVvDxcVFj9JRioMQgtmzZ8t1mbK1tUVaWpqepdIuv/32G8aNGyezLDAwUK4bo7GTnZ2NQYMG4a+//lJYb+HChZg3b56epKKYMjIVG5cuXYKfnx88PT0RGBgIb29v2NjYGI0PZUmE4zh8+vQJf//9N/bu3QsnJydcvHiRKjcoFG1ACJCTUSCGhhaxsAEEQkybNg1r164tVGRjY4MdO3YYbXwNU4cQAu7JPUiuh4F7/hjcq0ggJ1dxZWEJtlI1sNVrQ9jcB2zN+kb3DouKikJQUBDOnz8PAOjQoQP8/f1RpUoVhIaG4urVq5g2bRqsrKxAxCIg/ROvnAMDmFsCto5gjHiVXxnSP37Es9AwRN+8g9gHj5CVkgJWIISjRzlUaNQAFZs1RpWWzcGagiWjKAvITJFvnaEs5laAtX2+0tSYePbsGaZMmYKPHz+iefPmWLVqFaysrAwtlsacP38ePXv2lJt9wcPDAz/++CMuX76Mjx8/olKlSvkBScuXL69nabUPkUoAcQ5/7bIsYGZZSDlsCsgLdjtnzhwsWbLEABJpl59//hkzZswotM/V1RUvX740uRgbBVHG6mbXrl0mmW6eon+KKDakUinc3d1Rq1YtnD592uRyP5cEXr58iTZt2qBVq1Y4dOiQocWhUEwbQvgVVKJckCp1kAjM4VSqNLKyslCmTBk4ODigZcuW+Prrr+Hj42M0JrBEIuJN4wkAM3PAzMLoJvvKQAiBJDQE4mP7QGLfAAIBICMwHoD8MsbdE2a9B0PY3t9gYxaLxbh8+TKCgoLw4MEDVKpUCf7+/ujYsaPMIK4kKx0k7gXIu9dAdobsRm0cwLhVAeNWGYyRrvTLIvr2XfyzdhNuHTwGqVgMVigEJ5XmKwVYgQCEEBCOg6NHObSfOAY+Y4bD2tHRsILLghBeoSHSonUrwwJ2LkbtnlLSuHHjBtq3b4+MjKL3Wq9evXDs2DEA/PPnzZs3CAsLQ1hYGGJiYuDq6orWrVvDx8cHXl5eRv9cJYTwz5TUD0BmGu8u9TlmFoCNI2BfCoy5cbzDiuPnn3/G4sWLkZaWBmtra8ycORNz5841tFha4/Hjx5g+fTqSkpLQunVrLFu2zGRT9haEEILRo0fLVG5YWFggMzMTrIkp2iiGoYhiIzQ0FB06dMD169fRrFkzQ8n1xbNy5UosXLgQHz58UJi1gEKhKECXlhqFuiGYMH0mOn7VGR07doSjkUy+CCFA+ieQhCgg5UPRiZfQHLBzBlOmIuBU1ug/xgGA+5CAnA3LwD24xcc4UXZ1PLcuW7cRLCbOAVu6rG4FzSUhISE/HWt6ejpat24Nf39/1K1bV+7vTcQ54J7fBhJeAWCglEsDw4KpWAeMZ22jXmkVZWbi+JxFuPDrFrACATiJcrFuGJaFrWspBO7YhLr+vjqWUgUIATI+8avd2oZhcpUbZtpvmyKT+/fvo0mTJoXSowqFQrx48QKenp5yj3v//j0uX76MsLAwPHv2DLa2tmjRogV8fHzQoEEDCIXGo6Ai2RnA+zeqKeJsHADXCmCE5roTjPLFM3z4cOzevTs/5o25uTlOnDiBLl26GFgyiqlQRLGxYMECbN68Ge/evTOJj9ySyqNHj1CnTh2EhoaiXbt2hhaHQjFNRFm5pvv6gAGs7JRKC6sPSGYqyIvbvPuCwslxbpm5FZiqDcE4Gm9sDemzh8heOI13N1FXWcUKAAsLWM5bC4FXHe0KCN6tMC8da0REBFxdXeHn5wdfX1+l4hCQpARwj67kTpTVcGmwcQRb1weMtb3qx+qYj2+isa5TdyS+ep0fC0UVGJYF4Th0nDoBfdYsNY4VvIxk7VpqfA7DAval+OvWCCHiHOBTAkhGMpCVxt+XDMvHCrGxB+PkBsbCtCx/3759i2+//RaPHz+Gh4cHDhw4AA8PD5XaSEtLw7Vr13Dp0iXcvXsXAoEATZo0QZs2bdCsWTODuO8QQoCkOOBTgnoNMCxQ2hOMnenGU6EYP2/evMGBAwfg4uKCwYMHlwhXN4r+KKLYmDx5Mv755x88evTIUDJRAHz48AGlS5fGX3/9hZ49expaHArF9JBKeGsNfSIw47MbGBiS8Aok6n7uvFjFyXGZSmAq1wNjZP790hdPkD13IiAW8ZltNIFlAaEZLJdsgqCa5llrkpOT8ffffyM4OBgJCQlo0qQJAgIC0KxZM5WyXJHEt+AeXNIwRgMDCM3ANu4MxsZBg3a0S1J0DFZ6d0Tah0SlrTQU4TNmBAZtWWvYBRhRNm+toWuEFoCtk9EoTQGASMUgcS+ApHgUqzS1cwbj7gXG4sudoOTk5ODmzZsICwtDREQEcnJyULduXfj4+KBVq1Y6t/IjhADvonIV3RpSysOoFeCfQzhprsViNu+SKjDjXfiMUPmrMnlB0fMzLxH+OcEKeYtMI1WIUii6oohtHCGEphs1AvLOAafpBzyF8iVCCCDK1H+/UjG/GdB0nLyNBInWQDH9Lopfha3RzGis9khGOnKWztSOUgPg25CIkb3sB1hv3A/GxrZQcU5ODkaNGoU1a9bIzA5DCMHjx48RFBSEsLAwWFlZoXPnzli2bBnKlSunlkgkNVELSg0AIIBEDO72P2CbBxiFb7xEJMJG/75I+/ABnEQ7bmFh/9sBt1o10GGS7EwBOofjgMxk/fQlyeGtQoxAaQoAJCMF5PU9QCIjLkPhmvw/aZ9AnoUD5WuCcdKPC5ixYWFhgVatWqFVq1YA+Hh2Dx8+xKVLl7B3714kJyejatWqaNOmDXx8fLQfOP5DjHaUGgCQ+BZEIARjZ9zZYUhOJsj7aOBDdIH07v9ZLxIbBzClKwLOZcGYmgKAcLxVnyyLVEIATsSXsQLAzJLG6qF8Mah8pe/atQvDhw9HVFQUKlasqPRxCxYswMKFC4vNFQ4ADMNg/vz5WLBggariUSgUCv8Ro/EEUU3EOQZTbJCkeM2UGnkkxYHEPAFToZbmbWmBnJ3rQVI/aUepkQfHAanJyNmxHpbf/Zi/Oz09HZ06dcLt27fRokULjB8/HgCfjjU0NBTBwcF48eIFatWqhYCAAEyePFnj4G1EKgX36KpanidyWgTEOeCeRvBuKQZWUIUsXY24x0+1fk8e++En1PHvjNJVq2i1XaXITtfvMyYrlc+WYuBzSTKSQV7eUTEYMwEI4Z9NhAPjrJ7yzyAQAnCSXKVqAUsjVsgHYGaFap0TgUCA+vXro379+vjuu+9ACMHLly8RFhaGH3/8EQkJCShbtmx+5pWqVasqvI8jIiJw8eJFfP/990XqkYwUPkioNnkfDWJpB8bMOGNukA8xIK8fouhDtcDfGSkgUfeA+JdA9aamY1HESXODSSvx/OGkvOWqmaXRppFWBMlKB3lyE+TxdSA9BQABLG3A1GgEprY3GHvqFkUpDFXhKYDjOKxZswZbtmxBfHw8qlevjtmzZ2PgwIEqt3Xr1i3MmTMHV69eBSEELVq0wKpVq9CgQQPtC06hfOlIdBDIT1k4Kb/peQWIiHP4mBra4u0zEGc3MLZO2mtTDaQvn0F6Pkg3jXMcpBeCIPXvDUEVL3z8+BHt27fHo0ePwHEcduzYAUIIzp8/D47j0L59e0ydOhVVq1bVqhjkzUM+PoF2WwUSY4DEt4Cr4dJRJka9RsjSNTpRAnBSDgcmfo9JZ45pvW2FEALk6NkijBBAnM0rNwwEkYhzXdzUVzCSmKeAlR0YKxNIT5k3KZR17XISIEfCKzUsbDR+3jMMg6pVq6Jq1aoYPnw4ACA+Ph5hYWFYv349Xrx4AQcHB7Rq1Qo+Pj6oW7duIevqrVu3Yv/+/bh16xb27dsHMzNeuU44jg8Uqm0IB3x4A5Srpv22NYS8fwPyRgUFf3YGyJOrQK1WRmHhphCOU16pURBxbhp0E1FuEEJAboeC3DgHcLkuNnlkpoHcvQRy51+gZlOwbXqafNpzivbQ25Uwd+5czJo1S1/daYU5c+ZgxYoVGD16NJo2bYoTJ05g0KBBYBgGAwYMULqd27dvo3Xr1ihfvjzmz58PjuOwefNmtG3bFhEREahRo4YOR0GhfGFwnM6zoBSLRKT3CQiJe6GEabgqMCCvH4Kp46PFNlVHHHJMcTpXTREIIA45hoReQ9G+fXs8f/48v+jp06coU6YM9uzZA1tbWwWNqA+RSkBinumkbQDgop9AYEDFxqXfduisbU4iweOz/+DDy1dwrVJZZ/0UQZQFLZrXKE92hmEVG3GRstOCqtpO9GOguvG4usmEk/JWOcWRl07c0lbrymw3Nzf0798f/fv3B8DH8rl69SoOHDiAOXPmwNzcHM2aNYOPjw+uXbuGzMxMnDhxAq1bt8aZM2fg5OTEu59o4ZzJJDMVRJRtVMoAkpqomlKDPwoQi0AiI4DarY0uvlQ+eVne1H32iLN5lxQTcLsh14JB7l5SUCH3N3hyA1xmGli/QNNzJ6LoBL3dvUKhEJaWxvPwK47Y2Fj8/PPPmDBhArZu3YrRo0fj1KlT8PHxwffffw+pCh/ZP/30E6ysrHDt2jVMnz4d33//Pa5evQqO4/Djjz8W3wCFQlEeTvPAhBoj1a8MhJMCCVHQ7mSLAKmJIJnatiRQQYLMDEj/Pas7pQYASKWQXDyLBjWqFVJqAADLsnB0dNSZUgMA7wOuq4kHAKR8AElP1l37CpCIRAj7305wOjx/rECAS//bqbP2ZZK3+qlvpGLtumOpABFlq59No3BLvCIgPUkLbekIQnJXxVUgW45lhxZxdHSEv78/VqxYgaCgIPz5559o2bIlzp07h1evXgHg4wNFRESgcePGiIyMBFLe61QmpGjZxUVDSOzz4ivJPhLISgeSdfx7aQIn1chaCoBu0lJrGe75PcVKjc958xTk5nndCUQxKbSi2AgJCYGPjw9sbGxgZ2eHgICAIllVFixYUEQ7n5OTg6lTp8LV1RV2dnbo3r073r59K7OP2NhYjBgxAmXKlIGFhQVq166NHTsKrwRdvHgRDMPg0KFDWLp0KTw8PGBpaYmOHTvixYsXKo3pxIkTEIvF+f7VAG8qOG7cOLx9+xbXrl1Tuq2wsDB06tQJLi7/BVpyc3ND27Ztcfr0aaSnK7EqQKFQlEMTaw2G5c2Krez51K1maipjCadf//uUD8pNjt2rgWn4FZgWPcG27MWnkVQIA3yU/UzWB9yLJ0pbobC1G8LmrytFNqv/HSn2WEYqwT//24QtW7ZgwIABqFevHjw9PSEUCrF//35Nh6GYpDjwAe2Kh23YEaxPX7DtBoBt2QtMtSb8NVsMJCleQyHVI/b+Q2SlpChV19rREeOO78ey6MfYkPUey948Qo8lPxW7qs9JpXj8t54/ajWxjLKyB5zc+E2dFUZdKsEU8emza8jVE4xXCzD1OoCt3xGwcfyvzL4UmOrNwdRtD8arJeDsXqQ58jFWt/JqglSMIkpiSzvA2qHwVsj8nej93FhZWaFt27Zo3749zM0Lx7p48+YNfFq1UN5lys4FKF8LqNwQqFSfdzFRxjooI1l1wXUEyUpXHCC1bCUwdduCadwFTIOOYDyKWkuTdzpw29EWipQSrEC5bxepWHPliI4hdy6CadgO7KAZYMcth2D8SqDcfxZ5TOdBYIfOgWD8Sr4MALl/BUSrFqsUU0VjV5S9e/di6NCh8PX1xcqVK5GZmYktW7agdevWuHPnjsIAo6NGjcK+ffswaNAgtGzZEhcuXEBAQECReu/evYO3tzcYhsHEiRPh6uqKkJAQjBw5EqmpqZgyZUqh+itWrADLspgxYwZSUlKwatUqDB48GNevX1d6XHfu3IGNjQ1q1iycCrBZs2b55a1bt1aqrZycHJl5mK2trSESifDw4UN4e3srLRuFQlGAJhYbFtb8RFGcnRtN3AJ5gRhVhnAAoyfTyPRkFIz2LhdGwK+6OrsBljZKNExA0j4pOe3WPtKXz/jUrEqsUnNvo5D987z8v4XN2kDo0wlc5OPiO2JZ1LQyQ/3BwzF27FgAvI9vXFycStZ56kBSEqGspQ1J+wS8e81n9KtQE2z5GuAyU0FiIxUcxQBpH7Uhqsq8uXWXj0GghJLPysEeZWvWwOWtu5D2IRFdZk+D35zvkZLwHhc3/k/hsfGPnkIiEkForodAhpqsmgot+GcMIeoHAZWKDeInX8Tqh2WB1ETAwbXwBNjcCkzFuoAoByQuEoyzG9jyXuBEmYUnnenJIIQYnzsKUfC856SFyz5XootFfIpNPXPq1ClIpVJ4eHjAyckJzZs3R48ePdC2aUMgTQkrG6E5mDIVecu/xBg+OKN9KRDXCkBsMW5yEhEIJzUKNwDyIRry3oOMe3Uw5aqCpCeDJLwCWAEYWUG+0z6CZGeAUer9qEcIp+DbJjfOC5D77SJU/O0iMcwzRBnIuxggMQ6oWAvk9VMwlWsDnwcIJQB5ehNM4w7/7RNlg7y4D8arsX4FphgdGik20tPTMWnSJIwaNQpbt27N3z906FDUqFEDy5YtK7S/IPfu3cO+ffswfvx4bNq0CQAwYcIEDB48GPfv3y9Ud86cOZBKpXjw4EG+1cPYsWMxcOBALFiwAGPGjCmkOMjOzsbdu3fzNdhOTk6YPHkyHj58iDp16ig1tvj4eJQpU6bISzcvBVdcXJxS7QBAjRo1EB4eDqlUmh/sSSQS5StaYmONeOWCQjE1ODUtJdhc31OJ+L8UagIzfjKirmID+vnYI5m50cKL4+1TEACMnbOSig0AGcqtuOsCEpv3oaoEKcmQXv5v5d7865EAAPHxP4s/lmFAYt98touBu3vRlWZtQvIDwSlZ/8VtfuIkNAdTugJg44DizzsBSUvWREy1SXjyDAKhEFJx8Stpn97GYkHNJvxvAsDMwgL9f12J8g3qFnssJ5Eg8dVrlPWqrrHMxXempqKLYfnzlZ3OKwLUDXanY0WbXD4Pbvsuin+WWDsUUmwwLu5gGBZcYjTwMRYkJwtMlYZgSpUHKajYkOY+Z41ugkXkK65IMVYZRKqZ0kpNvvnmG/Tt2xeNGjUqlKGJJL8DlPEkZBg+YyEn/e8825dSfpFAlK38+0SXZMh5D7IsUKYSH88oMiJXScDJf3JmphrHeAqiSLkvEPDXXN63CyMBhGb8u0LWt4uhY5ApgLx9zl+PN/8BADBlPYsoNsi5P/nnZ0HFBsMAMZEAVWx88WjkinLu3DkkJydj4MCBSExMzN8EAgGaN2+O0NBQuccGBwcDACZNmlRo/+fWF4QQHD16FN26dQMhpFA/vr6+SElJwe3bhTMBDB8+vJBZno8PH/wuzwdRGbKysmSm8MuLE5KVlaV0W+PHj0dkZCRGjhyJx48f4+HDhwgMDER8fLzKbVEoFB3B5j4OC33U5n2kqvGhqs/YgrqM6WHAmCVElAN1fkhBk1ZgPTwhfXgb3MunxR/Akdy+9IwaH5isdzcIWvYA41IOXEIUSNxLJfoxzDkUZ2VD2fPHSaX5Sg2GYVAnwBcA8OSfi0odL8rUc5YSVbFxUD4gpUIMlMZa2WvIwpr/V5QbhyQvHkne/kJtGuEES9HPywp4FxQre8DcGjLfCwZIM96wYUO0aNGi6DersvFYxDnAh2hAIATjWQdMaU+QnExAWbcMA8V9KYI8VwQrOzACAcBxYOr4gG3cBUz99oBTGdn19RwjSzkUXFd51xwr4BWoeUpTYw2CqoicLPXkJgQkh86lKBpabOQFWuvQoYPMcnt7e7nHvnnzBizLokqVwvnnP88Q8uHDByQnJ2Pr1q1yrT/evy8c7KdChQqF/nZy4tMVfvqkwPfuM6ysrJCTU/RDNzs7O79cWcaOHYuYmBisXr0au3fvBgA0adIEP/zwA5YuXarTwHQUCuULQJcfMAb8OGIEAqijVDLrwWetUspaA7ldGCJdnBq/LfcwDIy5JZgKNfkJyIcY4EOM1vvRBqyZEKqeP6G5OYbu/h9qde6AC79uwc0DxcdIAQCBmQyzcmPB3Iq3/EpPyp185P4mrCB3UmggZYUqMCxvkaDVNo3MDQWQf7lKRLlKb5JrNWXG/1/02WTKmIak7O/LCgCnsrwVw4fXvDuRsxtI6QpAghILgsZyHgVyLCRzJ/6MmTlI7HNwOZlgKtYBU7kByN0LRa1wjMCtpigKfuM8FykzCz6+BiEFLIeUcFE1JvLuK5VhADP9u4FRjA+NvuS4XC3t3r17UbZs2aKNCzX/UMzr45tvvsHQoUNl1qlXr16hvwVyHm5EBU26m5sbQkNDi/iA5llZlCtXTum2AGDp0qWYMWMGHj16BAcHB9StWzc/I0r16nown6VQvhSU9OkvQt6qU6FJYF5barSnz489K1sgWc1xK9O2gWBKlVF5osBWrgFBnUbgoqMgvaVkkGeGAVuqtOoCagrL8pOkPNcnZUh+n381snV8wLpVBlecYsPKTm0RNcHFs4JKGVGsHBww7vifqN7OB6cXLMfphcuVPta5goc6IqqOOkqiPGWGnUvh/XYuvLJDFVc31kCKRgsbICu1+Hp5wSrzUoDmBTH8PIglw6ofnFmnyJkMSgqcI0J4N8UiE2A1rft0hbLxPqzswJhZ8HFU0j8BTDIfh6lgQFhFGMuE0sIayEhFkXOXk5n/LU/iX/IKqrKVwFjbg1hYAZmfKTYsDJdSWS7FfU+Is/lrlGH569PSVr7S1IgtOZhS7vmWe6odCDAuqs3LKCUTjTQPedYWpUuXRqdOnVQ61tPTExzH4eXLl4WsNJ49KxyoKC9jilQqVbkPTWjQoAG2bduGJ0+eoFatWvn78+JiNGjQQOU2nZycCgUc/eeff+Dh4QEvLy+N5aVQKLmwAkCqxouRk/ArHwIh/0GYNxlRN7WjHld9GBtH5RS39i78B0/uhyjjVBbE0gZ4L8fkmGEAWyctSqoabJUaKscUMOs5EAAgPqlCNhOpFGwV/T+HGYbhfdmTlIjZ5OwGpkzF3PSKDBgPXiFebCpXhgFj76K4jo6o0LiB0h+pFjY2mHH5LNzr1MLDkHNIeBqJJl/3Qdr7D3gWqjj1n0vFCrBycNCGyMXD5lkRqaBEFGUXNm+3tufbyUxRPcOKrICH+sDGITf+Qu64bRz5iaSQl4exLwViYc1nO3EtD6ZUBRCOgHHh45KRxM+yK1nZGV/gUIB/5gnNCysyGJZX1Egl/KQxT2HwucuCmblBrRcyMjJw69YthIeH48aNG7A2F2LXwhnFHyjO4d8f1naFg8F+bo0iC1YAxgABU2XBlPKQnQFKKgE+xgKlPMCU9+JdFixt+RTGWZ+5hllYK6/Q0Sd5biby4r+YWfCKjLzrl2Hknz+hEVu3VfTiF1McXcE4lgKs+FgnjKcX4OAC8uQGmKr1CimfmJpNQTLTwNRqaiipKUaERmo7X19f2NvbY9myZRDLCA724YP8/NZ+fn4AgPXr1xfav27dukJ/CwQC9OnTB0ePHsXDhw9V6kMTevToATMzM2zevDl/HyEEv/32G9zd3dGyZUuN2j948CBu3LiBKVOmgDXUCgyFUhLRRKGQk8krN8wseQWHOEe9wKEMq98PXIfSUGalkCntCbZqIzCWvBUG414NbNVG8g8gBIxTUWs8fcFWq1V8pQIwpcpA0KI9uKRESP49q9O+tAXjqNy5gzgHjK0jmKqNwFRrBLACcK8fgUTdV3wcIWAcXbUiq6p4Nm4AVqjc/WhbygXudfhzUMfvK4w6sBOjDuxEwLyZCo9jhUJUbdNKY1mVhmFUnxhwEl5BmrflKSHFOapnWDGQYoN/DvynzOGzndQEkxs7gyntCbZ8TUCUBfL6AUCkYNyrA0JzcG+f8pYpBdtzdtOn+Krx+USdEH7oZhb8pJ9hc98N2YqP0yGEEDx//hx79+7FhAkT4Ofnh8DAQFy5cgVNmzbFjh07sGvfn8pdL6IsXrktFgEuHoCtE0hGinJuKAayBpOJfSm5KWpJ9GNeuebiDqZcVT77SeSNIvcfU6aicSrcAMWBdhmWH3tBCylZgW5ZgZG62vAwrABM3RZgajYF274vGAdeKc82bAu2fV++jrcf2La9849h2/cF28IfjLURXYsUg6GRxYa9vT22bNmCIUOGoFGjRhgwYABcXV0RHR2NoKAgtGrVChs3bpR5bIMGDTBw4EBs3rwZKSkpaNmyJc6fP48XL14UqbtixQqEhoaiefPmGD16NGrVqoWkpCTcvn0b//zzD5KSkmT0oBkeHh6YMmUKVq9eDbFYjKZNm+L48eMICwvDH3/8IdfdRRaXLl3CokWL0LlzZ7i4uCA8PBw7d+5Ely5dMHnyZK3LTqF80Wjy0iYckKN8lgqdyKAGjLkFSCl3IDEWilaSyYvbfGYNZbGw5lfwDATr4gq2bmNwj+4oFaCOJL5DZr+2KnbCgq3dwDCuKAAYt8ogr+4VXzEtCdyNENU7sLDm/ecNgJWDAxr16YHbR0+Akyi2vPn4JhpjGflxueTBSSRoNWKIuiKqh6ruQ5+TquaCDMMabFLCWNuDWNnnW22QmCcgMU9kV05NBElNlN8YKwQcDacwLRY2d5KYv+JNAFExwWnzFB46IiUlBREREQgPD8ft27eRk5ODatWqwdvbGzNmzEDFirIn5MTBVTmLsLSP6qWFNuD74XMYhgHKVgKJlpHiWyopXgnMCgAX3WbC0giBGQA5VhiiLPllBREaWxaiojAN2oI7sRXS0MMy3Wu5fSsLVGYBazuw/b7To4QUY0bjIBiDBg1CuXLlsGLFCqxevRo5OTlwd3eHj48Phg8frvDYHTt2wNXVFX/88QeOHz+ODh06ICgoCOXLly9Ur0yZMoiIiMCiRYtw7NgxbN68GS4uLqhduzZWrlwpp3XNWbFiBZycnPC///0Pu3btQrVq1bBv3z4MGjRIpXbc3d0hEAiwevVqpKWloVKlSliyZAmmTZumlTgkFAqlAMWZbOoDA5jmMu7VQRK1mzqaKV/T4KtXZgF9kfPglu464DiY+ffVXfvFwFhYAaXL8wFAdRAjhSlfw6DnsO2Eb3Hz4DGdtM2wLFyrVkY1fVpsALyySOPsJmpgaWNQVwemvBe/yq1pOx5euYGBjRihOX8/irMhlUplLmbl7ze30uozXyqV4vHjxwgPD0d4eDji4+Ph4OCAZs2aoVOnTvj+++/zM/QVi30pICkeOgkgmRes0pgo7QmkJQGfElQ+lKnWGIwxu2kwDP/s+TxejbIIhIYJkq0ijNAMbNcR4EL2AHGvIJFyEAoKKw2lHAeWZcHYO4HtNopaa1DyYchnjtmTJk3CxYsXcf9+MZpNik5JSkqCi4sLjh49it69exd/AIVC+Q9ZZsL6gmH5OBYGmICQmKfyV1FVggEcS4Op2cLgig0ilSJ75rfgop5rPz0kKwBbqSosV/5u0IkWyc4AF35Ky+Nj+JWsZv5gDGh6zHEc5jRujeT7j9ULClcME4OPoI5fZ623Wyzpn/T/jHEoY7jgobmQDzEgcZHqN+DkZhQKU6XhpPjfpg0YPKA/bG1s8nenpafjj4OHMXbCdxpb0bx//x7Xr19HeHg47t+/D0IIateuDW9vbzRv3lzlYPWfQz4l8DEmtI17dTDGptgAQDgpb50hK95GERg+DlHVhmAc5aR/NTYkIuXinxSEFfJKEVO578Cfx8v7tkJy5xLaVCuc7fJh3Ae8si6Lnt8vAGMswWspRoHxq+4oFApFVYTmhlNsCA0YQM69Om9OnPy++LpyYQALKzBVGxvF5IMRCGAx+SdkTZWdFUuzxgGLyT8ZfPWYsbQBU70JyNPrWmyVgK3V0qBKjbdv32LKlCmo36U9sl69QU56htaUG4xAAO8hAwyj1AD4AHd6esYQQgBLGzBGEI+LcS0PEA4kvqjbcLE4lQVT3ssonitKwwowcdr3mD57LmrX9IKdnS3S0tLx8PETcByHsd9NUak5kUiE+/fv51tjfPz4Ea6urvD29kbfvn2xYMECmGk7dbFjGV4Rp+5KvywcShulUgPg4zSgcgPAvhQkcS8gEGVBLJFAKBCAYRhI855BBBC4eoBxq2JaK/4Fg4MSArFYXOSa4TgODMPw95rQgreuMaX7Dvx5jBSbY9S6A/B0tkcFZ3sIGBYJqel4+i4JU6dORS+q1KB8hkzFhippUU2NrKwspKSkKKzj7OwMc/Pib5b09HSkpys2R3V1dVUpHkceJfkcUCg6h2H4IFr6Vm4wrEHcUP7rngW8vEGeRahligsAsLIBU6s1GHPj8cVly1eE+bfTIdqiXddD89HTwJavpNU21YVxqwJkpGrJ4gZgarU0WDYUQgh27NiBI0eO4JdffkHNmjXxqF17bOraD4RonpaYFQhQrk5N9P9Vd66oxSIw4y2z9OCSkpKegbHjpmL1mjVFXHUNAVPaE7C252MZiLPB5ZqFf07+flYAxsMLcCxjWkqNAmRkZCDiZmGXOGXcQd6+fZuvxHjy5AmEQiHq168Pb29vDBw4EC4uur9HGYYBcasKvH1WONuLulg7AKX0lF5ZTRiGAVzL43HsR4wbOQFDAjqgXCkXWFtZ4FNqOm4+eY7H71Jw+szfhhZVPQRmgKUQd27dxOuXkeju71dorvHi5SuE37qDwOEjTU6hIYs3Sal4k6REumnKF08RxYaNjQ3S0tIMIYteOHjwYLGxP0JDQ9GuXbti21qzZg0WLlyosE5UVBQqVqyogoQ8qan8DWxra6vysRQKBbyCQSrWvvuCIozA1JNhBYCXN/DuNZ+dQKnx56avLFcVTPlaBrdgkIVZ5+5AdiZEOzfwv7GGk2PzYRNh5ttTO8JpAYZhgKoNAYEA5HXRDGBKtsKbVddqAbZMRW2KpzSvX7/G5MmT0bZtW5w+fTr/Y7u2byeMOfoHtvYdAsJx4FRM45sHw7Jwr1cbk/8+ASt71YONahVLWz6VKycpvq4GOJbzxIKFC/Htt9+iV69eGD16tMEVBIytE+DVAkj5gIjgo6hX1RPWBSb6YrEE956/Qr02nWFR1hOMCfj2a0pWVlZ+utWIiAikp6fDw8MD3t7eGDFiBLy8vAyWBY8RmoF41ADiX2hmuWHnDJT2NPj1pzQMg2sPnuDag6IK49atWxtAIC3CMEj4kIjeA76BmZkZnJwcYW5mjk/JycjIyMDXX3+NwBGjDC0lhaJXirxp6tWrhxUrVuD169dqTciNHV9fX5w7d05hnfr16yvVVmBgYLEPxrJl1Yv8/e+//4JhGNSpU0et4ymULx6GAcytgWw9KWrNLI0mjVpedHg4uwHvXiP7zRNY5H5PS3InlAKWBcMwEEmlMHevBqZsJTDWBp4oFoNZ9wFgSpVBzqYVQHamUplSCsGygKU1LMbPhLBVB90IqQEMw4CpXB/EqSy4x1dVmIDkKqbsXcDWamGQ88hxHLZs2YKQkBCsXbsW1apVK1Knfnd/zIoIxY5vRiPh8VOVLBNZgQAcx6H9d2PQc9l8mFtba1N89WAYfqKX9lF3ClRrR0BoDi8vL5w+fRobNmxAjx49sG7dOlSuXFk3fSoJw7KAUxkM/HElYmJiUNnDDXbW1sgWifAyJg5iiQRJSUmwLKFKDY7jsG/fPoSHh+Ply5ewtrZG48aN4e3tjW+//Rb2hla8fQav3PACkt+pHnODFfAKDVsn3QhH0QixWIz379XMtkShlCCKvG26du0KS0tLrF+/Hr/88oshZNIpbm5ucHPTTv70ypUr6+TDIjs7G7/99htat26tcdAoCuWLhmX1Yy4uNDeoC4o8GHNLoLwXDodGYNGPM9HYqwrKlXIGy7L4mJKKO5FRaNulK9ZvMFxWEFURtmwPQa36yNm2DtKrF/jJZXEKDpYFCIGgRTtYjJoKxtFZP8KqCeNUBqx3N5B3r0FingEZyQAAkUSSn9yAYRiYCXMVaU5lwHrUAEq5G2Ql9fnz55gyZQoCAgJw8uRJhavS5RvUw5zbYTi/dhP++WUj0t5/ACMQgMiw4CAABEIBOIkUVVp5o/uSn1DNp6UOR6IGrACwc9GNcsPGkc+4kYtAIMCUKVPQrVs3TJo0Cb6+vpgwYYLBrAAKQgjByxgl0oqWIKRSKViWxbRp01CpUiWTsGJgGAZwKgti5wykJIKkfACTa3EkFktAQMAyzH8Z+8wsAcfSgJ2zQeP1UCgUijIUUWzY2dlh4cKFmDlzJjIzMzFmzBg0aNDAJB7Ypo5YLMaFCxewYsUK3Lt3DyEhIYYWiUIxfVhBrnIjAzpJeWcigblexibgZWzRuBs+JhjPh3F0huWMReA+jIfk7AkkhvwFu4xUsJ+dA44QpFnboZR/bwh9e4B1Vc+CzhAwAiGYclVB3Kpg0ewf8DA8DA2qesLBxhoc4ZCYnIbbz6PwzbjJGNCho0FklEqlWLduHcLCwrBp0yalrTyF5ubwnTkVnaZNxL2TwfhzxRpE37wNR7BgwZ/DHBB8gBTfTJqAtqOGwa1mDR2ORENYAZ9WMzNV9WwF8tqzcZSrLK1SpQpOnjyJrVu3omvXrli3bh2qV6+ueb8UALwlxpMnT/JjY0jluE2ZmZlh0KBBepZOOzBCc8ClHHKsnVCvlhca16mJyuXdYSYUIisnB09eRCGLY3Au9KKhRaVQKBSlkWkf+MMPP0AoFGLp0qX43//+BwsLC9jY2FDlhg7hOA6pqamQSqWoUqUKTp8+rVScDwqFogSsgM9ikJOlRX94PnsIBEac976Ew7qWhfk3Y7Dn7ScsnjsHte2t4WAmBAMgWSzBo9RMzFm0GD9+M8bQoqoNwzD4mJmDI/9ex5F/i2ZN6WugoT1+/BjTpk1D//798ddff6n1fSAwM0OjPj0Q/OQBfr55md8HXv2YZ4Ozc9Y0uLq6ak1uncGw/1lYZKaob71haQNY2hWrKGVZFmPHjoW/vz8mT56Mli1bYurUqf+ttFOUJjExMT/d6r1798BxHGrWrAlvb2/Mnz8fu3btgkSi2zgqBoNh8Px1NJ6/ji5SpKxbNoVCoRgLct+A06ZNw3fffYfQ0FA8ffoUmZlaTBNFKQLDMLC3t4e3tze1kKFQdAHD8sE9pWI+4J8m1hsCM34CQ+9ToyFTyuHGJ91nqPjSEYvFWL16NW7fvo3t27fD3d1dq+3rMdSvbjCzAOxdAYkIyMkAxHwWCo7jCk2OWZb9TwnBCgALG/6ZoqJbSYUKFXDs2DHs3r0bAQEB+Pnnn2lsLgWIxeIi6VZdXFzg7e2Nnj17Yt68edpPt0qhUCgUvaBQtW9mZobOnTujc2cD5YmnUCgUbcIwvHm3wIxXcEhE+SurYrEYAoGgkL+6SCSGmZkwV9HI/BdLwwh82ikUfXP37l18//33GDZsGGbPnk0V8PJgGF7BYWYBEIKx344CEYtQuaInLC0tIBZL8DEpCXcePMSWrdtQqXIVDbtjMGzYMHTu3BmTJ09GvXr1MGvWLDpBBxAbG5uvxHj8+DEEAkF+utWvv/4apUqVMrSIFAqFQtES1GaRQqF8eTAFlBQch7t3buPEX8dQv24dODrYQ2hmhoyMTLyKigIHBhO+m8RbfNCJHOULJCcnB0uXLsWLFy+wb98+lClTxtAimQ4Mg8iXUQgNDZVZzGkxxE25cuVw6NAhHDhwAP7+/li1ahUaNmyovQ6MnOzsbNy+fTs/3Wpqairc3d3h7e2NYcOGwcvLKz/9MIVCoVBKHlSxQaFQvmxYFomfkrFg6XKZxb169cKEyVP1LBSFYhzcuHEDs2fPxtixY7Fo0SJDi0MpBoZhMHDgQHTs2BFTp05FpUqV8NNPP8HCwsLQomkVQgiioqLyrTFevHgBS0tLNGrUCN7e3hg5ciQcHBwMLSaFQqFQ9AhVbFAoFAqFQilEVlYWFixYgHfv3uHgwYNwcXExtEgUFShdujT++OMPHDt2DP7+/li2bBmaN29uaLHUJi0tDTdu3EB4eDhu3bqFrKwsVK5cGd7e3pg0aRKqVKlCXaMoFArlC4cqNigUCoVCoeRz5coV/PTTT5g6dSq6detmaHEoGtC7d2+0a9cO06dPx+HDh7Fo0SJYW1sbWiyFcByHp0+f5ltjxMTEwN7eHk2bNkWbNm0wZcoUox8DhUKhUPQPVWxQKBQKhUJBRkYGfvzxR2RlZeHYsWNwdHQ0tEgULeDs7IydO3ciKCgIXbt2xYIFC9CmTRtDi5XPx48fERERgWvXruHu3bvgOA5eXl7w9vbGvHnz4OHhYWgRKRQKhWICUMUGhUKhUChfOBcuXMCSJUswe/ZsfPXVV4YWh6IDAgIC0Lp1a/zwww84fPgwli9fDltbW73KIJFI8ODBg3xrjMTERDg7O6N58+bo3r075s6dC3Nzc73KRKFQKJSSAVVsUCgUCoXyhZKamoqZM2dCKBTixIkTsLOzM7RIFB3i4OCA//3vf/jnn3/QvXt3/Pjjj+jUqZPO+ktISMDFixcRHh6OR48egWVZ1K1bF97e3li9ejVKly6ts74pFAqF8mVBFRsUCoVCoXyBhISEYPXq1Zg/fz7atm1raHEoeqRTp07w9vbGjz/+iEOHDmH16tU6ySKydOlStG3bFt988w1q1apF061SKBQKRWdQxQaFQqFQKF8QSUlJmDFjBpycnHD69GkaiPELxdbWFuvXr0dYWBh69eqF6dOnIyAgQKljCSF4/fo1wsPDkZSUJLfehg0b4OTkpC2RKRQKhUKRC1VsUCgUCoXyhXD8+HFs2LABS5cuhbe3t6HFoRgBPj4+OH36NObPn4/Dhw/jl19+gbOzc6E66enpuHnzJsLDw3Hz5k1kZWWhYsWK8Pb2hp2dHdLT0w0kPYVCoVAoPFSxQaFQKBRKCefDhw+YOnUqPD09ERQUBEtLS0OLRDEirK2tsXr1aly/fh19+/ZFz549YW9vj/DwcERHR8PW1hZNmzZFq1atMGnSpEJWPnPnzjWg5BQKhUKh8FDFBoVCoVAoJRRCCA4dOoRt27Zh5cqVaNSokaFFohgZnz59wvXr1xEeHo47d+7AwsICf/75J4RCIdavX4+GDRuCYRhDi0mhUCgUikKoYoNCoVAolBJIfHw8pkyZgtq1ayMoKIim0aRAIpHg4cOH+elW379/DycnJzRv3hz+/v6YPXs2LCwsAAB37tzBDz/8gOHDh2PgwIFUuUGhUCgUo4YqNigUCoVCKUEQQrBnzx78+eefWLNmDerWrWtokSgGIiEhId8a4+HDh2AYBnXq1IG3tzdWrlyJMmXKyD22YcOGCA4OxqpVq9C/f3+sW7cO7u7uepSeQqFQKBTloYoNCoVCoVBKCDExMZg8eTK8vb0RFBQEoZC+5r8UcnJycPfuXYSHh+P69etISUlBmTJl4O3tjYEDB6J27doqp1s1MzPDnDlz8OjRI4wYMQIDBgzAsGHDqPUGhUKhUIwO+sVDoVAoFIqJQwjB77//juPHj2Pt2rWoUaOGoUWi6BBCCKKjo/NdSiIjI2Fubo6GDRvC29sbgYGBWk2zmufOtG7dOvTu3Rvr1q2Dp6en1tqnUCgUCkVTqGKDQqFQKBQT5tWrV5gyZQo6deqEU6dOqbwqTzF+MjIy8tOt3rhxA5mZmfD09IS3tzfGjh2L6tWr69yKQigUYsaMGejevTvGjx+Prl27YsyYMTrtk0KhUCgUZaGKDQqFQqFQTJRz587h2LFjWLduHSpXrmxocShagBCC58+fIzw8HNeuXcPr169ha2uLJk2awNvbGxMmTICtra3B5KtevTpOnTqFzZs3o3v37pBIJAaThUKhUCiUPKhig0KhUCgUE0UoFOL48eNgWdbQolDUJDk5GREREfnpVkUiEapXrw5vb2/MmjULFSpUMLqYFizLYuLEiQgICEDt2rUNLQ6FQqFQKFSxQaFQKBSKqdK+fXuq1DBhRo0aBTc3NzRv3hy+vr6YOXNmfrpVU6BSpUpwdXVFdHS0oUWhUCgUyhcOVWxQKBQKhUKh6ID3798jMTFRbvm2bdtQpUoVPUpEoVAoFErJhCo2KBQKhUIxYqRSqaFFoCiBSCQqlG7106dPKF26NHJycgwtGoVCoVAoJR6q2KBQKBQKxUi5ffs2Tp06ZWgxKJ9BCMHbt2/z060+e/YMQqEQDRo0gLe3N7755hs4OzsDADp06IDIyEgDS2wYVqxYgcWLF8Pc3NzQolAoFAqlhEMVGxQK5YuHECK3jEb8pxiCnJwcLFq0CG/evIGvry+2bdtmaJG+aDIzM3Hr1q38dKsZGRkoX748vL29MXr0aFSvXp3GOpGBl5cX/P39sXLlSjRu3NjQ4lAoFAqlBEMVGxQK5YuFEILVq1dj+fLlcuucPn0avr6+2Lt3L0qXLq1H6ShfKtevX8ePP/6IiRMnYunSpZg0aZKhRfqiIITgxYsX+dYYUVFRsLa2zk+3Om7cOIOmWzUlevbsia5du2L69Olwd3fH/PnzYWlpaWixKBQKhVICoYoNCoXyxfLrr79i5syZCusQQvD333+jXbt2uH//PoRC+tik6IbMzEzMmzcPnz59wuHDh/NdGSi6JSUlJT/d6u3btyESiVC1alW0aNEC33//PTw9PdVKt8pxHLZt24YHDx7IrbNmzRrMmjULnp6emgzBqHF1dcWePXtw4sQJBAQEYPHixWjZsqWhxaJQKBRKCYN+oVMolC+WrVu3Kl33yZMnuHLlCtq2batDiSjqwHGcWmXGxKVLl7BgwQJ8//338PPzM7Q4JRapVIonT57kW2PExcXBwcEBzZo1Q6dOnfD9999rxaKA4zgMHToU+/btU1jvt99+w6lTpxAaGopq1app3K8x06NHD7Rp0wbff/89Dh8+jCVLlsDGxsbQYlEoFAqlhEAVGxQK5YuE4zi8efNGpWOioqKoYsOIkEgkmD59OrZv3y63zvLly/H+/Xv88ssvRmltk56ejtmzZ0MikeD48eOwt7c3tEglig8fPuD69esIDw/H/fv3QQhBrVq14O3tjUWLFqFcuXI66ffmzZvFKjXyiI2NxerVq1VStJoqTk5O2LZtG86ePYtu3bph3rx5aNeunaHFolAoFEoJwPi+8igUCkUPsCyLJk2a4NKlS0of07RpUx1KRFGVMWPGYMeOHQrrZGZmYsOGDUhPTy+2rr75559/sGzZMsyZMwcdO3YsUi6VSrF48WL88ccfcttYsmQJCCEYPny4LkXVGR8/fsTDhw/llkdERMDX11cppZRIJML9+/fz060mJSWhVKlS8Pb2Rp8+fTB//nyYmZlpU3y5qPJcUae+qePr64sWLVpg9uzZOHz4MFasWAE7OztDi/VFkZmZiYMHD8otj42NRXBwMPz8/NRyxaJQKBR9QxUbFArli2XUqFFKTyi8vb1Rq1YtHUukfc6fP4/ffvtNbnlQUBCaNm2KwMBAk/p4TU1Nxd69e5Wuv2/fPqxduxYODg46lEo5UlJS8MMPP8DS0hInT56UG4hy5MiR2L17t8K2Xr58iREjRiA9PR3fffedLsTVGeHh4ejSpQtSUlLk1unatSu6dOmCY8eOwcrKqlBZwXSrT58+hVAoRP369eHt7Y2BAwfCxcVF10OQS/Xq1XVavyRgb2+PTZs2ITQ0FD169MDMmTPh6+traLG+CNLS0tC1a1eF77/ExEQEBARg4sSJ+PXXX2nWHwqFYvTQpxSFQvliGThwoNJ+7QsWLDCpiT8AHDlyBL6+vrh27ZrcOq9fv8awYcPw008/6VEyzYmOjoZYLFa6vlgsRnR0tA4lUo7Tp0+jd+/eGDJkCH799Ve5So24uLhilRoFWblypcK0xcYGx3Ho27evQqVGHmfOnMHy5ctx+fJlrFmzBv3794e/vz8WLVqE1NRUjBgxAidPnsTx48excOFC+Pn5GVSpAQBt27ZVya2oe/fuOpRGNxBC8O+//yI5OVlunTNnzkAkEilsp3379jh16hTOnDmDUaNG4dOnT1qWlPI5W7ZsUVqpv3HjRly5ckXHElEoFIrmUMUGhUL5YhEKhUpN6L29vdG5c2c9SKRd5syZA6lUqlTdFStWICkpSccSaQ8vLy9YW1srXd/Kygo1a9bUoUSK+fjxI4YNG4awsDCcPn0arVu3Vlj//v37KrUfGxuLDx8+aCKiXnn48CFiY2OVrr9p0yZcunQJjRo1wvbt2xEcHIytW7dixIgRqFWrltGtJjs4OGDKlClK1fX09ERgYKBuBdIyhBBMmzYN7dq1Q2pqqtx6gwYNQs+ePZGVlaWwPRsbG6xduxYjRoxAnz59cPLkSW2LTCnAuXPnVKr/999/60gS3aJI2SuRSPQoifb5P3v3HdfE+ccB/PNcBnsLCIhbcdU9cNXRWjfWvbVaR9171PFz1L3qqtu21tXWvbCtWq21Cu4B7omiMpQ9QpJ7fn8coAgJSUhyiTzv14tXa3K5+x4XkrvvfZ/vk5qaiosXL2p8/tGjRxaRzGcYc7KsMwGGYRgz69mzJ/z8/LQuY43VGrGxsbh//77Oy6vVaoSEhJgwIuOSSqXo37+/zsv369dPtOah+/btQ7du3TB8+HAsXrw415CKvFSrVk2vbfj4+MDT09PQEM2uaNGiei3fpEkTTJs2Dc2bN7eaXgxjx47VqWpj+vTpkMvlZojIeP766y+sXLlSp2WPHz+ONWvW6LRsgwYNEBwcjAsXLqBfv36IjY0tQJSMJsWKFdNreX9/fxNFYjpbtmzROsNUSEgImjRpYpUX/9HR0ahfvz5mz56tcZnLly+jfPnyOHLkiPkCYxiRscQGwzCFmlQqxaRJkzQ+7+fnZ5XVGh4eHnqX44tZ0WCIb7/9VqdmkDKZDN9++60ZIsopKioKvXr1wo0bNxAcHIy6devq/FofHx+9ZuDp0aOHVSTfeJ5HeHg4jhw5giJFiuj8OmucAtfNzS3fqg0/Pz+9EnSWIjg42GTL29raYuHChRg9ejR69OiBPXv2iDLMKiMjAzt37tRY9aZUKrFr1y69hsRZCn3+njiOw+eff27CaIxv586dGDx4MF6/fq11ubNnz6Jx48ZISkoyU2TGMWrUKJ2q+hQKhc5D/izNo0ePcPz4cY3Pnz9/HlevXjVjRIw1YIkNhmEKvREjRmgc1jBz5kyruGD8ECEEX375pc7LV61aFSVLljRZPKbg7++PQYMG5bvcwIEDUaJECTNEJKCUYteuXejbty8mT56MuXPnwsbGRu/1aLsb9z47OztMnjxZ7/WbQ2xsLI4dO4aZM2eiQ4cO6NChA7Zt2wY3NzcsXrxYp3X4+/tb3VCNLGPHjtWafJs4caLVVWsA0DtpakjPk9q1ayM4OBjh4eHo2bNnvhepxpSWloYvv/wSffr00ZhUUavV6N27Nzp37oz09HSzxWYMnTt3RkBAgE7L9unTB6VLlzZxRMalz9TJERER+PPPP00YjXGpVCq9EoUZGRlWN5QoJCQEtWrVwr59+zQuExoainr16mmd2YcphCjDMAxDr1y5Qm1tbSmA7J9BgwaJHVaBPHr0iEokkhz7pOln3759YodrkIiICK37KJFI6NOnT80Wz4sXL2iXLl3o/PnzaUZGRoHX16RJk3yP3fjx440QecFlZGTQK1eu0LVr19I+ffrQ1q1b0z59+tC1a9fSy5cv5/p98DxPq1evnu/+rV+/XqQ9Mo527drluV82NjZUoVCIHZ5Bzp07p9PnStbP2rVrC7S969ev0xYtWtBffvmF8jxvpL3QbMOGDXrt39atW00ek7Ht3Lkz3/3iOI7ev39f7FD15u/vr9fxW7x4sdgh64zneerl5aXX/h0/flzssPVSrVo1nffN0dGRpqenix0yYyFYYoNhGCaTWq2mu3fvposXL6aRkZFih2MUAwcOzPfEoGrVqlStVosdqsFatmypcd+++OILs8TA8zzdunUrbdmyJQ0LCzPaek+fPq312Mnlcvrq1SujbU8fkZGRdN++fXTSpEm0bdu2NCgoiM6YMYMePXqUxsTE6LSOgwcPat0/Pz8/qz9pTU5OpkWKFMm1b7t37xY7NIPxPE8bN26s04WHt7c3TUlJKfA2lUolXbhwIe3UqRN9/vy5EfZCs44dO+p14ditWzeTxmMKKpWKli9fXut+9evXT+wwDdKpUye9jt/ff/8tdsh66dq1q877ZmNjQ9+8eSN2yDp7/fq1XsfOGo8fYzosscEwDPMRe/ToEeU4TutJgbVWa2QJCwvTuG83b940+fafPn1KO3ToQJctW0ZVKpXR11+6dGmN+9e1a1ejby8vaWlp9L///qPLly+n3bt3p23atKGDBg2iW7ZsoWFhYQbvN8/z1M/PT+P+rVy50sh7Io6UlBQ6evRoWq1aNdqqVSt68eJFsUMqsFOnTul00bFixQqjbvf27du0VatWdPPmzSar3hg5cqReF1bjxo0zSRym9ssvv2jdL2us1qCU0uDgYJ2PXbly5ahSqRQ7ZL1cunRJ5/0bNWqU2OHqJSMjg9rY2Oj193fv3j2xw2YsBKHUiia+ZxiGYfTWsmVLjWNsvb298fLlS4ubLlNfq1evxtixY7PHwxNCsGLFCp2n3DQEz/PYsGEDjh07hpUrV6JcuXIm2c4vv/yiscHk06dPjd4/hFKKJ0+eICQkBCEhIXj06BFsbW1Rs2ZNBAYGok6dOjrN9qGrlStXYty4cbkel8vlSExMNKg/CWN6lFI0adIE//77r8ZlvLy88OTJE72mZtaFWq3G6tWrcebMGaxcuRKlSpUy6voPHz6MDh066Lx8cHCwVTa4VavVcHFxQUpKSq7nqlWrhuvXr5s/KCOglCIwMFDrdKhZfvnlF/Tt29cMURlX+/btcfToUa3L2NjY4NGjR/nO/GZpWrdujT/++EOnZUuUKIHHjx9b/TkMYxwsscEwDJPlw49DK2wampewsDB88skneT63cOFCTJ061cwRmcbbt2+xceNGUErxzTffwN3d3WTbevjwIcaOHYvWrVtj2LBhJj+p6tatG/bs2ZPjsWXLlmHChAkFXndSUhIuXbqEkJAQXLlyBWlpaShdujQCAwNRv359lC5d2qQNdHmeR7Vq1RAWFpbj8Y0bN2LIkCEm2y5TcH///Tc+++wzjc8vWrQIU6ZMMdn2s/4OW7VqheHDhxvt75DnedSoUUOnmSdq1qyJy5cvW2WTaQD49ddf0bNnzxyPyeVyhIWFmSxZaw7Hjx9HmzZttC5Trlw53L59W7SpwAvi8uXLqFOnjtZlRo0ahdWrV5spIuM5d+4cGjdurNOymzZtwuDBg00cEWMtWGKDYZjCi/KAWiX88Grh3zkQgJMAEgnASYX/t9KT1xEjRmDdunU5HqtVqxYuXbpktSfkYnj/TvGqVavMOpPMqVOnsHnzZjg4OGDixIkGTc/L8zzu3buHCxcuICQkBM+fP4ezszPq1KmDwMBA1KxZ0+h313WhVqsxa9YsHDlyBO7u7pgxY4bWC2bGMlBK4evrm+eMJTKZDPHx8SZ/P/E8j40bN+Lo0aNGrZzav38/OnfunO9yhw8fRvv27Y2yTbH89ddfmD59Ol6+fIkqVapg7dq1Vp3UAIT3ZtWqVXMlTN9nrdUaWerXr4+QkJA8n+M4DhEREVZXrZGlRYsWOHnypNZlSpQogfv371vlzFKMabDEBsMwhY9aBagyALVSv9cRDpDZABKZVSY49u3bh1WrViEtLQ3du3fH+PHjWfmmHu7cuYPx48ejc+fO+Prrr60iIfT27VuEhoYiJCQEN27cgEqlQoUKFRAYGIjAwEAUK1ZM7BA/XpQKnzEqpfBftQrCkHAifJZIZcJniVQOWPHf4dGjRxEUFJRrWtTZs2dj1qxZZovj2bNnGDNmDBo3boyxY8dCIpEUaH26VG1Ye7XGx05bcsrFxQWxsbFWWa2R5ezZs2jSpEmezzVv3hynTp0yc0TGo0vVBqvWYD6kMbGhUqnwzz//YN++fXjw4IHVzdFtjZycnFCrVi1069YNVapUYV+UDGNslAcy0jIvMAqCADb2gMR6T4g+Vu/32DAWlUqFpUuX4vLly1i1apXFJgNUKhVu3bqV3RsjNjYW7u7uqFevHgIDA1G1alV2Z8sceDWgSBV+clWBaSCzBWwdrDZpun//fkyYMAEvX76Eq6srJkyYgMmTJ5s9DkopfvrpJ/z+++9Yvnw5KleuXKD15Ve18TFUa3zMKKXw9PTEmzdvcj03Y8YMfPfddyJEZVy1a9fGlStXcjwmk8lw+/ZtlC1bVqSojKNq1aq4detWns+5uroiKiqKfacxOeSZ2EhMTESrVq1w4cIFlCxZErVr14adnR270DYhSini4+Nx9uxZJCQkYOTIkVi9ejX7nTOMsaiUQlIDRixSk8gAuZ1VXoh8DCjPQ33jMtSXz0N9Lxz84/tAeprwpK0duNLlIClfGZI6DSGpVhskn7viDx48gK2tLfz9/bMfu3nzJiZOnIh+/fqhd+/eFvWZ/OrVq+wkRnh4OCQSCT755BMEBgaiXr168PT0FDvEwoVSID0FSE8yfB1SOWDvwpKmBRQZGYmxY8eievXqmDx5MmQymUHr4Xkebm5uSExMzPWcm5sb3rx5Y1GfCUxuDx8+RI0aNZCcnJz9WPv27XH48GERozIepVKJTp064cSJE1CpVChZsiR2796db/8Na3DkyBEEBQXl+dzEiROxdOlSM0fEWLpciQ1KKZo1a4YbN25g3759aNasGfvQNqOMjAxs3LgRo0ePxqxZszB79myxQ2IY66dUAEoTVZ1xEsDGgSU3zIiqVVAG74fywG7Q15FCDxS1Ou+FM58jRf0g69gTsjadQPK4aMxqYCmXy3Hp0iWoVCosWLAA9+7dw/fff4+iRYuaeK/yRtNTQGOeQx0fA0XsK/AZ6cjIUOJtcipeJKaBc/GEV6WaCKhcpcCl9+ZGKcWjcxdw63Awnl68gpc3w6BISQXhODh7e6JkvTooGVgHdXp1hXNRb7HD1U6tBFLijVANlsnehSVNC4hSit27d+Onn37C0qVLUb16dYPW8/vvv6N79+45HiOEYN++fejYsaMRIhUPVSqAtGRAkSJ8T1IqDIuS2wlViXZOeX5eWhue57F//37cu3cP3bp1s/r+IYVJYGAgQkNDczzm4+ODp0+fsmoNJpdciY2s7vn79++3+g9sazZmzBj8+uuvePnypdWdrDKMRTFlUiMLkQhl5BZ6EUKT44HEWNCU+MzyeAAyGxBHV8DJHXAuYjUJbPWzR1AsnSVUZ4BA9wocYVmudHnYTJoDSYkyOZ7dtGlT9gwjAwcORHh4OIYOHYquXbsaM3ydUErx6l4YVE9uwkdOAQpQUEg+rDghJPtChBQtDVKyCoitg9nj1RelFJd2/o4/FyxD1N374KRS8KrcCQEikQj7RwhqdA5Cu+9mwqtcmTzWKDJVBpD0FkatBgOEhKmdk8V+rliLqKgojB8/HmXKlMH06dMNmj748OHDmDp1KiIjI1GsWDEsXrwY7dq1M0G05kFTEoD4KCA1IfMRDZ+lhABOHoCrN4iN+ZsKM4xKpcLIkSNx4MABqFQqNG7cGNu2bYOLi4vYoTEWKFdi47vvvsPy5csRHR3NMmEiCg0NRWBgIM6ePavzlEcMw3xArRLuRJkDJxXucFnIRQilFHgTCRp5H0jRdPKa+W+5HYhPGcCnTL7DNcSk+vck0pfMFHaB11ChkR9OAhDAdvJ3kDb+HIAw3WmVKlUQEREBALCzs8P58+cNvsOrr+TkZFy+fFlo8HntKr6sURad6lQSwtX1/USEhpSkXC0Q37IWm6iKj3yJnYNH4c4fJ98lZnTASSUgnAQdFs5G0zGmn15XZyolkPQGRk9qZLF1AOycTbNuI6FqFZCaCKQnC3+XhMuM2wlEpn8SwVT27duHdevWYeHChahbt67Y4YiCqpVAdASQ/Fb/F7v7Au4+IMRC/vYYhmE+kCuxMWjQINy8eRMXL14UKyYGQEpKChwdHbFjxw707t1b7HAYxvpQCqQlwWQXHHmR2wlj5EVGM9JAH14T7sjpw84JpFxtoZLDwqj+PYn0RdMzD2dBj6lw0W8zZR5kTVpg6NCh2LJlC3j+XaPHevXq4cKFC0ZPEPA8j/v372f3xoiIiICjoyPq1KmDhvXqoo5NCriUuIJtpGgpcBUCLS5J9TLsNlY3b4fUuHjwmoYO6aBWj87ot20jJAb2TTAaygMJMbo3CDWUg6vw2WJhaGoSaMwzID4a7/4mP0ieOrqDeBYHcfYQIcLc3rx5gwkTJsDLywtz5syBnZ3wex07dixq166NPn36iByh6VBFKhB5r2DDpWzsAb8AqxyeQikFKLW4z8UCo/TdjEuZFW7gJMIPwxQyuRIb/fr1w9OnT3H27FmxYmIgnPxKJBJs3boVAwcOFDschrE+ilT9p3M1Bjsn4Y6lSGhaEmjYv4AyA/onAAhACEiFeiBu4vSUyIv68X2kjekPqHkYL1FFAI5D5KgZqNahMxQKBSQSCZydnWFra4vU1FT89ddfBb6z+/btW1y8eBEhISG4fv06VCoVAgICcky3SggBVavAXz0BJMXBKPtYtDS4ioEWU7kR8+gxltVrjrSExAIlNQAAhKB2z67ov32TuPuXEp/ZkNjECAGcPS3mQoXyPGjUYyD6GXQeDubiBVKsAohU5GRUpqNHj2LFihWYO3cuZDIZ2rVrBwcHB4SHh8PBwfKHc+mLKtKAF3cMr3R7n9wOKFbBKpIbVJEGGhMBxDwXhowBwt+TgwuIV0nAraj1Jjp4tbBPWfv1IU4CSG2ERsQW8j3AMKam96fSzz//jAEDBuDJkycoWbKkzq+bPXs25syZk2ue87wQQljjTIZhDMerxUlqAEJPD5HurtKM9AIkNYCsOz70bihQpRGIk/h3WalKBcXSWUaq1MixZgCA7ebv0bBeXTRu1hyVKlVCqVKlULx4cY1TBGqjUqkQFhaWXY0RHR0NNzc31KtXD23atMG3336rcXw//+Cq8ZIaAPD6MairF4iv+D0p1CoVfuw+AGmJRkhqAACluLzrd5Rv2ggNBvUv+PoMoVSYJ6kBCHdhUxMBRzfzbE9bKLwa9MkNIDmrqkjH92tCNGhaElC2JojM1mTx6apdu3Zo1KgRJk6ciH379iE+Ph7x8fGYOnUq1qxZk3NhSgFeldmgmAIgQlNizjouGCnPA68eGCepAQjv++ingI/lTiVKlQrQp7cyq4k+fJICyfGgydeFmc38ygFeJSwmCZwvSoW+YZoSGll4NZCRKtxosXEQmsJaIZqeAvrgBpAUL1TH2TuBlK0K4iT+5yFjeSw/3Sqi+fPnIzQ0FKGhoYiOji5QsoXneSxbtgzr16/Hq1evUL58eXz77bfo2bOncYNmGCb/L3xTb1tma/YTXkop6KNrBUhqvL8yHvT+JaD656LflVMe/g38s8cwyZAiXg2P1CQcHzUS8i59czy1bt06TJw4Effv30exYsXyfPnr168RGhqKkJAQhIWFgRCCKlWqIDAwEIsXL4a3t24zedC3r4GXDwq8O7nWe/8yqHtR0RuKnv7+Bzy/dkPnfhq62jt2Kiq2/Axu/nkfH5NKN1PvnizKdOFCRcSqDUop6LPw95IaespIFz6jytcFsYDqE1dXVzg4OGRPA6pSqbBv3z5MnDgRJUqUEN6vqgxApcj93lVB+IyX2gjDDy35ovhNpJCIM6bkONCktyBO7sZdrxHQ9FTQeyFAhg77rFaCRtwW/p6LV7L85AalQmJJnxs3lBf639g6WlVygya8AX/5JPDgBsDz72KnPOiF40CJAHC1Pwfx9te+IqZQMdsZ64wZMzB16lRzbc4oZsyYgaJFi6JGjRr4888/C7Su6dOnY9GiRRg8eDDq1KmDQ4cOoVevXiCEoEePHkaKmGGY7JNRMamV5u+18fYlEPfaeOtTpIG+uAtSoorx1qknqlZDuX8nTNsnhUJ5cDdkHXuBSCRQqVQYOHAgjhw5ArVajfPnz6Nbt25QKBS4fv06QkJCEBoaioSEBHh7eyMwMBA9e/ZE5cqVDZ7Bin90zcj7lImqQZ+FgwSI1yhRkZKC498tNnpSAwBUGQqcWLIK3dYsNfq6tVKrhItdc1OkCkPdxBIfBSTGFGAFFFCkgr5+DOIr/nSbN27cwC+//ALVezPyvHr1Cn379sXZf/4Rft+8ln4UWXfO1SqLahz9PqpUAPFG/F54X+xzUEc3i0oGUFUG6L3QzKSGHp850c+E72w/8d+XWikVBlajUqGRuq2jRb5PP0SjX4A/skU4jlk9jD6sOIq4D/75fXAteoOUEe88hbEsZktsSKVSSKXWVSCSNdwmNjYWnp6eBq8nMjISy5cvx4gRI7B27VoAQpPWJk2aYNKkSejatSub0pVhjEXbiai5qMyf2KCRxr/jj1ePQUUcS62+fB70bazJt0PfxkJ98Rziy1VGmzZtcPPmTSgUwoXr7NmzsW3bNsjlctSoUQOBgYHo378/XF1djbPtxDeZU4WaAKWgrx6DlqkhWm+Dy7v2QJFsmuoGXqVGyE870GHhLNg4OppkG3ky1xCUDylSRbswoZQHfXnfOCuLiQAt4g8iF39ISteuXfHw4UPExsYiLS0NCQkJ+O+///D0/h2U9PfTbSW8SnhPWOJ0qAVKROVDlSFMF+vgarpt6IlGPgQy0mFIMpy+fAB4+IDYmvGzRB88X7CEKuUzK0otZ6aivNDEt5lJjXTtCXHKAxTg/9oJrsMQEN9S5guSsVhGOVs9fvw4FixYgKtXr4LjOHz66adYsmQJKleunL1MXj02FAoFpk6dih07diA9PR3NmjXDunXr8txGZGQkZs6ciWPHjiE+Ph5ly5bFhAkTcjTWPHPmDJo1a4bffvsNDx48wPr16xEbG4uGDRti48aNKFtWv/GA+vQQ0ebQoUNQKpUYPnx49mOEEAwbNgy9evXChQsX0KhRI6Nsi2EKvYKMIyac0B+DkwCgQoJCmW7eGAxAUxN1Lw/3LQviXUo4CVdlANERoBHheS/Lq4UyZq8SxgtWD6rQf4Wx7Lr0ZXB0gu24/4ErWwHExRU0Pg6qv48jY/uG/KsFJBI8O/Aram7chcTExJwxqFQ4evSoye5K0qinOk97ytX4TOizIJECGQrQmOegD69qn5WDV4PGvgApKs5JX+j23SAcJ4zz1+LzyWPRYGBfFClbGhzHYVWztnjwz7l815+RmopbR/5A7Z5djBVy/gpSEWbnLEyFCgAJ0fp9VlBe+CEi3AhJiBE+DzWxdwbxKStUlPA8EP8a9NVDje9r+iZSmGJaRNWqVcOmTZtyPKZWqxH5PALFfYtmDjHhhL/PrKlsAeHvT2YrPEepcLGpyhB9qFCeEnRIDNs5gRSrkOthqlQAT29qf21irMUkNqhaBcQ+R15JDVK1KcgHiSf+wZUPZg4joNERIMUrmTZQQ6m1fO5IZELCIqtxOa8Wkm0ffjeoFBY/dIq/fAqkUj2QirUBFw8QwkF9cCPw8jEAgHzRC8SnFIiDMA22ev1U8P8dhaTrKDHDZixEgQdbbd++HW3btoWjoyMWL16MmTNn4vbt22jUqBGePn2q9bWDBg3CypUr8cUXX2DRokWQyWRo27ZtruWioqIQGBiIkydPYuTIkVi1ahXKli2Lr7/+GitXrsy1/KJFi3DgwAFMnDgR3377LUJCQkSdMvXatWtwcHBAxYoVczye1W3/2jUTlSEzTGFUkOaENvbCiWlWebHMxsC7G1Q4uTeXRN2aXJLilcCV/ARQZYA+uQEaeT+fqSqJUFEgEvXdMJ2PJ7F3BFe8FJR/HIBi0/cAKOQ9BkDWrqsOG1LD4eVz1K5dG+XKlYOvr292k8+0tLQcperGRhNidB6mQZPiQB9dA713CVArwfkHgPjmk7AnROf3h7HxPI/nl6/nm9QAAJmtDcKO/YG4iOd6bUMikyHishm/Qyk1vDGx1Eb4jCnIsBxtyQUToolaLpClMpBS1QE7JyGZkRInTPHqVVLzaxLyaOpoASQSCYr7eAMgwnfAh8eKcIDcXnhemS58fmYlw43dx6KAqEqp23s1Iw301aN3P0mZnxe69JFJTy5YkMb09qXWRCFNSwL/6Fr2D1LiP1wCiHkOaowGx8ZGaWb/rDwQkjkUiss8d1EKybe8mphnNcK1UDQ9Fbh/DZBIQZ/eFRqG5loIoHcvv/dvCsS8AI2JNFucjOUqUMVGcnIyRo8ejUGDBuXIevfv3x8BAQFYsGBBrmx4lhs3bmDHjh0YPnw4fvjhBwDAiBEj0Lt3b9y8mTNDPH36dKjVaty6dQseHkKX/m+++QY9e/bE7NmzMXTo0Oy5yAEgPT0d169fh1wulIK7ublhzJgxCAsLQ5Uq5h+H9erVK3h7e+e64+fj4wMAePnypdljYpiPFjXwpISTCienKuW7O7ISmXAxYsgJK1XDCLlj3TaVHJf/XX9OAviUAVUrQW+fF07IeXU+BbvUdMMk8kHVKtDnT3RfPjYaqUO7ZSeUiEwGm6ETwJUur9PrHeNjcfLPcyBSKWJjY3Hq1Cns3bsXly9fxsuXL4VmgkZGM7vz67z8w6vC3TapHMSrOODggnxLrikVLTkV8+ARlOm6VTwdn7sYAFCqfj14lNT9d61WKvHs8hWD4jMI5Q1LTBBOOF7pycIFh6HDu9RKACIM4UhJ0PycvQuIVCYk6d5EgibHgbh6A0X8gSgNf8OKVFBebRFNRHP4MHHFSZDjczzrbnfWrBQ8LxxLqY0wAwWllnM3XKHjEDC1Ckh+73Pew1f4b9yr/F+rUoKqVaI3mQYA+jZK+wLKDGGWFG1VUrxa+F24GD783CSotqnOM7/7KX2XjJPKNS+vVgnnNhaIPropnJdcPgkAIEVLAM45G9TSE7uEv7lazd89SDjQu5dBPHUcPsZ8tAp01n3ixAnEx8ejZ8+eiI2Nzf6RSCSoV68eTp8+rfG1wcHBAIDRo0fneHzs2LE5/k0pxb59+9C+fXtQSnNsp2XLlkhISMDVq1dzvGbAgAHZSQ0AaNy4MQDg8ePHBdldg6WlpeU5xZ+trW328wzDGImhN0Pf67idY2WEADDgRNWU/S4/lN9YVECYIk0iBXgepPpn4AKDQGq1BNx9tb/OkKE4xpCWpl/1Da9+VyVDCCR1GgIA1Ncv6vh6HkhLBQAUKVIE3bt3x549e/DkyROTJDWEbar1HrbEBbaHpEEHEA9f8K+fgL58lP+LMsQ5hskxpu+PAgCJr81499/QagsHF+FYF/QOtwmasOpEW3I3KxFs6ygkbTKniSZSmfYEjoVVOADI//dLPvieyPpv9mwTIh2fvKgNuDPv4AIitxOGNypSTbcdU8iv/4STO7haLUFqtQQpW1NzHyxNlRFi0lZZSXlh2AkhwlAwG3vhs0ah4dpCrM8QXSTFGzZzC+VB9bhJwHy8CpRiffBAaFbXvHnzPJ93dnbW+Npnz56B4ziUKZNzjGVAQECOf8fExCA+Ph6bNm3SWP0RHZ3zpKZ48eI5/u3mJsx1HBdn4BRlBWRnZ5fdiO596Zl3st6vNmEYhjGJzJMZIrMBfX4HfHoKSJkaIOVrg17+Q3PfALHOgQw9+ZLKYDNhFqQ1A5Fx6Feo/vlLn40atk1DGbCPfNi/IHJbkOIVQbxKgMY8B2LyG74hzkGkZjqB1mWoi6jkdsId/eS3QgVA1h19TpKZjLPgCw1dpCaCxj4HKeIPUrEBqFoNyvMgVjS1pNFQGJQHtxiuRYX/6jXDloW8f7V83tDYF0B6ilAl5FUCxK2oUBnw+EZeS5suRpMgQs8XUCGZwXHCv+V2QhWRNaEF+APire24MaZQoMQGn3kysX37dhQtWjT3yo0wC0rWNvr06YP+/fvnuUzVqlVz/FvTDCPmOsn6kI+PD06fPg1KaY7hKK9eCWV+vr753DFlGEZ3BIadl2Tf7X//ZDxreIchpecGxGAomRz57nh6avZnEH2R2VvDtyyIgyuojZ3mxIbMzNPWZrG107mpZjYHR9jNXApJ1VrI2LkZGTs36/5aQoRtmpNEqv8+xkdnH2WuSmNwPqXB55fYEKkLvr2bq1m24+Dhnv9CxmLIMIOsZEZmJUM2Jw8h2aFP5YJYwxykcq3VWzTyPmj0M+GCileDlK8LmpGm/W6+uafE1kV+v1/6wfdEdrPGd9ViFkPfYT429iD2zqCKNGG2E523I/4wFADCd5WmAuiXD7P/lyoVIC6emqdOFmkGKe20vK8kEiGZkdVTRQ3h71BTtZQlvUc/ZO9kWH8ywoE4iDgVNmMxCvRplFVt4eXlhc8//1yv15YoUQI8z+PRo0c5qjTu3buXYzlPT084OTlBrVbrvQ1LUb16dWzZsgV37txBpUrvui2HhoZmP88wjJEQzrA+G7xKKN+USIUT7qyLEUOHYphx5gLi4CrcuddGrRTu7HsVBylZRWjSZZd1Epukac2AoxkvGt/fskwG4usPGhmh2wts7WC3dDMkJctAdfk8+OdPIf20BWhCHNQ3Luf78hQnV7x99Rr+/v4mmwHlQ4QQYUYBXWa0cfcB8S4pzE4BAlJM6B2Sb/ktISDOHtqXMRHvgHKQyGRQK/NvYFimcQN4lS8LR88iAIDKbVuiSNnSuLD1F62vk8ikKFG7plHi1QnhoHf2NCM95wW+vbPw+ZKaoH8zULF6Gdg7AwmaPwtJ0dKgGenC+82jGAgh4DX11wAAua1F9GXIhZDMC3X6bkYUQOhJQDghASyVCxU4WY8DwuNZiUpLoe/0s26ZNyjj9ajWkEhFm0r6Q8TFM+9+QnZOIP4VhB4wahVIkWLC43l97hJOtO88rbQlqfjMvj9Z5y4fDpfSZ10iI2Wrgp4/ChQtBeJaBLATZpAiJSoALh6gdy6BlK0K2Ly7CUEq1gFNTQIpV0OssBkLUqA6wZYtW8LZ2RkLFiyAMo8Tl5gYzfNnt27dGgCwevXqHI9/OMuJRCJB586dsW/fPoSFhem1DUvRoUMHyGSyHFPZUkqxYcMG+Pn5oUGDBiJGxzAfmYLcPVKkCsmNrLsdSoXh48DNeYL74Z1gDeiTG6DREYCnP4h/BSAxBvTOeS3jdymIk3gneZIKVXQ+CSPOrpCUFJLt0toNYDt1Pmynzoe859f5v5jjEOPmiQULFqBt27bo2rUrlixZgrNnzyIlRccGfAYiLkV0e68oFSCOriBla4KUqwlwEvBPw0Gf5DMdI6WASMdQIpPBt2rl/BcEUH9AH/TevAaeZYRpaT+fOBq9N6/J93VqpQr+taoXJEz9EALoW43Kq4QEadZPVoWOUpHPrER5EKnpX77JMbktiG85EF8h4cZHhANvNTWfJIBzEeMGaEwyG+ECMWuWrKzHbOwz+xmkAqDvpnzNSBOOsVScyiiNshL0ui7r6AaqytBvFiVbR8NiM4UixfL+LM1s8kp8yoCUqAzI7UBfPwF9fueDBQng4WsxiZocCNFc4ZTVY4PywntSKhNuZOTZI4VYbONQAMIUrqUqg1SsA65ZFxAX4XOHq9EEXDNhSm8S2Bpck07Zr+GadQFX+zPAV5wpzRnLUqB0ubOzM9avX4++ffuiZs2a6NGjBzw9PREREYFjx46hYcOGWLt2bZ6vrV69Onr27Il169YhISEBDRo0wKlTp/Dw4cNcyy5atAinT59GvXr1MHjwYFSqVAlv377F1atXcfLkSbx9a5qu/du3b8ezZ8+Qmip8OJw9exbz5s0DAPTt21fnhnLFihXD2LFjsXTpUiiVStSpUwcHDx7Ev//+i507d2ocOsMwjAEKcjeC8rp3ks8vBnMmNhxdhbLaNE2VF5nUKtCHeswgQTjAs1iBQisISc1AqE4F67QsjX6F5DZ1DdsQzyOga29saC4k3JOTk3H58mWcP38eq1evRkpKCkqVKoXAwEAEBgaiXLlyRqvqIF4lQCMf5L9g0lvwl44bsAHy7g6lCGr36IIX126A5jP+ecfA4dgxcLje65fIZPikfWtDwzOMRF6waVcTDb0hQ8S72+rqDUTe19jslkbc1mNlFMRDvPdkvjgJoEgXLhbzolYB6uTcr7GwO+GEEFBnD2EmkPyoMgB9vhuyiJj4/hCRykHdfYE3L5Gjokqp0PF7j4J4mahRtDFI5ZqHjKp1nNo3a1YfC8bV/gz8vrVQ//17ns/zOxbnfk2rvmartGQsW4HrAHv16gVfX18sWrQIS5cuhUKhgJ+fHxo3bowBAwZofe2PP/4IT09P7Ny5EwcPHkTz5s1x7Ngx+Pv751jO29sbFy9exNy5c7F//36sW7cOHh4eqFy5MhYvzv0GN5atW7fin3/+yf736dOns2d6adSokV6d8hctWgQ3Nzds3LgRP//8M8qVK4cdO3agV69eRo+bYQo1SyhvNvMdEUII4FsW9NE1Y65VqOwQcRy8tFFzKNYvBZLzSdgUlKMTpI3eNcF2dHRE06ZN0bRpUwBChd3Tp08REhKCH374AQ8ePIBcLkfNmjURGBiIevXqwcXFxbBtu3rplpQyBCGAVwkQuQjTg2aq91VvHJ4+F+oM4880wEmlqNWjMxyLmHmojY2dcRKghmxXpJN3wkmAoqVBX+qQhMuPW1EQW4eCr8dUCAFsHIQZbHSpqCESYXlLvLBy8dItsWEITgo4uplm3QYifuVA46N1u8j/UJFiIA4Gfo6bAycRzi0M2TcAQpNRC+xr8wFSxBdcy77g/9gOSnkQDT2ostqMkkZBIKWrmDVGxnIR+kFHzX79+uHp06c4e/asWDExEJqmSiQSbN26FQMHDhQ7HIaxLorUAnz5G4Gds9lPcimloLf+AZLjYZSu7lIZSI0WICI1nsyi2LYeyj3bDGsopguOg6xLP9h8pV+1QHp6Oq5du4aQkBBcvHgRCQkJ8PHxya7qqFSpks7VeHzUM9Dwc4ZErx0h4Oq2Ff1k/cCkGfj7+x+MPnsJJ5Xi2+v/wadSBaOuVyeJseb/jHH2FDVxSykV7nynJsLgzxipHCQg0DLL/T9EKaBMR1pyImzk8uzzMrVaDU4igSI9HXZOLplDUiwwqZGJvn4MJOkxvERXniVAXL2Mv94CoinxoHcvZlYX6fg+dfEShvlZ+kw+lApJVT2nCQcgDBuysKoibWhUBOKCd8IlLR5KtRocISAgUFMeMokEcVQKj9a9QErrNtyRKRws4NYmwzCMkclsxEtsSGSinOQSQoBytUBvnDbspOfD9ZWtJXpSAwDk3fpDdeoY6NtY4yc3CIc3PJD8SV3oe2pka2uL+vXro379+tmPvXz5EqGhodixYwfCw8NBCEHVqlWzqzq8vPK+CCBexUGjigGxkTDmVIOkVFXRkxoA0HbudNw4cARvnj0HVRf8vQkAIARtZ38rTlIDAGwdgJR4821PKhe9Go0QApSqJiQ3DKlYkUiFKaatIakBCJ/jcjv4lfVFjy6d0SCwLpwcnZCUnIRz50Ow79BhxMTEih1l/jyLC41qtc1Qoy87J8DF03jrMyLi4ApUagD68CqQngylSg2ZNOcFPaUUFABHOMC7BIh/BRBi4UkN4F01kSIV4FVaZxd+NxMjET6vrCipAQDEuzgO8F74ft4K9A+sguLuzpBwHF4npuC3y3dQJ6grVrCkBvOBQpfYSEtLQ0KC9mms3N3dIZfnX65lzHUxDGNEnEQok+WNeCKnKxGTAcTOCajUEPT2f5lJAMMukkmZGiDuPsYNzkDEzh42E2Yj/Vv9+y/ki/KwnTAXkxYvQdWqVTFlyhTIZIZfdPn6+qJjx47o2LEjAECpVCIsLAwhISHYu3cvYmJi4Obmll3VUa1aNcjlchBCwFWoB/7yH8IJa4GnJieAmzdI8Ur5L2oGcjs7DPj1J3z/aSuoKS1w5QaRSFC2UX18PnmscQI0hMxWaBapMrC5sL7sxU9QARCSEmVrgb64CyToMcTBzhmkRGUQfWfqsABJSclYv3kr1m/emuNxW1vxhnjpg0ikoD5lgRf3YJTEqUQGeJe26J4GxM4RqNIYEeHXcf7wb+jcvCGk71XQvYp9iz+u3sHXU2ZZRAJfL4QIjWx5FRLfxMDJ3g6UUqgzk8aE4yCTSvHmbRyKFPW1ir4a2oS/isXkA2dyPV7H/KEwViBXYkMmkyHDBGNhLcVvv/2Wb++P06dPZ4+tNte6PqRQCCdLBTnJZphCzcbONH0LtJHZin5XhDh7AJ80Ab1/Sc/9J8Lwk7I1LSapkUVarTbkg8YgY8sqo65XPmgMHD9rhd+at8Rvv/2GNm3aYMmSJahRwzjTxslkMtSoUQM1atTAsGHDAABv3rzBxYsXcfToUcybNw8qlQoVKlRAYGAgGtaqDu/X4UB65qwLhnL1Ale1iUWVVZeoXRPDj+3F+rZdoVYqwRtYuUE4DqUC62Do4V8h0Xd2EmMiBHBwyZx+13hVNnmycxa9WuN9RCoDKfkJaEIMaPRTIDURlFIoVSqhYSWlkEok4DgOVGYLzqsE4OFn0RfCHzti5wTqVw54+aBgiVOpHPALALGGXg2EIF7Nodf0xbC3tUERV2fY2dggPjkF0W/j0bBhQwyaYWVJjSxEmN3k/JUb+GboUHzZvi08i3hALpcjLj4eFy9fgae3D3799VexI2UYs8r1Tenj44MjR45ArVZ/lLN1tGzZEidOnNC6TLVq1cy+rg9lzQ7j42NZFxgMYzUIB8jtNHe2NzZOonk6NjMjDi5AtebAywegLx8CqgxkKFWQSSU5Li6UKhWkEgmIRCI0mfSvZLEnrPJOvQFASG4QTv9pMrNkvlb+9ejsdRJC0KNHDzRv3hzjx49HyZIlMXPmTNjYGP+k18PDA61bt86e8pznedy9exchISGYvWgpEt/EYFSr+ggs46e1zDiPHQNAQUpUEoagWGDZcflmn2LChZP4ufcgvL5zT68LLMJxoDyPT4cPRofFcyC3szNhpDriJELzxGTTzMwGQEiWWmiVA3HxBHHxRPOGgSjl5YZPypeGs4M90hVKhD96ikvhd/HnP+fh5m45M2cUZsTeBbR4ZeD1E8OGEjm5C301LCjJpqvUdAUiXhs6G5Fli3j+HKvXbcj1ePfu3UWIhmHElevTqV27dpg/fz7Onj2LZs2aiRGTSfn4+BgtWWDMdX1oz549cHZ2RuPGjU2yfoYpFKRyod+EpinSjCWrNNSC7kgSjgOKBQC+5fDPwV9x/ewp1K1UDv5eRUA4gjcJSbh4+wHsvfzQa9Qkqxj3Lu/UG1zJMlCsmAsa/1b/nhscB+LiBpvx/4O0Vv1cT3t5eWHHjh04cOAA2rRpgwULFqBevXpGil5TSBwqVaqESpUqZTeKTkpKQvils/BOjUYRezlUajUkHJfrjjfP8yAcJyQ/XL3Ala0O4lzEpPEWVLFqn2Dq1X9xYvFKnFq+BumJicLfjYYkByeVglep4FetCjqvWIhyTRqZOeJ8yGwABzcgJc4E67YFHFwt6nMlL49evMLp86F5P2nhsRc2RG4H6l9RmHI4LgpQpkOlVoMAOW5mKlUqSDgOHMcJ/TTcigq9KxiGYSxYrsRGvXr1UKlSJQwYMAAnT55E2bJlxYirUDt69CiWLFmCgQMHmuSOIcMUKrLMcdAmSG5QSoUEgo2jUAlggQjHISJZhXGrfszz+REjRqC3FSQ1skhrBkKy8Xdk7NoC5fEDQHqa9gqOrOds7SBr9SXkvQeDODhq3UbHjh3RpEkTTJw4EXv27MF3330HOzNWCDg5OaFq87aglAKJsTj/+y+QpSehWpnisLcVvhPik1Nw6d5jSFy9UC+oO5y9/cwWX0FJ5XK0njkZn00chWt7DmLL9FlQvngFx/f+htSU4i14BLZrg07TJqFE7ZoiRpwPuS1A3IVmooZWEn3IxkG4oGSJAcbICCGAixeosyfiX7/AsrmzUKtKRZQvVRw2chlS09Jx/e4DRLyOwYyFS0HkFlAdxTAMo4NciQ1CCP788080a9YMAQEB+PTTT1GnTh3Y29uz8ZEmxPM8EhIScPLkSYSHhyMoKAgrV64UOyyGsX6EZE7HxwHKdKOu+sr1m6hYvSYcLKiXQWFAHBxhM3gs5H2HQnXmT0T/cQSpN6/AxzbnMJrX6Rmw/aQmvFu1h7RZKxBb3U/Q3d3d8eOPPyI4OBjt2rXD7NmzzV5BJ1yAeOLArWdYs2YNAEDCcaCg4HmhwqF79+7YeuoiEhMT4evrm92YtGLFihY/nFRuZ4d6/Xpi6eF92PfiAWQUkIOAAkgHBQ9g0LCBlp3UyCKzEWaJSE0s2PA3TiJUaVjIsDbm40UIgUpqiwUbfsrz+dKlS2Pm8rVmjophGMZweQ6UK1asGC5evIj9+/dj79692L9/P9LSzDROvRBzcnJC7dq1sWDBArRu3Zo1DmUYYyFEuPCQSIWLDiNMhwq5HZIy1Bg5chR+/PFHlvgVAcmswrhv44Lmq36Em0wCZ6kEBAQJKhXilGqcnL4cxT77zOBttGnTBg0bNsSUKVOwZ88eLFiwAI6O2is+TEn9wfCbVq1a4auvvgIAREZGIiQkBNu2bcPt27fBcRyqVauWPd2sp6dlTs+YRQlAaepGnKZEOCEpYeMg9DDITHBoGkqkVKoglUmFoUQSmTCcTW7HqjQYhmEYxgAaOwC5ubnh66+/xtdff23OeBiGYUyHkwgXHWqlMDQlM8Ghe5NGItxJlcoBjkOzZs1w/vx5bNmyBYMHDzZh4Iwu4pRqxCmNkLT6gIuLCzZs2IBTp04hKCgI06ZNw+eff2707RSUn58fOnfujM6dOwMQppu9efMmQkJC8NtvvyE2NhZFihTJruqoWrUqS6CbglQGSF2F2UyUCuzdtR3FinqjXOlSsLGxgUqlwpu3cQi9chVftGmLon7FhdcwDMMwDGMw62ttzDAMUxDkveQErwZUSiQlxAG8Gs5OTjkWVavVeB0dA79i/kK1h0SW627qt99+i86dO6N27dpGmyaUsUyfffYZ6tWrh2nTpuH333/H0qVL4eLiInZYGslkMtSqVQu1atXCiBEjAACxsbEIDQ3FwYMHMWfOHKjValSqVCk72eHnZz29OiwexwE2dli9+WdcuHAhz0XCwj5DUZbUYBiGYZgCY4kNhmEKL04CyCW4ee8RGjdujGJ+fnBycoRUKkVaWhpeRL7El19+id27d2teBcdh8+bN6NatGw4cOGDRF7pMwTk6OmL16tX4999/0alTJ4wfPx5t27YVOyydFSlSBG3bts2OWa1Wv5tudvZsREZGwsnJCXXr1kVgYCBq1qxp1sapDMMwDMMwhmCJDYZhmEwvIiMNel2RIkUwf/58fPPNN9i1axfrt1EING7cGEePHsWsWbOwd+9eLF++HO7u7mKHpTeJRILKlSujcuXK2UNPExMTcenSJZw5cwbLly9Heno6ypQpk13VUbp0afYeZxiGYRjGorDEBsMwjBHUr18foaGhWLVqFcaOHSt2OIwZ2NnZYcmSJbh48SK6deuG4cOHo1OnTmKHVWDOzs747LPP8Flm01VKKR4/fowLFy7g+++/x6NHj2BnZ4datWohMDAQderUgbOzs8hRMwzDMAxTmLHEBsMwjJGMGTMGvXr1woULF1C/fn2xw2HMpG7dujh27BjmzZuHvXv3YuXKlfDy8hI7LKMhhKBMmTIoU6YM+vTpAwBITU3F1atXERISgo0bNyIpKQn+/v7ZVR0VKlQAx6ZBZhiGYRjGTFhig2EYxkgIIdiwYQM6duyI33//HUWKFBE7JMZMbGxs8N133+HatWvo3bs3BgwYgJ49e360Qzbs7e3RqFEjNGrUKPuxFy9eICQkBD/++CPu3LkDqVSaY7pZDw8PESNmGIZhGOZjxhIbDMMwRuTi4oIVK1Zg8ODB2LdvH7trXcjUqFEDwcHBWLJkCbp3746VK1fC19dX7LDMolixYujSpQu6dOkCAMjIyMiebnbXrl14+/ZtjulmP/nkEzbdLMMwDMMwRsESGwzDMEZWvXp1tG3bFgsWLMCMGTPEDocxM5lMhunTpyM8PBwDBw5E9+7d8dVXX3201RuayOVy1K5dG7Vr18bIkSMBADExMQgNDcX+/fsxa9Ys8DyPhw8fihwpwzAMwzDWjt1KZBiGMYGvv/4ajx49wt9//y12KIxIKleujGPHjuHNmzfo1KkTnj17JnZIovP09ES7du0wb948HDlyBIcPH0bx4sU1Lp+RkWHG6BiGYRiGsVYsscEwDGMChBCsXbsW8+fPx6tXr8QOhxGJRCLBxIkTsXjxYgwfPhzr168Hz/Nih2UxJBIJXFxcND6/YMECtGnTBmPGjMHu3bvx5MkTUErNGCHDMAzDMNaAJTYYhmFMxMHBAWvXrsXgwYOhUqnEDocRUfny5XHkyBGo1Wp06NABjx49EjskqzB79mwcO3YMI0eOhEqlwrJly9C2bVt07twZCxcuxOnTp5GUlCR2mAzDMAzDiIz12GAYhjGhihUronfv3pg5cyYWLlwodjiMiDiOw8iRI9G2bVuMHTsWzZo1w6hRoyCRSMQOzaIRQlCuXDmUK1cOffv2BSBMN3vlyhWEhIRg/fr1SEpKQvHixbMbkwYEBLDGvQzDMAxTiLDEBsMwjIn17NkT586dw9GjR9GuXTuxw2FEVqpUKRw8eBBbt25Fu3bt8P3336NChQpih2VV7O3t0bhxYzRu3BgAQCnNnm528+bNuHv3LmQyGapXr5493ay7u7vIUTMMwzAMYyosscEwDGMGK1asQPv27VGlShWULFlS7HAYkRFCMGjQILRs2RJjx45FnTp1MHHiREil7GvZEIQQ+Pv7w9/fH127dgUAKBQK3LhxAyEhIdixYwfevn0LLy8vBAYGon79+qhSpQr7fTMMwzDMR4J9ozMMw5iBjY0NNm7ciKFDh+Lw4cOwsbEROyTGAvj7+2Pv3r3YsWMH2rRpg2XLlqFq1apih/VRsLGxQd26dVG3bt3sx6KiohAaGorff/8dM2fOBKUUVapUyR7CUrRoUREjZhiGYRjGUCyxwTAMYyalSpXCiBEjMGnSJKxevVrscBgLQQhB37590aJFC4wdOxYVK1bEt99+C7lcLnZoHx1vb28EBQUhKCgIAKBWqxEeHo6QkBBMmzYNr1+/houLC+rVq4fAwEDUqFGDJSEZhmEYxgqwzloMwzBmFBQUBBsbG/z2229ih8JYmKJFi2L37t2oVKkS2rZtiytXrogd0kdPIpGgatWqGDJkCH788UcEBwdj/fr1qFSpEv766y/06NEDbdq0wdixY/Hrr7/i6dOnbLpZhmEYhrFArGKDYRjGzBYsWIAOHTqgevXqCAgIEDscxoIQQtC1a1c0a9YM48ePh5+fH5sq2MxcXV3xxRdf4IsvvgAgNCa9f/8+QkJCsHjxYjx9+hT29vaoU6cOAgMDUbt2bTg6OoocNcMwDMMUbiyxwTAMY2YymQybN29G//79cfjwYdjb24sdEmNhihQpgl9++QWHDh3CyJEjxQ6nUCOEICAgAAEBAejfvz8AIDk5OXu62bVr1yIlJQUlS5bM7tVRrlw5Nt0swzAMw5gRS2wwDMOIwM/PD1OnTsWYMWOwefNmscNhLFSHDh0QHByMTZs2iR0K8x5HR0c0adIETZo0ASBUdURERCAkJAQbNmzA/fv3IZPJUKNGDcTHx4sbLMMwDMMUAiyxwTAMI5LPP/8c//33H3766ScMGDBA7HAYC8WaV1o+QghKlCiBEiVKoHv37gCE6WavX7+On3/+WdzgGIZhGKYQYHWSDMMwIpoxYwYOHTqEmzdvih0KwzBGZGNjg3r16sHHx0fjMsOHD8e3336LQ4cOISoqyozRMQzDMMzHhVVsMAzDiEgikWDz5s3o3r07Dh48CGdnZ7FDYqzIrVu3xA6BKYCsaZ8vXLiAKVOmICoqCm5ubtnTzVavXp1V7DAMwzCMDlhig2EYRmSenp747rvvMGzYMOzYsQOEELFDYqzErVu3MGjQICxduhRubm5ih8PoSSqVonLlyqhWrRq++eYbAMDbt29x8eJFHD9+HAsXLoRSqURAQEB2Y1J/f3/2GcEwDMMwH2CJDYZhCrWkpCScPn1a4/P37t3D3bt3UaFCBZPG0bBhQ1y4cAFr167FqFGjTLot5uPRq1cvlC9fHl26dMGYMWMQFBQkdkhMAbm7u6NVq1Zo1aoVAIDn+ezpZhcsWICIiAg4ODhkTzdbq1YtODg4iBw1wzAMw4iLJTYYhim0Xr9+jRYtWiAsLEzjMteuXUOVKlWwfft29OzZ06TxTJgwAd27d0fdunVRr149k26L+Xg0aNAAx44dw5w5c7B3716sWLECRYoUETssBsCrV68QExOj8fnw8HBUrFhR69SwHMehQoUKqFChAr766isAwnSzly9fxvnz57F69WqkpKSgVKlSOaabZVUdDMMwTGHCEhsMwxRakyZN0prUyKJWq9G3b1+0bNkS7u7uJouHEIJNmzahU6dO2LNnDzw8PEy2LebjYmtri4ULF+Ly5cvo0aMHhg4dii5durCLWxH9+uuv6NOnD9RqtcZlunfvjg4dOuC3337Tq5eGo6MjmjZtiqZNmwIQppt99uwZQkJC8MMPP+DBgweQy+WoWbMmAgMDUbduXbi6uhZwjxiGYRjGcrFZURiGKZQopQgODtZ5ebVajRMnTpgwIoGrqyuWLl2KIUOGgOd5k2+P+bjUrl0bwcHBCA8PR8+ePfH69WuxQyqUHj16hF69emlNamQ5dOgQvvvuuwJtjxCCkiVLokePHli1ahWCg4Px66+/okWLFggPD8c333yD1q1bY+DAgdi8eTNu3bqlU2wMwzAMYy1YYoNhmEKJEKJ3ub6np6eJosmpVq1aaNGiBZYsWWKW7VmzqKgorQmq4OBgq764f/bsmdaqogsXLuDNmzc5HpPL5Zg9ezamTZuGfv36YceOHaCUmjpUvaWlpWHUqFE4fvy4xmXGjRuHPXv2mDEq4zhy5Ihev/ODBw8aPQZbW1vUr18f48aNw6+//orjx49j3rx5KFKkCHbs2IEOHTqgffv2mD59Oo4cOYLo6Gijx8BYLkqp1s+WxMREPH361HwBMQzDFBBLbDAMU2h9/vnnOi/r6OiIOnXqmDCanIYOHYo7d+7gn3/+KdB6EhMTcfnyZY3P3717Fy9fvizQNsRy584d1KxZE8uWLdO4zIoVK1CzZk3cvn3bjJEZx8mTJ1GpUiWtzW03bdqEGjVq4MGDB7meq1q1KoKDg/HixQt07doVL168MGW4eqGUol27dli7di1SU1M1LhceHo7u3btj9+7dZoyu4ORyuUmXN5Svry86duyIxYsX4+jRo9i/fz+6dOmCFy9eYNKkSWjTpg369OmDNWvW4NKlS8jIyDBLXIx5qVQqDBgwAM2bN9e4TGxsLEqVKoW1a9eaMTKGYRjDscQGwzCF1sSJEyGV6tZqaNSoUXBycjJxRO8QQvDDDz9g7ty5BlccPHv2DDVr1sSaNWs0LnPq1CkEBATg7NmzhoYqmgkTJuiUlHn16hUmTJhghoiMJyMjA126dNF60Z/l+fPn+Prrr/N8TiqVYurUqfjuu+8wePBgbNmyxSKqN65cuYK///5bp2UppVi+fLmJIzKuxo0bm3R5Y5HJZKhRowaGDRuGbdu2ITg4GKtWrULZsmVx9OhRdO3aFW3btsWECROwZ88ePH/+PNf7R9uQFkt4rzG5/fDDD9i2bZtOy44aNQqhoaEmjohhGKbgWGKDYZhCq1SpUtmzDGjj6OiI8ePHmz6gPLa7Zs0aDB482KDx8AMHDsSjR4/yXS45ORlffvkllEqlIWGKglKKM2fO6Lz8mTNnrKpnyX///YeEhAS9lo+Li9P4fMWKFXH06NHsYy12ifmNGzf0Wt7aekJ88sknaNmypU7LSqVSjBkzxsQR6c7DwwOtW7fGnDlzcOjQIRw5cgSDBg1CcnIy5s2bhzZt2qBr164YM2YMypQpg8jISI3rql69Ovbt22fG6Bld6Dv06dChQ6YJhDEZa/q+YxhjYYkNhmEKtWnTpkEikWhdZtSoUaJNn1mpUiV0794ds2bN0ut1CQkJeg1jiYuLw3///adveKIhhKBMmTI6L1+mTBmtU2paGjc3N72Wl8lkcHBw0LqMRCLB2LFjsXz5cowaNQpr164V7eS3evXqei1ftWrVfP9OLY2uf7P9+/dH6dKlTRyN4TiOQ8WKFTFgwABs3LgRx48fx6xZs7B161Y8fvxY62ufP3+Obt264dSpU2aKltGFPjPwGLK8JXj16hV+/vlnjc8/ePAAe/futdqqojVr1mDgwIEanz9w4AC6d++uV4KcYayd9ZzlMQzDmECpUqUQFBSk8XmZTCZKtcb7+vTpg9jYWK1NFj9kZ2en94WgOYfaGEPHjh11XvbLL780XSAmUKVKFb2SaQ0bNtS5T0PZsmVx6NAhSCQStG/fPs/+HKZWvXp1VKhQQefle/bsacJoTKN+/fr5Vm1IpVJMmzbNTBEZzx9//IGUlBSdluV5Hps2bTJxRKbB87zGC1+e5632rvinn36q1/JiDZUy1JMnT9CwYUOsXLlS4zJRUVHo2rUrxo4da3XJjTVr1mD06NFah6mqVCr8/vvvaNGihdW+T9PS0jQ+p8swTaYQogzDMIXc/fv3KYA8f9q3by92eJRSStPS0ujnn39Onz17pvNrmjVrpnG/PvxxdXWlCoXChHtgfG/evKHOzs757puTkxONjY0VO1y9LVq0SOfjd+LECYO28fTpU9qhQwe6bNkyqlKpjLwH2u3atUunffP29qYpKSlmjc1Yzp8/r3XfunTpInaIBhk5cqTO700AtEiRIrR169b066+/pps3b6a3bt0y+/tNX/v27aMeHh757tfBgwfFDlVvsbGx1NHRUadjV7NmTcrzvNgh6+Wrr77S6/155coVsUPWS0BAgF77FxoaKnbIeklPT6e9evWiHMdp3a+mTZta5Xc7YzqsYoNhmEKvXLlyed79t7e3t5g7jba2ttiwYQOGDBmi80wFU6ZM0Xn9EyZMMNvMDMbi7u6uU2+C0aNHw8PDwwwRGdeIESN0irthw4b47LPPDNpGiRIlcODAAbi7u6Nt27ZmnT2mW7duqFixYr7LTZkyBfb29maIyPjq16+PUqVKaXx+4cKFZozGeOrWravX8v369UNwcDDmzJkDd3d3/PLLL+jQoQOCgoIwY8YMHD16FDExMSaKVn/nz59Ht27dck2l/KHY2Fh07twZFy9eNFNkxuHh4YHRo0frtOzs2bNBCDFxRMZ18uRJvZY/ceKEiSIxPpVKle8QsA/du3fPRNGYxjfffINdu3blW2ly5swZtGnTxkxRMVZB7MwKwzCMJeB5no4dO5YWKVKEOjg40Hr16tEHDx6IHVYu+/bto+PGjdNpWZ7naWBgYL53c9zc3Gh8fLyJIzeNN2/eUAcHB437Zm9vb9V3dHSp2jC0WuNDkZGRtEuXLnTevHk0IyPDKOvMz+7du/N9b1prtUaWY8eOUUJIrn37/PPPxQ7NYImJiflWM2T9EEJoWFhYnuvJyMigV65coWvXrqV9+vShrVq1or1796Zr1qyhly5dMtv78EMjRozQ64742LFjRYmzIGJjY7V+dsJKqzUopbRBgwZ6Hb/du3eLHbJe6tSpo9f+3b59W+yQdZaamkrt7e312r87d+6IHTZjIVjFBsMwDIRmlN9//z1iYmKQnJyMkJAQlC1bVuywcunUqRMIITrNNEAIwezZs/Ndbvz48XBxcTFCdObn7u6O3r17a3y+V69eVlmtkWXEiBGws7PT+HxAQIDB1Rof8vX1xe+//45SpUqhTZs2uH79ulHWq03Xrl3h7u6u8flhw4ZZbbVGljZt2uDnn3/O3k+ZTIagoCD8+eefIkdmOCcnJ0ycOFGnZbt164bKlSvn+ZxMJkPNmjUxYsQIbN++HcePH8fKlStRqlQpHDp0CJ07d0bbtm0xadIk7Nu3T+sMLMYUHR2t1/JRUVEmisR0PDw88M0332hdxhqrNQCgVatWOi8rl8vRtGlT0wVjArrM5palXr16evUzEltKSore/TP0/XtlPl6EUivrmMMwDFPIKZVKBAUFYc2aNfkmXyilCAgI0Ngg0tbWFq9fv7baxAYglIN7eXnlagBHCEFUVBQ8PT1Fisw4vvrqK2zbti3P53bv3o0ePXoYfZtRUVEYP348ypQpg+nTp5t0VoS5c+fmOYOIVCpFfHx8vrO9WBOe561qdh5tkpKSUKpUKa3DNQghuHXrlsbEhi7UajXu3r2LkJAQhISEIDIyEk5OTqhbty4CAwNRs2ZNrck/Q6xYsQITJkzQeflVq1bpPLTDkrx58wZeXl55lvx7eHggJibGKhMb8fHxKFmypE4zgowcORJr1qwxQ1TGo1Ao8p1qOcvx48f1SvRYgnLlyuHhw4c6Lfsxfk8wBSBuwQjDMAxjiIiICPr555/T1NTUfJfdsWOHxhLOXr16mSFa01u+fHmufVu6dKnYYRnF27dvqZOTU679CwgIMHmZ+N69e+lnn31m8uZzTZs2zTV8Ye/evSbdJlNwCxcu1Foi3rFjR5NsNyEhgZ48eZLOmzePduzYkbZu3ZqOHDmS7tixgz58+LDAfxfR0dE6l8Nba3PiLH379s1zv3788UexQyuQWbNm5Xvs5HI5ffHihdihGuSHH37Id//q1atnlUOJ8vo+1/QzaNAgscNlLAir2GAYpnCjVPjh1QBVC/8PACAAxwGcBCAcYIF3rf7880/s378fGzdu1LocpRRly5bN1XDM3t4eT548gZeXlynDNJuwsDCsWLEClFKMHz8en3zyidghGc3Tp0/RuXNnhIWFQSKRoFmzZti7d6/R71Tn5c2bN5g4cSI8PT0xZ84ck23z+PHj+OWXX+Dt7Y0pU6bAx8fHJNthjCcpKQkeHh5QKpV5Pn/r1i1UqVLF5HFQSvH48ePsqo5Hjx7B1tYWtWrVQmBgIOrUqQNnZ2e91jllyhQsWbIk3+WmT5+OefPmGRq6RRgwYAB2794NhUIBZ2dnzJ07V6fGzJYsPj4e/v7+SE5O1riMNVZrZFEoFChWrBhiY2M1LmON1RqAMJVrqVKl8h1iIpVKcf/+fa0NmpnChSU2GIYpnHg1oMoAVEoIif98cBJAagNIpBaV5Pjf//6HsmXLol+/fuB5Hjt27EDv3r0hkUhyLJecnIygoCD8999/UKvVCAgIwL59+6xq7C0jrqNHj2LFihWYO3cuGjVqJHY41oNSQK0CeJXw/4QIyVKJTEieWrk+ffpg586duR6vXLkywsLCRIhIkJaWhitXriAkJAQXL15EYmIi/P39ERgYiMDAQFSsWFHrsKCYmBiULFlS63h/JycnPHnyxKr7+LyPUmqVQ080GTt2LFatWpXncxzHISIiAn5+fmaOyng0DeMDAD8/Pzx//txqj6cuw8EGDRqEzZs3mykixhpoTWxQShEWFobHjx9DoVCYM65CycHBAdWqVUOxYsXEDoVhPl68GshIE/5rEALIbACp3CISHGq1Gh07dsSUKVPw7bff4vr167h48SJLWDAmER8fjylTpsDGxgYLFiyAo6Oj2CFZJl4NKNIAZZqQ1NCEcMJnia2DkOiwgM8UffE8j0aNGuHChQvZj/n6+uLOnTt6V0mY2osXL7KrOu7cuQOpVIpq1aohMDAQ9erVy5WgyK9q42Oo1viYxcfHw8PDI88eIo0aNcK///4rQlTGk1Vhk9cU8OvWrcOwYcNEiMo4UlNT4ePjg8TExDyf5zgODx8+ZNUaTA4aExvr16/HihUrdG7ewhhPgwYNsGDBAjRp0kTsUBjm40EpoFIASiMlaTkJILe3iDuuwcHB6NSpExQKBSQSCX7++Wf06dNH7LDMjsbHgaYkAhQgjk4grppn22AK5sSJE1i4cCGmT59utFlZPgq8GkhNBJTp+r+WkwJ2ToDc1vhxmcHt27cRHByMunXr4tNPPxU7HJ1kZGTg5s2b2cmOt2/fokiRItlVHUWLFoW/v3+eF8YSiQRRUVEfTbXGx2rmzJm5kk92dna4f//+R3Ej8e+//0bLli2hUr1LoPbp0wfbt28XMSrjGDduHFauXJnnc02aNMGZM2fMGg9j+fJMbCxevBhTp05Fjx490L9/f9SoUcMs43gLM0opEhMTcebMGaxbtw43btzA0aNH0bx5c7FDYxjrR3lAkVqAKg0t5PaAVGb89epo0aJF+P7773OMRf3qq6/w008/iRaTuVBFOlT/noAq5B/wD+4AifE5F3ByAVe+EqSBTSBt3ALExjovGKlaDaTEgybHCcOnMquGiJM74OAMQsRJriUnJ2PatGnIyMjA4sWLs2fWSU9Px+rVqzF58uR81xFx7QbCj5/A00tX8eL6TaQnJYOTSODiWxSl6tZGybq1UL1Tezi4uZl6dwqGUqESLDUROg1t00ZmC9i7WETStDCKiYlBaGgoQkJCspMeMTExuZb78ssvceDAAREiNC7K88J7V6kQ3sccJ7wH5bZWO4zhQ1u2bMGyZcsQFxeHatWqYdOmTShZsqTYYRlNeno6NmzYgKioKAwYMADly5cXOySjSE5OhoeHR66KFEIILl26hFq1aokUGWOpciU2Xr58iWLFimHy5MlYtGiRWHEVaunp6WjVqhWioqJw+/btj+aLhWFEQXkgPUX4r6nI7YRycjNTqVRo3LgxHjx4kGPKxRo1auDq1avZ/6aUAhnpQEq88F9QIV4HF8DW0eo+Y6hCAeWen6E8thdITxXK9zWNqsx6ztYesradIes6AMSEU5caC6UUiIsC/+I+8OZFzqa2whLCfzgJiE9pEL9yII7iXPyfPXsWs2fPxqRJk9C6dWsMGzYM27dvx549e9C6detcy1NKcXXvQfy1dBWeXboKTiIBpVS4wHoPJ5OCV6kglctRt1c3tJo2AV5ly5hrt3RHqfC3ZUiVhiaEAxzdRU2aMgKlUonatWvj5s2b2Y8VKVIEU6ZMQYMGDVCzZk3Y2lpX0pTyPJAcByREC0n/vBAiVBC5eAH2zlb3PcF8HM6dO4dWrVohJSUFgNAwdMOGDfj6669FjoyxRLkSG2vWrMGECRMQHR0NV1dXkcJijh07hnbt2pmtozjDfJQoBdKTTZvUyGJjL4yRF8GlS5cwbtw43L9/HzExMfDx8RHmt1dlANHPQF8/Fe7I5UUiBbyKg3iXArGz/H4J6nthUKycCxr1UnMyQxNCQLx8YDN2FiQVLPdzlaYmgr99AUiM1Z60yZK1jHdJcOVrg8jMn7hJTU3F//73P9y/fx8XLlxAbGwsypUrh9u3b0MqlWYvF//yFXYMHoWw4L9AOC5XMkMTTioFJ+HQcfFcNBv1jdamj2ZFqXCBqDJFHzICOHlYTXKD8rwwsxThQDhJ/i+wMi9evMCFCxdQv359ODk54eLFiwgJCcHVq1eRnp6OcuXKZQ9hKVWqlEUmAmjW+zUmQr8KRpkt4F0SxNbBdMExjAaUUpw7dw5JSUn44osvcnynMMz7ciU2+vTpgydPnuC///4TKyYGQkMgW1tbbN68GYMGDRI7HIaxThlpmaX75kAAO0fhTqtIrl69ipEjRyI0NBQvr1+AZ2q0jievBAAFfMuC+Few2IsS1fnTUCyfBYACOl4Q58JxAAhsxs+GtKHlDfXjXz4CvXcxM5mh75AGAsjk4D75FMTV/FP4ZmRkoFy5coiIiAAA2NraYsaMGZg+fToA4OmlK1j1xZdQJCWDVxs+LOyTdq0wZM8vkFnCXfLkOONWanyIEMDZU+jpY2EopUBaIuibl0LFyvt3/mU2gL0LiLsP4ORhkRf5xkQpxcOHD7N7dTx58gR2dnaoXbs2AgMDUbt2bTg5OYkbI68Gop4Kx8pQ7j6Am89HfzwZhrFOuRIbQUFB4HkeR48eFSsmJpOjoyO+++47jBs3TuxQGMb6qFWAIsW825RIARtx72hRXo3YC3/Cg1MatgI7R5CKDUBsLKuvkurSf1AsnGrgBf+HCEAIbKYugLRuY2OEZxT8i3ug9y8XfEWEA1etGYh70YKvSw/jx4/HunXrcsyi5uPjg5s3byI14gWWfdoKynSF0DOkAAjHoWKLZhh++DdI5eYfApYtIx1IiTP9dqQ2gKObRc2YQhWpoBG3gdQEZCdGNZHbgfhXAnF0NVN0liE1NTV7utlLly4hKSkJxYsXz67qCAgIMFvlEeXVwMsHwrDMgnL2BDz9rSa5QRVpwNuXoBkKoaJIIgNxcAFcvUEspfLLUJqmreekgEwu/NdKjhPDGEOeiQ0AOHz4sCgBMe84Oztj9uzZGD9+vNihMIx1oRRIT9J/qIIxiDgkhfI86N0QICF3ozvdEcDGDqRKYxALmZ2BfxODtJE9AUW68Y4pIYCNLezW7gbn4WmcdRYAjX0B/uY/xlshJwFXtw2Ivfmm22zRogUiIiKQlpYGlUqF1NRUJCQkoEHtOmj0MgFJUdEFqtR4HyEEX0wZh44LZxtlfXrjeSAx2nyfMfYuwmeLBaDxUaAR4ZnXUbrvP/EuBXhb5hCNfGUlVCky29wQvS8YKaU5ppu9e/cupFIpqlevnj3drLu78WdyopQCrx5lJqGMxMMPxM28iVN90cRY0KinQHxmY+33jxelwhAvrxIgXiVEGb5XILpOW0+IMIzISqeSzkJVSiAtBQAFbB1AZCImtBmLpvcgpZ9//hkDBgzAkydP9OooPHv2bMyZMwcaZpfNgRCCWbNmYfbs2fqGxzAMI1RriJHUAABlhniJjRd3C5jUAAAKKNJAH1wBKjUQ/SKEUgrFDwuBjAzjHlNKgYwMKNYugO3/Voi6n1SpAH8nxLgr5Xnwty+Aq/WF2fbtxIkTAIRjFhsbi4iICDx8+BD/LfweiVFRoGrj9bqhlOKvxd+jesd2KFW3ttHWqzNFsnk/Y9IShSbFYv89xkeDPgsz7LVRTwAApGhpY4ZkWpRm3hFX5DzehBMaMEvlOh8TQgj8/f3h7++Prl27AhCGb924cQMhISHYsWMH3r59Cy8vr+yqjk8++USnfgKhoaGQy+WoUaNG7ieT3ho3qQEAbyJB7V0srrIPED4baOR9IZmDD5IZ71MpgZcPQaOfAeXrClUc1kCfatSs2ZokamEaaStLbtDoF+DDLgAPrgFZSXFCgBIVwX3SAChWRrRZwRjLxN4NWsyfPx9BQUHw9vYGIaRAiRZjrothmHyYpJGfjniVaaaVzQdNjgMiHxhrbULjyuhnRlqf4fhbV8FfCzXN75RXg79+EfytK8Zftz5hPLohJMSMSjiG9NUjI683f4QQeHp6olatWmhYoRIybtw2alIjezsch19HTjT6evNFqeaZJEy5TVP28tAlhIw0oVKjIKKegCa9NU5ApqZWCgklZR6VYpQXHk9LFJYzkFwuR506dTBq1Cjs3LkTx48fx5IlS+Dn54c9e/agY8eOaNu2LaZMmYKDBw/i1atXea5n3rx5+OKLL3JN803VKqFRqClEPzXNeguIPr+bmdQAdKooUilB74aApiaaNC6jMHSIrTpDmM7XSlC1CupTv4Pfuwa4d/VdUgMQ/haf3QV/ZAv4g5tA0838WcxYNLMlNmbMmIG0NA1d+S3UjBkzcOnSpbwz4CKui2EYLXhelMRCDirDT3QNRZ/fQ467U0ZZ511Qc8woo4UyeJ9pGydyEmEbIqHKjMyTcNPc/acRd3WqlDSVf9ZtASc1zfHj1Wo8u3QVEVevm2T9GmUYcUiUPszdM+gD9MVdo+w3fX5b59lwRKNW6p68UqQWKLnxIW9vbwQFBWHBggU4cuQIDh8+jN69eyM6OhrTp09HmzZt0LNnT6xcuRIhISFQKBR48OABYmNjMWHCBAwZMgTqrAvBpLemmxVMkQpqjJ4dRkTfvAQyK4P0wqtB718SepFYqoImVFUKITFi4SjPg/9rl5DQEB7IayHhv6+fgj+0CdSKkjaMaZltvhypVGp10/NkDbeJjY2Fp2fBxmAbc10Mw2jBF+CLm3BCuTcnAUCFBIUhd0kLEoMBqCIViI/KdzlSowWIbc5x+vzdUCDudd4vUCqAt68BD19jhKk3mhgP9cV/9Toxl3boCdkXHUA8iwIpSVD+fQzK7Rs0v4BXQ33xHGhCHIiLmxGi1g+NeqLb/knl4CoGAk7uwphpZTro6yegj29of11qglB942L+752M1FRc+GUXeFX+FwtfTB6Lhl/3g2fZ0uA4DiuatsH9f87l+zpOKsW5zdvQa311I0SsI0Mrwhzd3411p7yQIEnT4y6xSim8ToTSa5qeIlwka2LvDOJTFrBzEpLL8a9BXz3MOxGiVACJMYCrt+kCLghKhQtA28xZrggRpg3PuuiVSIW/QcJlDlVRCBecds4mKfWXSCSoWrUqqlatiiFDhgAA4uPjcfHiRfz111+YN28enj59CgCIi4vD9u3bcevWLQQHB8M1MTr/Ddg5gvgF5HqYKhVAfsOOEmIAC5kCllKab4UaKV4JxLskAIC/9U/OZqpKBfD2FVCkmAmjLAC1ChoT4BKZMBNR1mdDVg+OD79blArh/WvBaHgIiGsRkF4TABcPEMJBfXAj8PIxAIB80QvEpxSIg9A/Sr1+Kuj5YJAmHcUMm7EQRvl2PH78OBo3bgwHBwc4OTmhbdu2CA/PWa44e/bsXON8FQoFxo0bB09PTzg5OSEoKAgvXrzIcxuRkZEYOHAgvL29YWNjg8qVK+PHH3/MscyZM2dACMHvv/+O+fPno1ixYrC1tcVnn32Ghw8f6r1f+vQQMee6GIbRoiB3XGzshaSGMl04iZDZCD+GxGDOO7pvNSQm8kBTk8Dfv5z9o33qPwL6Nu/SZ3NQP7itV1JD1nsIbL4aCZqciIzNK5Cxfweg0iHJRHmoH9wpQKSGo7oeO6kMcHABfflQ6H8CgCtZBaRY+XxeSEDj8k96mULEtZtQpeuWBJDZ2uLW0T8QF/Fcr23wKhXunT5rSHiGM3QK6ayhDakJwueDrYP+DUFFuuNK415BY0WYVAZSqjpg5yQkM1LiQDyLg3iV1Ly+Ny9NEaZxqDIAkLx7NREOkNsLzyvThc+nrGS42aYWB1xdXfHFF1/gf//7H8aNGwf5e7MDpaenIyQkBLWqV9Vt+EFGOujrx+9+shJYulRjWNLwjZQEIC1J8/MunoBnca1VGTTqqfHjMhZNCVVChM8RwmWeuyiF5IU8j/4nvMrwqdLNgFIe9PpZQCIDfXoXSIrPYyGA3r38/otA714WZr9hCr0Cp+22b9+O/v37o2XLlli8eDFSU1Oxfv16NGrUCNeuXdN6QT9o0CDs2LEDvXr1QoMGDfD333+jbdu2uZaLiopCYGAgCCEYOXIkPD09cfz4cXz99ddITEzE2LFjcyy/aNEicByHiRMnIiEhAUuWLEHv3r0RGhpa0N1lGMbSGZrY4KSZJ6fKdyeoEpkw1aIhZY6UB4gJh1C8v6mU+My7wDokU5QKIC5Kx6oSCiSbYTpLDfiHdwGO0+1ETG4DWfvuoGmpSJ8zXjiOGToeN04C/tFdoHaDggVsiMQ3ui2nSAUfchTZd+w4DqR8bWEaUK0oqK7bMLKIK9dAOE6nYQfH5i4CAJRuUA8eJUvotZ3oBw+RkZoKub0ZZg2hBRjqlpYk/J0STvj7M+TOqUopNKw0t5R4aLxbbO8CIpWBJsQITSWT40BcvYEi/pqHBaQmgFIqenPiXLIqMLI+SzkJctwDzGoWqkwXvid4XjiOUhvhMT2aiRrLn3/+iaSkJHh5ecHe3h4lS5ZEx44d0anlZwB0qDhUq3J+zrtnVujpUAUItRJUrQKxgCoAGhMBjVMPS+UgpaoKw/6K+GlOKKYmgqYmmnU2KZ1oHWKb+d2fVWlEaeZnhIa/V3UGwFnGjGe5vHgEJMWBXj4JACBFSwDOOWcKoid2CX9ztZq/e1CtAr13FaRqQ3NGy1igAn0SJScnY/To0Rg0aBA2bdqU/Xj//v0REBCABQsW5Hj8fTdu3MCOHTswfPhw/PDDDwCAESNGoHfv3rh582aOZadPnw61Wo1bt27Bw8MDAPDNN9+gZ8+emD17NoYOHQo7u3eZyfT0dFy/fj07g+3m5oYxY8YgLCwMVapUKcguMwxj6QytlMiazz5HhQDNLO3UcLJkijgMkZqo+/acPcDVayvctYqLEoYyaLvTmJ4i2gUIjXoJXfuGcMVLgdjYgibGw27VdnBFvMDHRiFj6yqoQ/KbRpWCvo4scLz6olnlwjotnPP4kiJ+wv9oGkb0vhQjz4igo5iHj8FJJFCb+A4h5SlinzyDb+WKJt0OgILf7XT2evdZo0jTf8w8FakHQJqWu/dZnx+2jsJdYifhPI1IZaASad5VJrxaSCDILO0Ci2r/LCUffE9k/ZfjTNfLIh9Vq1bFsmXL0LZtWwQEBGR/VtO4KOBN3lXQGtm7gMhtQdOSdH9vZqQDdo56Rm0CacnQ9D1NSlUVvstePnj32alJegpgaYkNbe8tygvfI3I7YSgYIPx9aapgsOSKjdfPMod46RsjAV49BVhio9Ar0FCUEydOID4+Hj179kRsbGz2j0QiQb169XD69GmNrw0ODgYAjB49OsfjH1ZfUEqxb98+tG/fPnsKuayfli1bIiEhAVevXs3xmgEDBuQoy2vcuDEA4PHjxwXZXYZhrIJ4jRJFo+MdZBrzDPTBFaGvRuIbEA9fkJI6JHtFaj5JVXpM25t5skacXaE6eQSKVd+BOLvCZtwswCmfk1QKUBEavhp0gkk4kMoNQdx9wD+/Cxqlw8w1Il1wqRQZZmtcqlJYSfO4lDjh7rgqQ5h+Ud8Le7E+3rQlVFITQWOfg9jYgavYAKRoGd2ag1riBVZBf78ifFb26dMHEyZMQIUKFXImoA35u3fL7HuiS8I0ezsW8p2raZiWhx/g7AH68mHmkI3M31F2Py0d1yMqbb9jkvk5ktlcVJku7FdeQ1HyXZfIlAoDK54oqMizRjGWoUAVGw8eCFMLNm/ePM/nnZ01n0w+e/YMHMehTJkyOR4PCMjZwCgmJgbx8fHYtGmTxuqP6OiczZGKFy+e499ubkKpblyceCXVDMOYiwHVFcC7k+wcjfmyhndY8IkAoPusIS/uZ/8vVaaDuHrpdmdKpHJxIpVmDrHJf1n+9UtQtRpEIoFy/w5AmQFpUA9ISpUDV8QbfJKWseCEgEhlxgtcV5ye9xakMnCfNAFx8wb/5Cbok1u6vU6EZpMAILWRm63SR2pjQC8cMbxfHeXoJlx86HNCLtbIDU6i9YKPRt4HjX4mXGDxapDydUEz0rRfJOr7/jeH/H6/9IPviexmjVmPW9DQGn3/7m3sQeychF4F+vTOsJR91jAchtjYg3ASkIC6OR7nAuqCf3Al95AbCxhWk5uW37FEIvwtqZRCfw01hL9DjfthIccrLzIbAxNlBERuadVfjBgK9NfLZ36Qb9++HUWLFs29ciPMgpK1jT59+qB///55LlO1atUc/5ZI8j7JF3PKO4ZhzETHC+FceJVQ+SCRCuNTOcm7sdSGxmEu9s5ASiK07ri9M0iJyqDxUYBKBeKVmQDWNtMBANg6iDYOnhTNp2T4fanJUJ39C7JmrSHvNxx8zCtw/qXAv4kB/yL/qga9tmUkJOuumi7DUSRScDW/AHF0FRovpiSCeJUQ7lJpbQ5KAEdXY4WsF8+ypcGrdasmKtu4AbzLl4WTZxEAQJW2LeFZtjT+2/pLvq8lHEGRUvr15TCYoRfjUhuhQiOrMihrdiJ9pwk1U9+eXGwdtTYaJkVLg2akC0lCj2IghIDXNu0mJxF+JxaHvOuDkjUjCpA5mw0nJKak8nexSzIToqoM0RKIGsn1/P1mzVKjS2+NHNuxkAtKO6fMYXc5vwfp21fC0JpMpERlEJkN+Gfheb+nLWSWlxy0vbd4XkgGZJ27fDhc6kOWmFDMRHxKClPM+5QCcS0C2AnHgpSoALh4gN65BFK2KmDzrhqFVKwDmpoE+JQSK2zGghQo85BVbeHl5YXPP/9cr9eWKFECPM/j0aNHOao07t27l2O5rBlT1Gq13ttgGKYQ4iSGN/dTpAoXmlllnUqFYY1DAbOe5BJHV9CYfGaTUCqEO6m+5YQZNpQK0JePQJ9rmw2ECNOLioQrU0GvY5mx5XsAgLRZKwAEfNhVKH5eCyjzma2AV4MrW6EAkRaASxEg5gXyzcbJbEAyExTEwxckcwpeGhcFPp9ZT4hIx7BE7Zq6DUkA0HBgX9T/qnf2v7+YNAYAdEpseJcvZ57GoYDwd23IZwzlhYtguS0AIrw+LVmYRlQfYlQWAYCDS54XjdnktiBF/IXfjyIVfES49uEM9i6W1zgUEBIZUhtQQkDeb9KaNTtWagKQkSp8R8hshQvKjDQhMS6ztZzqBQCw0eMCXSoDHN2EIXn5JbvfJ5FZRONQACCe/qCxeXwPpn/wd+af+VmfGJv7+93e2fIahwJCMkLT505Wjw2ZzbtzF7VS6H2SF4kIzYd15VcGcHYHqVgbXIXa2Q9zNZoAANR3LoEEtgZ5r6Eo16wL6MvHgIeP2cNlLE+BPo1atmwJZ2dnLFiwAM2aNYNMlvMLNyYmBp6ennm+tnXr1pg2bRpWr16d3TwUAFauXJljOYlEgs6dO2PXrl15Nv/Utg2GYQohXYdl5IXygEKHKe50icGcJ7huRYH8hiUoFaD3Luq5Ygrilrsaz1wk5SrpPisKAKSmIGP1POg96SLhhG2JgLh555+UAoD0FKj/3mnAFsQ7hv7VP4HM1hbK9PyrnrYNGIZtA4bpvQ1OKkVA808NCc9wUrnuTV+zqJVAUmzBty0RJ7FB3HyEoSYa0Ijb+q0vMzFniQ4dO44vPq0PW1vbvIv21SpAnUdCSozZarQgUhmoTMdZvVRK4NHV/Jf7kCUlARxchKoNbVO+AqA3z2hMIxPvkkYPy2ikNkJSLS9qpW7VX5zUsis2CAGp/ino33ug/ntPnsvwOxZ/+CKQyoHgfEubIULG0hUoseHs7Iz169ejb9++qFmzJnr06AFPT09ERETg2LFjaNiwIdauXZvna6tXr46ePXti3bp1SEhIQIMGDXDq1Ck8fPgw17KLFi3C6dOnUa9ePQwePBiVKlXC27dvcfXqVZw8eRJv3+qRXdbD9u3b8ezZM6SmCh8kZ8+exbx58wAAffv2RYkSupe+GnNdDMNowVnA3SMzx0Bs7EFdvYH4aBi1H4jMBnAXL7FBnF0gqfcp1KH/Gl6Fkx9OAkndRiDOrqZZfz5I0VKgD6+arpGigwvg7GGadedDbm+P+l/1xrktP4NXmeb48SoVGg3+yiTr1khmo39iwxhEmEo0C7F1AHXyyLybX8DPGJkN4GJ5N6Rev36NcePGoUKFCmjTqiUIr0eK1MbBsqo1srh4AXlVMRht/ZZzHAkhgG9Z0EfXDHk1IJMD7hZ811+S1XOqAH9/Mksc/pUTqVwPNPIR8CgM+X7WEAJ4+IDUb2OW2BjLV+Cz7169esHX1xeLFi3C0qVLoVAo4Ofnh8aNG2PAgAFaX/vjjz/C09MTO3fuxMGDB9G8eXMcO3YM/v7+OZbz9vbGxYsXMXfuXOzfvx/r1q2Dh4cHKleujMWLF2tYe8Ft3boV//zzbprA06dPZ8/00qhRI72SEcZcF8MwWnCckFjgRexsLsKdO+JfQeifYdR1VgQRedy4rE1nqC+cMd0GeDVkrTubbv35IFI5iE9Z0MgHMEWTWuEYinfB1WT4IJzdsNUk6+YkEhSvXQP+1avmv7AxZQ05MHffLhszDbfRgBSrAHr3QoH3mxSvLPrnyvsopdi5cye2b9+OpUuXvuvbppYCilRQSkEpBffenW6e54W7y4QISQ0LGY6Ri5MH8CbSNDMj2TiAWFg/CuLuA5qSALzWZxZEAnAcSPm6Qt8jS5X1XtN3+FoWqY3lvk/fQwgH7vOe4OUHgDuXoFTzkElyfl4o1WrIJBLAtzS4Vn1BZJZVLcWIh9APOmoGBQUBAA4fPixKQMw7zs7OmD17NsaPHy92KAxjXdRKoV+GGDipaM3H+Ig7QOT9/BfMFwFcioBUrC/6OHhKKRTzJ0N9LdT4VRucBFz1urCdsVTU/aRKBfiQo4Y3qs0LIYBzEXA1W4h+DHd+MxbnNv+sc78NXRGOw9TQv1Gidk2jrlcnaYlAuhGGremKcMLdd7H/HhOiQZ/qOBtPHoh3KZCillMy/uLFC4wdOxa1a9fGxIkTcze9pxS7tm9DnepVUa7su1n87t1/gKu3wtGzTz/Rj0l+aOIbIPqp8VfsXwnERtOUouKhlIK+fAC8fAidZkmTykEC6lpmb428qFX6D5mVyi2vB4wOjvy8Cc//3Id+9SrDTi4Mw1OpeRy8cR/xfhUwZPYi0b/fGMti+ak7hmEYfXFGKNk0lIh3DkixANCU+MwhKQavBbCxAylXyyJOGAghkA+fjLSRvYD0NOMdU0IAGxvYjJgi+n4SmQ24ioHgb54x4ko5cBaQmAKAzku/w62jfyDxdZTOs6TkhxCCllPHi5PUAAAbRyF5aq7PGDsni7goIS5eSPYoBdnrB5DL9DuFJEXLAF6WUZ1KKcXWrVuxb98+rFixAhUrVsx7QULwx8m/0bv/ALi6usDJ0QlJyUmIj0/AgAED0LNv3rP1WRQndyAlLrP5q5F4+FlkUgPI7NPgVx7UuQjSI+5BkhQLAgI1r0bWVKdymRTxKWlwK18V8CwOYgVDNLJJpMIsRRnpoGol1Gp1roScUqkU+h4SIiQ0LKz/i66i1RKM+PUvjN1zEu4OdpAQgjcpaVCo1Bg3roxFfL8xliXXtxIhBGojnXhYorS0NCQkaP9wd3d3h1ye/4eAMdeVl6xSR4Zh9EQIILc3TiNQfUhkojX3A4Q72AioizehJ+AOA2dzsXMEqdTAok70OHdP2EyYC8WCycIDBb2YJMKUjjbj54Bzt4wx4qSIH0j5OqD3L4ECeTct1AGF8D7gqjUDsXcyYoSGs3Vywshje7C00RdQpqUXOLlBOA6VW32O9rO/NVKEBuA4wN5VuGA0NamNMFuTBeB5HgPHTcHMKZNQxUECpMRDzfOQ5NGQUKVWQyqRADb2IP6VQBxcRIg4t6dPn2LMmDFo1qwZjh49ColEt+EH8fEJiI83YnLATAghoN6lgZf3jVNl5OL5bmpYC0ac3HFfZY/W7b9C9y8+hW8RD9jZyBGfnIIrdx4gjpfizD9nxQ7TMJwEsHXAv2fO4Py/Z9Cza2d4eHhAJpUiKSkZ50NDEX7vIb6dPsMiEqIFpVTziEo08/kcY5VyJTacnJzw5ImWucet3G+//ZZv74/Tp0+jadOmZl3XhxQKBVJSUuDsbCWlcQxjabLmdFfpPUeGgUjmVI7iehsXj27Tl+DIj+tgF/UQ4NU6XChnluv6lQcpVt4ixxlLa9UHJs+HYukMIbFh6LAGjhOSGhPmQlq7gXGDLCCuWHn8GxKKWk48bOQyAxI4BPEpqZBWawpXN8u68ChW7ROMPxOMVS2+RHpiYoGSG1Xbt8agX3+CRCZeEhGA8PeutDNtI1FChAawFnJxsmzZMjRr1gxVa9cFANDURBzavBYB/t4IKOkvJDIAPH7xCiE376D3yPGAo7tF3KTheR7r1q3Dn3/+iZUrV6JMmTL5v+gjQTgO1Le8MCQluQDJOHdfwK2oRRxPXb2KfYuVuw7merxRo0bmD8bIUtLS8O3/5uDb/83J9Vz37t0t5nODYcwlV2IjMDAQv//+O+Li4uDm5iZGTCbVsmVLnDhxQusy1apVM/u6PpS13sDAQINezzAMhBJMtco0jdM+ZGMvjIMXEc/zGDx4MJYtWwaHkhVA/UoDMRFIf3oHtkT4HWS1Vco6MU1XqmFbIgDEu6TFNYL7kLTepyALN0Kxcg7oqxf6X/gTAuLtB5ux/4OkvDjTu2oTHh6OL4eOxT9/HENFLhFIiNFtSFXWMkVLITJNhrnjpmDPnj05mh1aghK1amDW7YvYOWQ0bh45DiKRgOqY4OCkUkikUnReNg+fDhtkOftm7yIk2VQGVkhpRQBHj4JNYW1EZ8+eRVhYGLZt25b9GLF3xqLt+3HlyhVIJBxs5XIolEqoVGpwHIc+384XMeJ3Hjx4gLFjx6Jdu3Y4dOiQ5bx/zIhwHFC0NGhyHBAdoV+Dbbkt4F0KROQGtgzDMNrkSmx07twZo0ePxoIFC7BkyRKrysrqwsfHBz4+xpnOyZjrel9aWhqWLFmCihUronLlykZfP8MUGoQIjTzTU0yb3JDbW0S38UWLFqFly5aoWVPoO0BkcsC3LE5evo2hAwegVkAZ+Hq6gyMEbxKScPX+Y/T86mvMm9dJ5Mh1JylXEXbfb4Ny/w4oj/wGpKaAEgKi4eI/+zl7B8jadYOsc18QueUMs8mSnJyMLl26YMGCBahSJ1BIQMVHg4+8D8S8ACgPSinUmUMUs0v/JVIQnzIgfuVAHFxQDULSfdGiRZg2bZqo+5QXl6LeGHboV1w/cAR/LVuNJxcuAoSApzy4D+qK1KCQgEBma4vA/r3QcspYFClVUpzANSEEcHQDUuKN3PyVE3ojiDi07X1RUVGYM2cODh48qPG8UK3mkZJmxN+BEajVaqxcuRLnzp3DunXr2Ax0AIijG6iDC5AcD/Xb1+DTkiD7sGkqgHRFBmzdvYShJ3ZOH931AMMwH59cn2Q+Pj5YsmQJJk2ahGfPnqFfv36oXr067Ozs2IeaCVFKkZiYiNOnT2PDhg0IDw9HcHCw2GExjPUjnJDcUKQaf1YNQKjUsICLj9OnT+P+/fv46aef8nz+9Zs4HDt/2cxRmQaR20De42vIOvaB6r9TuLfrJ9i+eAofu5z9jF6nZyDNtwQCeg+EtOFnIDaWl9AAhM//oUOHolatWhgyZAiAzIoaN29I3LyhVqlQq0IZVCtbAq4O9qAAouMSkSqxwaG//s713Tx48GAMHDgQp0+fRrNmzUTYI+0IIajRKQg1OgUh8lY4pvbuj9e3wlEEEsgg9AlJAUU01Phq0gT0nj4Zdi6W0Z8hT4QADq7CkJTURBR42l6ZrVAJYiFVBWq1GoMHD8aqVavg5GQZfVt0ER4ejgkTJqB79+7Yv38/O4d9D8lMnMWlq1GsfHVUKVcGpf39IJfLkJqWjjuPnkBFpHj48KHYoTIMw+gsz1uMEydOhLOzM77//nu0b9/e3DEVaoQQNG7cGH/88QcaN24sdjgM83EgnDD/uyrDeHdVOYlQqWEBFx+vXr3CvHnzcOjQoUJ18k5sbCBr3gZHL97Et1v3wk0mhYtMAgIgQanGW6UK8+d3xLTmbcQOVauNGzfi2rVruHjxYp7Hj3AcbjyKwI1HETker1atWt7LE4K1a9ciKCgIFSpUMEllobH4fVIZaeVL4uStK3k+P6tFU8tOamQhREhyymyAtCTD+m5IpMLsJzLxe/W8b86cOejSpQuqVKkidig6USqVWLJkCa5fv44ff/wRvr6+Yodk0TIylLgafhdXw+/meLx0acuZlpdhGEYXGmunhwwZgsGDB+Pu3bt48uQJ0tMtq7zwY+To6IhPPvnEok9CGcZqESJcdEikQEa6fuOLc63HVqjSsIAkgkqlwuDBg7FmzRo4OjqKHY6o4pQqxCkNPK4iuXLlCqZPn45///3XqMfPwcEBa9euxZAhQ3DgwIFc0wEyJsJJhOoNO2cgIxXISINSkZ5nqT8AqHgKqa29kBSxwCkZ//zzT0RFRWHu3Llih6KT69evY/LkyRgwYACmTZtWqBK9DMMwhZ3WMx1CCCpWrKh5fm+GYRhrkzlNmtDwLyNz1hShdFylUoF/b7YNmUz27sSYkwIyufBfCzpZnjVrFnr27IlKlSyvGSajXVxcHLp27YpVq1aZ5PhVrFgRPXv2xKxZszB/vmU0cSw0OA6wdQRsHdG8cWMkxr1F6ZLFYWtjC6VKiTdv43D9VjjO/fcfKle2zIqC58+fY+nSpThy5IjYoeRLoVBg/vz5ePToEXbs2AEvLy+xQ2IYhmHMjN3CYRimcOI4odO73BZn/zmDRQsXoGqVynB2coJUKkVaWjqePHsGVzd3rFy12qKSGVmCg4MRFxeH3r17ix0KoydKKQYMGIAWLVqgT58+JttOr169MGLECAQHB6NNG8sekvOxUqvVuBl+GzfDb4sdis6USiWGDBmC9evXw87OTuxwtLp48SKmTZuGYcOGWU1lCcMwDGN8LLHBMEyhl6FU4fifJ3D8z9zTN3fs2NEikxoRERFYuXIlDh8+LHYojAGWL1+OiIgI/Prrr2bZVlBQEKpUqYLixYubfHuM9Zs6dSoGDRqEcuXKiR2KRmlpaZg1axZiYmLw22+/wcPDQ+yQGIZhGBGJ3/WOYRiG0UtGRgaGDBmCDRs2wNbWshoNMvk7d+4cFi1ahD179pjl+Nna2mLDhg0YMmQIMjIyTL49xrrt378fPM+jc+fOYoei0blz59CuXTs0adIEP/30E0tqMAzDMKxig2EYxtpMnjwZQ4cOZV3rrVB0dDR69OiBzZs3o0yZMmbbbunSpfHNN99g8uTJWLlypdm2y1iXhw8fYtOmTRZbCZacnIxp06YhIyMD+/fvh4s1zJjDMAzDmAWr2GAYhrEie/bsgUQiEYbIMFZFrVajd+/e6N69uyjH78svv4RUKsWePXvMvm3G8qWnp2PYsGHYtGkT5HLLm6Hl1KlTCAoKQlBQEDZs2MCSGgzDMEwOrGKDYRjGSjx48AA//vijxd5NZbSbN28eUlJSsGjRItFiWLhwITp06IBq1aqhfPnyosXBWJ5x48Zh/PjxFteHJSEhAVOmTIFcLsfhw4cL/bTWDMMwTN5YxQbDMIwVSEtLw/Dhw7F582bIZDKxw2H0dOLECaxbtw6//fabqMdPJpNh06ZNGDFiBNLS0kSLg7EsO3bsgIeHB1q3bi12KDkEBwejY8eO6NWrF1avXs2SGgzDMIxGrGKDYRjGCowZMwaTJk1CsWLFxA6F0VNkZCT69u2LX375Bf7+/mKHg2LFimHy5MkYM2YMNm3aJHY4jMjCw8Px22+/4eDBg2KHku3t27eYOHEiPDw8cPToUdjb24sdEsMwDGPhWMUGwzCMhdu2bRt8fHzwxRdfiB0KoyelUonu3btjyJAhaNmypdjhZGvRogV8fX2xbds2sUNhRJScnIzRo0dj8+bNkEgkYocDADhw4AC6du2KoUOHYunSpSypwTAMw+iEVWwwDMNYsFu3bmH//v3Yv3+/2KEwBpg2bRpsbW0xa9YssUPJZebMmejUqRNq1qyJTz75ROxwGDOjlGLEiBGYOXMmihYtKnY4iI6Oxrhx41CqVCkEBwfDxsZG7JAYhmEYK8ISGwzDMBYqKSkJY8eOxe7duy3mbiqju0OHDmHXrl24evWqRR4/iUSCzZs3o2fPnjh48CCcnJzEDokxo40bN6JChQpo2rSpqHFQSvHbb79h69atWLJkCWrUqCFqPAzDMIx1YkNRGIZhLBClFMOHD8ecOXPg5eUldjiMnh4/foxBgwbh119/hbe3t9jhaOTl5YU5c+Zg+PDhoJSKHQ5jJleuXMGJEycwZcoUUeN4+fIlunfvjocPHyI4OJglNRiGYRiDsYoNhmEYC7R+/XpUrVoVjRo1EjsURk/p6eno2rUrJk2ahMaNG4sdTr4aNWqECxcuYN26dRgxYoTY4TAmFhcXh0mTJmHPnj3gOHHub1FKsW3bNuzevRvLly9HlSpVRImDYRiG+Xiwig2GYRgLc/nyZZw5cwYTJ04UOxTGAOPGjYOfn59VHb+JEyfin3/+waVLl8QOhTEhSimGDh2KRYsWwcPDQ5QYIiIi0KlTJ8TExODYsWMsqcEwDMMYBavYYBiGsSBxcXGYPHky9u3bB0KI2OEwetq1axf++OMPXL16VbS74YYghGDjxo3o3Lkz9u7dC3d3d7FDYkxg+fLlaNy4MerWrWv2bfM8j02bNuHw4cP4/vvvERAQYPYYGIZhmI+X9Zx1MQzDfOR4nseQIUOwZMkSuLm5iR0Oo6c7d+5g1KhR+P33363y+Lm5uWHJkiUYMmQIeJ4XOxzGyM6dO4dr165h5MiRZt/2o0eP0KFDB2RkZODo0aMsqcEwDMMYHavYYBiGsRDLli1Ds2bNULt2bbFDYfSUkpKCLl26YO7cuahTp47Y4Risdu3aaN68OZYtW4bJkyeLHQ5jJNHR0Zg5cyYOHTpk1kowtVqNtWvX4uTJk1i1ahVKly5ttm0zDMMwhQur2GAYhrEA//77L8LCwjBs2DCxQ2H0RCnFsGHDULVqVQwfPlzscAps2LBhCAsLw9mzZ8UOhTECtVqNwYMHY9WqVXB2djbbdimlaNeuHezs7HD48GGW1GAYhmFMilVsMAzDiCwqKgqzZ8/GwYMHWV8NK7RlyxZcvHgRly5d+iiOHyEEP/zwA7788kvs2rXLoqerZfI3b948dOjQAVWrVjXrdiml2LRpE/z9/c26XYZhGKZwYhUbDMMwInr/bqqTk5PY4TB6unbtGqZOnYo9e/Z8VMfPyckJq1atwuDBg6FWq8UOhzHQiRMn8Pz5cwwcONDs2yaEsKQGwzAMYzYsscEwDCOiuXPnokuXLmzKQyuUkJCArl27YsWKFfjkk0/EDsfoqlSpgi5dumDOnDlih8IYIDIyEosXL8bq1atF2f7HUL3EMAzDWA+W2GAYhhHJX3/9hdevX6Nfv35ih8LoiVKKAQMGoGnTpujfv7/Y4ZhMv379EBUVhT///FPsUBg9KJVKDB48GD/88APs7e1Nuq2UlBSTrp9hGIZhdMF6bDAMw4jgxYsXWLp0KQ4fPix2KIwBVq5cicePH2Pnzp1ih2JyK1euRFBQECpVqsSGFliJadOm4auvvjLptKrp6emYO3cuoqOjTbYNhmEYhtEVq9hgGKbQS0xM1PocpdSo28u6m7pu3TrY2dkZdd2M6Z0/fx7z58/Hnj17CsXxs7Ozw/r16zFkyBAolUqxw2HycejQISgUCnTr1s1k27hw4QLatm2LunXrolSpUibbDsMwDMPoiiU2GIYptFQqFb7++mt06dJF4zKnTp1C6dKlcfv2baNt99tvv8WgQYNQrlw5o62TMY/Y2Fh0794dGzZsKFTHr2zZshg0aBCmTp0qdihWR1syiOd5o27r8ePHWLduHZYuXWrU9WZJTU3F+PHjsWXLFuzduxdffvmlSbbDMAzDMPpiiQ2GYQqtGTNm4Mcff8y3IuPp06do2rQp0tPTC7zNAwcOQK1Wo3PnzgVeF2NePM+jT58+6NSpk9Zk2Meqc+fO4HkeBw4cEDsUq3D//n3UqlULly9f1rhMkyZN8MMPPxhle+np6fjmm2+wceNG2NjYGGWd7ztz5gzatm2LFi1aYOvWrXBzczP6NhiGYRjGUKzHBsMwhRKlFLt27dJ5+ZiYGJw6dQpt27Y1eJuPHj3Cxo0bWV8NI7pz5w5Onz6t8fnTp0/jyy+/RKVKlQq8rQULFiA+Pt5kd8OtweLFixEUFISqVauiTJkyYodjseLi4vDpp58iKioq3+VGjhwJJyenAjcRnjBhAkaPHo2SJUsWaD0fSkpKwtSpU8HzPA4dOgRnZ2ejrp9hGIZhjIFVbDAMUyhRSpGUlKTXaxISEgzeXtbd1E2bNkEulxu8HuadkydPolatWvjrr7+0LlO7dm2ty+ji77//xurVq/H7778X6uMnl8uxadMmfPPNN0apYDp79ixu3bql8fkDBw7g5cuXBd6OuR07dizfpMb7fvrppwJtb9euXXByckK7du0KtJ4P/fXXX+jQoQM6d+6M9evXs6RGIWLs3lIMwzCmxhIbDMMUShzHITAwUK/X1K9f3+DtjRs3DuPHj0fx4sUNXgfzTtZ0q2lpafkum5aWhoEDBxp8ov7y5Uv07t0b27ZtY8cPQPHixTF+/HiMGzeuQOv5/vvv0aRJE9y/f1/jMuvXr0e9evW0LmOJXrx4odfyz58/N3hbd+7cwc6dOzFv3jyD1/Gh+Ph4DB48GMHBwThy5AiaN29utHUzluGff/5B+/btNT7/9OlTtG/fHs+ePTNjVAzDMIZjiQ2GYQqtUaNG6bxsu3btDO7+v2PHDnh4eKB169YGvb4gLl68iPXr12t8/uDBgzh48KD5AjKS27dv63XxGBkZifDwcL23o1Kp0LNnTwwcOFCU42epWrduDQ8PD+zYscOg1798+RLjx4/XadkXL15g0qRJBm1HLHXr1tVr+Tp16hi0nZSUFIwcORJbtmyBVGqc0cVHjhxBp06d0L9/f6xcuRIODg5GWS9jOUJCQtCqVSuEhoZqXIZSiqNHj6Jx48aIiYkxY3QMwzCGYYkNhmEKrdatW+t8QTFr1iyDthEeHo7ffvsNs2fPNuj1BXHixAk0adIEf/zxh8ZlwsPD0bFjR6xYscKMkRWcj4+PWV4zY8YMcByHOXPm6P1aY3n69GmejyclJYl6wTFnzhz8/vvvBiWM9B0adOLECajVar23I5ZPP/0U5cuX13n5oUOH6r0NSilGjhyJ6dOnG/Te/lBsbCz69euHc+fO4dixY2jUqFG+r0lOTtY4RI9Syi6ILdTGjRt1Hkr2/Plz1jCYYRirwBIbDMMUWoQQnRIO7dq1Q+3atfVef3JyMkaPHo3Nmzcb7W6qPqZPn67zyeuMGTOQmppq4oiMx93dXa9jUrNmTXh4eOi1jaNHj+KXX37B7t27RTl+6enpCAoK0tik8/Hjx/Dy8sLUqVNFGQ8vkUiwadMmjB49GsnJyXq91s/PT6/lfXx8IJFI9HqNmKRSKWbOnKnTsk2aNEHTpk313sbWrVtRpkwZowwT2bt3L7p3745Ro0Zh8eLFsLOzy/c1+/btg4eHBx4+fJjn85RSeHl5Yd68eaxfg4XRNxkZFhZmokhMS9t3WkpKitGnWzanyMhIrQmnGzdu4OzZs2aMiGHExxIbDMMUaq1bt0ZAQIDWZQyp1qCUYsSIEZg5cyaKFi1qaHgGUygUWqeZ/FBaWhquXbtmwoiMb/r06TovO2PGDL3W/fTpUwwYMAC7du0S5fgBwIoVK3DkyJF8l1u8eHGBm6MaqmjRovjf//6HESNG6HXxWq9ePTg5Oem8fIsWLQwJT1Q9evTQqWrDkGqu69evIzg4GNOmTTMgsneioqLQs2dP3Lp1C8HBwTpXsN2/fx/dunVDRkZGvsvOnDnTKoe7fcxq1Kih1/I1a9Y0USSmQSnFlClT8Omnn2pc5tq1ayhevDiuXLlixsiM486dO6hbty42b96scZm7d++iSZMmWL16tRkjYxhxscQGwzCFWn5VGxUqVDCoWmPTpk2oUKGCQXdijcHGxkbvniAVKlQwUTSm0aFDB1SvXj3f5apVq4YOHTrovF6FQoGuXbti/Pjxoh0/QGjuZ4plja1JkyaoUKECNm7cqPNrnJ2dMXr0aJ2WlUqlmDx5sqHhiUaXqo06dero/R5LSEjA+PHjsWnTJnCcYadxlFLs2LEDffr0wZQpUzBnzhzY2Njo/PpDhw7pdbd73759hoTJmEjfvn11XtbJyQlBQUEmjMb4Vq5ciSVLlkClUmldLjIyEs2bN0dsbKyZIjOOCRMm6Dxb1NixY/WaoclSnD17Fj///LPG54ODg7F//37zBcRYBZbYYBim0OvevTu8vb3zfG7p0qV6r+/q1av466+/MGXKlIKGViCdO3fWedkmTZroPVRDbIQQnappZs2apdcF4IQJE+Dl5SX68dOnR0N+VUemNmXKFJw4cQJXr17V+TXjxo3TqWqjf//+KF26dEHCE02PHj3g4uKi8Xl9ZzKhlOKbb77B/PnzUaRIEYNievHiBbp06YKIiAgEBwfrlBz8kL7DgqxpGFEWnufxyy+/4L///svz+X///Rc7duywyuEMjRo1wueff67TsmPGjIG7u7uJIzKunTt36rxsYmIijh07ZsJojEulUuHvv//WeXlKKU6cOGHCiIzvwIED+Oyzz3Du3DmNy9y7dw+dO3fGkiVLzBgZY/EowzAMQ1++fEmLFStGAVAAVCaT0eXLl+u9nri4ONqsWTMaGxtrgij1ExUVRe3s7LL3SdvP6dOnxQ7XIDzP5zhuH/74+flRtVqt8/p+/fVXWrx4cYs4fpcvX9bp2Lm6utK4uDixw6WxsbG0WbNmesUyffp0rfsmkUjoo0ePTBe0GcyePTvPffP19dV7Xd9//z1dsWKFQXHwPE83b95MW7ZsScPDww1aRxZd35tZP1u2bCnQ9syN53nar18/nfZt4MCBYodrkH///TfffXNycqJv3rwRO1S9lSlTRq/35/fffy92yHopXry4XvtnTd/vPM/rdfzkcjlNTEwUO2zGQrDEBsMwzHuePXtGQ0NDqUql0mn5mJgYqlQqKaXCF3K3bt1oSEiIKUPUy8SJE/M9MWjSpInYYRbIqlWrNO7bypUrdV7P3bt3qbu7u0Udv/bt2+d7/ObMmSN2mNlCQ0Npt27dKM/zOi3/5s0bKpPJNO5b+/btTRyxeXTt2jXHfnl4eNDIyEi91nH+/HnavXt3nX+373vy5AkNCgqiy5cv1/mzLT/NmjXT6cLDx8eHpqWlGWWb5hIWFqbXheO9e/fEDtkgn376qdb9mjFjhtghGqRPnz56HT9L+szXxddff63zvrm4uNDk5GSxQ9ZZZGSkXscOAD1x4oTYYTMWgiU2GIZhCqBFixa0Zs2a9OXLl3TZsmV01apVYoeUQ1RUFJXL5R/N3Zy8qNVqWq5cuVz7VbZsWZ2rNVJSUmiVKlUs7vjld2fcUqo13rd69Wq6bNkynZfXlry5e/euCSM1rxcvXtAffvhB57+3mzdvZichYmJiaLNmzWh8fLxe21Sr1XTt2rW0TZs29P79+/qGrNWZM2d0uuhYvXq1UbdrDrt379brwmrv3r1ih2wQbcdQIpFYZbUGpZReuHBB52NXp04dg5KFYnrw4AGVSCQ67d/s2bPFDlcvKpWKOjk56fX39+zZM7HDZiwES2wwDMMUQEBAAAVAPT09adOmTS3yBKl3794aTwjKli0rdnhGkZaWRnv16kU9PDyoh4cH7dmzp9a7xFkXmVmJj6+++op27drVIo9fu3btNB4/S6rWyMLzPO3Vqxc9d+6cTsvHxMRQR0fHXPvWvXt3E0dq2UqUKEHr1q1LX716RTt27EivXbum1+vv379P27RpQ9euXavXcCx95Fe1YY3VGpRSeu/ePb0urKx5uJSvr2+e+9S2bVuxQyuQVq1a6XTsjh07JnaoBunfv3++++bi4mJxiW9d9OjRQ+e/vapVq1rk9zYjDpbYYBiGoZRSnqdUraZUrXr3k8+XZWpqKvXz88v+gvXw8KATJkww2UWEobSVdv7yyy9ihyeKNWvWUEIIbdSoEV25ciUtV64cTUhIEDusPF26dCnPYyeVSi32pDUhIYE2b96cRkdHU0qFyoGwsDCNy0dERNDmzZtTV1dX6uvrS6dPn16oT1aTkpKyLzhdXFzo+PHjdX6tSqWiy5Yto0FBQfTJkyemC5LmX7VhjdUaWZo0aaLThdXnn38udqgF8uTJE2pvb59jn0qXLp09xNJa6VK1YY3VGlkePHhAOY77qKo1soSFhVFCiE5/f/v27RM7XMaCsMQGwzCFl1pFqSKV0rQkSlPi8/5JTaQ0PYVSpSJXoiM0NJS6ubnl+JK1t7e3yEZ58+bNy3VC0KZNG7HDEk2vXr2ykwOEELpt2zaxQ9Iqr2ZqXbp0ETssrW7cuEE7dOhAo6KiaIMGDWixYsXEDkk8PE8pn5U4VeebNP3vv/+oq6tr9rH29PTUKdkTHh5OW7ZsSbds2WK2CzZ/f/88LzjkcrlVVmtkOX36tE4XVv/++6/YoRaYQqGgq1atol9//TXdu3ev1V7sf6hhw4YfZbVGltatW2vcN7lcbrGJb110795dp2oNS7uRxIiLJTYYhilceF5IUqRqSWZo+1GkChcmlNKVK1fmqNaoW7euRZ/knjt3jn755Ze0RYsWdNeuXWKHI6qyZcvmOEGytbWlS5YsETssjd6+fUtLlixJAVBCCG3cuLFVnNB9++231MXFhQLCsARrPtHWm1JBaWoCpYmxlMa9ovTty5w/CdGUJmd+pnxwIblkyZIc709CCHVxcaFXrlzJc1MZGRl0/vz5tHPnzvT58+fm2LtsBw8ezPOiY9q0aWaNwxTyq9qw9mqNj93/2bvvsCiuLg7Avztb6EgVLCB2xd6x96hg7723iAWNJSYasX4qJqKxa4yx9xZLjD2aiL33XhAFpNctc78/BlCEhd1ld2fR+z6PT8LulDPssjtz5txzz549q/G1c3Nzy/cJnLt372o8vi5duogdXp5oU7XBqjWYzxFKKUU23r9/j507d2Lv3r149uwZUlNTs1uMMSAbGxtUrVoV3bp1Q4cOHWBlZSV2SAzzZeHVQGoSQPm8b0tmifpNmuHy5cuoVasWfvnlF9SpUyfv22V0QikFoiLAv3gM+vopkJwoPGFlA+JREpxXacDJFYSQjHWUSiWsra2hUqkyHrO0tIS9vT1evHhh1p+9CQkJsLS0hFQqFTuUHFFKMXfuXCxduhQREREAADs7O/z5559o3LixyNEZEaWAIhlITQTUqtyXT0cIILcGLG0AToI2bdrgr7/+AsdxKFSoEDp06IBZs2aB53ns3LkT/v7+GaveuHEDkyZNwsCBA9G7d+9M73VT2bRpEyZOnIjIyEjY2NhgzJgxmDt3rsnjMLQzZ86gadOmGp8/d+4cGjRoYMKIGF2VKlUKT58+zfL4qlWrMGLECBEiMqyuXbtiz549mR6zt7fH8+fP4eTkJFJUhtGwYUOcP38+2+fc3d0RGhoKjuNMHBVjzrJNbDx69AhNmzZFREQEWrZsiWrVqpn1id6XgFKKuLg4nDlzBpcvX0bjxo1x+PBh2NjYiB0aw+R/lAIqBaBMMehmHz55irgUFWrVrm3Q7TK5o4nxUJ//G+oT+4GIMOFBTiJcIALCa86rhf93dYekRUdIGrQCsbHDrVu3UKtWLSgUClhbW8PS0hIzZ87E0KFDYWlpKcrxfGlu376NBg0aICEhATz/MZE4a9YsTJ8+PeNnSikinz7D66s3EHbnPlLiE8BJJLB3LwiPGlVRtHoVWDs4iHAEelArgcQY3RIaWRDA2h4OboUhkUjQv39/zJgxAw5pv4OuXbvi+PHj+Ouvv1C9enXMnTsXjx8/RnBwMNzc3AxxFMxnihcvjhcvXmR5vGTJknjy5InpA2J0EhcXh+rVq2ckNyQSCb777jssWLBA5MgMg1KKadOmYcOGDUhKSkLNmjXxxx9/oHDhwmKHlmchISGoW7duts8tXLgQkyZNMnFEjLnLkthQKBQoWbIk7OzscOLEiS/iDyO/OXfuHHx9feHn54ft27eLHQ7D5G+UCgkNlcI42ycEsLAF2F0Dk6C8Gurj+6DevR5QKiFUpGqBEEAqg6TLYMy/dA/TZ8yAk5MT5s6di0GDBsHCwsKocRtK+le2GHfldfXhwwfMmDED+/fvR1hYGHieR/PmzXHixAkkRkXh4oat+GfZakS9eAUA4GRSEAjHxavVoDwPwhF4+7ZCI/9hKNuymfnenUtJBJLjDLa5py9fw7V4WdgXKJDx2PXr19GqVStERETAw8MDJUuWhL+/P7p27Wqw/TJZbdmyBX379s3y+I4dO9C9e3cRIjIMSnkgIQZIjhfevyqF8H1JCCC3EqqHrO0BK7t88XmTm9evX+P58+eoU6dOvvm8Z4A+ffpg69atmR6rWrUqrl279kW8LxnDypLYOHr0KHx9fXHjxg1UqVJFrLi+esHBwZgyZQrCw8NR4JMTG4ZhdGDspEY6QgBLW4CY30UX5dVAVBhobCSQEAUoUoTfi0wO2DqB2DkBLkVApHKxQ80VjXgH5aq5oE/v52k7sU7u2CBzx/g5/4NMJjNQdMZBk+JBw56CxkYA8R8AlVJ4Qm4J2LuAOLqBuJcAkZtvpUlMTAxmzZqFP/74A0qFEseWLMeecVOgTEoS0lLZj4jNwEkl4FVqFKtTE/3+WI2CZUqZJG6tJccDKQmG3y4nBeycAE4CSimqV6+OGzduCE9xHAYNGoR169YZfr9MFjNmzMD8+fOhUCggl8sxbdq0TJVH+Qnl1UD0OyA2Iq2qjSDHBLFUDji6C5837EKSEcHatWuxatUqpKamomvXrvjpp5/MN8nNiCpLYsPf3x9///03Hj16xD7ARPTmzRt4eHhg165d7G4Mw+hLpRDGu5sCJwEsbD4OhRAZ5dVA6GPQsCfCxTAh2VxApp3QEg5w9QQp5g0iM887WfzbV1DOnwAkxH8cYqIvTgLY2kH2/c/gChczTIAGRpPiwD+8DES9Ra4XHoQDCpUAV6q62b5+ABD+JhT/a9Ia6mev9Fqfk0pBOA7dl/+MukP6Gzg6PaUkCIkNY+GkgL0z/ti4CaNGjUJSUlLGUwULFsTRo0dRvXp14+1fC1StFi6SlSmgahUIJxESp/auIDLzT5jqIiwsDIUKFRI7DL3R5Hjg/fOPCVJdWNoAbsXN+jOGYZivW5buY2FhYShZsiRLaoisaNGisLCwQFhYmNihMEz+xPOmS2oAwsW2SgGYwUkfTYwFfXQJSP7kLnK2d8XTHqM8EP4SNCoUKFUDxMm8Ttzph/dQzv8OSIgTXte84tVAQhyU87+D/KflIC7m05uAUgr65iHo46v4mMzIZbgN5YG3T8FHvAZXoT6IcxFjh6mz5Lg4bOjQC/zLUL23wac1e902bAxS4uLRdLx/LmsYmUph3KQGAPAqpMZEYuTIkVAqlXBxcYFcLs/4d+rUKdESGzQlETTyDfDh7SfJRpL2bqUAHoA6uoG4FAVsCnwR55X5OqkRFwmEv9R/AymJwKt7oEXKgFjmr/5vVK0ClKnC94dUCsgsv4j3IwDhmNTKj03RCRGS95zUbG60MIypZElsqFQqyOVfVoY9v5LL5VAq9ciqMwxj2qRGOmUKIJEKJxUioXGRoPf+0yMBQAGVEvRBCFCiKoh7caPEpyvK81CuWWC4pEY6ngcS4qFcMx+y738GMYOyVkop6NProC/v6rM2oEwFf+MUSIUG4Mzk9QMAnuexrlNvvL11R7i7bwD7vvsBBYoUQvXunQ2yPZ1RKjQKNQELqLE4aD5KlCkPT09PeHh4iNpYnFIe9PVD4EMoslYTffb/0e9Bo98Bto5A8cogUvMe+vWlovFReUtqZGyIB0IfgRYtC2JhnfftGRGlFIj/ABr+Eoh+n/lJqRwoWAxw9TDrYXwaUQrwKkCpEP6bHUIAqQUglZnlMFmGMQad3+kbNmwAISTbDtE5CQwM1Do7SghBYGCgrqExDMMIeLXmL3tjU4o3NTZNjk9LaqihdVPN7Lbz7Aboh7eGCywP+DOHQB/eyvvwk2w3rgZ9dBv86T8Nv2090DcP9UxqfLadu+dBPz+RF9H5Fevw+PQ58AZKagAACMH2EeMQ906k40xJMM57UoORfXvim5YtUa5cOXGTGjwP+vRGWlIDyP1zJu35hGjQR5dBRfx81BsVkoZITRKqFlKThJ9z6Q1jLqgyFQh/YcAN8sC7Z6CGTDQbGE2OB73zD+jDS0B0eNYFVArQt49Bb54C//Ku0Eg1v6BUeA+mJuV8npPeYyzZtJ9VhkYj34I/fxDqoxuhPrwB/Jk9oKFPkc2kngyje2LjazJ37ly0b98ebm5ueUq2PHjwAJMnT0bVqlVhZ2eHQoUKwc/PD1euXDFswAzDCMQ8eVYrRTnhpZSCPrpisKoG+vSa6BchNDUFqp1rjb4f1c51oKkiVPh8gibFpQ0/MQQC/u55UH3G0RtY9JtQ7J88zfAbphSKhETsHivCdH+UAqmJJt4nL+7nGtI+Y17dBeKj9NtAajLo0xsGq9oxOkqFyr/kOOECUa0ULiTVyrQLxjjheTO+wKKUAu9fGD5GZSoQZZ5DpWlCjJDgT0nvR5PLsYe/BH181awTNRnSP3t0unFDhURsnqahNj0a9gLq3b+C37kE9PYF4Pld4OV90PtXwB9YA35rEOjT22KHyZgZkyU2pk2bhuRkcU8cdTVt2jRcvnwZ1apVy9N21q1bh7Vr16JmzZr4+eefMWHCBDx8+BA+Pj44ceKEgaJlGAaA8MWvFvmCztizsGTn/Yu00ngDncCqVAapHsgLPuQ0kGKC743UZGFfIuIfXjLgxQcVLiJf3jHQ9vT376r1UCuNc0LNq9W4secgPrwwQIm9LpQp4lzMmjqZ8rmY8Kwl/TqhQHI86PvnBgvJaGjaxWBun+UqhbCcuSY3khOMM2MPAMS8F3pXmBGamiT0l9K1ajE2AvRFPrhIViTrX32RmvSxD4eZoy/ugT+wGohIqwz7NO70/4/9AP7YZvA3z5k+QMZsmSyxIZVKYWmZv8axPX/+HGFhYdi8eXOettOrVy+8fv0a69atw/DhwzFp0iRcvHgRTk5ObMgNwxiaOZxomTixQikFffvE0FsFIl6LWrWhPrnfNM3PCIH6xH7j70cDmhSXdvfTkBdHFPTNI2F2HJGoFAr8u3q9Ue/QE47Dv6t/N9r2syVWdY9KIWpJOY3QbzabLCLfmPfd8fS74tpeBFI+bXkzTG7EZjMMw2AoEPfBiNvXHQ19DOj7efMhFNREfXP0wqvzeG5BhZ4cZo5GhIL/a7NQfarF3xT99xDo01smiIzJDwyS2Dh69CgaNmwIGxsb2NnZwc/PD3fvZr7Tl12PjdTUVIwfPx6urq6ws7ND+/bt8ebNm2z3ERoaisGDB8PNzQ0WFhaoUKEC1q9fn2mZM2fOgBCCnTt3Yu7cuShatCgsLS3RvHlzPHmi+0m/l5eXzutkp0aNGrC1tc30mLOzMxo2bIj79+8bZB8Mw6TJy4k/4YQpW63sASs7QKZnMpZXm/YkNyFa+7tyhUuBVGsJ4tMBpGYbEM8KmpelPBCZ/WeysdHkRNBXT7X+PZJyVWCx4USWf/JFWiSmKQV9/Qw0yUh3NnPbfdjT3BM4Ujm4yk3A1e8MrklvcPU7g5SomvM6KgUQqf8sJHn18uIVJH7QbthCi8kBmPbgKoJV0VjKx6JU4wZarUfVatzcezAvYepO34sLWyeggBvg4A4UKCh8zphq33lEkxOAxNiPDxQsBlK+LkjV5uCqtRCag6azdwEp5wNSpRmId33g81l61Cqh+sNc8WrN3yMyS8C6gPDv04aMOa0jEsrz2je4tXMGPLyBEtWA4lWAwqUBuVXu68WbT2KDqhRp02Nn/c4glZuAq+Wb6R8cPp8Ni4CGGyh5Zww5VQ+lTzef27mLSmGeCbhP8FdOglRpCK73RHDf/g+SUQuAwiUyniff9AY34EdIRi0QngPAh/zFem4wAAyQ2Ni0aRP8/Pxga2uLBQsWYPr06bh37x4aNGiQa4PRoUOHIjg4GN988w3mz58PmUwGPz+/LMu9f/8+Y9jG6NGjsWTJEpQqVQpDhgxBcHBwluXnz5+Pffv2YeLEiZg6dSpCQkLQp0+fvB6qwb179w4uLi5ih8EwX5a8NA21sBZOEJQpwsm3zEL/6VtN+SWr5Zh34ukNzquS0Djt+U3Q0Ee53JUkQjd9EdCXuiWjaehLKFfOyfinvigMLeGfPjDaPg2FxoTn/n6RygCbAqChj0EfXwYoBVe8EkjRsprXIQQ0NsKwwerg9bWbWs82I7W0wN3DfyH61Wud9xP59BlSE000TINX61/OrVYKfRmSYoXX29JG+MzRhUh9U2jkGwgzoKThOCAuElCkZF5QbgVSojLASUDfPARUCnCe5QE7p8zbi9D9dTYZTVVqnFSYTUPT36rKzBqjajszmFQO4uYFyORA5GsgMQbE2h5w9dRqH2bTeDPiTY6fozQ5HvzT6xn/siZ9qFC1IcZQ0txQmkNigwhJjYxzF3UO5y5mMFQ3BzQhBnhxD5BIQV88AOJjslkIoA8+61EY+wF4+8wUITJmLst0r7pISEjA2LFjMXToUKxZsybj8QEDBqBs2bKYN29epsc/dfPmTWzevBmjRo3C8uXLAQD+/v7o06cPbt3KXFL0448/Qq1W4/bt23B2dgYAjBw5Er169UJgYCBGjBgBK6uPmeWUlBTcuHEjY9paR0dHjBs3Dnfu3EHFihXzcsgGc+7cOVy4cAHTphmhqRrDfM30Pcni0qZpVSk/nkBIZMJ0afoMx6BqmGq0n1A++/m0i5/hJEChkqBqpdBYjfLCrCA5bxmIjzZkqFqjb54LVQzaJojiY8BfPJPxo6RjfwCA+uhO7dYnRNhn+aq6BWoI2iSPUpPAXziIjNeYk4CUqZXlgjETSkFFLBUPvXkHhOO0Gnbw1yzhzlvxunXg7FVMp/1QniLszn141ampV5w6yctQt+R44T1NOCEBK9HjFEysoXZJccj0+fLuOSgAYuMAWHw8/yIuRUAIBz78lXCRqEgGKVUdxMUjc5I0Od5UkesmfRrNLIhwnKpUQCLPvsJKrRLWN8XwOW2kJuW+DCB89lEqJO3SXxd7F+1vEihSdE/QGUGuSVylQqgUyqmyhlKhAjJLNYfIcopZIhHec+nnLkQlJMKl8uzPXcyssuhT6c1A6RWh/yBxLwbYf5YUPb5V+Oys0ezjg4QDfXwDpEhJk8XKmKc8nXUfP34cMTEx6NWrFyIjIzP+SSQS1KlTB6dPa27GduTIEQDA2LFjMz0eEBCQ6WdKKfbs2YN27dqBUpppP61atUJsbCyuXbuWaZ1BgwZlJDUAoGHDhgCAZ8/MI5sXHh6O3r17o3jx4pg8ebLY4TDMl0XfQon0O8uZEiPpJ6l6nKiasipSqch9h9Z2IBIpwPNC+bhPe5AarQCnwjmvJ9LdK5qSlLnUWwdcVR9whTzBP7gJ+uKRdisRDjRZywsBA6KU1+5ilVJ8+hqT9PL+3GYmUKbk/LwRJcfGGHaK15z2FRNjkv3kuRLLvqAwDEVmKfTq0Pbi82MAedu/vrS9y5t+gZv+vkuv6LD87MKX8uZzp/9Tml5fCythzH9uSW5zKofX9gJWmQpEvAIkUpBiFUEKFgNNTQLea9mU11wulHP7rrJzAlejFUiNViClqgsX/tluxxwrGnJ4X9GPyW4Q7mPCVNP3pzm9Rz+XlKBfYpDyoIlmmixlTCpPFRuPHz8GADRr1izb5+3tNY8fffnyJTiOQ8mSmbNrZctmLquNiIhATEwM1qxZo7H6Izw881hNT8/M5XOOjsLYz+hoce48fioxMRFt27ZFfHw8zp8/n6X3BsMwjFGkncwQmQXo6/vgUxJBSlYDKVMT9Mpfmk8KRbv5qP+OJa27AdChWiMdJ8bB6rhPwoFUqA/iXBj86/ug718YJSpD+LyvllH3peWQF9ElRgsXHJY2gNwSUFqKmnzSnjFeSzOpbMiNRCZU9KV+lmwlXNYKwXxySJlwEsDRHeB50IgXwnAip0KgBT2Bd+ZxQ1ArOXze0Mg3QEoiKK8GKVgMxNFdqFh8djO7DRkvRmPg1UJySmYh9Neg9JPKoVwqOc1NXr4z8st3AGNUeUps8GnlpZs2bYK7u3vWjUvztPlM++jbty8GDBiQ7TKVK1fO9LNEIsl2ObEbyygUCnTu3Bm3bt3CsWPHzGZYDMN8UfT9Hk8vl890l4NkuVOufRwmPDmysMp92EZKEiilIISAvknrrVG4FIiNA6iFlebEhr4NVPOI2NjpdSeQFCsNrlwV8KEvwN+8qP2KPA9ibafz/vKKECLcOdSmMkYqA1e5CYijO/hnN0Gfa9EJ3sIm70HqydbFBZxUAt5I071+ysbF2ej7AJD3v+tPX2dbR6FBoy6JDT2rmPJMKgO0GZGXXoEit8z8388rUziJSRNfWssuJo4THrf87G/J0kaYDSVTxZUZHZO2Q52s7ISEd0KMMAyDxABOhQAbBy33I9MzQAPLqR/WJ7OGUWUqSAFXIQmQ7XY0VHKIKbe/e2WKMEyKcGn9e2zTzmmyOScwx7+7dHaOH8/FdEE4EFsHg4fD5D95yjykV1sULFgQLVq00GndYsWKged5PH36NFOVxsOHDzMtlz5jilqt1nkf5oTnefTv3x8nT57Ezp070bhxY7FDYpgvE5EAVI8LKV4lXEhL0hrEcWnjVvW9m2rCuwfExgGUvsh5IbUSiHgNFPQE8aooDPWwsgdNTQaSNJVwkpx7OBgR8dRvrKykTVq1xl+7dVyT6r3PPLN3SevmnwOJFFyN1iC2DqCRoUBSHIibF6giBYh+l/06hIDYm+iCPxtFq1UGv1a75FTJhvVQsEwp2LoKDbUr+LWCa6kSuPDbxlzX5aRSFKpQPk+xak3fiziphXCRn17mnj40Q9dGfvr05TAEW6fMs6LYOAjHIBV+H8TeGdTCCvRDqPAZ4+oJyvMgzsJQtyzNQs31IoQQ4TX+9HVRKTMnWeVWwgWkIjnz41INvTdMSK1W4+7duwgJCcGbp48xc1jP3FdSpgo3/qztgAKuH2dD0ab5KCH6N9g2MOLonn2fDSs7EI9ywnNqFYhLUeHxhGyquDmpaN95OSIccrxrI7MQEgLpiXJCNL9+Yn2GaIGUrAR67gDg5gni4AJYCclEUqwcUMAZ9P5lkFKVM/f1KV8LNCkepLwJeiwxZi9P7+5WrVrB3t4e8+bNQ9OmTSGTZf7Cj4iIgKura7brtmnTBj/88AOWLl2a0TwUQJZZTiQSCbp06YKtW7dm2/wzp32YkzFjxmDHjh1YvXo1OnfuLHY4DPPlkkj0nxklNUk4qZNZQpjzPVW/xqEgpr2zquXFK32eVnbr6gECAsRFgL64k0PDVSrahTHxKCEkh3S5e+NUEFzNRqAxH8D/d0LHHXKiJTaIoxtobokNmUXGHSniUgTEReixQaPfgdeU2KAUxKGgASPVjUfNalqP5/YZ1Bd1Bn6cvaz5RKH/ljaJDfcK5SCVm+guK8dlPwQhN5QXLpjllgBIWqPGBO2naU4n0t1x4lIE9P3zjz87F85IWgAAcfMCAcBfPwH6/DZIoZLCjD3KVPCvH2RpkEtcPEwVuu5kFpkTG5QH1J+83hTCNWZ6s9B0mno2GFF4eDhCQkIQEhKS0Xi/QoUK8PHxQVs/PyDlfe5/g4pkIPyl0DDTuWhav4JYYYaU3FjYmE/ljVNh4NW9rJV+KoVQkVeopHBRr1SAvnsOGvrwsw0Q4buRy77qW1SECJUkms5HCAfI0xJMlBfOZbJLmhIiJG/MFLG0BspUAylcAly5GhmPc9WEm8Hq+5dBfNqAfNJQlGvaFTTiDYhLLv3CmK9Cnt7d9vb2WLlyJfr164fq1aujZ8+ecHV1xatXr3D48GHUr18fy5Yty3bdqlWrolevXlixYgViY2NRr149nDx5Ek+eZJ1ub/78+Th9+jTq1KmDYcOGwdvbG1FRUbh27RpOnDiBqCjjTEe4adMmvHz5EklJQgnlP//8gzlz5gAA+vXrh2LFtOvcHhwcjBUrVqBu3bqwtrbG5s2bMz3fqVMn2NiIVy7MMF+UvJyUUF4oLRYzBj0Qa3tQWycgIZfPQrUK9MlV7TfMSYH0JpUmRuQWIGUqgT66rX1yIyociqGtdd8Zx4GUrggiF+fOIylUEvTpDeQ45CklEeqTm3TbsIW1UFIukqLVqsCxmAeiX+Z+gbRl8ChsGTxK530QjqBW7+76hKc/qVz3Si61EoiPNMC+RUpsyC1B7V2AuA8AKOire6Cv7mW/cGxEzjNUyCy0TsaKgpNkrdr4VEo2FW4SmdE/9xUKBW7evImQkBBcvHgRUVFRcHV1hY+PD7p164ZZs2ZlGQJO3yuBeC1mRor/oN1ynzOj15FIJKCuHmlNTz/5LFWmavm9R0EKajHFrVg0zXICpFVnaFFhI7UQvaooN1zN5uB3/Qr16V3ZJuX4zQs+W4ED12GEiaJjzF2e03a9e/dG4cKFMX/+fAQFBSE1NRVFihRBw4YNMWjQoBzXXb9+PVxdXbFlyxbs378fzZo1w+HDh+HhkTmT7+bmhkuXLmHWrFnYu3cvVqxYAWdnZ1SoUAELFizQsPW8++2333D27NmMn0+fPp0x00uDBg20TmzcuHEDAHDhwgVcuHAhy/PPnz9niQ2GMRRzuBshwsUHKVIa9KEOPSW0UaiEMJOKSCQtOkL1ILvmbgbG85C06Gj8/WhALKwAdy/g3QsYstEb8fQW9W4qx3FoPHoEDkz5SaspX/Xah0SKOoP6GmXbGllYi9PwU2YpXo8NAKSgJ2hc3pMzpKCn+dzl10RuBaQKU7/yPA8um6GFGY9LpB+HbxgIpRRv3rzJqMZ48OABpFIpqlatCh8fH/Tu3RvOzlokFRwK6pew0AbhhCFKZoQULgUaEy7MOKTjZykpUgbk8z4q5oRwQmJCpU8Vafr6Ztg/5DPE3glc+6HgD64TpovWUHFEQUA4DlyrPiCFvEwbJGO2CP2so2b79u0BAAcPHhQlIOYje3t7BAYGYsKECWKHwjD5iyJZtGlKAQBW9ia/K0IpBX1wMa3fQl4vjglgYQVStbmoiQ2qVkMxoRcQF228KeoIAewdIf95K4gBGl7riyqSwV84aJj3LSGArSO4mm1Eny0kKSYGgSUqIyU2zuCvIeE4NPQfhq5LFhp0u7miFIiLMP00l7ZOovcz4MOeAu+e576gJgVcQYpXNv/EBiC8zioFXj17Ak+PolAqlRkNmGUyGV6+eo1iJUsbpLdGUlISrl69ipCQEFy+fBkJCQnw8PCAj48PfHx8ULZs2WyTK1odxrtn2feTyCsXD1GHumlCU5OE70JFCrT+LnTzAvEob/7vS0qF8xtde/OACA1F89HMITQuCq/2/wGX6DeQSyVQpQ0Hk6TNXvaMt0TZXiNBXMWpKmXMkxnc2mQYhjEwbWeZMNa+RTg5IoQAJauC3joNKFKRp+QGISBlaoma1ACE0mLpwAColvxkvJ1QipsVGqC2iEkNACByK3De9cDfOpP3jXEScBUaiJ7UUKlUWL52LR4WcUaxmNjcV9ABkUjgUKQQ2s014ntD487TZshIijPdPtObGouMuJcAVauERsS6snMC8apo/heP6dIaY5aqVA2NGtRDfR8f2NnZIi4uHucvhODCxUtITtai/P8zlFI8efIkoxrj2bNnsLKyQs2aNVG3bl2MHDkSdnYGnKHJ1VN4rxoyEWdpIzQaNUPEwhrwrg/64jZozHvwanWW2RJVajWkEgkglQmVGgW1q8AWHSFpMylxgCo1o91LdjIqiggnzI6Vj5IagFC5cUJpj4lTl6Nr9XIo5mQPKcchLC4Be64/RPdBw/ALS2own/nqEhvJycmIjc35BMvJyQlyLRqRGXJbDMMYUG5jpI1JxDuqRG4JVGgIevecnskNIiQ1yvuAmElneEm1euDrNgd/8bR+08DlhOPA12iAXY9fY8XAgfjll1/g5CTecRNXD5DydUHvZx2yqOUWAIkEXNXmIDYFDBqbru7cuYPRo0ejQ4cO2HvjCnaMGIeQ3zcbpmqDEBBC0H/zOljY2uZ9e/qQWwvl7ib4jFGreWz/8wh69e0HTuSkACEEpGhZYQaUt08BXg2e0mzjSq9uAAjgUgSkaBkQEYfS6ItSipOnz+Lk6bOZHre01G4q7NjYWFy6dAkhISG4evUqFAoFSpUqBR8fH3z33XcoXry4UZM9RCIFLVQSCH0Mgwx1k8gA9xJmnaAiMjlI6Rp4cOsGdiz/GYPatYSbswNkUimSUlJx+d4jnL7zFDOXrBI9AawzQoQmxFIZwl6/hI2FDAXs7TMtwvM87j54hErVqgvDc834tcpNTHIq1v1rgiGpzBchS2JDLpcjLs6EdyFMbMeOHbn2/jh9+jSaNGli0m19jlKK5ORkWFiYxzRaDJPvyK2AZBUM2bNAq32KfOJOrGyByk1Bn17XPA2oJtZ2IKVrin5R/DlpvzFQvn4G+val4ZIbHAdSuBgsB05AkI0tLl68iG7dusHf31/Umau4wqVALazB3/tX9+SUrYNQqSHiVJpKpRILFizAP//8g3Xr1qFUqVIAgB6rgpEcE4ub+/7MU3KDcBwIx2HI7k0o2aCuocLWIxAiTHkal0OTTAPhbOyRmJKKtm3bYvHixShbtqzR95kb4uopzEIR/Q7PL5xByaLuWZZ5FxkFV+/qkLl5gpjJlKDGplarcf/+/YxqjNDQUBQoUAC1a9dG8+bNMXHiRFhZGbYfhzaIlR1o4dJA2BPdZ/T5lFQOFCkDYgbVQ9pIpQSBazYjcI3QtF8i4aBOG9LQoEEDzMpvSY1PcRLcvPcQnTt3RtPGDeHi7Ay5TIaY2FhcuXYDPnXrYvv27WJHyTAmlSWx4eXlha1bt2pslpTftWrVCsePH89xmSpVqph8W597+PAhVCqV1g1KGYb5DCFCkz9DzHKiDTMpFQfSKjfK+QBRb0FDHwMJ0eB5HmqehyxtyIVKLZQlSyUSwMJamArPvYRZ3r0i1raQTQ6CcuEkgyQ3KCHgCheDbHIQiI1wx79OnTo4cuQI5syZg927dyM4OBgFC4ozfpw4FwZXtwPo89vC66dWQqFSQSaRZNwlzfR6WlgLjUKLlhX19bt+/TrGjh2LXr164a+//sp0DiGRSjFg23qMqFQTNo9fgHASULVupfFEIoGtizMGbP0NZZo2MnT4upNIheRGYozx9iG1ALG0xfDhw9GmTRsEBATAx8cH48ePzzIDhqkRiRRwKYoWo3+Eg4UUHu6uKGBrg4SkZIRHx+DSnYeIjIyE4xec1IiIiMDFixczplvleR7e3t7w8fHBzJkzqLupHQAAnzlJREFUUaSI+ZTKE2s7UE9v4P0L3acZBgB7F8ClqHlOh6oltdo4TYzFlJKSgqPHsl6L+NQVMfHLMCLJ8q3YqVMn/Pzzzzh9+jSaN28uRkxGVahQIRQqZJjp7wy5rc9t2bIFtra2aNGihVG2zzBfhfRu9Qrdx0HrhJMIpelmhBACOBcBcS6Cg9s349jurahRtiSKFnQGx3GIiI7FtYfPULhMBQT8NNusy4oBgNg7QPZjMFRbV4I/95eQuNL1zn/aOv/yVuDrtEVLe4dMT1tYWGD27Nm4fv06evfujcGDB6NXr16i/G6IVCilpiWqYMOiOYh++QS1yhWHawF78JTidfgHXH7wDLW/8UPLHp1ELfFPTU3N+L1t2rQJXl5e2S63ODgY1ccMR5uqNbB50LeIfPIMnFQCXpVzgoNIJKA8j9r9e6HTz3Nh7eBg+IPQl9xKeB8mGbaHCAVApBaArWNGGbmHhwd2796NjRs3ws/PDz///DMqVqxo0P3q69bjZ7j1+JnYYZiUQqHAd999Bx8fH3Tu3BkzZsyATCbOdLzaIjIL0CJlhKnBY8KB1KQsSW8AUCiVkEmlwmefdQHA0Q3EyoB9PxiGYYwgS2Kjbt26qFGjBnr27Im9e/eiQYMGZn/C+yVRKBTYsGED5s2bh4CAAK3HcDIMo4FULlx4GGt6Rk4iNOYy48/JGAWPFXuOZvucv3+RfPMZT6xsIBsyEXztxlBuXAJEvBMaouVWwZG+jHNByPqPQ50S3vD19UW5qtWzTC8OANWqVcPRo0exYMECdO/eHcHBwaLdeSUSKa6HRuHXlVuyff73Rn6iJjUuXryICRMmYMiQIZg9W3OC7Pz587h16xY2btwIQgimPbiKB3+fwrkVa3H/2EnwSqFXxce+DAI794KoM6AP6o8YBGcvM61gtLAW3mOJMQbpIUIpxeETZ+DbpUeW3hWEEAwYMADffPMNAgICULFiRXz//fdmf0GdH6VPt6rWUFkkl8uxceNGE0eVd4QQwM4ZsHNGalwMJo4eieoVy6GMlyfkcjkSk5Jw99FTvI9NwMyFi0Fk5lGJyDAMk5ssiQ2O43Ds2DG0aNECjRo1QvHixVG1alVYWVnlm5Pf/IhSiri4OJw/fx4xMTEYNGgQgoKCxA6LYb4MMgvhwkOPue1zJJUDMkuzTmp8ibhKtSBfsBH03jWoTh4Af/caiCI122Wp3AJcheqQNu8A4l0dhONgC2DVqlUYNGgQjhw5km2DZ5lMhmnTpuHu3bsYPHgwevbsiYEDB7LvwTTJycmYPn06njx5gp07d+aY+AkPD8eMGTOwf//+jN8fx3Hwbt0C3q1b4NTJk+jW4hu4gIMMRCiAAIVtiWK4/fSxqQ4pb2SWgH1BoXIjL0lUTgJi7YA3UXFYsHAhpk6dmu1ihQoVwvbt27Fz5074+vpiwYIFqF69uv77/colJyfj2rVruHDhAi5duoT4+HgULVoUPj4+4DhOY3Ijv6NySyzbtCPb56pUqYJZLKnBMEw+ku0ATWdnZ1y+fBlnz57Fnj178Pz5c0RHG2EObCYTW1tbjB49Gt26dUOlSpXYCTTDGJJEBlhJ9ZwD/jOECENPRJ4O9WtGOA6kYk3IK9ZE9IcPqF3CA5Ud7WAvE/pQxCpUuBUdj4tPX8HJxSXL+t7e3hg4cCCmTJmCxYsXa9xPhQoVcPjwYQQHB6NTp05YsmTJV9/76Ny5c5g8eTJGjx6NoKCgHL+r1Go1hg8fjiVLlmicwpKTSBAFHlHIXHlTRprPxvJznDB0RKUAUhIzEhxqtRocx2X5PalUKkikUmG6RolUqPySWwGEYMSIERg4cCDOnj2Lxo0bZ7s7Qgh69OiBZs2aYcKECfD09MT06dNZpWcuKKV49uxZRoPPp0+fwtLSEjVq1ICPjw+GDx8O+09mmRg5cqSI0TIMwzDa0nhWLpVK0bx58y+yzwbDMF+p9IaiapVw8aFOL3/XXHSRqZEy4YTqD4mMVWmYE47Dk7hkPInLppdKDs00+/bti/Pnz2PPnj3o0qWLxuWkUikmTpyI9u3b49tvv0W7du0wYsSIL7LBdk4SEhIwdepUvH//Hvv374ebm1uu68yePRudOnUym14QJiGVA7ZyYfiTMhUH9+yEq6MDSpXwgoXcAiqVClExMbh45Ro6dO6KAs6ugDTzUBJCCJYvX44OHTpgy5YtcHfPOutIOldXV2zatAn79++Hn58f5s6dCx8fH2MfZb4RFxeHy5cvZ0y3mpKSgpIlS8LHxwcBAQEoUcK8py5lGIZhtMNuNzIM8/WRSIV/lAfUKrx9/Qrv3oaiUgXvTMMS3oSG4s3bd/CpV0+YC55VaHxxgoOD0aZNG1SpUiVjalJNypQpg0OHDmHFihVo3749goODc13nS3HixAlMmzYNEydORNeuXbVa5++//8bbt28RGBho3ODMFccBFlZYu3kHjh7NvsfNm/ZdUECafX8MW1tb/Prrrxg2bBj2798PiSTnCpaOHTuiUaNGmDRpEnbv3o1Zs2bB2tq8mhobG8/zWaZbtbOzQ+3atdGkSRNMmDBBlOlWGYZhGONjZ+kMw3y9CAdI5bj/9AVatmwJQLg7L5VKkZqaCkopOnXqhL2Nm4kcKGMslpaWWLduHYYMGYKjR4/metHDcRxGjx4NPz8/jBs3Dk2bNsXYsWNzvejMr2JjYzFx4kSkpKTg8OHDcHZ21mq9N2/eICgoCAcPHjRyhF82b29v9OjRAzNmzMCcOXNyXd7JyQm//fYbjh49inbt2mHGjBlo1MgMpsY1ksjIyIzpVm/evAm1Wp0x3eqMGTNQtGhRsUNkGIZhTOTrqqNlGIbJhUqlQkpKCqgBZjdg8oeSJUti3LhxGDdunNbrFC9eHAcOHICtrS3atm2LBw8eGDFCcRw+fBitWrVC+/btsWnTJq2TGkqlEsOHD8eKFSvY3XED6Nu3Lz58+KCx6iM7bdq0wb59+7Bt2zaMGTMG8fHxRozQNJRKJa5du4bly5ejX79+aNOmDQICAvD8+XN06NABu3fvxuHDhxEUFIQuXbqwpAbDMMxXhlVsMAzDMF+9Tp064fz589i4cSP69++v1TqEEAwbNgytW7fGuHHjULt2bUycOBFSaf7+ao2KikJAQADkcjn++usvODg46LT+Dz/8gMGDB6N06dLGCfArtHjxYrRr1w4VKlSAp6enVuvY29tj5cqVOHXqFDp06ICpU6dmVKblB2/fvs0YUnLv3j1wHIfKlSvDx8cH3bt3h6urq9ghMgzDMGYkf599MQzDMIyBzJ8/H76+vqhevbpOzS49PDywZ88ebN68Gb6+vli0aBEqV65sxEiNZ+/evVi4cCFmz56t10Xw/v37oVQqte7DwWjH0tISq1atwvDhw3Hw4MFspyjWpFmzZqhduzZ+/PFH7Nq1CwsXLtQ5WWVsKSkpuHbtGkJCQnDp0iXExcWhcOHC8PHxQf/+/VG+fPkvdrgXwzAMYxgsscEwDMMwAGQyGdavX4/evXvj6NGjsLW11XpdQgj69euHli1bIiAgAOXKlcMPP/yg0wWomMLDwzF27Fi4uLjg+PHjGqdmzcmzZ8+watUq1lfDSEqWLInhw4fnOkVxdmxtbbFkyRKcP38eXbp0wfjx49G2bVsjRZozSimeP3+eUY3x5MkTWFpaonr16vDx8cGQIUNQoEABUWJjGIZh8i/WY4NhGIZh0nh4eGDatGkYOXKkXn1W3N3dsW3bNnh7e8PX1xdXr141QpSGQynFtm3b0KFDB4waNQrLli3TK6mRkpKCkSNHYs2aNfkmmZMfde7cGRzHYffu3Xqt36BBAxw6dAjnzp3DwIED8eHDBwNHmFV8fDxOnTqFefPmoXPnzvDz88Mvv/wCnucxduxYHD58GHv37sW0adPQokULltRgGIZh9MIqNhiGYRjmE61atcK///6LVatW4dtvv9V5fUIIunfvjqZNm+K7775DkSJFMGPGDFhaWhohWv29ffsWo0ePRvHixXHy5Mk8TQ363XffISAgQOv+D4z+5s+fj/bt26NKlSp69TGxsrLCggULcPnyZfTo0QPffvstunTpYoRIga5du8LZ2Rm1atVCw4YNERAQ8NVNQcswDMOYBqvYYBiGYZjPzJgxA4cOHcKVK1f03oarqys2btwIHx8f+Pr64r///jNghPqjlOL3339H165dMXnyZPz88895utjcunUrChQoAF9fXwNGyWgik8mwZs0ajBo1CsnJyXpvp1atWjh8+DBu3bqF3r174/379zpv48OHDznGsGvXLuzcuROTJk1Cw4YNWVKDYRiGMRpWscEwDMMwn5FIJFi/fj26dOmCP//8E46Ojnpvq0OHDmjUqBEmTZqEXbt2Yc6cObCxsTFgtNp79eoVRo0ahSpVquDUqVN5riK5f/8+tm3bhn379hkoQkYbHh4emDhxIgICArB69Wq9t2NhYYGZM2fixo0b6Nu3LwYOHIjevXuDEJJlWZVKhdu3b2f0xoiIiICTkxNUKpXG7We3HYZhGIYxBlaxwTAMwzDZcHNzw//+9z8MHTpUr34bn3J0dMS6devQunVrtGvXDmfOnDFMkFrieR6rVq1Cnz59MGvWLMydOzfPSY3ExESMHj0aa9asyfdT3OZHrVq1gpubGzZu3JjnbVWtWhVHjhzBy5cv0a1bN4SGhiIsLAz79u3DlClT0LZtW3Tu3Bm7d+9G0aJFERQUhCNHjmDz5s169WRhGIZhGENjZyIMwzAMo0HDhg1x4cIFLFq0CJMmTcrz9lq1aoW6devi+++/x65duzB//nyjXxg+ffoUo0aNQv369XHy5EmDNPeklMLf3x/Tp09HoUKFDBAlo48ZM2agU6dOOk9R/LmUlBRcv34dVlZWSEpKQtWqVVGuXDn069cPffv2hbe3N5tulWEYhjFrrGKDYRiGYXIwceJEhISE4Ny5cwbZnr29PVasWIGuXbuiQ4cOOHbsmEG2+zm1Wo3g4GAMGTIEixYtwk8//WSwGUvWrl2LMmXKoEmTJgbZHqMfiUSCtWvXYuzYsYiPj9dqnfTpVrdt24Zx48ahTZs26NmzJ44fP44KFSpg69atePfuHTp16oQjR47A3t6eJTUYhmEYs8cqNhiGYRgmBxzHYd26dWjXrh327t2LggULGmS7TZs2Re3atTFt2jTs2rULQUFBeerl8akHDx7A398frVq1wokTJww6VOTatWs4duwYdu3aZbBtMvpzc3NDYGAgRo0ahY0bN2bpa5GQkIArV64gJCQEV65cQVJSEry8vODj4wN/f3+ULl06214YEyZMQLt27eDv7w9fX1+MHDkSHMfuhzEMwzDmiSU2GIZhGCYXjo6OCA4OxuDBg3HgwAGD3cG2sbHB4sWL8d9//6FLly4ICAhA+/bt9d6eSqXCzz//jOPHj2PFihUoW7asQeJMFxMTg4kTJ2LXrl3sIteMNGrUCBcuXMDy5cvRokWLjAafL1++hK2tLWrVqoV69ephzJgxOjWuLV26NA4ePIiVK1eiffv2CA4ORqlSpYx4JAzDMAyjH5bYYBiGYRgt1KxZE76+vpg1axZmzpxp0G3Xq1cPR44cQWBgIHbv3o1ffvkFLi4uOm3j9u3bGD16NLp06YJjx44ZfPgApRQjR47EvHnz4OzsbNBtM/qJiorCpUuXEBISgmvXruHy5cu4cOECOnTogB9++AEeHh55npmE4zj4+/vDz88P48aNQ+PGjTFu3Dg2PIVhGIYxK+x2C8MwDMNo6dtvv8WTJ0/w999/G3zblpaWmD9/PsaMGYOePXti165dWs3GolAoMHPmTEyaNAnr16/H2LFjjXLRGRwcjLp168LHx8fg22Zyp1KpcOPGDaxatQoDBw6Er68vxowZg0ePHsHX1xe7du3C3bt3ERYWhpYtW8LT09Og0616eXlh//79KFCgANq2bYv79+8bbNsMwzAMk1esYoNhGIZhtEQIwapVq+Dr6wtvb28ULVrU4PuoVasWjhw5gnnz5mHPnj2wtbXVuOyLFy/QvHlz9O3bF0eOHDHa8JD//vsPly9fxpYtW4yyfSard+/eZQwpuXPnDgCgUqVK8PHxwfz58+Hu7p5lHQsLCyxYsADDhw/Hzp07DZrYAIT3/5AhQ9CqVSsEBASgRo0aBt0+wzAMw+iLJTYYhmEYRgd2dnZYuXIlBg8ejMOHD0Mmkxl8H3K5HIGBgbh58ybatWuncbn9+/fj4MGD8PT0NHgM6SIjIzFt2jTs27fP4BfKjCA1NRU3btxASEgILl68iJiYGLi5ucHHxwe9evVChQoVtG4AW6tWLTRu3NhgUxRnp2jRoti1axe2bNmC8PBwo+yDYRiGYXTBhqIwDMMwjI4qVqyIPn36YOrUqUbdT5UqVXJsJjpu3DijJjV4nsewYcOwePFiFChQwGj7+VoFBgbC19cXPXr0wF9//YVy5cph+fLlOHLkCH7//XeMGDECVapU0XlWG39/f9y8edNgUxRnhxCCvn37sn4rDMMwjFlgFRsMwzAMo4cBAwZg2LBh2L9/Pzp27Gi0/eQ0vMTYFRRz585F27ZtUaVKFaPu50umUqk0PtevXz80aNDA4EOICCFYuXIlOnTogO3btxtsiuLssCaiDMMwjDlgiQ2GYRiG0dPSpUvRpk0bVK5cGSVKlBA7HIM6efIkXrx4gWnTpokdSr5BKcWjR48yemO8ePECt2/f1rh8yZIljdYXxc7ODkuWLMGwYcOwd+9eloBgGIZhvmhsKArDMAzD6MnKygpr167FkCFDkJKSYvDtx8fH48yZMxqfP3HiBHieN/h+3759i//973/49ddfWV+NHERHR+PYsWOYOXMmOnToAD8/P6xcuRIWFhaYMmUKjhw5gmrVqokWX6VKldCpUyfMmjVLlP2HhISIsl+GYRjm68MSGwzDMAyTB6VLl8bo0aMxfvx4g27377//RsuWLeHh4aFxGY7j0K5dOzx+/Nhg+1WpVBg2bBiWLVsGa2trg203v1Or1bh16xbWrFmDwYMHw9fXF6NGjcL9+/fRqlUr7NixA0eOHEFwcDB69uwJLy8vs0gKDRw4EG/fvjXKFMW52bZtGwICApCYmGjyfTMMwzBfFzYUhWGYr1pISAgWLFig8fnz589j8eLFGDdunNFKxpn8r0uXLjh37hy2bNmCPn365GlbMTEx+O6776BWq3HkyBEEBgZqXLZZs2Zo2rQpxo0bh4YNGyIgICDPQw6mTZuGfv36oVy5cnnaTn73/v17XLx4ESEhIbh9+zYopahYsSJ8fHwwd+5cFCpUSOwQtbZ06VK0a9fOaFMUa7JkyRJcvnwZ7dq1w7Rp09CsWTOT7ZthGIb5urCzdIZhvlqnTp1Cs2bNcOLECY3LREREYMKECRg0aBAopSaMjslvFi5ciN9//x337t3Text//vknWrduja5du2LDhg1wcnLKdZ1ixYph3759cHR0hJ+fH+7evav3/g8dOoSEhAT07NlT723kRwqFApcuXcLSpUvRp08f+Pr6YsqUKXj79i26d++Offv24dChQ5g/fz46duyodVIjLi4ux+lQnz9/bpLPFSsrK6xYsQLDhg2DUqk0+v4+9c033+DAgQPYu3cvvv32W8TFxZl0/wzDMMzXgVVsMAzz1Zo1axaSk5O1Wnbjxo34/vvvUb58eSNHxeRXcrkc69evR9++fXH06FHY2NhovW5kZCQCAgJga2uLv//+G/b29jrtmxCCwYMHo1WrVggICEDVqlUxefJkyGQyrbfx4sUL/Prrrzh48KBO+85vKKV48+YNQkJCcOHCBTx48AByuRxVq1aFj48P+vbtq1VCKTfHjh1Dp06dcvyMadiwIQYNGoS1a9cavblnmTJlMHjwYEydOhWLFi0y6r4+Z2dnh2XLluHMmTPo2LEjJk+ejNatW5s0BoZhGObLxio2GIb5KvE8jwsXLui0zr///mukaJgvhaenJ6ZOnYpRo0ZpfSd+165daNu2LQYNGoRVq1bpnNT4VJEiRbBz504UL14cvr6+uHHjhlbrpaamYsSIEVi1ahUsLCz03r85SkpKwrlz5xAUFITu3bvDz88Pc+bMQUJCAoYPH45Dhw5h//79CAwMROvWrQ2S1AgPD0f79u21Spz+/vvvWLJkSZ73qY1u3bpBqVRi//79Jtnf55o0aYI///wTf//9N4YMGYLo6GhR4mAYhmG+PCyxwTDMV4njOJ17CHh7exspGkZfZ8+exaBBgzQ+P2jQoBxnFTGGNm3aoGjRoli7dm2Oy7179w7du3fH+fPnceLECTRv3jzLMvfu3cPVq1c1buPUqVMIDQ3N9BghBL1798bmzZsRFBSEn376CampqTnGMnHiRIwePRrFixfPcTlzRynF48ePsWnTJvj7+8PX1xf9+vXD+fPnUbNmTfz22284cuQIVq9ejUGDBqFcuXJG6Z1z5MgRKBQKrZffu3evwWPQJCgoCCtXrsSzZ89Mts9P2djY4JdffsHQoUPRtWtXHDhwQJQ4GGGopSZxcXGs6SvDMPkKS2wwDPPV6tixo9bLFilSBDVq1DBeMEYSGRmZY6XJ7du3RbvAyaszZ85kjN/X5ODBg2jVqhVOnz5twsiAmTNnYv/+/bh27VqW5yil2Lx5Mzp37oyxY8diyZIlsLW1zbLc/v37Ua1aNfz3338a97Np0yZUr14dt2/fzvKcm5sbtmzZgipVqsDPzw+XLl3Kdhs7duyAtbU12rVrp8MRGk5SUlK2jysUilynso2NjcXx48cxe/ZsdOrUCX5+fli2bBmkUikmTpyIw4cPY8+ePZg6dSqaNm0KOzs7YxxCFrpWvZiySkYul2PNmjUYMWKEUaYo1lbdunVx+PBhXLx4Ef369cvxIpsxLEopZsyYAU9PT43LPH/+HM7OzqJV9zAMw+iMMgzDfKWioqKovb09BZDrv2XLlokdrs4ePnxIixYtmuuxWVpa0qNHj4odrs66deum1WsHgHbt2tXk8YWFhdH69evT6OjojMdev35NO3ToQCdPnkyTkpI0rpucnExtbGy0Pj4fH58cY4mMjKQDBgygkyZNyrTfBw8eUF9fX6pUKvN8vLpKTEykXbp0oRKJRONxOTs70z/++INSSqlKpaK3bt2ia9asoYMHD6Zt2rShPXv2pL/88gv977//aHJyssmPQZOXL19SQojWr19gYKDJYzx06BD99ttv87SN1NRU6ubmpvG4Xr16pdV2rly5Qps3b063b99OeZ7PU0yGJpVKNX5u5ldbt27V+r0pkUjow4cPxQ5ZLzdu3NB4XA0aNBA7vDw7cuSIxuPr0aOH2OHl2bp16zQe3/jx48UOjzFDrGKDYZivlqOjIwICAnJdrkiRIhgyZIjxAzKwoUOH4s2bN7kul5KSgu7du+c6XMHc5DTbxOfev39vxEiy5+7ujjlz5mDYsGHgeR7r1q1Dz5498eOPP2LBggWwsrLSuO6///6rUxn4xYsXERUVpfF5Z2dnbNiwAY0aNYKfnx/Onz+PpKQk+Pv7Y+3atZBKTd9LfMyYMdizZw/UarXGZT58+IABAwagYcOG6NChAzZv3gwXFxfMnj0bR44cwbZt2zB+/HjUrVsXlpaWJow+Z56enujVq5dWy1pbW2PUqFFGjigrPz8/ODg4YMuWLXqt/+eff8LZ2TnHv60SJUogKCgo123VqFEDR44cwYMHD9CrVy+EhYXpFROjnV27dmm9rFqtZlUbZiqniitNlXAM8yVjiQ2GYb5qAQEBsLa2znGZqVOnmtVFkzZiYmJ0anYaHx+P8+fPGzEiw2vQoIFRljWkJk2aoHjx4qhQoQJevXqFkydPolatWrmuV7BgQZ32Y2lpqVXT0bZt22Lv3r3YuHEjatWqhYCAABQuXFinfRkCpVSnvhI+Pj44dOgQFixYgE6dOokSs66mT58OQkiuy40ePRqurq4miCirWbNmYdu2bTpPUXznzh107twZCQkJOS6nUqkwefJk7Ny5M9dtyuVyzJgxAz/88AMGDBiAjRs3sim2zYQ272Nzc/v2bcyaNUvj87du3cL//vc/k09/bAhqtRpjxoxB9+7dNS7z559/olq1anj58qUJI2MYcbHEBsMwXzVHR0f0799f4/M2Njb5slrDxsYGcrlcp3WcnZ2NFI1xjBo1SqveBBYWFvD39zdBRJnxPI9ly5YhJCQE7u7uaN26tda9FLy9veHu7q71vho3bqx11YWDgwPq1KmDmjVr4pdffsHJkye13o+hhIaG6jQVrYuLixGjMY5y5crlWrVhbW2NiRMnmiiirKRSKdauXYsxY8bkmqT41O7du6FSqbReftu2bVovW7lyZRw5cgRhYWHo0qULXr9+rfW6hhYREaGxz4tarUZkZKSJIzKMhg0b6rS8WIlhfV29ehWNGjXKMXkaFxeHH374AV26dMmxaswc/fTTT1i2bFmuf4M3btxA48aN82Xyhuf5HP/23759my+PizEyscfCMAzDiO3Dhw8ax8OPGDFC7PD01rJlS63HUbu4uFCFQiF2yDobO3Zsrsc2ZswYk8f16NEj2qJFCzp37lyqUChoZGQkrV+/Po2IiNB6G8HBwVq/fv/884/W271x4wbt2LEjVavVND4+no4ZM4aOGDGCxsTE6HOouUpKSqLnzp2jQUFBtFu3brRNmzZ02LBhtGnTplof382bN40Sm7Hdv3/f7N6b2Tl9+jTt37+/1v0tJkyYoPVrB4A2b95cr7ju379PW7duTVevXm3y3htBQUFaHdvixYtNGpchxMTEUAcHB62Or169embX9yQ3Xbt21en9efbsWbFD1hrP89TDw0On4zt58qTYYevkw4cPtFatWrkel6enJ3306JHY4TJmhCU2GIZhKKWLFi3K8qVZokQJqlKpxA5Nb6dOndL6xGfBggVih6uX0NBQamFhofG4LCwsaGhoqMniUalUdNGiRbRp06b07t27mZ4LCQmh7dq1o2q1WqttJSUlUXd3d4NeNMbGxtJmzZrR8PDwTI+fPXuWNm3alB45ckTrbWWH53n65MkTunnzZjp69Gjapk0b2rlzZzp37lx68uRJGhsbm7Hsq1evqEwmy/X4OnXqlKeYxFa1atVsj4sQkuV1ENPcuXPp6tWrtVp29+7dOl1YTZs2Te+4VCoVXbx4MW3Xrh19+vSp3tvRxaFDh3Q6vmPHjpkkLkOaNWuWVsf2999/ix2qzgoVKqTT6zdv3jyxQ9aaSqWi1tbWOh3ftm3bxA5bJ35+flofW4kSJfJd4o0xHpbYYBiGSXP27FnaqlUrWqtWLTpz5sx8ndSgVLjIbNSoUa4nBi4uLjQ+Pl7scPU2YsQIjcc2fPhwk8Vx9+5d2qRJE7po0SKN750lS5bQWbNmab1Nbao2tK3W4Hme9u7dm/7777/ZPp+YmEi/++47OmjQIPrhwwetthkbG0tPnDhB58yZQzt16kTbtGlDR48eTTdv3kyfPHmS6wnnt99+m+vxXb9+XatYzNWlS5cox3FZjqtv375ih5aJWq2mnTt3plevXs112dTUVOrp6anVhYdcLtd6dpScPHnyhPr5+dGlS5dqnRzU14ABA3S6cBw6dKhR4zEGbao28mO1BqWUNmvWTKfXb9++fWKHrBNtvtc//ff8+XOxQ9ZaTEyMVgnvT/9duXJF7LAZM8ESGwzDMF8wbao28mu1Rro3b95oPLY3b94Yff8KhYLOmTOHtmjRIteyWJ7nac+ePemJEye02nZSUlKO075WqlRJ6ziXLFlCf/7551yXu3DhAm3WrFmWk321Wk3v3LlD161bR4cOHUrbtGlDu3fvThctWkTPnz+f4/S1mrx69UrjdJpA/q/WSPfXX39RDw8PKpFIqI2NjdkOcYuMjKRNmzbNNEWxJqtXr9bqomPUqFEGi0+tVtOVK1fSNm3aGHUK0n79+ul0YTV48GCjxWJMM2bMyPG48mO1BqWULl26VOvXzt7eXqv3uznZvn271sfn6+srdrg6iY2N1WmqbAD00qVLYofNmAmW2GAYhvmC8TxPy5cvr/GEwMrKKl9Xa6TLbkx1ly5djL7f69ev04YNG9Jly5ZpfRc5NjaWNmjQQOshMjlVpBw4cECrbYSEhNAePXpoffc1JSWFjh8/njZp0oROmDCBtmvXjvr5+dGJEyfS3bt309evX2u1HW106dJF4/Hl92qN/CgkJIR279491/eKNlUbhqrW+NzLly9px44d6cKFC6lSqTT49letWqXThdW6desMHoMpxMTEUIlEku0xubu758tqDUopTU5O1no4yk8//SR2uDpTqVTU29tbq+O7ePGi2OHqrEqVKlr/7dnY2NCUlBSxQ2bMBEtsMAzDfOFyGg8/cOBAscMzmJEjR9KCBQvSggULGv2OeEpKCp0+fTpt06aNXmW+N2/epN98841WF2Xx8fHU0dExy2tXrVo1rfalzV14hUJBr169SpctW0b79u1L27RpQ/v27UunTJlCa9euTTdt2mS0i5wnT55k+94sWbKkUfbH5C44OFir6p7cqjaMOUSD53n6+++/02+++Ybevn3boNuOj4+nLi4uWl1Yubm50cTERIPu35SGDRuW7XFt3bpV7NDyRJuqDXt7exoVFSV2qHrRpmojv1VrpNuwYYPWiY3JkyeLHS5jRlhig2GYr5taTalSQWlqMqXJCZQmx1OaHCf8NyWRUkUKpSolpfn0zhWlwgVAdnd37Ozs8u1JnZguXrxI69WrR9euXZuni/3ffvst00nZ2bNnaWRkZLbLvnv3jjZt2pTa2tpSBwcH2qdPH42z2Dx69CjjLnl634Rr165lWiY0NJTu2bOHTpo0ifr5+dH27dvTadOm0UOHDmVpaKlQKOisWbNot27d6Nu3b/U+3pxMnDgx03vTwsKCPnjwwCj7YnLH8zzt1auXxn4s6VJTU3NsZGiMao3PhYaG0q5du9JZs2YZdGanBQsWaHVh9csvvxhsn2IZMmRIRhPmAgUK0F9//VXskPIsOTmZurq6fnHVGulUKlWuFVP5sVqDUkqVSiUtWbJkrn971tbWZtWAmREfoZRSMAzDfE0oBdRKQKUAeG3nryeAVC784zijhmcMKSkp6NGjB06ePAmVSoXKlStj586d8PLyEju0fCM5ORkzZszAw4cPsXz5chQtWjTP2xw8eDDat2+PM2fOYM2aNVixYgUGDhyYp2327NkTp0+fxurVq3Hv3j0UKFAA1apVQ0hICC5duoS4uDgULlwYPj4+8PHxQfny5SGRSHLd7p07d/Ddd9+hV69eGDBgAAgheYrzc2fPnsXatWtRokQJ+Pv7w83NzaDbFwWlwmeMWgmo1RDOxwEQDpDKAIkMMPDv0VBiY2PRqVMn7NixA66urhqXmzp1KubPn5/l8aZNm+LUqVPGDDEDpRTbt2/H+vXrsXDhQlSrVi3P20xISEDx4sURGRmpcRk3Nzc8e/YM1tbWed6fOaCUGvzvWkxz587FtGnTsn1OKpUiPDwcjo6OJo7KcFauXIlRo0Zl+1zZsmXx4MEDE0dkOH/88Ueu34WTJ0/GggULTBMQky/kmNhITEzEsWPH8OzZM6Smppoyrq+SjY0NqlatioYNG2p1kskwjI7SExqKFGRcYOhDIgPklsLFCWM2qFoNpKYCoICFJYgBP0fPnz+PSZMmwd/fH3369DHYyf+LFy9QuXJlqFQqJCcno1+/fti4caPe26OUonz58nj48CHkcjmkUilatmyJmjVrwsfHB7Vq1UKBAgX03r5KpcLixYtx4cIFBAcHw9PTU+9tfdFUCiA1SbvPGokMsLAG5FZml+S4efMmZsyYgT179kAikWD//v0oXbo0KlSokGm5QYMGYePGjeB5HgBQt25dnDt3zuTnMuHh4Rg/fjyKFy+O6dOnw8LCIk/bW7hwIaZMmaLx+V9++QXjx4/P0z4Y40lJSYG9vT2USmWW59q1a4eDBw+KEJXh8DwPJycnxMbGZnlu//796NChgwhRGYZKpUKRIkUQHh6e7fMymQyhoaE5Jl2Zr0+2iQ2e5zFx4kSsWrUKycnJsLe3h5WVlRjxfTUopYiPj0dycjLc3NwQFBSEfv36iR0Ww3w5eB5QJAO8ykAbJMKFiFRmoO0xuqJKJZTnTkF15QLU926Df/ks7a44AI4D51UCEu/KkNasC1nDZiCynF8rhUKBW7duoWbNmhmPJSQk4IcffkBYWBh+/fVXuLu7Gyz+M2fOoF+/fnjz5k3GY5UqVcKtW7e03kZ8fDyuXLmCCxcu4OrVq0hOTsa5c+eQkJAAALCwsEDFihVx6NAhg8b+8OFDjB8/Hh06dMCwYcPA5cMqJqNQKYCkWECtz+cMAaxsAQsbs0pw/Pbbb3j16hXevn2L7du3Y8SIEVi0aFGW5ZKTk3H79m2ULVs2T8kzQ9i7dy+WL1+OefPmoU6dOnpvJyEhAU5OTtleGMvlckRHR38x1Rpfqo0bN2LAgAGZHnN1dcWLFy++iNfuyZMnqFOnDqKiogAAHMdh5syZGitV8pP//e9/+OGHH7J9rmPHjti3b5+JI2LMXbaJjREjRmDt2rWYPn06BgwYgBIlSogR21eHUopLly5h8eLF2LlzJzZt2oQ+ffqIHRbD5H+8GkhJMM62pRaAzMKsLkS+dDQpCanbf4di3w7Q2BhAIvmY0Phc2nPE3gHyzj1g0XMgiLVNtovOnDkTQUFBuHv3LooVK4aTJ0/ixx9/xMSJE9G1a1eDH0fnzp1x5swZREdHZzzm4eGBly9fZqoIoSoFkBgLmhCDyPfvEBoaivtPnuHyvUeISFSgavXq8PHxQfXq1fHu3TvUq1cP79+/z1jfyckJU6dOxcSJEw0aP8/zWL58OY4fP47g4OBM5wp3796Fk5MTChUqlOt21Eol3t69j9Bbd5AcGwcikcChSGEUq1EVDkUK54/SeEqB5HggNTHv25LIABsHQCLN+7YMIDQ0FJUrV0Z8fDyUSiXq1auHf//9V+ywcvXhwwdMnDgRzs7OmDVrlt4Xsf7+/lixYkWWx8eNG4fg4OA8Rik+qlYBKYmAKlV4HxNOqEi0sAbhvozq4cuXLyMwMBBhYWFo1qwZ5syZA0tLS7HDMqirV68iNDQUrVq1ynOlkrlQKpVwdXXNUpEilUrx5MkTFCtWTKTIGHOVJbHx+PFjlClTBr/++itGjx4tVlxfNZ7n0aNHD1y8eBEvXrxgd8IYJi/UKsNcbOREKgdklmab3KDpF12JMUBqWmm8TC5cPFnb56uTV9W1S0ia+yPohwihCkcXHAfi7ArrH+ZAWiPzXdz379+jSpUqeP/+PapXr44aNWogKSkJwcHBcHFxMeARZHb16lUEBATgwYMHiIyMRIECBXDr1i14eHgg/tUTpLy8DxeZ8DXN8zx4ABwhIISAAMJ7zrkwiHsJwNYRe/bsQc+ePaFWq1GoUCE0aNAAixYtMuqQkWfPniEgIAAtWrTA6NGjoVAo4O3tDS8vL409FiileHT2PM4sX4NbB45AnXZHnHCc8H5NOzUpUMgNDYYPQsPhg+BQOPckiSh4HkiIEoa5GZKto/C5IqJjx45h6NChmaqKSpUqhcePH4sYlW4OHz6Mn3/+GYGBgWjUqJFe2xg4cCC2bNkClUoFqVSKAQMGYN26dQaO1HSoWgXEfwBiwgFliuYFLW0BBzfA1gGEDb1kRPD8+XM0a9YML168AAC4uLhg9+7daNy4sbiBMWYpS2Jj3rx5mDdvHsLDw7+IEq386p9//kHjxo3x33//oW7dumKHwzD5E88DKfGm2ZfMUqjcMCM0NRn0/XPg3XOhRB4AkJ58Sfvo5zjA1RPEvQSIjbjl4zmhlCJ101qkrlsmxKxrUiNd2roWQ0bDov+wjGqATp06Yf/+/WmLcBg6dChWr15toOhzd/XqVQwfPhzXr19Hz/a+mNm/I0oWcgVPKbhcE2YEAAUc3dE/8Gfs2ncAXbp0QVBQEIoUKWKK8EEpxdq1a7F//37Y2tpi3759sLe3x/bt29GyZctMy4Y/eYoNA0bi2X8XwUml4FU5D9sgHAdCCNpMm4Q2P0yEVC435qHohueFC0SDDXH7jMjJjaCgICxZsgTv3r2DOq0qqnDhwhlNadNRygOpyUJ1HOEACyuzSpjGxsZi8uTJkMvl+N///gdbW1udt6FWqxETEwNHR8d8e8OJUiq8X8NfAlSHz1CpHHAvAWJlZ7zgGCYHycnJUCgUog9zY8xblsRGr169EBYWhjNnzogUEgMIX6AymQyrVq3C8OHDxQ6HYfIfSoVKDa1nPTEAS1vADE7mKaXAu2egL+6k3fnOrVFq2oVxoZIgnt4gZlIC/6mU9cuRusGwiQaLASNgOcQfV65cQatWrTLGKAPCbAdXr141WmIgLCwMFy9exIULF3D37l1wHIdKlSqhfumi+KZM4bRkhq4NbgkUPI8o55IoXK6SMcLO1Z9//omuXbtCoRASaWXKlMHdu3chlQrvqQt/bMGWEePAq9XgVTr+bRKCwhXKY/ThXXDy9DB06LqjVKjUyEgaGom9izA8RSRxcXGYN28etm7dirdv30IikeDEiRNoUL8+EBsO+uENkBSXUWWTwdIWxKkQ4FQIRMT4P3XixAnMmzcPP/zwA1q0aJHx+J9//gkvLy9UqiTO340pUF4NhD0VesDoy7EQ4FwkfwwP+5p8UuWWUTnKXiPmK5QlsdG+fXtQSvHnn3+KFROTxs7ODjNnzsSECRPEDoVh8h9las4ltsZAOCG5IeIJBVWrQB9eAmLe575wdixtQCo0ALEwn4o9xd+HkDwn+wZieWX5wxyUHDoKoaGhAIRO63Z2dlCpVOjWrZtBys1TU1Nx/fp1hISE4OLFi4iLi4O7u3vGdKve3t6QSCSgYU+FZFReEQJSzgfEoWDet6UDhUKBSpUq4dGjRxmPWVhYYNasWZg8eTLOrFiL7f7f5WkfnFQCO1dXTPrvOFy8RB5fnZIIJMcZfz8SKWDnIvqFSkJCAhYuXIiFCxdi7tSJGN+ttfA5mxtOAlKkDOBYyCwuiBMSEjB16lSkpqYiKCgICoUCVatWhYuLC27cuGEWMRoa5dXAm4eGGZZp7woULJYvfk+UUiAhGjQyNK15uBqQyoXqRFcPEDOrstQJpUKlmFKRtWKMEKH/l1Qu+ucGw5hStokNABqnQNqwYQMGDRqE58+fw8vLS+sdBQYGYubMmchhdtmPQRGCGTNmIDAwUOvtf4ns7e0RGBjIEhsMoytKTXPBkR0Rh6RQnge9/x8QG5GHrRBhqtRKTUDk4jdX4yPDEd+3PZCcnPWOcF4RAt7CAs0fvYNX9ZqoXLkyypUrh2LFiqFYsWJwc3PTebpKSilevnyJkJAQhISE4PHjx7CwsEC1atUyplt1cHDIul70e9AHIQY6MAj9RKo0A7HMvlGqMezZswdDhw6FlZUVkpOTERcXB57nYW1tjb/W/o4tfYYaZD+cVAqX4sUw7eZ/kIs1Y5taBcTl5e9MR1Z2QtLUDCS/fACLmFDdV3RwEyrCzKRXw7lz5zBjxgxER0fjxo0bsLOzQ3BwMAYPHpx1YUrTqv8oACJU5uWTC0ZKKRD2ROixZCjORYVqHDNFKQUiXgtDMVMSkVGVmAkBnNxBCpUEsbYXIco8UCuFRI0234lm3gNMGzT2AxAfLQyfsrYTXrd8fDyM8ZhfvbEZmTt3Li5evIiLFy8iPDxc72TL27dvMXnyZFy+fDmjjLNMmTLw9/dH//792R8nwxiasUvDc9x3qmh3Seibh3lMagAABVJTQJ9cBcrXE/3zKXnx/4CUVMMnNQCAUnBKJc717gSbeUsyPRUbG4sGDRpg+PDhGDRokMZNJCQk4MqVKwgJCcGVK1eQlJQELy8v1K1bF/7+/ihVqlSuv0OqUoA+vWaQQ8rAU9An14AKDUz2Gnbp0gWdOnXC+/fv8erVK7x48QJ3797Fqb+OYee344XGoPr2RvkEr1Ih4ulzHJw+B10XzTVA5HowdkPizyUnABbWQlWYiGjEK/2SGgAQ8x6UEMDDW/TPFQBo2LAhBg4cmDHcNz4+HrNmzUKPHj1gY5OWEOTVwvdJdt8pUrnwzwyGH+Yo/oNhkxoA8CEU1MYBxEKkxGIOKK8GfXYTiH736aPZLQlEvQONfg+UrAbi6GaqEPNGpRCSGrosz/Npnx/i/91pi6rVoM9ug97+D3j3MvOTDq4gleuDlK2ev6tuGIMzWWJj2rRp+P777021O4OYNm0a3N3dUa1aNRw7dkzv7URGRuLNmzfo2rUrPD09oVQqcfz4cQwcOBAPHz7EvHnzDBg1w3zlKBWSC2Lun1ebfKpGmhgrlBobZmtCt/yIV0BB8cr9+bdvoDp3Crr3mtCBWg3V+TNQh76GpIjQt+H+/fto164dnj17hoIFC2YkNniex6NHjzKqMV6+fAlbW1vUqlUL9erVw5gxYz5eEOmAvnkEKA08owYoEB8FRL4BXE3Xj4LjOBQqVAiFChVCnTrCzDMV4xU4fW21QZIa6SjP48Qvy1BvcD8U9i5nsO1quXMgNcm0+wQFFCnCxYlIaHI86Ns8zoYS/Q6wcwYc3Q0TVB5ERUVh2rRpSE39+H3x+vVrfP/99/j1119zH86YnvAww8bR6SivFj7HDb9lIPwF4FHeCNvWH6UU9OkNHYZiCr0p6JOrQJlaIAVcjRle3qmUuiU10vEqQJEEyPNHcoOmJIE/+gcQ9iL7eGMiQP/ZD3rjH3DthoIUcDZ5jIx5MtmZt1QqzWgell+kD7eJjIyEq6v+H3aVK1fO0ox19OjRaNeuHZYuXYrZs2frXO7MMIwGvNo4d/d1oVKYPrFhsKTGJ9t8/UCYMUWkE6HUA7vSZjExcgNYjoPi4C5YfTsBe/bswejRo/HunXC379q1a5g5cyauX78OlUqFMmXKwMfHBz/88AM8PDzy/LuhahXw/gWMlbyhYc9ATJjY+FxKQgLOr90Aqjb8a8hJOJxdsRa9lv1s8G3nSJ8LC0NISRQtsUEpBX193zDbevMAsHcRvUlxSEgILC0t4eXlBYVCAaVSiZiYGKxatQqTJwTAw03LaZ6VKWk9Dcxotp508VHG+/xMSQBNTTKrfkwIf6l3fyn65BpQpRmI1Dwa3WZBqZCc0JdaJfwz1+NLQ1VK8H/+BkSmVYbldD4XHwN+3ypw3caA2OSz4USMURjkW+Xo0aOYN28erl27Bo7j0KhRIyxcuBAVKlTIWCa7Hhupqan4/vvvsXnzZqSkpKBp06ZYsWJFtvsIDQ3F9OnTcfjwYcTExKBUqVL47rvvMo2FPHPmDJo2bYodO3bg8ePHWLlyJSIjI1G/fn2sXr0apUqV0um4dOkhog8vLy8kJSVBoVDASqxxwgzzpcnLSRzhALlVWmkxFe6O6NOA1FhTP2pAFSnAh7fQ6uK4cCkQt+LCBZJKAYS/An11N/tlU5OA2HDAQZwSXeXxwzq9njbB6yApXQ6wtAKNjoLy3EmkrPg592oIXg3l34cwMuQm9uzZg8TEj8MM4uPj0bhxY3z//fewsDDCXdkPododo0QGUqoaYOMAyOTC3eSIN7lfbCbGgCbGijaV79Wd+6BIyj0R8M3kANQf0h+upUqA4zj80sQXj86ez3EdXqXGhd+3oEvQHNP22lDmYaiblT2Q3vckNly3zyteJVSLiDEcJTkOSM5h6mxre5BCpYReIDwPxLwDDXuS/UUJrxYuPp1NMxWxJr6+vvD19QUAJCYm4vXr13j16hWuXL6MokUKpw0p5ISkRUrCx9dKIk3rWcB9rBBUJAuPm0n/kAyxWlzkW9mBFM1a9USVqcCLW7lsP0LUqr5PUUpB3z3P9jlSuUmWBAz/+GrmJAivFirc3IsbM0z9qXP4HpPIhKqh9Pcfr07rwfFZlZwq1fwTG9fPgBQtBdKyJ1DAGYRwUO9fDbx9BgAg3/QGKVQ8I5GhXjkV/LkDkLTuJ2bYjJnIc2Jj06ZNGDBgAFq1aoUFCxYgKSkJK1euRIMGDXD9+vUckwNDhw7F5s2b0bt3b9SrVw+nTp2Cn59fluXev38PHx8fEEIwevRouLq64ujRoxgyZAji4uIQEBCQafn58+eD4zhMnDgRsbGxWLhwIfr06YOLFy/m9XDzJDk5GYmJiUhISMDZs2fx+++/o27duiypwTCGlJfERvoYdmWKkNyQWQCg2nX+/1T61GumqnSIjYA2SQ3i6Q1StCxofJRQUs5JQHK6y0gIaPR7EBESG3xMNGhkuE7rqJ88hOLEUYBSWPTsD4suvcG/eg7Fvh25rks/ROL6tSewtraGXC5HdHS0EAfPg1JqnKQGABoXhewb231GKgWs7EDfvwBUCpAipUGKlgFVpgAaTuYzxEcBIiU2Hv/zLziJBLwq52SfzNIStw/9hWqd28FZh9lOFElJeHPzNkr41M5rqNrTt4eP1EL4jMnLZ4NKKcqwBxr9Dhrfp1IZSPGqwudF2BMQW0cQV09ArRKaN2a3vagwEJETG5+ysbFBuXLlUK5cOXzTpJHwoFolXDB++loRTijnp1T4npDIhGR4ei8OmfgNl9NRXg2kalFdpEgGDXv68WdbBxA757Smm7kQq0l3duIic6ymEoZSPfn4QDZ9R+j7F4Cbl1n0gMlC03kIIR8/V9LPXaRy4X35eS8gXi38M9O+MFStBr19AaRiXdAXD0BKVADsnT5bCKAProDUaJb2Mw88vwuaGMeqNpi8JTYSEhIwduxYDB06FGvWrMl4fMCAAShbtizmzZuX6fFP3bx5E5s3b8aoUaOwfPlyAIC/vz/69OmDW7cyZ4h//PFHqNVq3L59G87OwjiqkSNHolevXggMDMSIESMyJQdSUlJw48YNyOXCCbujoyPGjRuHO3fuoGLFink55DxZsmQJpk6dmvFz8+bN8fvvv4sWD8N8kfRNbHBS4ctepfx44SKRCRcjuiY20uMwUak1TYgRTm5yKtnkJEChkqBqJei9/4STAV6d8+V02lR5YlA/uqfzOinLgkDs7AFbO8iatISkWAmdRnhc3bkVXM26uHHjBg4cOIC//voLz549w/nz59G0aVOd49FKQhS0CjI1BfTGyYwfKeFAilcCsSmQy9oENCEGYp2mP7twKdekBgAcnjUfAFCiXh2dEhuEELy8ct10iQ2ez3oXVBuEE5JLKQnCBYe+nw1qcRIbSIyDxvepdQEQqQw0NkJoKpkQLSRDXTwADYkNJMeDUmp+F5CUpn3+px0rJwHwSRVGemNoZcrHpowSqfA9oUgW/msux6RtHxi1Ku1zKI1zYeG/0WG5r6tIAeV5EE78ShUa+QY5JomVCqF3VE7nCIpkICEGsHM0QoR5wKtz+NwhH2+mqFXCf6VyaPw9qJSA3DwTG3hxH0hJBL1yAgBA3ItlSWzQ41uFv7n0xEb64/cvg9RsbrJQGfOUp7Pu48ePIyYmBr169UJkZGTG4xKJBHXq1MHp06c1rnvkyBEAwNixYzM9HhAQgK1bt2b8TCnFnj170L17d1BKM+2nVatW2L59O65du4b69etnPD5o0KCMpAYgdL4GgGfPnoma2OjVqxdq1qyJiIgIHDp0CO/fv0dyskhjdRnmS6Vvf430E7NMJw80rbRTizvqhopDHykJue/P2g5EIgVVpoJUbQ5iYQWamgT6/DYQ9VbzeskJho1VSzRSv9ldbLf8Cc5BOClV/H0IikN7tN/nh0hIJBLUqFEDNWrUwKxZs6BSqaDS4sJcb9rcURWiy/RTegd/GpPb74lqd+fVSKJfvTHq9jmpFB9eGKM5ogb6JDUAIanBqz8mNvRlwAasOslpFpj0RLClrXBsdsINKCKVgUqkwsXW5ygvJAfy8rswCoocP+vJZ98T6f/luE/WNZPEhj4JeZsCIHIr0KQ47RMjKgVgBlODC/Hm8NrZOYGr0UqoZImNAH1xJ/vqK0UyADNLbOT0/U55IWa5lTAUDBA+azR9t+j7GWYC9MPbtL5aOsZIAfpBi0Qc88XLU2Lj8WOhO3azZs2yfd7eXnNJ0MuXL8FxHEqWLJnp8bJly2b6OSIiAjExMVizZo3G6o/w8Mzlyp6enpl+dnQUPqDSS4vFUqxYMRQrJtyJ6tWrF4YPH44WLVrg4cOHbDgKwxiMyI1DxaDNiUraiRGRWYC+vg8+JRGkZDWQMjVBr/ylubxerJMgPZMJSdMngHNyhrznAMiatYby3Cmozp7Qal2aTS8Ooze+1jUBRjiQUtVAHAoK5eMftJh6U8QTWXV2F7WG3ofClNM76/H5IrcS7uQnRAkVAOl39DlJ2gl8PvjMyuk9lBQHGvkaxMUDpHw9oZxcm7v4Yjd5zk5eQzKjvIZev1+HtNlqMk2VmuuOdN+PMeTQoJhGvhEqAXg1SMFiII7uQsXis5tZFzZ2s2q95PQ7JmlDoKiQzOA44We5Vd6ajYpBpYR+f0A0b72PmC9Gns7W+LSM2qZNm+DunnXqLkOcDKbvo2/fvhgwYEC2y1SuXDnTz5pmGKFm9iXatWtXrF27Fv/88w9atWoldjgM84XQo7oC+HiHIFPzt/ThHXpsz5QntxItmoGlJGWUftM3j4QLlcKlQGwcQC2sNCc2OJFmLtCzp4X65lWkn5Zaz1wEeesOWic2iJH6aOSI4wC1lokHiRSkbB2QAi6grx9oPxOOiLNPyCwskao0btWPXI8pdvWnxx92ejLD7rMpCe2chWSHLnfWxbpo5qQ5Ni+koY9Aw18KF1S8GqRMbVBFcvbVGhnbNMNy+Nx+v/Sz74mMZo3pj5tLVgMfqxC1ZWENYm0PmpoMJMVqv565NEzNqSnmJ701qDJVmNY1vbrhc9p8n5pcDu8riUR4rVVK4W9UDeHvUORZh/RiYaXnUD8CYsFuEDN5TGykV1sULFgQLVq00GndYsWKged5PH36NFOVxsOHmU/UXF1dYWdnB7VarfM+zF36MJTYWB2+QBiGyZm+04Pyqo99MaTyjxcj+syKApj0ZI9Y2wslnDklYNRKIOI1UNATxKsiaEoSYJV+EpvDbAe2DoYOVyuch26d9qW160PWwhfqO9cBEMi79AIAqJ9qPw2urvs0CGt7oblnbjgJSMWGwmsd/R40OUGYVUKZKjTN04QQYR8iKVyxPJ6HXM51uVIN68GtTCnYuQpTbFb0awXXUiXw728bc1xPrVSicIWsMzoYjT4X44qUzBf41vbCdpJi0+5Q6rJ/kS5WrOwy92H4DHEvIczORAiIc1EQQsBr6q8BCLP8iNErJDeE+zgTSvp/gbQmopyQAJbKhQqc9McB4fFPq3HMga7DfBzTblDG6FCtQTjzmebWpoDQH+Pz70ErOxCPckIPGLUKxKWo8Lim/lHWGhIeYsopScXzwg2Y9HOXz4dLZdmWGSYU0xCPMqAXjwGFioM4uABWQtKaFCsHFHAW+miUqiwkQNLXKV8LNCke8CyrabPMVyRPZ96tWrWCvb095s2bB2U2JbwREZrH/rZp0wYAsHTp0kyPBwcHZ/pZIpGgS5cu2LNnD+7cuaPTPsyFphh/++03EEJQvXp1E0fEMF+wvHxppyYJyY30ux3KVP3GKQOmvYtl6wBtqkro85ug4a8AVw8Qj3JAXATo/f9ybEpGbMUZaywpWUanO440NhqSEqVgOeo7WI6ZBMjkSNm8Dqm/r9JqfR5Al4nfY/DgwVizZg1u3boFdQ6lzQZj66jdxZBMDpKWoCCObuDK1ARXpiZI0VxO5igVbapXAPCqXQOcFtWb9Qf3Q791y+BaUphq8ZtJ49Bv3TKt9uFZo1qeYtQJIbonF3iVkCBN/5dePapM1f3upEh3k3P9HJBbghQuDVK4DACAf3UXiNI05p2IljDVisxCuEC0sP74fSJLn9GGTyvvpx+nfFUkC6+xuVzgp5NbaZ9okcoBW0dQlQKI+6D9PiyszaYBLHH1RLbfg2lNXkmhkiDFKgByK9B3z7OfKtveGcTSlBVgWiKc5s+d9B4blBfek1KZcCNDU48UM57ulRQsCrgUASlfC1zTriAFhCo3rlpjcE27Csv4tAHXuHPGOlzTruCqNwEpWUmUmBnzkqfUv729PVauXIl+/fqhevXq6NmzJ1xdXfHq1SscPnwY9evXx7Jl2Z+YVK1aFb169cKKFSsQGxuLevXq4eTJk3jy5EmWZefPn4/Tp0+jTp06GDZsGLy9vREVFYVr167hxIkTiIrS4m6XHjZt2oSXL18iKUn4cPjnn38wZ84cAEC/fv0y+mXkZu7cufj333/RunVreHp6IioqCnv27MHly5cxZswYlCpVyijxM8xXKS+JDcrn3CRPW5/e6TOFAq7CyUpud3/VKtAnV3XYMAVcxJmSkVhYgitRGvzTR1qNFVc/vIeEoT303BmBtGRpHFi/G2FhYbh48SK2bt2Ku3fvAgAqVaoEHx8f+Pj4oGDBgvrtQ9Ou03tl5CY1GfyFA/rsQXh/iKRS29Y4vTT35NIfg77FH4O+1Xn7TsU84Fa2tD6h6U8qAxR56B0Sl4cbMmKVlzu5A+80v0/pK11mMaJmNdVrFhIZkByveepQtQpQfz68ipjdEAZCCKh1gWynNc1CpQB0+m5IY0YJKmJlC2rnlLUCTpmq9fceKehl+MAMRWYBpGr43FErcxwqliG98siMcdWbgP97C9Sndmb7PL95QZbHSM0W4AoVN3ZoTD6Q52/I3r17o3Dhwpg/fz6CgoKQmpqKIkWKoGHDhhg0aFCO665fvx6urq7YsmUL9u/fj2bNmuHw4cPw8PDItJybmxsuXbqEWbNmYe/evVixYgWcnZ1RoUIFLFiQ9Q1uKL/99hvOnj2b8fPp06czZnpp0KCB1okNPz8/PH36FOvXr0dERAQsLS1RuXJl/P777xr7hjAMoyexSrU/ZeKLD8JJQN2KA6GPYbhGbkS4e6VpHLIJyNt3Rcovc02zr3bC3aBChQqhY8eO6NixIwBApVLhzp07CAkJweTJkxEREQFHR0fUqVMHPj4+qFKlSqZZuHRWwFW4E6ztDAQ6IYBzYRARZywo17wJnIsXE2YuMXCfK8IRNB0zEpypp5qUW2q+6DUmmXhTiRKZJahjIe2mAM15S4ClDWDrlPuiYiFpMabo0BvG0sa8hqGkcyioXWJDLwSwFy9pmh1SuDTow4v6rAlY2QIO5nU8mXASISmRl2bQ5jj86zOkVGWQiFDQ62e0WRrwKsemeWUyEPpZR8327dsDAA4ePChKQMxH9vb2CAwMxIQJE8QOhWHyl5QEcTubW9qafBwrVSlArx3X3ARUD6RyUxAR78jRpETEdWgKpOrZ50RbFhaw338axMZWq8WjoqJw6dIlhISE4MaNG1CpVChbtmxGVUfRokV1Ks+m719k353fAEilRqINJ0p3bu0GbBk+NvcFdUAIgWUBe8x5ehM2Tia+SKYUiA03/Wwztk6iXphQlRL04QXd+4JkQkDK1Aax0u5vTVS8Wkg4Uh5KpRIy2ceKjIyfCZd5yIqZoZQCr+4aJxFXwNUsKxxo+EvQl3d1WIMIQ/2864uaBNYKz6cl3PSdncnMhktpQCkFvfEP1CF/garVwgjAT75TVWoeEgkHUqEOuAYdQDRMGsF8fcy7HolhGEYfUhHvSnASUU5yiVQOUsqA/XqKlhM1qQEAxNoGFn0GG/VOKAUg7TFA66QGADg5OaF169YIDAzE/v37cfDgQQwbNgyJiYmYO3cu2rZti+7duyMoKAjnzp3LGM6oUcFigJ0TDD7lRaGSoic1AKD+kP4o3ag+OKnh/i4opeizKtj0SQ3g4x19U+Ikol+UEKkMxKsKQDi968KIR/n8kdQAhN+5pS3adumBv46fQExsLBRKJaJjYnDk2N9o17WnKElsXRBCAPcSht+wRAY4e+S+nAhIwWIgxasgt89TPv2+rqVN/khqAELfKX2qg2SWon9+6IIQAq5aY+yyKInv95/Bo/dRSExVIkWpwquoOCz8OwTzX6ohadyZJTWYTMygZtu0kpOTc52FxMnJSavSYkNui2EYA5JI816yqS8R76gSp0JAsYqgL7M2WtaJcxGhuagZsOg7BMrTf4N/+dzwVTgSCZIcnDFo617MqlQLderU0WszHMehXLlyKFeuHAYOHAgAiI+Px5UrV3D+/HkEBwcjOTkZxYsXz6jqKFWqVEZVByEEKFUd9NaZnKfH1JpQVm0uryHHcRjwxyrMq94IKXFx4PPYlJUQglq9u6NG9865L2wsFjYfmw2bgnUBsxjqQGwKIMy6EORhD+Fkr22CggizpXh4gzi6GTU+gyMEx06cxOG/jmV5ytLS0ixek9wQC2tQFw8g8rXhNupewqwvKIlLEcDOCXFP70Lx9gmcC9iDUgqe5yFJi/vhm/fwbtwacHQHMfVwtrxIS7hBmQpemQoCZDouQBhCKZFIQCQy4ZwkP079CiCZEiw+eRmLT2adWWt86VoiRMSYuyzvdEIIVCpDnFiZpx07duTa++P06dNo0qSJSbeVHbVabfqxwwzzJSBEKLs0RCNQXUhkojeQI0VKAxIp6PNbaT0NtL23SoRl3UuAFK9sPp3upTJY/zQfCSP7AgpquGQV4QCpFG6LVmCbowsmTZqEXbt2YdasWbC2ts7z5u3s7NC0aVM0bdoUgFBh8OLFC4SEhGDZsmV48uQJ5HI5qlevDh8fH9SuXRv23vVA7/0HqNXQv1cKASytQbzrgZjRyayLVzGMP/UnFjdri+S4eFA9kxuEEFRu74sBv68Q9z1KCGDjAMTrMIOEvuRWZjM2PjU1FYP8x2H1yhVwkiuBD2/B8zx4ykP6yYWVOm0KSolEIvTqKVI2f9wR/1I5uAkzt2icqUYHhUplzNBkzoiFFV4oZajVph++8amGIq7OsLSwQGx8Iq7cfwzHwh4413mw2GHqh3CA3AonTv+DHVu3oHuXjnB3c4NcLseHqChcuHgJb8LeY8mv2s0sxTBfiixnPY6OjtlOq/qlaNWqFY4fP57jMlWqVDH5tj4XHx+PpKQkODg46LU+w3z10ud0N2DPiZylJVPMAHEvDhRwAX1yDYiPAoXmolyeAhwBYGEFUqo6iIgzaGgiKVkGNguXI3HSt4BKJYwzzgtOSGrYLFgOSckycILQLPro0aNo27YtAgMD0ahRI4PEno4QguLFi6N48eLo1asXACAlJQXXr19HSEgI1q9fj9jYWNTwLoMAv4ZwsJTqNzDFoSBIqWogZnIh/CmPqpVRZsoY3F2yBsqw9zqty0kkoJSi1fcT0G7mD5BoMYWs0Unlwp1TXZpM6oqTAGZ0ETlp0iT4+/vDq0RJAAB1L4El0yejqJM9aniXgZ2NFVJSlbj16Cku332ImUtWg1iYx+fi14wQAjgXBZVaABGv9EsQS2WAe0lRG0rrQ6lS4fD5rHf8GxQ2z6E0ulDzPNZv3IT1Gzdlea5HDz1nCWOYfCzLmUGTJk2wceNGvH37FoULFxYjJqMqVKgQChUqZHbb+tyhQ4cAQO9qD4ZhIIwr5dWmKRe3sDarsmRiZQdSqTFoQjSe/XcSiItEicKZy8DffYhGeLIaVVq2AxzczKZKIzvSarVgE/wbkqaNB42J0j+5wXEgDk6wnrMY0oqZE89t2rRB/fr1MWXKFOzatQvz5s2DnZ3xTuItLS1Rt25d1K1bN+Oxt2/f4tzFi7COfoWGpQpDLpWAInPjtE9lJK2kchCvioCLbo1LTen27ds4+t957H5xF6eXrsJf8xYhKTpG+LvRMGMKJ5WCV6ngWbMaei1bhGI1DdhHxhAsbYX3osIIs9pwEsDO2WymZ9yxYwcsLS0zmswDQm+fbcfP4+rVrNNpchyHWas2mjJEJhekgCuotb2Q3EibLYVSmu1nBk+p8LlD0mY/cSkKYsb9RBiGYbJ8W3bo0AEymQzffffdFz0kxZyFh4dj9uzZqF27Nry8vMQOh2HyL0KEsfDEyCdjFtZmO4aV2Driv3dJKN3tWzi07IPyvUajQu8xcPcbhCLth2DdPzdBHN3N9mL4U9KKVWC3+QBkbToID+gyxjttWVnrDrDbfCBLUiOdvb09Vq5ciY4dO6JDhw65VuUZWuHChdGxUyd8M3gMLOu3By1WEU/efUBictaZYT7ExuNtogqkTC2QGq1AXD3M9nWMj49HQEAA1q5dC5lcjm8mjsWCsMcYvGUdaLEiSETmRBUPikioUb5LO/x4/Ty+DzllfkkNQPiMsbYXEhyGJJEKSQ0zuZB8+PAhNm7ciLlzTTP9MmM8RGYBUrg04FUZKdZO+O/6LSR99vkSFRuH/67fAVw9geJVhYacZvJeZBiG0STboShbt25Fjx498OjRI/Tp0wfVqlWDlZWV2Z4wfQkopYiLi8Pp06exefNmqFQq7N27V+ywGCb/S5/BIDVJGGNsIJRSJCUnw9rBRWjQlQ/EJyUj/pURpv0zIWJrB+spM6Hu2AOp+7ZD+fdhQKWEilIQAJK07yk1pcKMJ4QAUhlk3/jBolNPSMp6a7Wf5s2bo06dOvjxxx+xe/duLFy4EAUKFDDegWWDSGSQFimFFWeWYtmyZShe2A2OdjbgeYrw6FiERnxA1apVUbhwYZQvXz7TdLPmhFKKUaNGYebMmShYsGDG4zILC9Tu3R0rjx/F5g33IQcgAwEFkAIKHsDEgG/hUbWyWKFrhxDAyk7og5EYk/cKMUtb4Z+ZnHMlJSXB398ff/zxR6YpT5n8jcgskCC3R8Oew8BxHFydHCGXSZGUkoIP0bEoUaIEnvbIpz0oGIb5KmV7i7FLly7466+/8Ouvv2Lq1KlQKEw1Rp1xdnZGp06dMHnyZJQuXVrscBjmy0CIUFWhVgIKw1zYE6kMv2/bBMJx8Pf3N8g2Ge1JynrD+vtZoP4TEX72JH7xH4lKNpYoIJWAAIhRqXEnMQXjlq2Ee5MWIHa69ymwtbXFkiVLcP78eXTu3Bnjx49H27ZtDX8wWqCU4lnouyyPjxs3Dv3798eDBw8QEhKCWbNm4c2bN7C1tUXt2rVRt25dVK9eHVZW4vU5WLFiBSpXrowGDRrkuJwCgELvpqlmQCoXSvZTEoXGxVr0McjU/0ZmCVjZit6A+HNjx47F999/jyJFiogdCmMkPM/jfaQJGuEyDMMYkcba6RYtWqBFixZITExEWFgYUlKylsEyhmVra4siRYqwOyIMYwyECBcenBRQpghJDr22w6XNCS+D/+jR6NGjB2rXro1atdjUY2IgdvZQV6+Dha/Cs31+dLXaeiU1PtWgQQMcOnQIgYGB2L17N37++Wc4OzvnaZuGxHEcvL294e3tjcGDhTuscXFxuHLlCs6ePYtffvkFycnJKFmyZEZVR4kSJUxShXn58mWcOXMGO3bsMPq+zAIRptqFpQ2gTAWUKXjz4hkKu7tlmeXsQ1Q0rOzsYW3vIDQeNsNS//Xr18PDwwMtWrQQOxSGYRiGyVGug8JtbGxQqlQpU8TCMAxjfBwnVG9QHlApAZUClFeDEAJKKdRqdUazxo/zwpOPs6xwkowScUIIVq9ejS5dumD37t1wcnIS7bAY47KyssKCBQtw+fJl9OjRA99++y26dOkidlga2dvbo1mzZmjWrBkAoeLj+fPnCAkJwZIlS/D06VNYWFigRo0a8PHxQa1atWBvb9jZN6KjozFlyhTs2bPn65u6nBBAbgnILdF92GjcunUTxTyKwtLCAkqlCh+io/E27B3u3LmDCgXNa+hQups3b+LgwYPYs2eP2KEwDMMwTK7Ms9sdwzCMsRFOGBMvs8DjRw/Rr08fVK5YAXZ2dpBKJUhOTsHzFy9RrUYNzJ6juWGeo6MjFi5ciOHDh2Pnzp1f3wXcV6ZWrVo4fPgw5s6diz179mDx4sVwc3PLfUWREUJQokQJlChRAr179wYAJCcn49q1awgJCcGaNWsQHx+PIkWKZFR1lC9fXu/3M8/zGD58OBYuXAhHR0dDHkq+lJiYhHsPHokdhtbi4uIwfvx47Nix45MEL8MwDMOYL5bYYBjmq0cpcOnKVVy6knXKwpJlyua6fs2aNdGsWTMEBQVhypQpxgiRMSMWFhaYNWsWbty4gX79+mHgwIHo1atXvmuwbWVlhfr166N+/foZj7158wYXL17Ehg0bcP/+fXAchypVqsDHxwd16tSBi4uLVttetGgRmjZtipo1axorfMZIKKX49ttvMXv2bLi6uoodDsMwDMNohSU2GIZhDODbb79F//798c8//6BRo0Zih8OYQNWqVXH48GEEBQWhe/fuCA4OzvcNFosWLYqiRYtmDLNRKpW4desWQkJCsH37dnz48AHOzs7w8fFB3bp1UalSpSx9of755x/cuXMHf/zxhxiHwOTRsmXLUL169UwJL4ZhGIYxdyyxwTAMYwCEEKxYsQIdO3bE1q1b88XwBCbvZDIZfvjhB9y7dw9DhgxB9+7dMWjQoHxXvaGJTCZDjRo1UKNGjYzZfyIiInDp0iXs27cPM2fOhFqthre3N3x8fFCyZEnMnDkT+/fv/2J+B1+Tixcv4vz589i+fbvYoTAMwzCMTthgcIZhGAOxs7PDkiVLMGzYMKjVarHDYUzI29sbhw8fRnR0NDp16oSXL1+KHZLRuLq6ws/PD7Nnz8aBAwdw4MAB9O/fH5GRkWjfvj0UCgWGDRuGX375Bf/99x+bVS2f+PDhA6ZOnYrVq1ezpBTDMAyT77DEBsMwjAFVrFgRXbt2xcyZM8UOhTExiUSC7777DkFBQRg1ahRWrFgBnufFDsvoJBIJKlasiNDQUMyePRvnzp3D6tWrUblyZZw6dQq9e/eGr68vxo4di61bt+LZs2eglIodNvOJ9GavixYtgoODg9jhMAzDMIzO2FAUhmEYA+vfvz9GjBiBY8eOoVWrVmKHw5hY6dKl8eeff2LlypVo3749goODv/hp0//++2+8e/cuI6FXoEABtGjRAi1atAAgNKR8+vQpQkJC8Msvv+DZs2ewsrJCjRo1EBYWJmboDIAFCxbgm2++QfXq1cUOhWEYhmH0whIbDMMwRhAcHIz27dvD29sbHh4eYofDmBjHcfD394efnx/GjRuHJk2aYOzYsV/k1Jlv3rxBUFAQDh48qHEZQghKlSqFUqVKoW/fvgCApKQkXLt2Dfv27TNVqEw2zpw5gwcPHmDDhg1ih8IwDMMwemNDURiGYYzAysoKK1aswPDhw6FUKsUOhxGJl5cX9u/fDzs7O/j5+eH+/ftih2RQSqUSw4YNw4oVK2BlZaXTutbW1mjQoAEqVqyocZlJkyZhxowZOHr0KKKiovIaLvOZd+/eYfbs2Vi+fDnrq8EwDMPka6xig2EYxkhKly6NoUOH4vvvv8fPP/8sdjiMSAghGDp0KFq3bo1x48ahZs2amDRpEqTS/P8VPHXqVAwdOhSlS5c2yvbnzZsHS0tLhISEYMuWLYiKioKrqyt8fHzg4+ODSpUqfRG/RzGo1WoMGzYMv/76K2xtbcUOh2EYhmHyhFVsMAzDGFGXLl3A8zz27t0rdiiMyIoWLYrdu3fDw8MDvr6+uHnzptgh5cm+ffugVqvRpUsXo+1DJpOhVq1aGDNmDDZv3owjR44gKCgo43fZuXNntG3bFlOmTMG+fftYvw4dzJgxAz169IC3t7fYoTAMwzBMnrHbHAzDMEa2YMECtG/fHpUrV/7im0gyOSOEoG/fvmjRogXGjx+PMmXK4Mcff4RcLhc7NJ08ffoUq1evzrGvhrEULFgQ7dq1Q7t27QAIlQf37t1DSEgIpk2bhrCwMNjb26NOnTrw8fFBtWrVYGlpafI4zdnRo0fx4cOHjH4nDMMwDJPfscQGwzCMkcnlcqxZswZDhgzBwYMHde5FwHx53N3dsW3bNuzevRu+vr6YP38+atasKXZYWklJScHIkSPx22+/mUVCRiKRoFKlSqhUqRKGDRsGAIiJicHly5dx4sQJLFy4EKmpqShTpkzGEJZixYp9tT0lXr16hcWLF4uSlGIYhmEYY2GJDYZhGBPw9PTEhAkTMH78eKxatUrscBgz0bVrVzRp0gTfffcdChUqhMDAQLOvLhg/fjwmTJgAT09PsUPRyMHBAS1btkTLli0BCNPNPn78GCEhIVi4cCFevHgBa2tr1KxZEz4+PqhZs+ZX0WdCoVBg+PDhWLlypdm/zxiGYRhGFyyxwTAMYyJt2rTBv//+i02bNqFfv35ih8OYCRcXF/zxxx84ePAg/Pz8MHv2bNSrV0/ssLK1ZcsWODs7o02bNmKHohNCCMqUKYMyZcqgf//+AIDExERcvXoVISEhWL58ORISElCsWLGMqo4yZcqA476sVmRTpkzBiBEjULJkSbFDYRiGYRiDYokNhmEYEwoMDESnTp1QvXp1VKhQQexwGDPSvn17NGrUCJMmTcLOnTsxd+5c2NjYiB1Whnv37mHHjh3Yt2+f2KEYhI2NDRo1aoRGjRoBEKo6Xr9+jZCQEKxZswYPHz6EVCpFtWrV4OPjg9q1a8PJyUnkqPW3e/ducByHTp06iR0KwzAMwxgcS2wwDMOYkFQqxdq1a9GnTx8cOHDgqyh/Z7Tn4OCAtWvX4u+//0a7du0wffp0sUMCACQkJGDMmDHYsmULJBKJ2OEYBSEEnp6e8PT0RPfu3QEAqampuHnzJkJCQrBp0yZER0ejYMGCGVUdFStWzBfTzT5+/Bi//fYb66vBMAzDfLHM/9uYYRjmC+Pu7o7p06fD398fGzZs+GqbGDKaffPNN6hbty6+//57nDt3TtRYKKUYPXo0pk+fDnd3d1FjMTULCwvUrl0btWvXznjs3bt3uHjxInbs2JGReKpYsSJ8fHxQp04ds/sdJScnY9SoUVi/fj1kMpnY4TAMwzCMUbDEBsMwjAiaNGmCCxcuYPXq1Rg5cqTY4TBmyM7ODsuXL0fnzp1x+/Zt0eJYs2YNypYtiyZNmogWgzlxd3dHhw4d0KFDBwCASqXC3bt3ERISgqlTp+L9+/dwcHDImG6WUipqvAEBAZg4cSI8PDxEjYNhGIZhjIklNhiGYUQyZcoUdOvWDbVq1UKNGjXEDocxU0WLFhVt39euXcPx48exc+dO0WIwd1KpFFWqVEGVKlUwYsQIAEB0dDQuXbqEv/76Cw8fPhQtto0bN8LNzQ2tWrUSLQaGYRiGMYUvq903wzBMPsJxHNasWYNJkyYhOjpa7HAYJpOYmBhMnDgRq1ev/uJmBzE2R0dHtGrVCjNmzEC5cuU0Lvfbb7/h7NmzSExMNHgMd+7cwe7duzFjxgyDb5thGIZhzA2r2GAYhhGRs7Mz5s+fjxEjRmDHjh2s3wajk/j4eKNsl1KKkSNHYv78+XB2djbKPhigcuXKuHDhAn799VckJibCy8sr03Sz+n4exMfHY9y4cdi6desX2+yVYRiGYT7FEhsMwzAiq127Nho2bIiff/4ZEydOFDscJh9ZuXIl3Nzc0K1bN4MmxRYvXoz69etnaprJGF6tWrUypn2mlOLly5cICQnBypUr8ejRI8jlclSvXj1julkHB4dct0kpxahRozBjxgy4ubkZ+QgYhmEYxjywxAbDMIwZGD16NPr06YN///0X9evXFzscJp+YMGEC7t+/j169eiE4ONggM3L8999/uHbtGjZt2mSACBltEULg5eUFLy8v9OzZEwCQkpKCGzduICQkBL///jtiY2Ph7u6eUdVRoUKFLBUZK1euRMWKFdGoUSMxDoNhGIZhRMESGwzDfNXu37+P//3vfxqfP3z4MGrWrIm+ffsadZgIIQSrVq1Cx44dsWPHDri6uhptX8yXQyqVYsaMGbh16xb69++Pvn37ol+/fnq/VyMiIjB9+nTs27ePDYsyAEopkpOTNT6fmpqa4/qWlpYZSYx0YWFhuHjxIrZu3Yo7d+6AEIJKlSrBx8cHFhYWOHXqFGv2yjAMw3x1WDcwhmG+Wjdu3ECDBg1yvDP99OlT9O/fHz/88IPR47G3t0dwcDCGDRsGtVpt9P0xX47KlSvjyJEjCAsLQ5cuXfD69Wudt6FWqzF8+HAsXrwY9vb2Rojy63Lt2jV4eXnhxo0bGpepW7cuZs6cqdOUsIUKFULHjh0xf/58HDp0CPv27UP37t3x+PFjDBw4ENHR0ejXrx+WLl2KS5cuQaFQGOBoGIZhGMa8scQGwzBfrYULFyIqKkrrZSMjI40ckXCB2r59e8yZM8fo+2K+LFKpFFOmTMG8efMwfPhwrF27VqcL5rlz56Jdu3aoXLmyEaP8OkRERKBZs2Z49epVjsspFAoEBgZi5cqVeu8rfbrZkJAQHDx4ECdPnsTSpUtRunRpHD58GN26dYOvry8mTJiAXbt24fXr1zq9LxiGYRgmP2CJDYZhvlohISFaL8vzPK5evWrEaD4aPHgwXr9+jePHj5tkf4x5i4uL0+m5cuXK4dChQ0hMTESHDh3w/PnzXPdx4sQJvHr1CoMHD85TrLp6/Pgx7t+/r/H5M2fOICEhwYQRGcaff/6J2NhYrZffsmVLnva3aNEiNGnSBLVq1QIgzLbUpk0bzJw5EwcOHMChQ4cwbNgwJCQkYM6cOfDz80P37t0RFBSEc+fOISkpKU/7Z/KnnBJcKpXKhJEwDMPkHUtsMAzz1apYsaJRl8+LpUuXYsGCBQgNDc3TdmJjY3H58mWNz9+/fz/P+xDTpUuXcpxJZtKkSbh48aIJIzKct2/fombNmvjjjz80LjNu3Dh06dIFKSkpmR6XSCQICAjA4sWLMWbMGPz666/geT7bbYSGhmL+/PlYunSpQePPze7du1GhQoUcX5+pU6eiQYMGCA8PN2Fkeffhwwedls9LNdi5c+dw69YtjBo1SuMyHMehfPnyGDRoEFavXo0jR47gt99+Q82aNXH+/Hn069cPbdq0gb+/PzZt2oTHjx+zqo4v3JYtW1CpUiWNz7969Qrly5c3WUKfYRgmr1hig2GYr1aPHj20XrZ+/fooUqSIEaPJzNraGsuXL8ewYcOgVCr12sbz589RrVo1LFu2TOMyp06dQtmyZXHmzBk9IxXP+fPn0aRJE2zbtk3jMtu3b0fTpk1x7tw5E0aWd5RSfPPNN1pdVOzduxcjRozI9rmSJUvi4MGDkMlkaNu2LR49epTpeaVSieHDh2P58uWwtrY2SOzaiIuLQ58+fbR6b9+8eRNTpkwxQVSG82mzT2Msny48PByBgYFYsWKFzs1e7ezs0LRpU0ydOhV79uzBkSNHMHHiREilUixbtgx+fn7o1KkTZs+ejePHj+tUgcKYtyNHjqBfv365JgwfPHiAZs2a4eXLlyaKjGEYRn8sscEwzFerZ8+eKFOmjFbLBgYGGjeYbJQtWxYDBw7Ejz/+qNf6gwcP1moYQmJiIjp16pTvmgwGBwfnOONEuuTkZAQHBxs/IAO6desW7t69q/Xye/bsyVK1kY7jOIwcORKrVq3ClClTEBQUlFFmPm3aNAwYMABly5Y1SNzaOnXqlE7vt6NHjxoxGsOrX7++Tr1Kcqq20EStVmPYsGFYsmQJ7OzsdF7/c4QQFC9eHL169cKSJUtw5MgRbNu2DS1atMCdO3cwcuRItGnTBkOGDMHatWtx+/Zt3L59W+PFMaUUFy5c0FgpxIhnw4YNWlfkxMXFYe/evUaOiGEYJu9YYoNhmK+WRCLBTz/9lOty9evXR/PmzU0QUVbdu3dHSkoKDh48qNN6MTEx+Oeff3Ra/t9//9U1PFFpk7TRZ1lzEBMTo9PySUlJuU4d6unpib1798LFxQV+fn5YtmwZkpOT0b179zxEqh9dpzPOb9MfcxyHGTNmaLVsmzZtUKdOHZ33MWvWLHTu3NmoQ+QsLS1Rt25djB8/Htu2bcPRo0cxa9YsODs7Y+zYsahcubLGGXgopahXrx6GDBnCZnkyM2/evNFpeX1mWRIbz/N4/PixxucjIyN1HjJmTq5du4bly5drfP78+fP4/fff2ZAy5qvCEhsMw3zVevbsCS8vrxyXCQwM1LnM25CCgoKwfPlynS7Ora2tIZPJdNpPfpviU5fyfX0uHMVUo0YNSKVSrZf39vZGgQIFcl2OEIJBgwZh5syZmDNnDpycnPQe6pQX1atXh6Ojo9bLi5VYzIuOHTtqVbWhTzXY33//jbdv32LAgAF6RJY3RYoUgZeXl9bD1zZs2ICNGzcaNyhGJ7Vr1zbq8mJLTU1F165d0a1bN43LPHjwAIULF8aBAwdMGJlh/PPPP2jUqBEOHz6scZnQ0FAMHjwYAQEBpguMYcRGGYZhvnKrV6+mALL95+XlRXmeFztE+uLFC9qyZUuanJys9TrNmjXTeFyf/3N0dKQKhcKIR2B4d+/epYSQXI+NEELv3Lkjdrg6GzZsmNav36pVq7TebkrK/9u78/AoqrRt4PepXrMnZGPfZBMQBUUQFVlEDQzquKAsKiiiA7zu44yiAygq6LiM64gwoizjqKjfK6gj+KKoA8gysoMhECAJSwIkIWTppc73RyWBJJ303tUF9++6cgGd6lNP0d3VdZ465zmV8pprrpF79+6VS5YskVdffbXctGlTGI/Es2effdanY7NarfLAgQMRjy8Uli5d2uSxDRw40O82Dx48KIcOHSrLy8vDELFvnnnmGZ/fmwBk8+bN5aOPPio/+eQTefDgQd3i9seePXvk6NGjmzyuMWPGyH379ukdqt+2bt3q07kTgMzMzJSnTp3SO2S/TJs2zef3pslkMtz55corr/Tr87d37169Q/bbBx98ILt06dLoMWVkZMgXXnhBut1uvUOlKMLEBhGd81wul4yNjfX45fnee+/pHV6tL7/8Uk6ePNnn7f/973/7fOEza9asMEYePrfffrvXY7vtttv0DjMg+/btk2az2evxtWnTRlZVVfnc7pQpU+SXX35Z++8jR47IMWPGyGnTpsnKyspwHIpHxcXFMiUlxevx+fOejzZut1umpqY2emw///yzX+05HA553XXXyd9++y1MEfvmrbfe8qtjde+998rt27fL+fPny3vvvVdmZWXJW2+9Vb700kvyxx9/1DVJ40lubq5s2bKlT8fWunVrwyRrzjRq1Cifju+VV17RO1S/devWza/351tvvaV3yD5zOp3SZDL5dXwLFizQO2y/vP766z4f2x/+8Ae9w6UowqkoRHTOM5lMWLZsGUwmU53Hb7zxRkycOFGnqBr63e9+h4SEBCxZssSn7YcNG4bLLrvM63YpKSn4n//5n2DD08XTTz/d5DQhIQSefvrpCEYUOu3bt8eECRO8bjdt2jRYrVaf2vzoo48QHx+P3/3ud7WPZWRkYPHixejduzeGDx8eseVxk5KS8MgjjzS5jcViwZ///OeIxBMOiqLgqaee8vi78847DwMGDPCrvSeeeAL33HMPOnfuHIrwAubv1KCrr74a3bt3x9133425c+fiq6++wrx589CnTx+sXr0a48aNQ1ZWFqZOnYpFixZhz549utYG+OCDD1BQUODTtnl5eVi4cGGYIwo9b+dOAMjMzGx0xaVoVv+7PNTb68lsNqNjx45+PSfSxaGDoaoqXnjhBZ+3f/fdd4NaLpvOMnpnVoiIosWxY8fkk08+KcePHy+///57vcPxyOl0yhEjRsidO3f6tL0vozaMOlqjxg033NDosY0cOVLv8IKyb98+qShKo8fXrFkzn0dr7Ny5U44YMUI6nc5GtykqKpLjx4+Xjz76aETuohcXF0ubzXbWjbapb/LkyXWG/rdv316eOHHCrzY+//xz+eCDD4YlvkDccsstPt1R7dKli3S5XF7bU1VV7tmzRy5atEhOnTpVZmVlyd///vdy1qxZcuXKlbKkpCQCR6W5/vrr/bojftNNN0UstlBq6twJg47WkFLK++67z6/Xz2hTFR955BGfj61ly5YRHYkXrPz8fL9eOwDy22+/1TtsihJMbBARGUxBQYEcOnSoLCsr87qtqqpNzlO12+0R7TCEw5YtWxo9vs2bN+sdXtCuuuqqRo/v6aef9qmNsrIyOXToUFlQUODT9suWLZODBw+Wq1evDiZ0n9x2222NHl9ubm7Y9x8pZWVlctmyZTI7O9un7b/77rvaujc5OTny2muv9WvKUbg19bk782fRokUB76O8vFz+9NNP8q9//ascNWqUzMrKkhMnTpTz5s2T27ZtC9v8+qeeesqvjtXMmTPDEke4NfUa2mw2w9XWqLFz584mE8Jn/lx33XV6h+u3Q4cOSbvd7tPxvfHGG3qH6xdVVZucvufp5/Dhw3qHTVGCiQ0iIgP67rvv5IQJE3wqbLp48eJGLwjGjh0bgWjDr2/fvg2O7ZJLLtE7rJDYtGmTx0J/MTExPhWTVVVVTpgwQX733Xd+7be4uFhOmjRJTp06VZ48eTLQ8L06duyYTEhIaHB848aNC9s+o52qqjIzM1P26tVL/vbbb3LYsGFy//79eofVgLdRG76O1vDHwYMH5aeffiofe+wxOWLECDly5Ej51FNPyWXLlsnCwsKQ7GPz5s0+d6qMWpy4Rvfu3T0e17333qt3aEEZO3asT6/fmjVr9A41IA8//LDXY2vZsqVfBcejxeTJk33+/F111VV6h0tRhIkNIqIaqlr94z799yj27LPP+lTcVFVV2alTpwYXBLGxsSHrCOjN6XTKwYMHS5vNJq1Wqxw0aFCTUy6MZuHChXWmbKSkpMhff/3V47aqqtZJeL333nvy2WefDXjfK1askIMHD5YrVqwIuA1v8vLy5ODBg2VSUpJs2bKlzyNRzlb5+fmyRYsWEoCMi4uT06dP1zskj7yN2ghmtIavHA6H3LBhg3zzzTfluHHjZFZWlhw3bpx888035YYNGwJe7enmm2/2qWNl9OlSpaWlsk2bNnWOaejQoXqHFTRfRm0YcbRGjUOHDjU5jc+IozVqHDhwQFqtVp8+f6tWrdI7XIoiQkodqzMREelJqoDLCahu7Ueq9TYQgGLSfkxm7U8vxdYiSVVV3HLLLfjLX/6Ciy66CA6HA9988w2uv/76BtueOnUKN9xwA3766Se43W5069YNS5cuRZcuXXSInAKhqirWrVuHxMRE9OjRo9HtZs+ejU8//RRff/018vPzMXPmTCxduhSKEni98LKyMjzxxBOoqqrCSy+9hKSkpIDbOidJqZ1jaggFaOL1WL58OW699VZUVFQAANLS0nD77bfjtddei7pCh+effz527drV4PG4uDiUlJToEm9hYSHWrVuHtWvXYvPmzVBVFd27d0f//v3Rv39/tGrVymsbW7ZswYUXXtjkNkIIbN26tcnPo1H88ssv2LBhA7KystChQwe9wwmJkSNHYtmyZY3+fs2aNejfv38EIwqtsWPHNlpMPC4uDkVFRbDb7RGOKjSmTJmCt99+u8ltBg0ahFWrVkUoIjICnxIbDocDlZWVkYjnnBYXFxd1FyxEZyW3C3A5ALfTv+cJBbDYAJMlahIcRUVFGDVqFN544w2MGTMGeXl5OHr0KM8l57Bhw4Zh5cqVaNOmDVJTU7FixQqkpaWFpO0ff/wR06dPx6OPPooRI0aEpM2zkpTaOcZRCbgd2jmnPqEAZgtgtgHWmDqJjsceewwvv/xy7b9tNhtSUlLwww8/RF0ycsOGDejfvz/cbnedx+fNm4d77rlHp6jqcrvd2LlzJ9auXYu1a9ciPz8fSUlJuPTSS9G/f3/06dPHYwfwlltuwdKlSxtt97bbbsNHH30UztApCNu3b0fPnj09/q5jx47IycmJcEShlZ+fj9atW3v83aRJk/Duu+9GOKLQOXjwIDp27AiXy8O5s9qqVaswaNCgyAVFUa/RxMauXbswd+5cLF26FAcOHIh0XOes3r1749Zbb8X999+PlJQUvcMhOrtICTgq/E9o1CcEYI3VRnFEgRdffBEzZsxARUUF0tPTsXr1anTr1k3vsEgn3bp1w+7duwEAycnJePDBBzF9+nSvSzv6qry8HNOnT0dRURFefvllNGvWLCTtnhWkBKpOAVXldUdo+MIaA9jjAZMZ/fv3x7p162C329G8eXM88MADmDx5Mmw2W3jiDtKaNWswZcoU7N27FxkZGZgxYwbGjBmjd1hNKikpwfr167F27Vps2rQJlZWV6NSpU+2ojg4dOmDr1q1NjtrYtm3bWTFa42x2xRVX4Oeff27w+PLlyzF8+HAdIgqtJ554ArNnz67zWJs2bZCTkwOLxaJTVKFx/fXX48svv/T4u06dOiE7OzvCEVG085jY2LRpE66++mpYrVbcfPPN6Nu3L2JiYkJ2UUQNSSlRXFyM7777DsuWLUO3bt2wcuVKXjAShYrbpXU2EMLZd2YrYLHrNnrD7XbjwQcfxEcffYRjx44BAEwmE95//33ccccdusQUaWrhYbjX/ww1Zzfc2TuAUye1lzg+AabO50M5rxtMfS+Hkt5c71CDIqUEqioAVxUAAVjtENaGd5hrOmf5+fm1j8XExGDSpEl47bXXQhrTunXr8OSTT2LKlCm46aab6sS6detW9OrVy2sbbpcL+Vu2Yf+G/6Jg2w5UniyDYjIhqUUm2vS5CO379kFKa+/TBqKCywGcKvY/oVFfTALi05ojMTER06ZNw6RJkwzfQTECKSVycnJqR3Xs3bsXdrsdq1evrj2/nqlr164ep+AYkayZKiUloCgQytkz4s/lciErKwurVq2C2+1GUlISXn31VUyYMEHv0ELms88+w0svvYTS0lJcd911eOGFF2C1WvUOK2jZ2dmNjlD78MMPz5nrHPJdg8SGy+VC69at0a5dO3z77becR6uDrVu3YsiQIRg0aBA++eQTvcMhMj6XQxupEQ6KGbDF6pLcyMvLwxVXXIFjx46hrKys9vHx48fj/fffr/23rBmpcqpEGxoPaEPgYxOBmHgIEXjtBb24t/8K5xdL4N74H+0BRQHqDYWHYqqtm2K6eAAsN46BqcdFkQ00CNLtgjySC3lkP1B6rOFII6sdSEqH0rwDkNoKQlGwceNGDBkyBKWlpTCbzWjRogVGjx6NadOmITExMeQxVlVVYdasWcjJycFrr72GjIwMLFiwAFOmTMHWrVvRsWNHj88rLjiEn95bgB/enoeTRwsBACaLBWdekqjVQ5A7D7wcg6ZOwkW/HwmTOTpGSdUhJVB5Cqg8GbImjx47gWZtO8F8FnROjKy8vBz//ve/cdttt8HpPP35s9ls+OabbzBw4MCgatfoSbocQGkRUH5SS/qfWWPKZAZscUBcIpCQetYkOlwuF8zReA6hRs2cORMzZsyo89jNN9+MTz/9VJ+AKKo1SGysWLEC11xzDTZu3Ig+ffroFdc57+WXX8a0adNQWFiIhIQEvcMhMi6XE3CUh3cfOiY3VFXFkiVL8Oyzz6KgoABlZWW44IILsGXLFkhHBeTRA8DR/VpyxxPFBKS1hshoBxEb+o5vqMnyU3AseBOuFf+rxe7r3fHqbc3Drod1/FSI2LjwBhoEqaqQ+7dDHtjhuTZDHQKA1EZwdOqDv374Cf785z+jVatWGD9+PP70pz8hPj4+7DH/97//xR//+EfccssteO6555CXl4eBAwfihx9+qLOdqqr44a25WPr403A7nJBq/YK9DQmTCdLtRqtePTFh4Vy07uV5zrwupAQqTmrTT0JNMQEJqdqfpKuysjLMmTMHGzduRJcuXdC3b19s2rQJu3btgslkwkUXXYT+/fujX79+SE1N1TvcJkmnAyg6qI0u8oUQQFI60KzlWZPgIGPZuHEjXn75ZVRUVGDSpEnIysrSOySKUg0SG4899hg+/vhj7N+/n1NPdJSTk4NOnTph2bJlLNBGFCjVDVSWed8uFMxWbY68TlRVxaeffoo//elPOHz4EMpztkHm79Y6Xl5Vd47T2kC06w5his5h7+qhPFT+5QHI44WADx1ijxQFolk67M+8DqWF56JrepKnSqBu+8n3Tkc9WwuOY/H63zDzhTmIjY0NbXBeOJ1OnH/++bUF+VJSUrBkyRJcd911AIDy4mK8c+MYZP/wU0DtKyYTIIBbX52NwVPvC1ncQak4Gd5zjGICEtO0QqNRSlaVA8cPQzortVFTigKYrRApmYZIlgbL4XBg8+bNtVNYjh8/joyMjNpaHRdccEHUjBKQpUVA4UEPK4D5wGwBMjtAxPBmGxFFpwaJjQkTJmD37t34z3/+o1dMBO2L0mazYcGCBbjrrrv0DofIeKTUOhyBXMAFyhane0FR1VmFY2u+Qao9wDtrFhtE1/4QsdF18aoeKUDFnyYBJ0uDr2GgmICERMTMfhdK8+ip3yBLj0H978rTc90DIQRgj4PSZxiELbKJjY8//hj33XcfiouLax/r3LkzduzYAUdZGV4emIVDO3ZBrT9lKAC/nz0T1/7p4aDbCYrLAZxsWHsh5KwxQFxy+PfjByklUHoMsvAAcPJ49aPVCVLU3BSTQEwCRHobICXznLrbf/To0drlZrdu3QpVVdGjR4/aZEeLFi0iGo+UEjheAJw4HHxjzTtCxBunuL2sGVXlqNSuB0xmICYRwnIWTPOSElBd2sg+qVZ//KqXqTdbo2b1NqJIaZDYuPPOO5Gbm4vVq1frFRNBu/tqMpkwf/583H333XqHQ2Q8zirAGeFlqoUA7Am6XUxIlwNy5xqgogyBF0kVgMkE0f3yqLkzJ50OVDw8HvJQXvBJjRqKCaJFK8S8+kFUXODK8lKo67+pnnoSZIFbIYCYBCiXXAdhjtzomzZt2tQuD19aWgoAUBQFjzzyCFps3Ik9q38OSVKjxsR/LcAlo27yvmE4SAmUFobu/ehNfIpWqDgKSLcLcu9moOyE70+yxkB06h3xZFu0cLvd2LFjR+2ojkOHDiExMRH9+vVD//790bt3b4/LzYaKPHEYOJbvfUNftewc9aNxpNsFHCuAPJLrYVSVAJq1gMhoB8QnG2+Ees1y0q6qppPgZqv2cw4lFenc5ndiY8GCBZgwYQL27duH9u3b+7yjGTNmYObMmWhkddm6QQmB6dOnNygWcy5hYoMoCFICFaX67Nsao11IRJiUEjJ7A1B8FMGv/FK96sYFgyBM+l8QORa9C+dnCwMfxdAYIWC5aRys4+4Pbbt+klKFuvFb7c53KI+xVWeYul4auva8cDqdyM/Px4EDB7B3715s27YNmzZtgm3PAbQ7eDS0OxMCMUmJmLlrIxIzM0Lbti/CPQWlPqEASRm634GVLqd2nqn0t6aIAExmiC6XQNijt76NR6pb60TWJh21Ywm2w1hcXNxgudkuXbrUjupo3769zx3uEydOwGq1Ii6u4f+trDwF5IV49RaTGWjbAyJKljyvT5YUQeZs8lKjqHqEUWKalnSL0imYDUhV+/z5MxrVGqtNJTIY6XYD+7ZD3bleK6AtJRCbCNG1N0SX3hCW6Fz+mvQTnWekKPHcc89h3bp1WLduHY4ePRqyZMvixYsxbtw4xMXF1VnJgIhCpP7qEZHkrNIlsYFjBUDxkRA1pq2iIvN2QbTrEaI2A6MWHITzs0WhT2oAgJRwfrYI5sHDobRqG/r2fQ0j7zftoi3U8rMhM9pBpGSGvm0PLBYL2rdvj/bt22PgwIEAgNIjRzGtQ0+E/BMpJapOluGTR57EPYvnhbp1r/vWlo6O5D5V7e6sjqM2pKpC7v01gKQGAEjA7YLcswnoeqkxOiSqqhWebjAqp+ZuuUNLbNhiA6qBkpycjGHDhmHYsGFaq1IiOzsba9euxUsvvYR9+/YhNjYWl1xyCS677DJccskljRYCfvTRR/HDDz/g22+/xXnnnXc6UimBI7l+x+aV2wUU5QGZ7UPfdpDkiSOQezb6sqX2R2mRNtKx22URHeEWkECSGkB1AXVjJTfU7F8hf/xf7XiFOH0NUHoc8nAu5M/LIS4ZAtF7kPFG3FDYRKwa1VNPPYWKijAttxgmTz31FNavX4/evXuHrM2ysjI8/vjjHrPqRBQizir99i1VH1ayCPEupQp5cEfoGz6yD7JK3/O285vPw3uXWihw/vvz8LXvhVRVyNztYWpdQD0QhveFH36a9wFcVY2syBMk1e3Ghn8tRcmhENQN8IezKrK1e2pURjiZUt/xAm3J6IBJwOmAPLw3ZCGFjapqI3K8TTVS3drUv0CLGZ9BCIEuXbrgzjvvxNtvv42vv/4aH374IS6//HL88ssvmDBhArKysnD//fdjwYIF2LVrF9Tq/W7YsAF79+7FwIED8dVXX51u9FRx+KZknjymLRkbReSpEm2khr8qyiD3bPJpVLmu6i/L6w+PSbropG79D+SKf55Oonp6XVwOyLXfQF39RfS/bhQxEUtsmM3msM4fDId9+/bh0KFDWLRoUcjanDVrFhISEnDjjTeGrE0iOoNU9el0nEmNbGIDxUfDlsyRhfvD0q5P+66qgmvll+G9GFPdcK34ErJKp2TYsfww1oKR2hzzCn1GBqpuN354a65PS7oGTEr8NO+D8LXviUOnZJ9Lp4QKqqe6FR4MRUvAsUNa/YNoJWX18r2+dpaqtw9D5youLg4DBw7E448/jk8++QRfffUVnnzyScTGxmLu3LkYOXIkRo4cif37tfN0QUEB7rrrLkyfPl3r7JUUhjymOsLdvp9kfnbgr8PJY5EpBhwotyv478IoS0R5Ig9mQ/74/3x/wva1kNvWhC8gMpSQJDa+/vprXHnllYiLi0NCQgJGjBiB7dvr3oGaMWNGg6FCVVVVePjhh5Geno6EhARcf/31yMvL87iP/Px83H333cjMzITNZkOPHj3wj3/8o84233//PYQQ+Pjjj/Hcc8+hdevWsNvtGDp0KPbs2eP3cflTQ8QX2dnZePXVV/HKK69EzdJfRGedYL74haKtbBKTCMQkBD7sO4QFEn0hfSwKJy4cAuXS39X5QbKXaQpFns/JkaDm7AIq/LtLbb5hNGLe+gixH3+P2Pe/hOUOH+pnVFZAzdkZYJTBkYV5vo1IMVuhXDAQyoAboVx1O5QBN0J0vNC3fRSFsGigHw7t2IWSQ75Nj7rm8Ycwc/cmvO0uxt9lKbpcdYVPz5Oqiq3LvgkmTP8FOtUtvhmQlAkkN9fqZcQEUHzRpdM0u1MlTU9BiU2E6HwxRK9BED0HQrTq0vj7WqrA8QiPsvGH26XVkLDHa69RbFLdWhpn/s6eoE09jNBIPSEE2rZti1GjRuGVV17B8uXLMW3atDrX10VFRXj++efRr29fyIqT3huNiYfodHGDH7Tr6f25ZcWBH0yIyaoKoKTpWj6ibXcofYdD6TscaFDrRUAe0S+R71VTSQmT5fR7MiZRu47xND3K5QjPtM4QUjf+H0TvQVDGPAblDy/ANHkO0LJj7e/FNWOg3DUNpslztN8BkBv/D9Igo1EovIJObCxcuBAjRoxAfHw85syZg6effho7duzAFVdcgdzc3CafO3HiRLz22mu45pprMHv2bFgsFowYMaLBdkeOHEH//v2xcuVKTJ06FX/729/QqVMn3HPPPXjttdcabD979mx8/vnneOyxx/DEE09g7dq1GDt2bLCHGrSHHnoIgwcPxvDhw/UOhejsFcyXmy1Wu4B1VmoXqRab9hPJGALhx+oEsuIk1D2ban+8Di13VEI69bnLo+bs9msaimXsJNjGT4UsK4XjvVfg+GwR4PKhsyGEti8dyNIi3y40zRYgLgmyYA9ktjZ/XGnfE6J1l6afJ8QZy3FG1v6Nv/q8rcVux9Zl3+DEAf9HBeRt2RbS1VaaJNXAP99up1bUuLxEe83tcdo5x982dKAlTxv5LJotEOf1BmISIAv2AGUnIDLaQmR2aLy9olCM/ggTVxUAUb2EZr3PplC0QowQ2veEVLWC0Yqp+nmR99NPP6GkRDuPp6WloW3btrjoootwy8jhjb1idTkqIQ/vPf1Tc77wpZaKszK8I7L8IAsPNL1BUjqQ3raJDrAEio9AOiK8mpovpGz8sy/E6TovzkptO5NZe196omcNMi/kiaNAwV7AZIbM3QWcLPawESB3baj7WPlJIDfEBXLJkIIaNlBWVoYHHngAEydOxNy5c2sfv+uuu9C1a1c8//zzdR4/0+bNm7Fo0SJMnjwZb731FgBgypQpGDt2LLZs2VJn22nTpsHtdmPr1q1ITU0FANx///0YPXo0ZsyYgfvuuw8xMac/wJWVlfj1119htWoF/FJSUvDggw9i27Zt6NnThwx0GCxfvhzffvstNm/erMv+ic4ZgV5kKebqi1Pn6TsjJgtgtgUwzUNqFyIRKGgl3S7Anwsxp0MrMupP56yiFLCk+R9ckNSD+wBF8W0EjNUGy8jbICvKUTnzEe11dPj4uikK1AORn/cvVRUo93H1nqpyqGuXoXZ4vKJAdLlEWwa0yZ3I0x2VCCvYtgMmiwVup/cL6eXPzAYAdBzQD6nt2/m1H1dlFQr37kNm504BxemXYBIoFSe1c4JQtOlqgawoEeHRYLUqm5iaEZcMYbZAFh8FivIgTx7XCtamtwYaq6ehc+2eRkmpnRtrzo+KCXXuAZqt2mvorNS+J1S1eoUUm1bDIELn/TMVFRWhb9++uOGGGzBy5Ej07NkTiqJUvx4+JJDcrrrJ8WYttT99LUbtqPAw+kEHTSX4zVaIDr2AQzlAWqumE4qnigFr85CHF5Qmv6+rC2tKeToZZ7ai0c9rFI9skLk7ACEgN6wEAIjm7YDEZnW3WbFE+8xdPOT0g0KB3LcNoqO+xc5Jf0ElNlasWIHi4mKMHj0aRUVFtY+bTCb069cPq1atavS5NcWNHnjggTqPP/TQQ1iyZEntv6WUWLp0KUaNGgUpZZ39XHvttfjoo4+wadMmXH755bWPT5gwoTapAQBXXnklAGDv3r26JDYcDgcefvhh3H///ejevXvE909EPlCqL17rzGGX1cM5q5eFi0b+Dn9OaAblkiztrlXxUcjcrd7n3eo0H15WVvg8bFZp2wHCZocsLUbM3xZCScuAWnQEjvl/g3vtD00/WZXaviLNnwvMev8PIq2V9pcTPgzp1+kOXdXJMkTqc6PtKxKCPJ7EjNPnmqqKAFZX0ek81NQUmJrEb0w8YIsBErUkqDBbIU1mz+cPqUKqKoQSsVJvvvF2vhH1vidq/qz9/oh8YmP27NmefxFIBzY2CcJq16aw+PrejJIRG019j4kOvYDKU5AF2afPnY2JyvovTbwvpaoll6wx2hRaQHvtG0seRvNUlIryuiug+Eqq2rLGdM4LKrGRnZ0NABgyZIjH3ycmNj5/dP/+/VAUpc6yVADQtWvXOv8uLCxEcXEx5s6d2+joj6NH686pa9u27rJ9KSnaHa0TJ3wfrh1Kr776KoqKijBz5kxd9k9EZzE/LqJl4UHt4k51Q2S2g2jWAlDd2hKOTe8kqBAD5k+np/riWiQmw/nRfMgjBbD+4XHYHp6O8ok3AiebGBkhUHcOfaQE0gESCkT3yyCatYB6cJdvc8J1WgpPmGqSguGnGKVu1akTWufYHgdY7YDTHsbisSHU1GexvBSy8CBEehuI7pdDut1nJC2aeP3PxiUao+mQAvn/rVka2peEaTD7CQfRyDk8tRWQmKpN4bPFno7XGqONdqyfAApg6d7wa+r/WFTXA5NaMkNRtH9bY6qXeTUQUxDfwybjLGVL4RPUlUDNMlMLFy5E8+YNh22FokBmzT7GjRuHu+66y+M2vXr1qvNvUyMfDD2WAyopKcGsWbMwefJklJaWorRUu7guKyuDlBK5ubmIjY1FRkZGxGMjOisFepFVc9epzkVNzZ2DKL7DYbZoMfuyWkJBdu1fpbMKIikDiPWhgKGtkbm6YaakpMLt4+upHi6AdLshTCY4P1sEOB0wX387TB06Q0nLhNpkYkNApKSGKGo/KCZtSK2vdwjNFigXXAWRkgl13xbIfVt9e55Nn2Hiya1aRmz+fXLLFhHZT9CdnjPvKsenaJ0PfxIbenW6zFYAjd8RlXm7IY/kaska1Q3RtZ9WzLGx0UKKqUFB+ajgLSZZ73ui5s/a93kUHZPZ6n2bM9liIWIStNfN1ylygPYdFA2sdq1+TT3CFguhmCC6XlrncaXrpVCzNzacchNIXa1wa+p9aTJpyQyXU/u8uaElNhqb6haNn7sayemBjQASCkRyeujjIcMJKvNQM9oiIyMDV199tV/PbdeuHVRVRU5OTp1RGrt31y3gVrNiitvt9nsf0eDEiRMoKyvDiy++iBdffLHB7zt06IAbbrgBX3zxReSDIzobBXrnXa1eSs1k1i4IFdPpudT+EkrELh6EUCBjE7V5wU2JSYBo212bd+12QaS30R73Vn9BCG2IuQ6Ujl19rylQXgbX6m9hGZwF652ToRYegtKmA9RjhVDzvIxqcLthOq9r09uEgRACSEj1bS67yQylzzUQ8cmQxwqAU6UQGe0gnZXAiSaeLwREog5JGwBt+1zoc1HPTlcOQGaXTkhI16Yx9BxxLdI7dcTP8z/0+tykFs0RnxahYwz0/GK2aR2vmikd9uo5/v5OE9KpEykS0yCbqGEgWpynFV0UAiKtNYQQUA/va2xrrZBjNBJCO/+r7rrncVN1Atnl0H5vtp1+HDj9eDR1Gv0tTFuzQpavtTUA7f/E3wRKmIjUlpAeYpfHD9VZHUa06wFhsUHdv73h96bZCiR4qVukB6E0fgNDVbUbMDXXLvWnS9UXxSMbxHkXQK7+AkhrCZGcBsRoSXnRrhuQlAq5cz1Ep151braI8/tClp+EOL+vTlFTNAkqsXHttdciMTERzz//PAYPHgyLpe6HpbCwEOnpnr+8srKy8OSTT+L111+vLR4KoMEqJyaTCTfffDOWLFnisfhnU/uIBhkZGfj8888bPP76669jzZo1+Oc//4kWLSJ0p4noXBDMlIKqcu0Oas2wTmdVAIVDEVhRwGAkplWvbtLEyBKXQ7uT2uI8rXPkrNIq4Od5qSQe3wxCp7vESqdufm3vmPcqAMA8+DoAAuq2Taha8KZWMNXrvs4PJMSgieR0LdnkbVSQxQYRn6w9J7UlRKpW4E+eOAK1qcSGlBBJkS/8CgDtLunj83zpy+++A5eNP7162TV/fBAAvCY2FJMJHQf0Cy5QfwihdQz8TUhIVXue1Q5AaB3nijKg0s/aIHp1SlJbAIf2NP5aWu1aslQoWqHb/duB44caaUxCpLcOW6hBq0lsnNlhr7mLX16iDe+32LUfKbX6BqoLsCboE29jLDbt+9CXWhtmCxCfAuly+reKkj0+ekbeJGdqr1n9WhuV9T5nbaq/V0qLGny/i8x2un3fNakm4ebpRktNjQ2L7fS1i9vpuai4UPSZdukjYbZAdL8USG0BpdvFtY8rva8CALh3rofonwVxRkFRZfAtkEWHIJL0SeBTdAnq6jsxMRHvvPMO7rjjDvTp0we333470tPTceDAASxfvhyXX3453nzzTY/PveiiizB69Gi8/fbbKCkpwYABA/Ddd99hz549DbadPXs2Vq1ahX79+uHee+9F9+7dcfz4cWzatAkrV67E8ePhqfi+cOFC7N+/H+Xl2hy11atXY9asWQCAO+64A+3aea/cHhsbixtvvLHB41988QV++eUXj78joiAEc1EiVaAqBAWoInzhINLbQB5qeO6sw1kFmb2h6W08tZ3p3woVoaS0aA3lvK5Q9/7mWzGx8lNwvD4Lfi1OKwSUDl2gtNCnoyWad4TM3eZ9w8pTcP/fYv93YLEC1UmQSEtIT0P3a4di14pVXkdufDDhD/hgwh/83ofqduOyu8YEGmJgLFb/ExtuJ3CyyPt2TRFCt06JMFshk5tX115o+FmU+7f73pg9DohNCl1woVazOpaHaQ0AtKlj7noJKYvNv5pAESCEgExM820EhssJ5Gzyfyc6JU09EYoCZLaDzM9ucju55XvPaWQhgPS2nn4THRpLbADVU1B8OCdZbNE1qsgDcfEQqJ++CfeqTz2OOlEXzTljYwFYbFBunhrBCCmaBX1bccyYMWjZsiVmz56Nl156CVVVVWjVqhWuvPJKTJgwocnn/uMf/0B6ejoWL16ML774AkOGDMHy5cvRpk2bOttlZmbil19+wTPPPIPPPvsMb7/9NlJTU9GjRw/MmTOnkdaDN3/+fPzww+lq+qtWrapd6eWKK67wKbFBRBEW6B3VUIrwXVVhj4NMzgR8ufPvD6sdSNZ32TvziFvheH1W+HYgJcwjbglf+16I2AQgpUWjHcYgW4do1QVCxzt0g6dOwo5vVoancSGQ1CITPYdfE572G2ONrV7+NMJscbp2SkRGW8gTjY3C8KOdzPbRc5e/MRYbAOl9xShAm5ZijsK6DIA25cefqSX+MJmBuOTwtB2o5h2BkiKgrBj+nk9F+14Q0Vhfo4YQ1QVBA1zBSzFF9TSUGsIeC+WGe6F+OQ8oPoZGX8fq/w9l5D0QKdE7cp8iS8h6FTXvvPNO5ObmYvXq1XrFRNCKpppMJsyfPx9333233uEQGYvq9n+Id6iYLP7PbQ4B6aiA3PJ9SNeoF936QyTqe0dOOqpQ8cA4yMLDoV9WUFEg0jIR88ZiCKt+F7SyrBjq+q9Cvwyf1Q6l/0gIHefAq6qKFwdcjQMb/wvVFbr3Zo07338HA86YwhIxJ4/51ukNpaQM3YeRy2MFkAd2BN5AehsorSNfzyZgbqc2lU31UOBXMWujd6K8syiL8sKT3GjeESI++upRSJcTMnt9dXLDN6JdD4gMg9ysdFb6P0VWKIA9PupHa5xJOioht6+F3PofoKze6CmrHaJHf4gLBkDER/HoL4o4g6yPRkTkB8Xk+9ziUNPpjo+wxgDte0Hu/W9oGszsoHtSAwCE1QbbQ39B5RP3h75xVYXtob/omtQAABGfDNGhF+TezSFtVzn/Ml2TGgCgKAomfPgunrngMmjl+kPUrtmE84cNifw0lBr2eKAsPNNgPbLYdU9qAFp9F6huyLzd3jeuL7UVRKsuoQ8qnEwW7UdV6yY3FHPUTT1pVLOWQNmJ0Cbi4pKjMqkBaHUa0LUfZMEe4Oj+RladEgAkEJekjWqL1mK2nljsWqLC15EbJrM2ysxASQ0AEFY7RO9BkBcOBA7tgzx5AlBVbZRjm84Qka5lRobg8V2hx7KokVJRUYGSkkbmTVZr1qwZrFbvF4OhbKu+s/k1IIoIa0zkR22YLLp2PkRaK8DlgDzgx3x3T1JbQbTtHpqgQsDU7QJYbh0P5ycLQtqu5da7YDq/l/cNI0C0665duBUeCE17HS+sLTCqt8wunTH23b/hwwBqaHiimExIbJ6JO+e/pd+UBotN6yw4ysO/LyGiqiaFSG8DWGMg83cDVRWo7SQ2xmyBaN4RqF4txZAUBVCiY/UPfwlFgWzZGcjbFZpkvy0WyGwffDthJBQTROuukC07AccPa6NWHBVagspsAeKTITLaQfiy3Hk0MlePFHI5tB9PK6CYradXeDMwoShAq/OiaSFlimINEhsxMTG1xTLPRv/617+81v5YtWoVBg0aFNG26qt5DWJjIz+kneisoJi0ec+uAFY1CUTN/FedieYdAKsNct+W6qVSfU2SapcNonUXoEWnqOuAWEZPhCw7CdfXS0PSnjnrJlhG3xuStkJBCAVKj8uh7hTAES/L03pr67yLoLTrEaLIQmPA+LFwnDqFj6Y+pnW0ApxWpJhNSGzeHI9+vxxJLfSt/4LYBG1YeGPLKoZsP8lRNzpAJKUBialA2YnqqQ5HG24Ul6wlQZLTo3OliXOIsNohW3cD8n8Lrv6UPQ5o0VnXuj3+EIoJSGulJf3PNtWFM2G2auegmhuiQkR0yXmiaNKgxsYrr7yCadOmobCwEPHx8XrFFTaHDh3C9u1N3828+OKLkZLifYhdKNuqb+XKlRg2bBg2btyIPn36+P18IoL2RV91KjJTUmxxkV/mtQnSWQV5cCdwLN9L7Ybqu62JaRBtu0f1HSwpJZxfLIFz8btavsbf17X6Ytwy7j5YbhwTdckbQDtGeXgf5G/r/UxMAbDFQuk+ACIlM2zxBWvLsq/x4YTJKD9R7HWlFE96Dr8Gd8x/C0nNo+QY3U6t3ka4RlnGJGjTXqKcdLu0ef9ul3YeNFt0nwZFDUnVDRQe1N6zfhHa6krJmVF53iQiAjwkNnJzc9GhQwe88847uP/+MMxpJq+klBg9ejR++eUX5OTk8EuEKBhSalNSwnlX1RqrDW+NQtLpAI7lQZ48rhVTc1VpfWWzWbsTHJ8MkdYawh6nc6S+U/fvRdUbs6Dm7Patlkr1NkrHrrA98BSUdh0jE2gQZFUFZN5ubelClwMNhvsLcbozbY+HaNMVomUnQ8w7PnX8OD7/8wysWbAYqtsFqTaeFFBMJqhuN1LatMINz/0F/cbdHn3fieFKbtgTgJjoT2qQ8cjKU9ooG291YhQFSEwHktKje8UQIiJ4SGwA2soo//znP/Hqq69i3LhxSE5O1iG0c1Nubi7mzJmDv//975g3bx7uuecevUMiMr5wjtywxUZ9VfyzkZQS6s4tcH61FO71PwKO6sJ4NZ3emq82qxWmvlfCMvxmKOf3ir5OsRdSdQPFRyFLj2vD/p1VgBAQVjuQ0Ewr8JqYarjjAoCyomP4z/uLsHXZNziw6VdUldVdQrVZ29boOKAf+t1xO3pcezUUUxQPf1fdwKni0BRorKmpEQVT2+jsJt0ubeniqvLqlTakNo3BatdGIdpitRoHREQG4DGx4XK5MHHiRHz44Ycwm83o3LkzYmNjDXnhZBSqqqKkpAR79uyB3W7HX//6V0yZMkXvsIjOHlJqoxX8XSatMYpJ63gYZK7x2Uy63ZAFB6Hu+w3yVBkgJUR8ApQOnSFatoWI5g4xAdC+A4vz8lFZdkorDpqZjlij3VSRUitQWF4Kv6YQncliB2ITeV4hIiLyk8fERo38/Hx8/vnnyM7ORkWFj8sKUcASEhLQt29fjBgxAgkJCXqHQ3R2Ut3V1dEDHb1xRsEuJnuJqD6paueYyvK6S4Q2SgC2mKir00NERGQkTSY2iIjOWqr79FJpvlBMp5dYY0KDiLyRUjvPuJ2Ay6n9XUqtXIpQtHOJ2cJzChERUQgwsUFE5zYptTusqvt0xwM4vWSaYtJ+2PEgIiIiIopKTGwQERERERERkWGx1DERERERERERGRYTG0RERERERERkWExsEBEREREREZFhMbFBRERERERERIbFxAYRERERERERGRYTG0RERERERERkWExsEBEREREREZFhMbFBRERERERERIbFxAYRERERERERGRYTG0RERERERERkWExsEBEREREREZFhMbFBRERERERERIbFxAYRERERERERGRYTG0RERERERERkWExsEBEREREREZFhMbFBRERERERERIbFxAYRERERERERGRYTG0RERERERERkWExsEBEREREREZFhMbFBRERERERERIbFxAYRERERERERGRYTG0RERERERERkWExsEBEREREREZFhMbFBRERERERERIbFxAYRERERERERGRYTG0RERERERERkWExsEBEREREREZFhMbFBRERERERERIbFxAYRERERERERGRYTG0RERERERERkWExsEBEREREREZFhMbFBRERERERERIbFxAYRERERERERGRYTG0RERERERERkWExsEBEREREREZFhMbFBRERERERERIbFxAYRERERERERGRYTG0RERERERERkWExsEBEREREREZFhMbFBRERERERERIbFxAYRERERERERGRYTG0RERERERERkWExsEBEREREREZFhMbFBRERERERERIbFxAYRERERERERGRYTG0RERERERERkWExsEBEREREREZFhMbFBRERERERERIbFxAYRERERERERGRYTG0RERERERERkWExsEBEREREREZFhMbFBRERERERERIbFxAYRERERERERGRYTG0RERERERERkWExsEBEREREREZFhMbFBRERERERERIbFxAYRERERERERGRYTG0RERERERERkWExsEBEREREREZFhMbFBRERERERERIbFxAYRERERERERGRYTG0RERERERERkWExsEBEREREREZFhMbFBRERERERERIbFxAYRERERERERGRYTG0RERERERERkWExsEBEREREREZFhMbFBRERERERERIbFxAYRERERERERGRYTG0RERERERERkWExsEBEREREREZFhMbFBRERERERERIbFxAYRERERERERGRYTG0RERERERERkWExsEBEREREREZFhMbFBRERERERERIbFxAYRERERERERGRYTG0RERERERERkWExsEBEREREREZFhMbFBRERERERERIbFxAYRERERERERGRYTG0RERERERERkWExsEBEREREREZFhMbFBRERERERERIbFxAYRERERERERGRYTG0RERERERERkWExsEBEREREREZFhMbFBRERERERERIbFxAYRERERERERGRYTG0RERERERERkWExsEBEREREREZFhMbFBRERERERERIb1/wGFdxMczUh16AAAAABJRU5ErkJggg==", + "image/png": "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", "text/plain": [ "
" ] @@ -161,7 +161,7 @@ "outputs": [ { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -205,7 +205,7 @@ "outputs": [ { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -232,12 +232,67 @@ "fig.set_dpi(100)" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Plotting with `matplotlib-sankey`" + ] + }, { "cell_type": "code", - "execution_count": null, + "execution_count": 9, "metadata": {}, - "outputs": [], - "source": [] + "outputs": [ + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "clustree(\n", + " adata,\n", + " cluster_keys=[f\"leiden_{str(resolution).replace('.', '_')}\" for resolution in [0.1, 0.4, 0.7, 1.0]],\n", + " title=\"Clustree of PBMC68k\",\n", + " transition_plot=\"sankey\",\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "clustree(\n", + " adata,\n", + " [f\"leiden_{str(resolution).replace('.', '_')}\" for resolution in [0.1, 0.4, 0.7, 1.0]],\n", + " title=\"Clustree of PBMC68k colored by CD8A\",\n", + " transition_plot=\"sankey\",\n", + " node_color_gene=\"CD8A\",\n", + " node_colormap=\"Reds\",\n", + " show_colorbar=True,\n", + ")" + ] } ], "metadata": { diff --git a/pyclustree/_clustree.py b/pyclustree/_clustree.py index ff24a5f..86f9e98 100644 --- a/pyclustree/_clustree.py +++ b/pyclustree/_clustree.py @@ -1,11 +1,17 @@ from collections.abc import Callable from logging import warning +from typing import Literal +from warnings import warn import networkx as nx import numpy as np +import pandas as pd from anndata import AnnData from matplotlib import pyplot as plt from matplotlib.colors import Colormap +from matplotlib_sankey import from_matrix, sankey + +# from matplotlib_sankey._colors import colormap_to_list from numpy.typing import NDArray from ._utils import order_unique_clusters, transition_matrix @@ -30,6 +36,15 @@ def clustree( show_fraction: bool = False, show_cluster_keys: bool = True, graph_plot_kwargs: dict | None = None, + transition_plot: Literal["network", "sankey"] = "network", + sankey_spacing: float = 0.01, + sankey_curve_type: Literal["curve3", "curve4", "line"] = "curve4", + sankey_ribbon_alpha: float = 0.2, + sankey_ribbon_color: str = "black", + sankey_show_legend: bool = False, + sankey_rel_column_width: float = 0.15, + sankey_annotate_columns: Literal["index", "weight", "weight_percent"] | None = "index", + sankey_annotate_columns_font_kwargs: dict | None = None, ) -> plt.Figure: """Create a hierarchical clustering tree visualization to compare different clustering resolutions. @@ -89,32 +104,56 @@ def clustree( Defaults to True. graph_plot_kwargs (Optional[dict], optional): Additional keyword arguments to pass to `nx.draw`. Will override the default arguments. Defaults to None. + transition_plot (Literal["network", "sankey"], optional): Type of plot. Defaults to `"network"`. + sankey_spacing (float, optional): Spacing between column items in sankey plot. Range: 0.0 to 1.0. + Defaults to 0.01. + sankey_curve_type (Literal["curve3", "curve4", "line"], optional): Shape of flow ribbons in sankey plot. + Defaults to "curve4". + sankey_ribbon_alpha (float, optional): Transparency of flow ribbons in sankey plot. Range: 0.0 to 1.0. + Defaults to 0.2. + sankey_ribbon_color (str, optional): Color of flow ribbons in sankey plot. Defaults to "black". + sankey_show_legend (bool, optional): Whether to display legend in sankey plot. Defaults to False. + sankey_rel_column_width (float, optional): Relative width of column rectangles in sankey plot. + Range: 0 < value < 1. Defaults to 0.15. + sankey_annotate_columns (Literal["index", "weight", "weight_percent"] | None, optional): + Annotation type for sankey column rectangles. Defaults to "index". + sankey_annotate_columns_font_kwargs (Optional[dict], optional): Font customization for sankey annotations. + Defaults to None. Returns: plt.Figure: The matplotlib figure object of the clustree visualization. """ + if transition_plot == "sankey": + if scatter_reference is not None: + warn( + message="'scatter_reference' not supported when using sankey plot. Argument is ignored.", + category=UserWarning, + stacklevel=1, + ) + # Ensure all cluster keys are present in adata.obs assert all(key in adata.obs for key in cluster_keys), "All cluster keys should be present in adata.obs." - assert ( - scatter_reference is None or scatter_reference in adata.obsm - ), "The provided scatter reference is not valid. It should be present in adata.obsm." + assert scatter_reference is None or scatter_reference in adata.obsm, ( + "The provided scatter reference is not valid. It should be present in adata.obsm." + ) if node_color_gene is not None: if scatter_reference is not None: raise ValueError("Currently, you cannot provide both a scatter reference and a node color gene.") if node_color_gene_use_raw and node_color_gene not in adata.obs.columns: - assert ( - node_color_gene in adata.raw.var_names - ), "The provided gene should be present in the adata.raw.var_names." + assert node_color_gene in adata.raw.var_names, ( + "The provided gene should be present in the adata.raw.var_names." + ) else: - assert ( - node_color_gene in adata.obs.columns or node_color_gene in adata.var_names - ), "The provided gene should be present in the adata.var_names/adata.raw.var_names or adata.obs." + assert node_color_gene in adata.obs.columns or node_color_gene in adata.var_names, ( + "The provided gene should be present in the adata.var_names/adata.raw.var_names or adata.obs." + ) - if isinstance(node_colormap, str): - node_colormap = plt.get_cmap(node_colormap) + # TODO: fix in matplotlib sankey + # if isinstance(node_colormap, str): + # node_colormap = plt.get_cmap(node_colormap) df_cluster_assignments = adata.obs[cluster_keys] @@ -138,199 +177,346 @@ def cluster_sort_key(cluster): if order_clusters: unique_clusters = order_unique_clusters(unique_clusters, transition_matrices) - # Create the Graph - G: nx.Graph = nx.DiGraph() - - layers: dict[int, list[str]] = {} - - # Add the nodes and store cluster info directly in the graph - for i, key in enumerate(cluster_keys): - for cluster in unique_clusters[i]: - node_name = f"{key}_{cluster}" - cluster_cells = df_cluster_assignments[key] == cluster - node_size = np.sum(cluster_cells) - - # Store info directly in the node - G.add_node( - node_name, - level=i, - key=key, - cluster=cluster, - size=node_size, - cells=cluster_cells, - ) + # Create the plot + figsize = (x_spacing * len(cluster_keys), y_spacing * len(unique_clusters[0])) + fig, ax = plt.subplots(figsize=figsize, dpi=300) - layer_key = int(len(cluster_keys) - i) - if layer_key not in layers: - layers[layer_key] = [] - layers[layer_key].append(node_name) - - # Compute node sizes scaled to the desired range - max_size = max(G.nodes[node]["size"] for node in G.nodes) - for node in G.nodes: - G.nodes[node]["display_size"] = np.clip( - (G.nodes[node]["size"] * node_size_range[1]) / max_size, - *node_size_range, - ) + if transition_plot == "network": + if isinstance(node_colormap, str): + node_colormap = plt.get_cmap(node_colormap) - # Add edges between each level and the next level - for i, transition in enumerate(transition_matrices): - for parent_cluster in transition.index: - parent_node = f"{cluster_keys[i]}_{parent_cluster}" - - for child_cluster in transition.columns: - child_node = f"{cluster_keys[i + 1]}_{child_cluster}" - weight = transition.loc[parent_cluster, child_cluster] - - if weight > edge_weight_threshold: - G.add_edge(parent_node, child_node, weight=weight) - - # Prepare node colors - if isinstance(node_colormap, list): - # Multiple colormaps for different levels - assert len(node_colormap) == len( - cluster_keys - ), "The length of the colormap list should match the number of cluster keys." - assert ( - node_color_gene is None - ), "The node_color_gene argument is not supported when providing a list of colormaps." - - # Apply appropriate colormap to each node based on its level + # Create the Graph + G: nx.Graph = nx.DiGraph() + + layers: dict[str, list[str]] = {} + + # Add the nodes and store cluster info directly in the graph + for i, key in enumerate(cluster_keys): + for cluster in unique_clusters[i]: + node_name = f"{key}_{cluster}" + cluster_cells = df_cluster_assignments[key] == cluster + node_size = np.sum(cluster_cells) + + # Store info directly in the node + G.add_node( + node_name, + level=i, + key=key, + cluster=cluster, + size=node_size, + cells=cluster_cells, + ) + + layer_key = str(len(cluster_keys) - i) + if layer_key not in layers: + layers[layer_key] = [] + layers[layer_key].append(node_name) + + # Compute node sizes scaled to the desired range + max_size = max(G.nodes[node]["size"] for node in G.nodes) for node in G.nodes: - level = G.nodes[node]["level"] - cluster = G.nodes[node]["cluster"] - cmap_level = ( - plt.cm.get_cmap(node_colormap[level]) if isinstance(node_colormap[level], str) else node_colormap[level] + G.nodes[node]["display_size"] = np.clip( + (G.nodes[node]["size"] * node_size_range[1]) / max_size, + *node_size_range, + ) + + # Add edges between each level and the next level + for i, transition in enumerate(transition_matrices): + for parent_cluster in transition.index: + parent_node = f"{cluster_keys[i]}_{parent_cluster}" + + for child_cluster in transition.columns: + child_node = f"{cluster_keys[i + 1]}_{child_cluster}" + weight = transition.loc[parent_cluster, child_cluster] + + if weight > edge_weight_threshold: + G.add_edge(parent_node, child_node, weight=weight) + + # Prepare node colors + if isinstance(node_colormap, list): + # Multiple colormaps for different levels + assert len(node_colormap) == len(cluster_keys), ( + "The length of the colormap list should match the number of cluster keys." ) - norm_level = plt.Normalize(vmin=0, vmax=len(unique_clusters[level]) - 1) - color_idx = unique_clusters[level].index(cluster) - G.nodes[node]["color"] = cmap_level(norm_level(color_idx)) - - elif node_color_gene is not None: - # Color nodes by gene expression - # Get the expression values for the specified gene - if node_color_gene in adata.obs.columns: - gene_counts = adata.obs[node_color_gene].values - elif node_color_gene_use_raw: - if adata.raw is None: - raise ValueError( - "The raw data is not available. Please set `node_color_gene_use_raw` to False or provide raw data." + assert node_color_gene is None, ( + "The node_color_gene argument is not supported when providing a list of colormaps." + ) + + # Apply appropriate colormap to each node based on its level + for node in G.nodes: + level = G.nodes[node]["level"] + cluster = G.nodes[node]["cluster"] + cmap_level = ( + plt.cm.get_cmap(node_colormap[level]) + if isinstance(node_colormap[level], str) + else node_colormap[level] ) - gene_counts = adata.raw.X[:, adata.raw.var_names == node_color_gene] + norm_level = plt.Normalize(vmin=0, vmax=len(unique_clusters[level]) - 1) + color_idx = unique_clusters[level].index(cluster) + G.nodes[node]["color"] = cmap_level(norm_level(color_idx)) + + elif node_color_gene is not None: + # Color nodes by gene expression + # Get the expression values for the specified gene + if node_color_gene in adata.obs.columns: + gene_counts = adata.obs[node_color_gene].values + elif node_color_gene_use_raw: + if adata.raw is None: + raise ValueError( + "The raw data is not available. Please set `node_color_gene_use_raw` to False or provide raw data." + ) + gene_counts = adata.raw.X[:, adata.raw.var_names == node_color_gene] + else: + gene_counts = adata.X[:, adata.var_names == node_color_gene] + + # Flatten gene_counts if it's 2D + gene_counts = gene_counts.toarray().flatten() if hasattr(gene_counts, "toarray") else gene_counts.flatten() + + # Apply transformer to get expression value per cluster + transformer = np.mean if node_color_gene_transformer is None else node_color_gene_transformer + + # Calculate expression for each node + gene_values = {} + for node in G.nodes: + cells = G.nodes[node]["cells"] + gene_values[node] = np.nan_to_num(transformer(gene_counts[cells]), nan=0) + + # Create color normalization + gene_min, gene_max = min(gene_values.values()), max(gene_values.values()) + norm_gene = plt.Normalize(vmin=gene_min, vmax=gene_max) + + # Assign colors + for node in G.nodes: + G.nodes[node]["color"] = node_colormap(norm_gene(gene_values[node])) + else: - gene_counts = adata.X[:, adata.var_names == node_color_gene] + # Single colormap for all nodes based on level + norm = plt.Normalize(vmin=0, vmax=len(cluster_keys) - 1) + for node in G.nodes: + G.nodes[node]["color"] = node_colormap(norm(G.nodes[node]["level"])) - # Flatten gene_counts if it's 2D - gene_counts = gene_counts.toarray().flatten() if hasattr(gene_counts, "toarray") else gene_counts.flatten() + # Calculate the positions of the nodes + if scatter_reference is not None: + # Get the median x and y positions of the scatter reference for each cluster + x_positions = adata.obsm[scatter_reference][:, 0] + y_positions = adata.obsm[scatter_reference][:, 1] - # Apply transformer to get expression value per cluster - transformer = np.mean if node_color_gene_transformer is None else node_color_gene_transformer + node_positions = {} + for node in G.nodes: + cells = G.nodes[node]["cells"] + node_positions[node] = (np.median(x_positions[cells]), np.median(y_positions[cells])) + else: + node_positions = nx.multipartite_layout( + G, + align="horizontal", + subset_key=layers, # type: ignore + scale=1.0, + ) - # Calculate expression for each node - gene_values = {} - for node in G.nodes: - cells = G.nodes[node]["cells"] - gene_values[node] = np.nan_to_num(transformer(gene_counts[cells]), nan=0) + # Prepare edge widths scaled to desired range + edge_weights = [G.edges[edge]["weight"] for edge in G.edges] + if edge_weights: # Only scale if there are edges + max_weight = max(edge_weights) + edge_widths = np.clip( + (np.array(edge_weights) * edge_width_range[1]) / max_weight, + *edge_width_range, + ) + else: + edge_widths = [] - # Create color normalization - gene_min, gene_max = min(gene_values.values()), max(gene_values.values()) - norm_gene = plt.Normalize(vmin=gene_min, vmax=gene_max) + # Plot the scatter reference if provided + if scatter_reference is not None: + ax.scatter( + adata.obsm[scatter_reference][:, 0], + adata.obsm[scatter_reference][:, 1], + c="lightgrey", + alpha=0.5, + s=10, + ) - # Assign colors - for node in G.nodes: - G.nodes[node]["color"] = node_colormap(norm_gene(gene_values[node])) + # Prepare graph drawing parameters + graph_plot_kwargs_base = { + "G": G, + "with_labels": True, + "labels": {node: G.nodes[node]["cluster"] for node in G.nodes}, + "pos": node_positions, + "node_size": [G.nodes[node]["display_size"] for node in G.nodes], + "node_color": [G.nodes[node]["color"] for node in G.nodes], + "edge_color": "black", + "width": edge_widths, + "font_size": 8, + "font_color": "white", + "font_weight": "bold", + "edge_vmin": 0, + "edge_vmax": 1, + "arrowsize": 10, + "ax": ax, + } + + if graph_plot_kwargs is not None: + graph_plot_kwargs_base.update(graph_plot_kwargs) + + # Draw the graph + nx.draw(**graph_plot_kwargs_base) + + # Add edge labels if requested + if show_fraction: + edge_labels = {edge: f"{weight:.2f}" for edge, weight in nx.get_edge_attributes(G, "weight").items()} + nx.draw_networkx_edge_labels( + G, + node_positions, + label_pos=0.4, + edge_labels=edge_labels, + font_size=6, + rotate=False, + alpha=0.8, + bbox={ + "alpha": 0.8, + "ec": [1.0, 1.0, 1.0], + "fc": [1.0, 1.0, 1.0], + "boxstyle": "round,pad=0.3", + }, + ) - else: - # Single colormap for all nodes based on level - norm = plt.Normalize(vmin=0, vmax=len(cluster_keys) - 1) - for node in G.nodes: - G.nodes[node]["color"] = node_colormap(norm(G.nodes[node]["level"])) + # Calculate positions for cluster keys and scores + need_level_positions = show_cluster_keys and scatter_reference is not None + y_positions_levels: NDArray[np.float64] | list[float] + if need_level_positions: + y_positions_levels = np.linspace( + ax.get_ylim()[1], + ax.get_ylim()[1] - len(cluster_keys) * 1.0, + len(cluster_keys), + ) - # Calculate the positions of the nodes - if scatter_reference is not None: - # Get the median x and y positions of the scatter reference for each cluster - x_positions = adata.obsm[scatter_reference][:, 0] - y_positions = adata.obsm[scatter_reference][:, 1] + # Show the name of the cluster key and scores + if show_cluster_keys: + x_min = ax.get_xlim()[0] if scatter_reference is None else ax.get_xlim()[1] + 2 + + # Determine y positions and colors + facecolor: list[str] | list[tuple[float, float, float, float]] + if scatter_reference is None: + # Use node positions for y-coordinates in hierarchical layout + level_nodes: dict[int, list[str]] = {} + for node in G.nodes: + level = G.nodes[node]["level"] + if level not in level_nodes: + level_nodes[level] = [] + level_nodes[level].append(node) + + y_positions_levels = [ + max(node_positions[node][1] for node in level_nodes.get(i, [])) for i in range(len(cluster_keys)) + ] + facecolor = ["white"] * len(cluster_keys) + else: + # Use previously calculated y positions for scatter layout + if isinstance(node_colormap, list): + warning("Cannot show colored cluster keys when providing a list of colormaps. Showing white keys.") + facecolor = ["white"] * len(cluster_keys) + else: + norm = plt.Normalize(vmin=0, vmax=len(cluster_keys) - 1) + facecolor = [node_colormap(norm(i)) for i in range(len(cluster_keys))] + + # Add text labels for cluster keys + for i, key in enumerate(cluster_keys): + ax.text( + x_min - 0.5, + y_positions_levels[i], + key, + fontsize=12, + color="black", + ha="center", + va="center", + bbox={ + "boxstyle": "round", + "facecolor": facecolor[i], + "edgecolor": "black", + }, + ) - node_positions = {} - for node in G.nodes: - cells = G.nodes[node]["cells"] - node_positions[node] = (np.median(x_positions[cells]), np.median(y_positions[cells])) - else: - node_positions = nx.multipartite_layout( - G, - align="horizontal", - subset_key=layers, # type: ignore - scale=1.0, - ) + elif transition_plot == "sankey": + # Add sankey plot - # Prepare edge widths scaled to desired range - edge_weights = [G.edges[edge]["weight"] for edge in G.edges] - if edge_weights: # Only scale if there are edges - max_weight = max(edge_weights) - edge_widths = np.clip( - (np.array(edge_weights) * edge_width_range[1]) / max_weight, - *edge_width_range, - ) - else: - edge_widths = [] + df_cluster_assignments = adata.obs[cluster_keys] - # Create the plot - figsize = (x_spacing * len(cluster_keys), y_spacing * len(unique_clusters[0])) - fig, ax = plt.subplots(figsize=figsize, dpi=300) + transition_matrices = [ + pd.crosstab( + df_cluster_assignments[cluster_keys[i]], + df_cluster_assignments[cluster_keys[i + 1]], + ) + for i in range(len(cluster_keys) - 1) + ] + all_matrices = [] + for i in range(len(cluster_keys) - 1): + all_matrices.append( + from_matrix( + transition_matrices[i].to_numpy(), + source_indicies=transition_matrices[i].index.tolist(), + target_indicies=transition_matrices[i].columns.tolist(), + ) + ) - # Plot the scatter reference if provided - if scatter_reference is not None: - ax.scatter( - adata.obsm[scatter_reference][:, 0], - adata.obsm[scatter_reference][:, 1], - c="lightgrey", - alpha=0.5, - s=10, - ) + sankey_color = node_colormap + gene_values = {} + + # Calculate cluster sizes for column heights + column_item_totals = [] + for key in cluster_keys: + cluster_sizes = {} + for cluster_name in unique_clusters[cluster_keys.index(key)]: + cluster_sizes[cluster_name] = int((df_cluster_assignments[key] == cluster_name).sum()) + column_item_totals.append(cluster_sizes) - # Prepare graph drawing parameters - graph_plot_kwargs_base = { - "G": G, - "with_labels": True, - "labels": {node: G.nodes[node]["cluster"] for node in G.nodes}, - "pos": node_positions, - "node_size": [G.nodes[node]["display_size"] for node in G.nodes], - "node_color": [G.nodes[node]["color"] for node in G.nodes], - "edge_color": "black", - "width": edge_widths, - "font_size": 8, - "font_color": "white", - "font_weight": "bold", - "edge_vmin": 0, - "edge_vmax": 1, - "arrowsize": 10, - "ax": ax, - } - - if graph_plot_kwargs is not None: - graph_plot_kwargs_base.update(graph_plot_kwargs) - - # Draw the graph - nx.draw(**graph_plot_kwargs_base) - - # Add edge labels if requested - if show_fraction: - edge_labels = {edge: f"{weight:.2f}" for edge, weight in nx.get_edge_attributes(G, "weight").items()} - nx.draw_networkx_edge_labels( - G, - node_positions, - label_pos=0.4, - edge_labels=edge_labels, - font_size=6, - rotate=False, - alpha=0.8, - bbox={ - "alpha": 0.8, - "ec": [1.0, 1.0, 1.0], - "fc": [1.0, 1.0, 1.0], - "boxstyle": "round,pad=0.3", - }, + if node_color_gene is not None: + node_expr: dict[str, dict[str, float]] = {} + + for key in cluster_keys: + node_expr[key] = {} + for cluster_key_name in adata.obs[key].unique(): + expr_mean = np.mean( + np.array( + adata[(adata.obs[key] == cluster_key_name), :].raw[:, [node_color_gene]].X.todense() + ).ravel(), + axis=0, + ) + + node_expr[key][cluster_key_name] = expr_mean + gene_values[key + cluster_key_name] = expr_mean + + norm = plt.Normalize( + np.hstack([list(v.values()) for v in node_expr.values()]).flatten().min(), + np.hstack([list(v.values()) for v in node_expr.values()]).flatten().max(), + ) + + if isinstance(node_colormap, str): + node_colormap = plt.colormaps.get(node_colormap) + + combined_cmap = [] + + for cluster_key in cluster_keys: + combined_cmap.append( + [ + tuple(float(r) for r in node_colormap(norm(node_expr[cluster_key][key]))[:3]) + for key in node_expr[cluster_key].keys() + ] + ) + + sankey_color = combined_cmap + + sankey( + all_matrices, + color=sankey_color, + ax=ax, + spacing=sankey_spacing, + column_labels=cluster_keys, + annotate_columns=sankey_annotate_columns, + rel_column_width=sankey_rel_column_width, + curve_type=sankey_curve_type, + ribbon_alpha=sankey_ribbon_alpha, + ribbon_color=sankey_ribbon_color, + show_legend=sankey_show_legend, + annotate_columns_font_kwargs=sankey_annotate_columns_font_kwargs, + column_item_totals=column_item_totals, + show=False, ) # Plot the colorbar @@ -359,60 +545,6 @@ def cluster_sort_key(cluster): elif show_colorbar and isinstance(node_colormap, list): warning("Colorbars are not supported when providing a list of colormaps. Ignoring the argument.") - # Calculate positions for cluster keys - need_level_positions = show_cluster_keys and scatter_reference is not None - y_positions_levels: NDArray[np.floating] | list[float] - if need_level_positions: - y_positions_levels = np.linspace( - ax.get_ylim()[1], - ax.get_ylim()[1] - len(cluster_keys) * 1.0, - len(cluster_keys), - ) - - if show_cluster_keys: - x_min = ax.get_xlim()[0] if scatter_reference is None else ax.get_xlim()[1] + 2 - - # Determine y positions and colors - facecolor: list[str] | list[tuple[float, float, float, float]] - if scatter_reference is None: - # Use node positions for y-coordinates in hierarchical layout - level_nodes: dict[int, list[str]] = {} - for node in G.nodes: - level = G.nodes[node]["level"] - if level not in level_nodes: - level_nodes[level] = [] - level_nodes[level].append(node) - - y_positions_levels = [ - max(node_positions[node][1] for node in level_nodes.get(i, [])) for i in range(len(cluster_keys)) - ] - facecolor = ["white"] * len(cluster_keys) - else: - # Use previously calculated y positions for scatter layout - if isinstance(node_colormap, list): - warning("Cannot show colored cluster keys when providing a list of colormaps. Showing white keys.") - facecolor = ["white"] * len(cluster_keys) - else: - norm = plt.Normalize(vmin=0, vmax=len(cluster_keys) - 1) - facecolor = [node_colormap(norm(i)) for i in range(len(cluster_keys))] - - # Add text labels for cluster keys - for i, key in enumerate(cluster_keys): - ax.text( - x_min - 0.5, - y_positions_levels[i], - key, - fontsize=12, - color="black", - ha="center", - va="center", - bbox={ - "boxstyle": "round", - "facecolor": facecolor[i], - "edgecolor": "black", - }, - ) - # Set the title of the plot if title is not None: ax.set_title(title, fontsize=16, fontweight="bold", pad=10) diff --git a/pyclustree/py.typed b/pyclustree/py.typed new file mode 100644 index 0000000..e69de29 diff --git a/pyproject.toml b/pyproject.toml index 9256e5d..956963d 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -1,11 +1,10 @@ [build-system] build-backend = "flit_core.buildapi" - requires = [ "flit-core>=3.4,<4" ] [project] name = "pyclustree" -version = "0.4.1" +version = "0.5.0" description = "Visualize cluster assignments at different resolutions" readme = "README.md" license = { file = "LICENSE" } @@ -14,23 +13,26 @@ maintainers = [ { name = "Malte Kuehl", email = "malte.kuehl@clin.au.dk" }, ] authors = [ { name = "Malte Hellmig" }, { name = "Malte Kuehl" } ] -requires-python = ">=3.10" +requires-python = ">=3.11" classifiers = [ "Development Status :: 3 - Alpha", + "Framework :: Matplotlib", "Intended Audience :: Healthcare Industry", "Intended Audience :: Science/Research", "License :: OSI Approved :: GNU General Public License v3 (GPLv3)", "Natural Language :: English", "Operating System :: OS Independent", "Programming Language :: Python :: 3 :: Only", - "Programming Language :: Python :: 3.10", "Programming Language :: Python :: 3.11", "Programming Language :: Python :: 3.12", + "Programming Language :: Python :: 3.13", + "Programming Language :: Python :: 3.14", "Typing :: Typed", ] dependencies = [ "anndata", "matplotlib", + "matplotlib-sankey>=0.3.2", "networkx", "numpy", "pandas", @@ -38,8 +40,8 @@ dependencies = [ # for debug logging (referenced from the issue template) "session-info", ] - optional-dependencies.dev = [ + "build>=1.4", "coverage", "docutils>=0.8,!=0.18.*,!=0.19.*", "flit", @@ -72,21 +74,18 @@ optional-dependencies.dev = [ "types-networkx", ] optional-dependencies.sklearn = [ "scikit-learn" ] - # https://docs.pypi.org/project_metadata/#project-urls urls.Documentation = "https://pyclustree.readthedocs.io/" urls.Homepage = "https://github.com/complextissue/pyclustree" urls.Source = "https://github.com/complextissue/pyclustree" -[tool.flit.sdist] -exclude = [ "docs/*", "test/*" ] +[tool.flit] +sdist.exclude = [ "docs/*", "test/*" ] [tool.ruff] line-length = 120 extend-include = [ "*.ipynb" ] - format.docstring-code-format = true - lint.select = [ "B", # flake8-bugbear "BLE", # flake8-blind-except @@ -120,33 +119,29 @@ lint.per-file-ignores."docs/*" = [ "I" ] lint.per-file-ignores."tests/*" = [ "D" ] lint.pydocstyle.convention = "google" -[tool.pytest.ini_options] -log_format = "%(asctime)s %(levelname)s %(message)s" -log_date_format = "%Y-%m-%d %H:%M:%S" -log_level = "WARN" -log_cli = true -testpaths = [ "tests" ] -xfail_strict = true -addopts = [ +[tool.pytest] +ini_options.log_format = "%(asctime)s %(levelname)s %(message)s" +ini_options.log_date_format = "%Y-%m-%d %H:%M:%S" +ini_options.log_level = "WARN" +ini_options.log_cli = true +ini_options.testpaths = [ "tests" ] +ini_options.xfail_strict = true +ini_options.addopts = [ "--import-mode=importlib", # allow using test files with same name ] -[tool.coverage.run] -source = [ "pyclustree" ] -omit = [ "*/test/*" ] - -[tool.coverage.report] -exclude_lines = [ - "if __name__ == __main__:", - "raise", - "except", - "warning", +[tool.coverage] +run.omit = [ "*/test/*" ] +run.source = [ "pyclustree" ] +report.exclude_lines = [ "def __repr__", "def __str__", + "except", "file_path = Path", + "if __name__ == __main__:", + "raise", "return None", -] # don't complain if non-runnable code isn't run: -ignore_errors = true - -[tool.coverage.html] -directory = "docs/coverage_report" + "warning", +] # don't complain if non-runnable code isn't run: +report.ignore_errors = true +html.directory = "docs/coverage_report" diff --git a/tests/test_pyclustree.py b/tests/test_pyclustree.py index eae6fec..6115e04 100644 --- a/tests/test_pyclustree.py +++ b/tests/test_pyclustree.py @@ -95,3 +95,184 @@ def test_scatter_reference(): node_colormap=["#FF0000"] * len(cluster_keys), node_color_gene="CD8A", ) + + +def test_sankey_basic(): + """Test basic sankey plot functionality.""" + adata = sc.datasets.pbmc3k_processed() + + # Run leiden clustering for different resolutions + for resolution in [0.2, 0.4, 0.6, 0.8, 1.0]: + sc.tl.leiden( + adata, + resolution=resolution, + flavor="igraph", + n_iterations=2, + key_added=f"leiden_{str(resolution).replace('.', '_')}", + ) + + # Create a sankey visualization + fig = clustree( + adata, + [f"leiden_{str(resolution).replace('.', '_')}" for resolution in [0.2, 0.4, 0.6, 0.8, 1.0]], + transition_plot="sankey", + ) + + assert isinstance(fig, plt.Figure), "clustree with sankey plot should return a matplotlib Figure object." + + +def test_sankey_with_gene_coloring(): + """Test sankey plot with gene expression coloring.""" + adata = sc.datasets.pbmc3k_processed() + + # Run leiden clustering for different resolutions + for resolution in [0.2, 0.4, 0.6]: + sc.tl.leiden( + adata, + resolution=resolution, + flavor="igraph", + n_iterations=2, + key_added=f"leiden_{str(resolution).replace('.', '_')}", + ) + + # Create a sankey visualization with gene coloring + fig = clustree( + adata, + [f"leiden_{str(resolution).replace('.', '_')}" for resolution in [0.2, 0.4, 0.6]], + transition_plot="sankey", + node_color_gene="CD8A", + ) + + assert isinstance(fig, plt.Figure), "clustree with sankey and gene coloring should return a matplotlib Figure." + + +def test_sankey_parameters(): + """Test sankey plot with various parameter combinations.""" + adata = sc.datasets.pbmc3k_processed() + + # Run leiden clustering for different resolutions + for resolution in [0.2, 0.4, 0.6]: + sc.tl.leiden( + adata, + resolution=resolution, + flavor="igraph", + n_iterations=2, + key_added=f"leiden_{str(resolution).replace('.', '_')}", + ) + + cluster_keys = [f"leiden_{str(resolution).replace('.', '_')}" for resolution in [0.2, 0.4, 0.6]] + + # Test different curve types + for curve_type in ["curve3", "curve4", "line"]: + fig = clustree( + adata, + cluster_keys, + transition_plot="sankey", + sankey_curve_type=curve_type, + ) + assert isinstance(fig, plt.Figure), f"Sankey plot with curve_type={curve_type} should work." + + # Test different spacing values + fig = clustree( + adata, + cluster_keys, + transition_plot="sankey", + sankey_spacing=0.05, + ) + assert isinstance(fig, plt.Figure), "Sankey plot with custom spacing should work." + + # Test different ribbon parameters + fig = clustree( + adata, + cluster_keys, + transition_plot="sankey", + sankey_ribbon_alpha=0.5, + sankey_ribbon_color="blue", + ) + assert isinstance(fig, plt.Figure), "Sankey plot with custom ribbon parameters should work." + + # Test different annotation types + for annotate_type in ["index", "weight", "weight_percent", None]: + fig = clustree( + adata, + cluster_keys, + transition_plot="sankey", + sankey_annotate_columns=annotate_type, + ) + assert isinstance(fig, plt.Figure), f"Sankey plot with annotate_columns={annotate_type} should work." + + # Test with column width parameter + fig = clustree( + adata, + cluster_keys, + transition_plot="sankey", + sankey_rel_column_width=0.25, + ) + assert isinstance(fig, plt.Figure), "Sankey plot with custom column width should work." + + # Test with legend + fig = clustree( + adata, + cluster_keys, + transition_plot="sankey", + sankey_show_legend=True, + ) + assert isinstance(fig, plt.Figure), "Sankey plot with legend should work." + + # Test with colorbar + fig = clustree( + adata, + cluster_keys, + transition_plot="sankey", + show_colorbar=True, + ) + assert isinstance(fig, plt.Figure), "Sankey plot with colorbar should work." + + +def test_sankey_with_scatter_reference_warning(): + """Test that sankey plot ignores scatter_reference with a warning.""" + adata = sc.datasets.pbmc3k_processed() + + # Run leiden clustering for different resolutions + for resolution in [0.2, 0.4]: + sc.tl.leiden( + adata, + resolution=resolution, + flavor="igraph", + n_iterations=2, + key_added=f"leiden_{str(resolution).replace('.', '_')}", + ) + + # This should produce a warning but still work + with pytest.warns(UserWarning, match="scatter_reference.*not supported.*sankey"): + fig = clustree( + adata, + [f"leiden_{str(resolution).replace('.', '_')}" for resolution in [0.2, 0.4]], + transition_plot="sankey", + scatter_reference="X_umap", + ) + assert isinstance(fig, plt.Figure), "Sankey plot should work despite scatter_reference warning." + + +def test_sankey_with_title(): + """Test sankey plot with title.""" + adata = sc.datasets.pbmc3k_processed() + + # Run leiden clustering for different resolutions + for resolution in [0.2, 0.4]: + sc.tl.leiden( + adata, + resolution=resolution, + flavor="igraph", + n_iterations=2, + key_added=f"leiden_{str(resolution).replace('.', '_')}", + ) + + fig = clustree( + adata, + [f"leiden_{str(resolution).replace('.', '_')}" for resolution in [0.2, 0.4]], + transition_plot="sankey", + title="Sankey Clustree Visualization", + ) + + assert isinstance(fig, plt.Figure), "Sankey plot with title should work." diff --git a/uv.lock b/uv.lock new file mode 100644 index 0000000..a56ee7a --- /dev/null +++ b/uv.lock @@ -0,0 +1,3610 @@ +version = 1 +revision = 3 +requires-python = ">=3.11" +resolution-markers = [ + "python_full_version >= '3.12'", + "python_full_version < '3.12'", +] + +[[package]] +name = "accessible-pygments" +version = "0.0.5" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "pygments" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/bc/c1/bbac6a50d02774f91572938964c582fff4270eee73ab822a4aeea4d8b11b/accessible_pygments-0.0.5.tar.gz", hash = "sha256:40918d3e6a2b619ad424cb91e556bd3bd8865443d9f22f1dcdf79e33c8046872", size = 1377899, upload-time = "2024-05-10T11:23:10.216Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/8d/3f/95338030883d8c8b91223b4e21744b04d11b161a3ef117295d8241f50ab4/accessible_pygments-0.0.5-py3-none-any.whl", hash = "sha256:88ae3211e68a1d0b011504b2ffc1691feafce124b845bd072ab6f9f66f34d4b7", size = 1395903, upload-time = "2024-05-10T11:23:08.421Z" }, +] + +[[package]] +name = "alabaster" +version = "1.0.0" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/a6/f8/d9c74d0daf3f742840fd818d69cfae176fa332022fd44e3469487d5a9420/alabaster-1.0.0.tar.gz", hash = "sha256:c00dca57bca26fa62a6d7d0a9fcce65f3e026e9bfe33e9c538fd3fbb2144fd9e", size = 24210, upload-time = "2024-07-26T18:15:03.762Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/7e/b3/6b4067be973ae96ba0d615946e314c5ae35f9f993eca561b356540bb0c2b/alabaster-1.0.0-py3-none-any.whl", hash = "sha256:fc6786402dc3fcb2de3cabd5fe455a2db534b371124f1f21de8731783dec828b", size = 13929, upload-time = "2024-07-26T18:15:02.05Z" }, +] + +[[package]] +name = "anndata" +version = "0.12.10" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "array-api-compat" }, + { name = "h5py" }, + { name = "legacy-api-wrap" }, + { name = "natsort" }, + { name = "numpy" }, + { name = "packaging" }, + { name = "pandas" }, + { name = "scipy" }, + { name = "zarr" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/84/81/29809c5710123bb37ea9d9de9da0e83dda5be9d8419cce256e4406b37c44/anndata-0.12.10.tar.gz", hash = "sha256:73a73c99ca50400eb9dc7f2fdd400cf677ea4bb9ef1f7c04691c0fc557e43d7f", size = 2254675, upload-time = "2026-02-06T14:02:24.716Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/4c/f4/4d0193dc5bab3af74e9560a8b45830d88ac707467d15ceff7e3df17adc41/anndata-0.12.10-py3-none-any.whl", hash = "sha256:e3d940d8e34373dc250f998c1011c1da52721f980de9d83a0599daa2baa286e5", size = 176574, upload-time = "2026-02-06T14:02:23.097Z" }, +] + +[[package]] +name = "appnope" +version = "0.1.4" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/35/5d/752690df9ef5b76e169e68d6a129fa6d08a7100ca7f754c89495db3c6019/appnope-0.1.4.tar.gz", hash = "sha256:1de3860566df9caf38f01f86f65e0e13e379af54f9e4bee1e66b48f2efffd1ee", size = 4170, upload-time = "2024-02-06T09:43:11.258Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/81/29/5ecc3a15d5a33e31b26c11426c45c501e439cb865d0bff96315d86443b78/appnope-0.1.4-py2.py3-none-any.whl", hash = "sha256:502575ee11cd7a28c0205f379b525beefebab9d161b7c964670864014ed7213c", size = 4321, upload-time = "2024-02-06T09:43:09.663Z" }, +] + +[[package]] +name = "array-api-compat" +version = "1.13.0" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/68/36/f799b36d7025a92a23819f9f06541babdb84b6fd0bd4253f8be2eca348a4/array_api_compat-1.13.0.tar.gz", hash = "sha256:8b83a56aa8b9477472fee37f7731968dd213e20c198a05ac49caeff9b03f48a6", size = 103065, upload-time = "2025-12-28T11:26:57.734Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/df/5d/493b1b5528ab5072feae30821ff3a07b7a0474213d548efb1fdf135f85c1/array_api_compat-1.13.0-py3-none-any.whl", hash = "sha256:c15026a0ddec42815383f07da285472e1b1ff2e632eb7afbcfe9b08fcbad9bf1", size = 58585, upload-time = "2025-12-28T11:26:56.081Z" }, +] + +[[package]] +name = "astroid" +version = "3.3.11" +source = { registry = "https://pypi.org/simple" } +resolution-markers = [ + "python_full_version < '3.12'", +] +sdist = { url = "https://files.pythonhosted.org/packages/18/74/dfb75f9ccd592bbedb175d4a32fc643cf569d7c218508bfbd6ea7ef9c091/astroid-3.3.11.tar.gz", hash = "sha256:1e5a5011af2920c7c67a53f65d536d65bfa7116feeaf2354d8b94f29573bb0ce", size = 400439, upload-time = "2025-07-13T18:04:23.177Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/af/0f/3b8fdc946b4d9cc8cc1e8af42c4e409468c84441b933d037e101b3d72d86/astroid-3.3.11-py3-none-any.whl", hash = "sha256:54c760ae8322ece1abd213057c4b5bba7c49818853fc901ef09719a60dbf9dec", size = 275612, upload-time = "2025-07-13T18:04:21.07Z" }, +] + +[[package]] +name = "astroid" +version = "4.1.0" +source = { registry = "https://pypi.org/simple" } +resolution-markers = [ + "python_full_version >= '3.12'", +] +sdist = { url = "https://files.pythonhosted.org/packages/b0/79/f1e971b3700bcc24c09b3f0d47745d8404675a74afc10b32df8e4929dfdc/astroid-4.1.0.tar.gz", hash = "sha256:e2fbab37f205a651e6a168cb1e9a6a10677f6fa6a1c21833d113999855b04259", size = 412160, upload-time = "2026-02-09T02:19:57.705Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/3f/38/b2becedff0bef4af9ff474b82e2dcaefca608b6d24753d0b460c94003d91/astroid-4.1.0-py3-none-any.whl", hash = "sha256:2f8263bc7a33cbe8fc2bf5a3d37cfa8327a3284bf4afe3f47f5f0debba638e36", size = 279168, upload-time = "2026-02-09T02:19:55.89Z" }, +] + +[[package]] +name = "asttokens" +version = "3.0.1" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/be/a5/8e3f9b6771b0b408517c82d97aed8f2036509bc247d46114925e32fe33f0/asttokens-3.0.1.tar.gz", hash = "sha256:71a4ee5de0bde6a31d64f6b13f2293ac190344478f081c3d1bccfcf5eacb0cb7", size = 62308, upload-time = "2025-11-15T16:43:48.578Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/d2/39/e7eaf1799466a4aef85b6a4fe7bd175ad2b1c6345066aa33f1f58d4b18d0/asttokens-3.0.1-py3-none-any.whl", hash = "sha256:15a3ebc0f43c2d0a50eeafea25e19046c68398e487b9f1f5b517f7c0f40f976a", size = 27047, upload-time = "2025-11-15T16:43:16.109Z" }, +] + +[[package]] +name = "attrs" +version = "25.4.0" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/6b/5c/685e6633917e101e5dcb62b9dd76946cbb57c26e133bae9e0cd36033c0a9/attrs-25.4.0.tar.gz", hash = "sha256:16d5969b87f0859ef33a48b35d55ac1be6e42ae49d5e853b597db70c35c57e11", size = 934251, upload-time = "2025-10-06T13:54:44.725Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/3a/2a/7cc015f5b9f5db42b7d48157e23356022889fc354a2813c15934b7cb5c0e/attrs-25.4.0-py3-none-any.whl", hash = "sha256:adcf7e2a1fb3b36ac48d97835bb6d8ade15b8dcce26aba8bf1d14847b57a3373", size = 67615, upload-time = "2025-10-06T13:54:43.17Z" }, +] + +[[package]] +name = "babel" +version = "2.18.0" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/7d/b2/51899539b6ceeeb420d40ed3cd4b7a40519404f9baf3d4ac99dc413a834b/babel-2.18.0.tar.gz", hash = "sha256:b80b99a14bd085fcacfa15c9165f651fbb3406e66cc603abf11c5750937c992d", size = 9959554, upload-time = "2026-02-01T12:30:56.078Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/77/f5/21d2de20e8b8b0408f0681956ca2c69f1320a3848ac50e6e7f39c6159675/babel-2.18.0-py3-none-any.whl", hash = "sha256:e2b422b277c2b9a9630c1d7903c2a00d0830c409c59ac8cae9081c92f1aeba35", size = 10196845, upload-time = "2026-02-01T12:30:53.445Z" }, +] + +[[package]] +name = "backports-tarfile" +version = "1.2.0" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/86/72/cd9b395f25e290e633655a100af28cb253e4393396264a98bd5f5951d50f/backports_tarfile-1.2.0.tar.gz", hash = "sha256:d75e02c268746e1b8144c278978b6e98e85de6ad16f8e4b0844a154557eca991", size = 86406, upload-time = "2024-05-28T17:01:54.731Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/b9/fa/123043af240e49752f1c4bd24da5053b6bd00cad78c2be53c0d1e8b975bc/backports.tarfile-1.2.0-py3-none-any.whl", hash = "sha256:77e284d754527b01fb1e6fa8a1afe577858ebe4e9dad8919e34c862cb399bc34", size = 30181, upload-time = "2024-05-28T17:01:53.112Z" }, +] + +[[package]] +name = "beautifulsoup4" +version = "4.14.3" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "soupsieve" }, + { name = "typing-extensions" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/c3/b0/1c6a16426d389813b48d95e26898aff79abbde42ad353958ad95cc8c9b21/beautifulsoup4-4.14.3.tar.gz", hash = "sha256:6292b1c5186d356bba669ef9f7f051757099565ad9ada5dd630bd9de5fa7fb86", size = 627737, upload-time = "2025-11-30T15:08:26.084Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/1a/39/47f9197bdd44df24d67ac8893641e16f386c984a0619ef2ee4c51fbbc019/beautifulsoup4-4.14.3-py3-none-any.whl", hash = "sha256:0918bfe44902e6ad8d57732ba310582e98da931428d231a5ecb9e7c703a735bb", size = 107721, upload-time = "2025-11-30T15:08:24.087Z" }, +] + +[[package]] +name = "bleach" +version = "6.3.0" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "webencodings" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/07/18/3c8523962314be6bf4c8989c79ad9531c825210dd13a8669f6b84336e8bd/bleach-6.3.0.tar.gz", hash = "sha256:6f3b91b1c0a02bb9a78b5a454c92506aa0fdf197e1d5e114d2e00c6f64306d22", size = 203533, upload-time = "2025-10-27T17:57:39.211Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/cd/3a/577b549de0cc09d95f11087ee63c739bba856cd3952697eec4c4bb91350a/bleach-6.3.0-py3-none-any.whl", hash = "sha256:fe10ec77c93ddf3d13a73b035abaac7a9f5e436513864ccdad516693213c65d6", size = 164437, upload-time = "2025-10-27T17:57:37.538Z" }, +] + +[package.optional-dependencies] +css = [ + { name = "tinycss2" }, +] + +[[package]] +name = "build" +version = "1.4.0" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "colorama", marker = "os_name == 'nt'" }, + { name = "packaging" }, + { name = "pyproject-hooks" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/42/18/94eaffda7b329535d91f00fe605ab1f1e5cd68b2074d03f255c7d250687d/build-1.4.0.tar.gz", hash = "sha256:f1b91b925aa322be454f8330c6fb48b465da993d1e7e7e6fa35027ec49f3c936", size = 50054, upload-time = "2026-01-08T16:41:47.696Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/c5/0d/84a4380f930db0010168e0aa7b7a8fed9ba1835a8fbb1472bc6d0201d529/build-1.4.0-py3-none-any.whl", hash = "sha256:6a07c1b8eb6f2b311b96fcbdbce5dab5fe637ffda0fd83c9cac622e927501596", size = 24141, upload-time = "2026-01-08T16:41:46.453Z" }, +] + +[[package]] +name = "certifi" +version = "2026.1.4" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/e0/2d/a891ca51311197f6ad14a7ef42e2399f36cf2f9bd44752b3dc4eab60fdc5/certifi-2026.1.4.tar.gz", hash = "sha256:ac726dd470482006e014ad384921ed6438c457018f4b3d204aea4281258b2120", size = 154268, upload-time = "2026-01-04T02:42:41.825Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/e6/ad/3cc14f097111b4de0040c83a525973216457bbeeb63739ef1ed275c1c021/certifi-2026.1.4-py3-none-any.whl", hash = "sha256:9943707519e4add1115f44c2bc244f782c0249876bf51b6599fee1ffbedd685c", size = 152900, upload-time = "2026-01-04T02:42:40.15Z" }, +] + +[[package]] +name = "cffi" +version = "2.0.0" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "pycparser", marker = "implementation_name != 'PyPy'" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/eb/56/b1ba7935a17738ae8453301356628e8147c79dbb825bcbc73dc7401f9846/cffi-2.0.0.tar.gz", hash = "sha256:44d1b5909021139fe36001ae048dbdde8214afa20200eda0f64c068cac5d5529", size = 523588, upload-time = "2025-09-08T23:24:04.541Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/12/4a/3dfd5f7850cbf0d06dc84ba9aa00db766b52ca38d8b86e3a38314d52498c/cffi-2.0.0-cp311-cp311-macosx_10_13_x86_64.whl", hash = "sha256:b4c854ef3adc177950a8dfc81a86f5115d2abd545751a304c5bcf2c2c7283cfe", size = 184344, upload-time = "2025-09-08T23:22:26.456Z" }, + { url = "https://files.pythonhosted.org/packages/4f/8b/f0e4c441227ba756aafbe78f117485b25bb26b1c059d01f137fa6d14896b/cffi-2.0.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:2de9a304e27f7596cd03d16f1b7c72219bd944e99cc52b84d0145aefb07cbd3c", size = 180560, upload-time = "2025-09-08T23:22:28.197Z" }, + { url = "https://files.pythonhosted.org/packages/b1/b7/1200d354378ef52ec227395d95c2576330fd22a869f7a70e88e1447eb234/cffi-2.0.0-cp311-cp311-manylinux1_i686.manylinux2014_i686.manylinux_2_17_i686.manylinux_2_5_i686.whl", hash = "sha256:baf5215e0ab74c16e2dd324e8ec067ef59e41125d3eade2b863d294fd5035c92", size = 209613, upload-time = "2025-09-08T23:22:29.475Z" }, + { url = "https://files.pythonhosted.org/packages/b8/56/6033f5e86e8cc9bb629f0077ba71679508bdf54a9a5e112a3c0b91870332/cffi-2.0.0-cp311-cp311-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:730cacb21e1bdff3ce90babf007d0a0917cc3e6492f336c2f0134101e0944f93", size = 216476, upload-time = "2025-09-08T23:22:31.063Z" }, + { url = "https://files.pythonhosted.org/packages/dc/7f/55fecd70f7ece178db2f26128ec41430d8720f2d12ca97bf8f0a628207d5/cffi-2.0.0-cp311-cp311-manylinux2014_ppc64le.manylinux_2_17_ppc64le.whl", hash = "sha256:6824f87845e3396029f3820c206e459ccc91760e8fa24422f8b0c3d1731cbec5", size = 203374, upload-time = "2025-09-08T23:22:32.507Z" }, + { url = "https://files.pythonhosted.org/packages/84/ef/a7b77c8bdc0f77adc3b46888f1ad54be8f3b7821697a7b89126e829e676a/cffi-2.0.0-cp311-cp311-manylinux2014_s390x.manylinux_2_17_s390x.whl", hash = "sha256:9de40a7b0323d889cf8d23d1ef214f565ab154443c42737dfe52ff82cf857664", size = 202597, upload-time = "2025-09-08T23:22:34.132Z" }, + { url = "https://files.pythonhosted.org/packages/d7/91/500d892b2bf36529a75b77958edfcd5ad8e2ce4064ce2ecfeab2125d72d1/cffi-2.0.0-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:8941aaadaf67246224cee8c3803777eed332a19d909b47e29c9842ef1e79ac26", size = 215574, upload-time = "2025-09-08T23:22:35.443Z" }, + { url = "https://files.pythonhosted.org/packages/44/64/58f6255b62b101093d5df22dcb752596066c7e89dd725e0afaed242a61be/cffi-2.0.0-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:a05d0c237b3349096d3981b727493e22147f934b20f6f125a3eba8f994bec4a9", size = 218971, upload-time = "2025-09-08T23:22:36.805Z" }, + { url = "https://files.pythonhosted.org/packages/ab/49/fa72cebe2fd8a55fbe14956f9970fe8eb1ac59e5df042f603ef7c8ba0adc/cffi-2.0.0-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:94698a9c5f91f9d138526b48fe26a199609544591f859c870d477351dc7b2414", size = 211972, upload-time = "2025-09-08T23:22:38.436Z" }, + { url = "https://files.pythonhosted.org/packages/0b/28/dd0967a76aab36731b6ebfe64dec4e981aff7e0608f60c2d46b46982607d/cffi-2.0.0-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:5fed36fccc0612a53f1d4d9a816b50a36702c28a2aa880cb8a122b3466638743", size = 217078, upload-time = "2025-09-08T23:22:39.776Z" }, + { url = "https://files.pythonhosted.org/packages/2b/c0/015b25184413d7ab0a410775fdb4a50fca20f5589b5dab1dbbfa3baad8ce/cffi-2.0.0-cp311-cp311-win32.whl", hash = "sha256:c649e3a33450ec82378822b3dad03cc228b8f5963c0c12fc3b1e0ab940f768a5", size = 172076, upload-time = "2025-09-08T23:22:40.95Z" }, + { url = "https://files.pythonhosted.org/packages/ae/8f/dc5531155e7070361eb1b7e4c1a9d896d0cb21c49f807a6c03fd63fc877e/cffi-2.0.0-cp311-cp311-win_amd64.whl", hash = "sha256:66f011380d0e49ed280c789fbd08ff0d40968ee7b665575489afa95c98196ab5", size = 182820, upload-time = "2025-09-08T23:22:42.463Z" }, + { url = "https://files.pythonhosted.org/packages/95/5c/1b493356429f9aecfd56bc171285a4c4ac8697f76e9bbbbb105e537853a1/cffi-2.0.0-cp311-cp311-win_arm64.whl", hash = "sha256:c6638687455baf640e37344fe26d37c404db8b80d037c3d29f58fe8d1c3b194d", size = 177635, upload-time = "2025-09-08T23:22:43.623Z" }, + { url = "https://files.pythonhosted.org/packages/ea/47/4f61023ea636104d4f16ab488e268b93008c3d0bb76893b1b31db1f96802/cffi-2.0.0-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:6d02d6655b0e54f54c4ef0b94eb6be0607b70853c45ce98bd278dc7de718be5d", size = 185271, upload-time = "2025-09-08T23:22:44.795Z" }, + { url = "https://files.pythonhosted.org/packages/df/a2/781b623f57358e360d62cdd7a8c681f074a71d445418a776eef0aadb4ab4/cffi-2.0.0-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:8eca2a813c1cb7ad4fb74d368c2ffbbb4789d377ee5bb8df98373c2cc0dee76c", size = 181048, upload-time = "2025-09-08T23:22:45.938Z" }, + { url = "https://files.pythonhosted.org/packages/ff/df/a4f0fbd47331ceeba3d37c2e51e9dfc9722498becbeec2bd8bc856c9538a/cffi-2.0.0-cp312-cp312-manylinux1_i686.manylinux2014_i686.manylinux_2_17_i686.manylinux_2_5_i686.whl", hash = "sha256:21d1152871b019407d8ac3985f6775c079416c282e431a4da6afe7aefd2bccbe", size = 212529, upload-time = "2025-09-08T23:22:47.349Z" }, + { url = "https://files.pythonhosted.org/packages/d5/72/12b5f8d3865bf0f87cf1404d8c374e7487dcf097a1c91c436e72e6badd83/cffi-2.0.0-cp312-cp312-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:b21e08af67b8a103c71a250401c78d5e0893beff75e28c53c98f4de42f774062", size = 220097, upload-time = "2025-09-08T23:22:48.677Z" }, + { url = "https://files.pythonhosted.org/packages/c2/95/7a135d52a50dfa7c882ab0ac17e8dc11cec9d55d2c18dda414c051c5e69e/cffi-2.0.0-cp312-cp312-manylinux2014_ppc64le.manylinux_2_17_ppc64le.whl", hash = "sha256:1e3a615586f05fc4065a8b22b8152f0c1b00cdbc60596d187c2a74f9e3036e4e", size = 207983, upload-time = "2025-09-08T23:22:50.06Z" }, + { url = "https://files.pythonhosted.org/packages/3a/c8/15cb9ada8895957ea171c62dc78ff3e99159ee7adb13c0123c001a2546c1/cffi-2.0.0-cp312-cp312-manylinux2014_s390x.manylinux_2_17_s390x.whl", hash = "sha256:81afed14892743bbe14dacb9e36d9e0e504cd204e0b165062c488942b9718037", size = 206519, upload-time = "2025-09-08T23:22:51.364Z" }, + { url = "https://files.pythonhosted.org/packages/78/2d/7fa73dfa841b5ac06c7b8855cfc18622132e365f5b81d02230333ff26e9e/cffi-2.0.0-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:3e17ed538242334bf70832644a32a7aae3d83b57567f9fd60a26257e992b79ba", size = 219572, upload-time = "2025-09-08T23:22:52.902Z" }, + { url = "https://files.pythonhosted.org/packages/07/e0/267e57e387b4ca276b90f0434ff88b2c2241ad72b16d31836adddfd6031b/cffi-2.0.0-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:3925dd22fa2b7699ed2617149842d2e6adde22b262fcbfada50e3d195e4b3a94", size = 222963, upload-time = "2025-09-08T23:22:54.518Z" }, + { url = "https://files.pythonhosted.org/packages/b6/75/1f2747525e06f53efbd878f4d03bac5b859cbc11c633d0fb81432d98a795/cffi-2.0.0-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:2c8f814d84194c9ea681642fd164267891702542f028a15fc97d4674b6206187", size = 221361, upload-time = "2025-09-08T23:22:55.867Z" }, + { url = "https://files.pythonhosted.org/packages/7b/2b/2b6435f76bfeb6bbf055596976da087377ede68df465419d192acf00c437/cffi-2.0.0-cp312-cp312-win32.whl", hash = "sha256:da902562c3e9c550df360bfa53c035b2f241fed6d9aef119048073680ace4a18", size = 172932, upload-time = "2025-09-08T23:22:57.188Z" }, + { url = "https://files.pythonhosted.org/packages/f8/ed/13bd4418627013bec4ed6e54283b1959cf6db888048c7cf4b4c3b5b36002/cffi-2.0.0-cp312-cp312-win_amd64.whl", hash = "sha256:da68248800ad6320861f129cd9c1bf96ca849a2771a59e0344e88681905916f5", size = 183557, upload-time = "2025-09-08T23:22:58.351Z" }, + { url = "https://files.pythonhosted.org/packages/95/31/9f7f93ad2f8eff1dbc1c3656d7ca5bfd8fb52c9d786b4dcf19b2d02217fa/cffi-2.0.0-cp312-cp312-win_arm64.whl", hash = "sha256:4671d9dd5ec934cb9a73e7ee9676f9362aba54f7f34910956b84d727b0d73fb6", size = 177762, upload-time = "2025-09-08T23:22:59.668Z" }, + { url = "https://files.pythonhosted.org/packages/4b/8d/a0a47a0c9e413a658623d014e91e74a50cdd2c423f7ccfd44086ef767f90/cffi-2.0.0-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:00bdf7acc5f795150faa6957054fbbca2439db2f775ce831222b66f192f03beb", size = 185230, upload-time = "2025-09-08T23:23:00.879Z" }, + { url = "https://files.pythonhosted.org/packages/4a/d2/a6c0296814556c68ee32009d9c2ad4f85f2707cdecfd7727951ec228005d/cffi-2.0.0-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:45d5e886156860dc35862657e1494b9bae8dfa63bf56796f2fb56e1679fc0bca", size = 181043, upload-time = "2025-09-08T23:23:02.231Z" }, + { url = "https://files.pythonhosted.org/packages/b0/1e/d22cc63332bd59b06481ceaac49d6c507598642e2230f201649058a7e704/cffi-2.0.0-cp313-cp313-manylinux1_i686.manylinux2014_i686.manylinux_2_17_i686.manylinux_2_5_i686.whl", hash = "sha256:07b271772c100085dd28b74fa0cd81c8fb1a3ba18b21e03d7c27f3436a10606b", size = 212446, upload-time = "2025-09-08T23:23:03.472Z" }, + { url = "https://files.pythonhosted.org/packages/a9/f5/a2c23eb03b61a0b8747f211eb716446c826ad66818ddc7810cc2cc19b3f2/cffi-2.0.0-cp313-cp313-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:d48a880098c96020b02d5a1f7d9251308510ce8858940e6fa99ece33f610838b", size = 220101, upload-time = "2025-09-08T23:23:04.792Z" }, + { url = "https://files.pythonhosted.org/packages/f2/7f/e6647792fc5850d634695bc0e6ab4111ae88e89981d35ac269956605feba/cffi-2.0.0-cp313-cp313-manylinux2014_ppc64le.manylinux_2_17_ppc64le.whl", hash = "sha256:f93fd8e5c8c0a4aa1f424d6173f14a892044054871c771f8566e4008eaa359d2", size = 207948, upload-time = "2025-09-08T23:23:06.127Z" }, + { url = "https://files.pythonhosted.org/packages/cb/1e/a5a1bd6f1fb30f22573f76533de12a00bf274abcdc55c8edab639078abb6/cffi-2.0.0-cp313-cp313-manylinux2014_s390x.manylinux_2_17_s390x.whl", hash = "sha256:dd4f05f54a52fb558f1ba9f528228066954fee3ebe629fc1660d874d040ae5a3", size = 206422, upload-time = "2025-09-08T23:23:07.753Z" }, + { url = "https://files.pythonhosted.org/packages/98/df/0a1755e750013a2081e863e7cd37e0cdd02664372c754e5560099eb7aa44/cffi-2.0.0-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:c8d3b5532fc71b7a77c09192b4a5a200ea992702734a2e9279a37f2478236f26", size = 219499, upload-time = "2025-09-08T23:23:09.648Z" }, + { url = "https://files.pythonhosted.org/packages/50/e1/a969e687fcf9ea58e6e2a928ad5e2dd88cc12f6f0ab477e9971f2309b57c/cffi-2.0.0-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:d9b29c1f0ae438d5ee9acb31cadee00a58c46cc9c0b2f9038c6b0b3470877a8c", size = 222928, upload-time = "2025-09-08T23:23:10.928Z" }, + { url = "https://files.pythonhosted.org/packages/36/54/0362578dd2c9e557a28ac77698ed67323ed5b9775ca9d3fe73fe191bb5d8/cffi-2.0.0-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:6d50360be4546678fc1b79ffe7a66265e28667840010348dd69a314145807a1b", size = 221302, upload-time = "2025-09-08T23:23:12.42Z" }, + { url = "https://files.pythonhosted.org/packages/eb/6d/bf9bda840d5f1dfdbf0feca87fbdb64a918a69bca42cfa0ba7b137c48cb8/cffi-2.0.0-cp313-cp313-win32.whl", hash = "sha256:74a03b9698e198d47562765773b4a8309919089150a0bb17d829ad7b44b60d27", size = 172909, upload-time = "2025-09-08T23:23:14.32Z" }, + { url = "https://files.pythonhosted.org/packages/37/18/6519e1ee6f5a1e579e04b9ddb6f1676c17368a7aba48299c3759bbc3c8b3/cffi-2.0.0-cp313-cp313-win_amd64.whl", hash = "sha256:19f705ada2530c1167abacb171925dd886168931e0a7b78f5bffcae5c6b5be75", size = 183402, upload-time = "2025-09-08T23:23:15.535Z" }, + { url = "https://files.pythonhosted.org/packages/cb/0e/02ceeec9a7d6ee63bb596121c2c8e9b3a9e150936f4fbef6ca1943e6137c/cffi-2.0.0-cp313-cp313-win_arm64.whl", hash = "sha256:256f80b80ca3853f90c21b23ee78cd008713787b1b1e93eae9f3d6a7134abd91", size = 177780, upload-time = "2025-09-08T23:23:16.761Z" }, + { url = "https://files.pythonhosted.org/packages/92/c4/3ce07396253a83250ee98564f8d7e9789fab8e58858f35d07a9a2c78de9f/cffi-2.0.0-cp314-cp314-macosx_10_13_x86_64.whl", hash = "sha256:fc33c5141b55ed366cfaad382df24fe7dcbc686de5be719b207bb248e3053dc5", size = 185320, upload-time = "2025-09-08T23:23:18.087Z" }, + { url = "https://files.pythonhosted.org/packages/59/dd/27e9fa567a23931c838c6b02d0764611c62290062a6d4e8ff7863daf9730/cffi-2.0.0-cp314-cp314-macosx_11_0_arm64.whl", hash = "sha256:c654de545946e0db659b3400168c9ad31b5d29593291482c43e3564effbcee13", size = 181487, upload-time = "2025-09-08T23:23:19.622Z" }, + { url = "https://files.pythonhosted.org/packages/d6/43/0e822876f87ea8a4ef95442c3d766a06a51fc5298823f884ef87aaad168c/cffi-2.0.0-cp314-cp314-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:24b6f81f1983e6df8db3adc38562c83f7d4a0c36162885ec7f7b77c7dcbec97b", size = 220049, upload-time = "2025-09-08T23:23:20.853Z" }, + { url = "https://files.pythonhosted.org/packages/b4/89/76799151d9c2d2d1ead63c2429da9ea9d7aac304603de0c6e8764e6e8e70/cffi-2.0.0-cp314-cp314-manylinux2014_ppc64le.manylinux_2_17_ppc64le.whl", hash = "sha256:12873ca6cb9b0f0d3a0da705d6086fe911591737a59f28b7936bdfed27c0d47c", size = 207793, upload-time = "2025-09-08T23:23:22.08Z" }, + { url = "https://files.pythonhosted.org/packages/bb/dd/3465b14bb9e24ee24cb88c9e3730f6de63111fffe513492bf8c808a3547e/cffi-2.0.0-cp314-cp314-manylinux2014_s390x.manylinux_2_17_s390x.whl", hash = "sha256:d9b97165e8aed9272a6bb17c01e3cc5871a594a446ebedc996e2397a1c1ea8ef", size = 206300, upload-time = "2025-09-08T23:23:23.314Z" }, + { url = "https://files.pythonhosted.org/packages/47/d9/d83e293854571c877a92da46fdec39158f8d7e68da75bf73581225d28e90/cffi-2.0.0-cp314-cp314-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:afb8db5439b81cf9c9d0c80404b60c3cc9c3add93e114dcae767f1477cb53775", size = 219244, upload-time = "2025-09-08T23:23:24.541Z" }, + { url = "https://files.pythonhosted.org/packages/2b/0f/1f177e3683aead2bb00f7679a16451d302c436b5cbf2505f0ea8146ef59e/cffi-2.0.0-cp314-cp314-musllinux_1_2_aarch64.whl", hash = "sha256:737fe7d37e1a1bffe70bd5754ea763a62a066dc5913ca57e957824b72a85e205", size = 222828, upload-time = "2025-09-08T23:23:26.143Z" }, + { url = "https://files.pythonhosted.org/packages/c6/0f/cafacebd4b040e3119dcb32fed8bdef8dfe94da653155f9d0b9dc660166e/cffi-2.0.0-cp314-cp314-musllinux_1_2_x86_64.whl", hash = "sha256:38100abb9d1b1435bc4cc340bb4489635dc2f0da7456590877030c9b3d40b0c1", size = 220926, upload-time = "2025-09-08T23:23:27.873Z" }, + { url = "https://files.pythonhosted.org/packages/3e/aa/df335faa45b395396fcbc03de2dfcab242cd61a9900e914fe682a59170b1/cffi-2.0.0-cp314-cp314-win32.whl", hash = "sha256:087067fa8953339c723661eda6b54bc98c5625757ea62e95eb4898ad5e776e9f", size = 175328, upload-time = "2025-09-08T23:23:44.61Z" }, + { url = "https://files.pythonhosted.org/packages/bb/92/882c2d30831744296ce713f0feb4c1cd30f346ef747b530b5318715cc367/cffi-2.0.0-cp314-cp314-win_amd64.whl", hash = "sha256:203a48d1fb583fc7d78a4c6655692963b860a417c0528492a6bc21f1aaefab25", size = 185650, upload-time = "2025-09-08T23:23:45.848Z" }, + { url = "https://files.pythonhosted.org/packages/9f/2c/98ece204b9d35a7366b5b2c6539c350313ca13932143e79dc133ba757104/cffi-2.0.0-cp314-cp314-win_arm64.whl", hash = "sha256:dbd5c7a25a7cb98f5ca55d258b103a2054f859a46ae11aaf23134f9cc0d356ad", size = 180687, upload-time = "2025-09-08T23:23:47.105Z" }, + { url = "https://files.pythonhosted.org/packages/3e/61/c768e4d548bfa607abcda77423448df8c471f25dbe64fb2ef6d555eae006/cffi-2.0.0-cp314-cp314t-macosx_10_13_x86_64.whl", hash = "sha256:9a67fc9e8eb39039280526379fb3a70023d77caec1852002b4da7e8b270c4dd9", size = 188773, upload-time = "2025-09-08T23:23:29.347Z" }, + { url = "https://files.pythonhosted.org/packages/2c/ea/5f76bce7cf6fcd0ab1a1058b5af899bfbef198bea4d5686da88471ea0336/cffi-2.0.0-cp314-cp314t-macosx_11_0_arm64.whl", hash = "sha256:7a66c7204d8869299919db4d5069a82f1561581af12b11b3c9f48c584eb8743d", size = 185013, upload-time = "2025-09-08T23:23:30.63Z" }, + { url = "https://files.pythonhosted.org/packages/be/b4/c56878d0d1755cf9caa54ba71e5d049479c52f9e4afc230f06822162ab2f/cffi-2.0.0-cp314-cp314t-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:7cc09976e8b56f8cebd752f7113ad07752461f48a58cbba644139015ac24954c", size = 221593, upload-time = "2025-09-08T23:23:31.91Z" }, + { url = "https://files.pythonhosted.org/packages/e0/0d/eb704606dfe8033e7128df5e90fee946bbcb64a04fcdaa97321309004000/cffi-2.0.0-cp314-cp314t-manylinux2014_ppc64le.manylinux_2_17_ppc64le.whl", hash = "sha256:92b68146a71df78564e4ef48af17551a5ddd142e5190cdf2c5624d0c3ff5b2e8", size = 209354, upload-time = "2025-09-08T23:23:33.214Z" }, + { url = "https://files.pythonhosted.org/packages/d8/19/3c435d727b368ca475fb8742ab97c9cb13a0de600ce86f62eab7fa3eea60/cffi-2.0.0-cp314-cp314t-manylinux2014_s390x.manylinux_2_17_s390x.whl", hash = "sha256:b1e74d11748e7e98e2f426ab176d4ed720a64412b6a15054378afdb71e0f37dc", size = 208480, upload-time = "2025-09-08T23:23:34.495Z" }, + { url = "https://files.pythonhosted.org/packages/d0/44/681604464ed9541673e486521497406fadcc15b5217c3e326b061696899a/cffi-2.0.0-cp314-cp314t-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:28a3a209b96630bca57cce802da70c266eb08c6e97e5afd61a75611ee6c64592", size = 221584, upload-time = "2025-09-08T23:23:36.096Z" }, + { url = "https://files.pythonhosted.org/packages/25/8e/342a504ff018a2825d395d44d63a767dd8ebc927ebda557fecdaca3ac33a/cffi-2.0.0-cp314-cp314t-musllinux_1_2_aarch64.whl", hash = "sha256:7553fb2090d71822f02c629afe6042c299edf91ba1bf94951165613553984512", size = 224443, upload-time = "2025-09-08T23:23:37.328Z" }, + { url = "https://files.pythonhosted.org/packages/e1/5e/b666bacbbc60fbf415ba9988324a132c9a7a0448a9a8f125074671c0f2c3/cffi-2.0.0-cp314-cp314t-musllinux_1_2_x86_64.whl", hash = "sha256:6c6c373cfc5c83a975506110d17457138c8c63016b563cc9ed6e056a82f13ce4", size = 223437, upload-time = "2025-09-08T23:23:38.945Z" }, + { url = "https://files.pythonhosted.org/packages/a0/1d/ec1a60bd1a10daa292d3cd6bb0b359a81607154fb8165f3ec95fe003b85c/cffi-2.0.0-cp314-cp314t-win32.whl", hash = "sha256:1fc9ea04857caf665289b7a75923f2c6ed559b8298a1b8c49e59f7dd95c8481e", size = 180487, upload-time = "2025-09-08T23:23:40.423Z" }, + { url = "https://files.pythonhosted.org/packages/bf/41/4c1168c74fac325c0c8156f04b6749c8b6a8f405bbf91413ba088359f60d/cffi-2.0.0-cp314-cp314t-win_amd64.whl", hash = "sha256:d68b6cef7827e8641e8ef16f4494edda8b36104d79773a334beaa1e3521430f6", size = 191726, upload-time = "2025-09-08T23:23:41.742Z" }, + { url = "https://files.pythonhosted.org/packages/ae/3a/dbeec9d1ee0844c679f6bb5d6ad4e9f198b1224f4e7a32825f47f6192b0c/cffi-2.0.0-cp314-cp314t-win_arm64.whl", hash = "sha256:0a1527a803f0a659de1af2e1fd700213caba79377e27e4693648c2923da066f9", size = 184195, upload-time = "2025-09-08T23:23:43.004Z" }, +] + +[[package]] +name = "cfgv" +version = "3.5.0" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/4e/b5/721b8799b04bf9afe054a3899c6cf4e880fcf8563cc71c15610242490a0c/cfgv-3.5.0.tar.gz", hash = "sha256:d5b1034354820651caa73ede66a6294d6e95c1b00acc5e9b098e917404669132", size = 7334, upload-time = "2025-11-19T20:55:51.612Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/db/3c/33bac158f8ab7f89b2e59426d5fe2e4f63f7ed25df84c036890172b412b5/cfgv-3.5.0-py2.py3-none-any.whl", hash = "sha256:a8dc6b26ad22ff227d2634a65cb388215ce6cc96bbcc5cfde7641ae87e8dacc0", size = 7445, upload-time = "2025-11-19T20:55:50.744Z" }, +] + +[[package]] +name = "charset-normalizer" +version = "3.4.4" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/13/69/33ddede1939fdd074bce5434295f38fae7136463422fe4fd3e0e89b98062/charset_normalizer-3.4.4.tar.gz", hash = "sha256:94537985111c35f28720e43603b8e7b43a6ecfb2ce1d3058bbe955b73404e21a", size = 129418, upload-time = "2025-10-14T04:42:32.879Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/ed/27/c6491ff4954e58a10f69ad90aca8a1b6fe9c5d3c6f380907af3c37435b59/charset_normalizer-3.4.4-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:6e1fcf0720908f200cd21aa4e6750a48ff6ce4afe7ff5a79a90d5ed8a08296f8", size = 206988, upload-time = "2025-10-14T04:40:33.79Z" }, + { url = "https://files.pythonhosted.org/packages/94/59/2e87300fe67ab820b5428580a53cad894272dbb97f38a7a814a2a1ac1011/charset_normalizer-3.4.4-cp311-cp311-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:5f819d5fe9234f9f82d75bdfa9aef3a3d72c4d24a6e57aeaebba32a704553aa0", size = 147324, upload-time = "2025-10-14T04:40:34.961Z" }, + { url = "https://files.pythonhosted.org/packages/07/fb/0cf61dc84b2b088391830f6274cb57c82e4da8bbc2efeac8c025edb88772/charset_normalizer-3.4.4-cp311-cp311-manylinux2014_armv7l.manylinux_2_17_armv7l.manylinux_2_31_armv7l.whl", hash = "sha256:a59cb51917aa591b1c4e6a43c132f0cdc3c76dbad6155df4e28ee626cc77a0a3", size = 142742, upload-time = "2025-10-14T04:40:36.105Z" }, + { url = "https://files.pythonhosted.org/packages/62/8b/171935adf2312cd745d290ed93cf16cf0dfe320863ab7cbeeae1dcd6535f/charset_normalizer-3.4.4-cp311-cp311-manylinux2014_ppc64le.manylinux_2_17_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:8ef3c867360f88ac904fd3f5e1f902f13307af9052646963ee08ff4f131adafc", size = 160863, upload-time = "2025-10-14T04:40:37.188Z" }, + { url = "https://files.pythonhosted.org/packages/09/73/ad875b192bda14f2173bfc1bc9a55e009808484a4b256748d931b6948442/charset_normalizer-3.4.4-cp311-cp311-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:d9e45d7faa48ee908174d8fe84854479ef838fc6a705c9315372eacbc2f02897", size = 157837, upload-time = "2025-10-14T04:40:38.435Z" }, + { url = "https://files.pythonhosted.org/packages/6d/fc/de9cce525b2c5b94b47c70a4b4fb19f871b24995c728e957ee68ab1671ea/charset_normalizer-3.4.4-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:840c25fb618a231545cbab0564a799f101b63b9901f2569faecd6b222ac72381", size = 151550, upload-time = "2025-10-14T04:40:40.053Z" }, + { url = "https://files.pythonhosted.org/packages/55/c2/43edd615fdfba8c6f2dfbd459b25a6b3b551f24ea21981e23fb768503ce1/charset_normalizer-3.4.4-cp311-cp311-manylinux_2_31_riscv64.manylinux_2_39_riscv64.whl", hash = "sha256:ca5862d5b3928c4940729dacc329aa9102900382fea192fc5e52eb69d6093815", size = 149162, upload-time = "2025-10-14T04:40:41.163Z" }, + { url = "https://files.pythonhosted.org/packages/03/86/bde4ad8b4d0e9429a4e82c1e8f5c659993a9a863ad62c7df05cf7b678d75/charset_normalizer-3.4.4-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:d9c7f57c3d666a53421049053eaacdd14bbd0a528e2186fcb2e672effd053bb0", size = 150019, upload-time = "2025-10-14T04:40:42.276Z" }, + { url = "https://files.pythonhosted.org/packages/1f/86/a151eb2af293a7e7bac3a739b81072585ce36ccfb4493039f49f1d3cae8c/charset_normalizer-3.4.4-cp311-cp311-musllinux_1_2_armv7l.whl", hash = "sha256:277e970e750505ed74c832b4bf75dac7476262ee2a013f5574dd49075879e161", size = 143310, upload-time = "2025-10-14T04:40:43.439Z" }, + { url = "https://files.pythonhosted.org/packages/b5/fe/43dae6144a7e07b87478fdfc4dbe9efd5defb0e7ec29f5f58a55aeef7bf7/charset_normalizer-3.4.4-cp311-cp311-musllinux_1_2_ppc64le.whl", hash = "sha256:31fd66405eaf47bb62e8cd575dc621c56c668f27d46a61d975a249930dd5e2a4", size = 162022, upload-time = "2025-10-14T04:40:44.547Z" }, + { url = "https://files.pythonhosted.org/packages/80/e6/7aab83774f5d2bca81f42ac58d04caf44f0cc2b65fc6db2b3b2e8a05f3b3/charset_normalizer-3.4.4-cp311-cp311-musllinux_1_2_riscv64.whl", hash = "sha256:0d3d8f15c07f86e9ff82319b3d9ef6f4bf907608f53fe9d92b28ea9ae3d1fd89", size = 149383, upload-time = "2025-10-14T04:40:46.018Z" }, + { url = "https://files.pythonhosted.org/packages/4f/e8/b289173b4edae05c0dde07f69f8db476a0b511eac556dfe0d6bda3c43384/charset_normalizer-3.4.4-cp311-cp311-musllinux_1_2_s390x.whl", hash = "sha256:9f7fcd74d410a36883701fafa2482a6af2ff5ba96b9a620e9e0721e28ead5569", size = 159098, upload-time = "2025-10-14T04:40:47.081Z" }, + { url = "https://files.pythonhosted.org/packages/d8/df/fe699727754cae3f8478493c7f45f777b17c3ef0600e28abfec8619eb49c/charset_normalizer-3.4.4-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:ebf3e58c7ec8a8bed6d66a75d7fb37b55e5015b03ceae72a8e7c74495551e224", size = 152991, upload-time = "2025-10-14T04:40:48.246Z" }, + { url = "https://files.pythonhosted.org/packages/1a/86/584869fe4ddb6ffa3bd9f491b87a01568797fb9bd8933f557dba9771beaf/charset_normalizer-3.4.4-cp311-cp311-win32.whl", hash = "sha256:eecbc200c7fd5ddb9a7f16c7decb07b566c29fa2161a16cf67b8d068bd21690a", size = 99456, upload-time = "2025-10-14T04:40:49.376Z" }, + { url = "https://files.pythonhosted.org/packages/65/f6/62fdd5feb60530f50f7e38b4f6a1d5203f4d16ff4f9f0952962c044e919a/charset_normalizer-3.4.4-cp311-cp311-win_amd64.whl", hash = "sha256:5ae497466c7901d54b639cf42d5b8c1b6a4fead55215500d2f486d34db48d016", size = 106978, upload-time = "2025-10-14T04:40:50.844Z" }, + { url = "https://files.pythonhosted.org/packages/7a/9d/0710916e6c82948b3be62d9d398cb4fcf4e97b56d6a6aeccd66c4b2f2bd5/charset_normalizer-3.4.4-cp311-cp311-win_arm64.whl", hash = "sha256:65e2befcd84bc6f37095f5961e68a6f077bf44946771354a28ad434c2cce0ae1", size = 99969, upload-time = "2025-10-14T04:40:52.272Z" }, + { url = "https://files.pythonhosted.org/packages/f3/85/1637cd4af66fa687396e757dec650f28025f2a2f5a5531a3208dc0ec43f2/charset_normalizer-3.4.4-cp312-cp312-macosx_10_13_universal2.whl", hash = "sha256:0a98e6759f854bd25a58a73fa88833fba3b7c491169f86ce1180c948ab3fd394", size = 208425, upload-time = "2025-10-14T04:40:53.353Z" }, + { url = "https://files.pythonhosted.org/packages/9d/6a/04130023fef2a0d9c62d0bae2649b69f7b7d8d24ea5536feef50551029df/charset_normalizer-3.4.4-cp312-cp312-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:b5b290ccc2a263e8d185130284f8501e3e36c5e02750fc6b6bdeb2e9e96f1e25", size = 148162, upload-time = "2025-10-14T04:40:54.558Z" }, + { url = "https://files.pythonhosted.org/packages/78/29/62328d79aa60da22c9e0b9a66539feae06ca0f5a4171ac4f7dc285b83688/charset_normalizer-3.4.4-cp312-cp312-manylinux2014_armv7l.manylinux_2_17_armv7l.manylinux_2_31_armv7l.whl", hash = "sha256:74bb723680f9f7a6234dcf67aea57e708ec1fbdf5699fb91dfd6f511b0a320ef", size = 144558, upload-time = "2025-10-14T04:40:55.677Z" }, + { url = "https://files.pythonhosted.org/packages/86/bb/b32194a4bf15b88403537c2e120b817c61cd4ecffa9b6876e941c3ee38fe/charset_normalizer-3.4.4-cp312-cp312-manylinux2014_ppc64le.manylinux_2_17_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:f1e34719c6ed0b92f418c7c780480b26b5d9c50349e9a9af7d76bf757530350d", size = 161497, upload-time = "2025-10-14T04:40:57.217Z" }, + { url = "https://files.pythonhosted.org/packages/19/89/a54c82b253d5b9b111dc74aca196ba5ccfcca8242d0fb64146d4d3183ff1/charset_normalizer-3.4.4-cp312-cp312-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:2437418e20515acec67d86e12bf70056a33abdacb5cb1655042f6538d6b085a8", size = 159240, upload-time = "2025-10-14T04:40:58.358Z" }, + { url = "https://files.pythonhosted.org/packages/c0/10/d20b513afe03acc89ec33948320a5544d31f21b05368436d580dec4e234d/charset_normalizer-3.4.4-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:11d694519d7f29d6cd09f6ac70028dba10f92f6cdd059096db198c283794ac86", size = 153471, upload-time = "2025-10-14T04:40:59.468Z" }, + { url = "https://files.pythonhosted.org/packages/61/fa/fbf177b55bdd727010f9c0a3c49eefa1d10f960e5f09d1d887bf93c2e698/charset_normalizer-3.4.4-cp312-cp312-manylinux_2_31_riscv64.manylinux_2_39_riscv64.whl", hash = "sha256:ac1c4a689edcc530fc9d9aa11f5774b9e2f33f9a0c6a57864e90908f5208d30a", size = 150864, upload-time = "2025-10-14T04:41:00.623Z" }, + { url = "https://files.pythonhosted.org/packages/05/12/9fbc6a4d39c0198adeebbde20b619790e9236557ca59fc40e0e3cebe6f40/charset_normalizer-3.4.4-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:21d142cc6c0ec30d2efee5068ca36c128a30b0f2c53c1c07bd78cb6bc1d3be5f", size = 150647, upload-time = "2025-10-14T04:41:01.754Z" }, + { url = "https://files.pythonhosted.org/packages/ad/1f/6a9a593d52e3e8c5d2b167daf8c6b968808efb57ef4c210acb907c365bc4/charset_normalizer-3.4.4-cp312-cp312-musllinux_1_2_armv7l.whl", hash = "sha256:5dbe56a36425d26d6cfb40ce79c314a2e4dd6211d51d6d2191c00bed34f354cc", size = 145110, upload-time = "2025-10-14T04:41:03.231Z" }, + { url = "https://files.pythonhosted.org/packages/30/42/9a52c609e72471b0fc54386dc63c3781a387bb4fe61c20231a4ebcd58bdd/charset_normalizer-3.4.4-cp312-cp312-musllinux_1_2_ppc64le.whl", hash = "sha256:5bfbb1b9acf3334612667b61bd3002196fe2a1eb4dd74d247e0f2a4d50ec9bbf", size = 162839, upload-time = "2025-10-14T04:41:04.715Z" }, + { url = "https://files.pythonhosted.org/packages/c4/5b/c0682bbf9f11597073052628ddd38344a3d673fda35a36773f7d19344b23/charset_normalizer-3.4.4-cp312-cp312-musllinux_1_2_riscv64.whl", hash = "sha256:d055ec1e26e441f6187acf818b73564e6e6282709e9bcb5b63f5b23068356a15", size = 150667, upload-time = "2025-10-14T04:41:05.827Z" }, + { url = "https://files.pythonhosted.org/packages/e4/24/a41afeab6f990cf2daf6cb8c67419b63b48cf518e4f56022230840c9bfb2/charset_normalizer-3.4.4-cp312-cp312-musllinux_1_2_s390x.whl", hash = "sha256:af2d8c67d8e573d6de5bc30cdb27e9b95e49115cd9baad5ddbd1a6207aaa82a9", size = 160535, upload-time = "2025-10-14T04:41:06.938Z" }, + { url = "https://files.pythonhosted.org/packages/2a/e5/6a4ce77ed243c4a50a1fecca6aaaab419628c818a49434be428fe24c9957/charset_normalizer-3.4.4-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:780236ac706e66881f3b7f2f32dfe90507a09e67d1d454c762cf642e6e1586e0", size = 154816, upload-time = "2025-10-14T04:41:08.101Z" }, + { url = "https://files.pythonhosted.org/packages/a8/ef/89297262b8092b312d29cdb2517cb1237e51db8ecef2e9af5edbe7b683b1/charset_normalizer-3.4.4-cp312-cp312-win32.whl", hash = "sha256:5833d2c39d8896e4e19b689ffc198f08ea58116bee26dea51e362ecc7cd3ed26", size = 99694, upload-time = "2025-10-14T04:41:09.23Z" }, + { url = "https://files.pythonhosted.org/packages/3d/2d/1e5ed9dd3b3803994c155cd9aacb60c82c331bad84daf75bcb9c91b3295e/charset_normalizer-3.4.4-cp312-cp312-win_amd64.whl", hash = "sha256:a79cfe37875f822425b89a82333404539ae63dbdddf97f84dcbc3d339aae9525", size = 107131, upload-time = "2025-10-14T04:41:10.467Z" }, + { url = "https://files.pythonhosted.org/packages/d0/d9/0ed4c7098a861482a7b6a95603edce4c0d9db2311af23da1fb2b75ec26fc/charset_normalizer-3.4.4-cp312-cp312-win_arm64.whl", hash = "sha256:376bec83a63b8021bb5c8ea75e21c4ccb86e7e45ca4eb81146091b56599b80c3", size = 100390, upload-time = "2025-10-14T04:41:11.915Z" }, + { url = "https://files.pythonhosted.org/packages/97/45/4b3a1239bbacd321068ea6e7ac28875b03ab8bc0aa0966452db17cd36714/charset_normalizer-3.4.4-cp313-cp313-macosx_10_13_universal2.whl", hash = "sha256:e1f185f86a6f3403aa2420e815904c67b2f9ebc443f045edd0de921108345794", size = 208091, upload-time = "2025-10-14T04:41:13.346Z" }, + { url = "https://files.pythonhosted.org/packages/7d/62/73a6d7450829655a35bb88a88fca7d736f9882a27eacdca2c6d505b57e2e/charset_normalizer-3.4.4-cp313-cp313-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:6b39f987ae8ccdf0d2642338faf2abb1862340facc796048b604ef14919e55ed", size = 147936, upload-time = "2025-10-14T04:41:14.461Z" }, + { url = "https://files.pythonhosted.org/packages/89/c5/adb8c8b3d6625bef6d88b251bbb0d95f8205831b987631ab0c8bb5d937c2/charset_normalizer-3.4.4-cp313-cp313-manylinux2014_armv7l.manylinux_2_17_armv7l.manylinux_2_31_armv7l.whl", hash = "sha256:3162d5d8ce1bb98dd51af660f2121c55d0fa541b46dff7bb9b9f86ea1d87de72", size = 144180, upload-time = "2025-10-14T04:41:15.588Z" }, + { url = "https://files.pythonhosted.org/packages/91/ed/9706e4070682d1cc219050b6048bfd293ccf67b3d4f5a4f39207453d4b99/charset_normalizer-3.4.4-cp313-cp313-manylinux2014_ppc64le.manylinux_2_17_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:81d5eb2a312700f4ecaa977a8235b634ce853200e828fbadf3a9c50bab278328", size = 161346, upload-time = "2025-10-14T04:41:16.738Z" }, + { url = "https://files.pythonhosted.org/packages/d5/0d/031f0d95e4972901a2f6f09ef055751805ff541511dc1252ba3ca1f80cf5/charset_normalizer-3.4.4-cp313-cp313-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:5bd2293095d766545ec1a8f612559f6b40abc0eb18bb2f5d1171872d34036ede", size = 158874, upload-time = "2025-10-14T04:41:17.923Z" }, + { url = "https://files.pythonhosted.org/packages/f5/83/6ab5883f57c9c801ce5e5677242328aa45592be8a00644310a008d04f922/charset_normalizer-3.4.4-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:a8a8b89589086a25749f471e6a900d3f662d1d3b6e2e59dcecf787b1cc3a1894", size = 153076, upload-time = "2025-10-14T04:41:19.106Z" }, + { url = "https://files.pythonhosted.org/packages/75/1e/5ff781ddf5260e387d6419959ee89ef13878229732732ee73cdae01800f2/charset_normalizer-3.4.4-cp313-cp313-manylinux_2_31_riscv64.manylinux_2_39_riscv64.whl", hash = "sha256:bc7637e2f80d8530ee4a78e878bce464f70087ce73cf7c1caf142416923b98f1", size = 150601, upload-time = "2025-10-14T04:41:20.245Z" }, + { url = "https://files.pythonhosted.org/packages/d7/57/71be810965493d3510a6ca79b90c19e48696fb1ff964da319334b12677f0/charset_normalizer-3.4.4-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:f8bf04158c6b607d747e93949aa60618b61312fe647a6369f88ce2ff16043490", size = 150376, upload-time = "2025-10-14T04:41:21.398Z" }, + { url = "https://files.pythonhosted.org/packages/e5/d5/c3d057a78c181d007014feb7e9f2e65905a6c4ef182c0ddf0de2924edd65/charset_normalizer-3.4.4-cp313-cp313-musllinux_1_2_armv7l.whl", hash = "sha256:554af85e960429cf30784dd47447d5125aaa3b99a6f0683589dbd27e2f45da44", size = 144825, upload-time = "2025-10-14T04:41:22.583Z" }, + { url = "https://files.pythonhosted.org/packages/e6/8c/d0406294828d4976f275ffbe66f00266c4b3136b7506941d87c00cab5272/charset_normalizer-3.4.4-cp313-cp313-musllinux_1_2_ppc64le.whl", hash = "sha256:74018750915ee7ad843a774364e13a3db91682f26142baddf775342c3f5b1133", size = 162583, upload-time = "2025-10-14T04:41:23.754Z" }, + { url = "https://files.pythonhosted.org/packages/d7/24/e2aa1f18c8f15c4c0e932d9287b8609dd30ad56dbe41d926bd846e22fb8d/charset_normalizer-3.4.4-cp313-cp313-musllinux_1_2_riscv64.whl", hash = "sha256:c0463276121fdee9c49b98908b3a89c39be45d86d1dbaa22957e38f6321d4ce3", size = 150366, upload-time = "2025-10-14T04:41:25.27Z" }, + { url = "https://files.pythonhosted.org/packages/e4/5b/1e6160c7739aad1e2df054300cc618b06bf784a7a164b0f238360721ab86/charset_normalizer-3.4.4-cp313-cp313-musllinux_1_2_s390x.whl", hash = "sha256:362d61fd13843997c1c446760ef36f240cf81d3ebf74ac62652aebaf7838561e", size = 160300, upload-time = "2025-10-14T04:41:26.725Z" }, + { url = "https://files.pythonhosted.org/packages/7a/10/f882167cd207fbdd743e55534d5d9620e095089d176d55cb22d5322f2afd/charset_normalizer-3.4.4-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:9a26f18905b8dd5d685d6d07b0cdf98a79f3c7a918906af7cc143ea2e164c8bc", size = 154465, upload-time = "2025-10-14T04:41:28.322Z" }, + { url = "https://files.pythonhosted.org/packages/89/66/c7a9e1b7429be72123441bfdbaf2bc13faab3f90b933f664db506dea5915/charset_normalizer-3.4.4-cp313-cp313-win32.whl", hash = "sha256:9b35f4c90079ff2e2edc5b26c0c77925e5d2d255c42c74fdb70fb49b172726ac", size = 99404, upload-time = "2025-10-14T04:41:29.95Z" }, + { url = "https://files.pythonhosted.org/packages/c4/26/b9924fa27db384bdcd97ab83b4f0a8058d96ad9626ead570674d5e737d90/charset_normalizer-3.4.4-cp313-cp313-win_amd64.whl", hash = "sha256:b435cba5f4f750aa6c0a0d92c541fb79f69a387c91e61f1795227e4ed9cece14", size = 107092, upload-time = "2025-10-14T04:41:31.188Z" }, + { url = "https://files.pythonhosted.org/packages/af/8f/3ed4bfa0c0c72a7ca17f0380cd9e4dd842b09f664e780c13cff1dcf2ef1b/charset_normalizer-3.4.4-cp313-cp313-win_arm64.whl", hash = "sha256:542d2cee80be6f80247095cc36c418f7bddd14f4a6de45af91dfad36d817bba2", size = 100408, upload-time = "2025-10-14T04:41:32.624Z" }, + { url = "https://files.pythonhosted.org/packages/2a/35/7051599bd493e62411d6ede36fd5af83a38f37c4767b92884df7301db25d/charset_normalizer-3.4.4-cp314-cp314-macosx_10_13_universal2.whl", hash = "sha256:da3326d9e65ef63a817ecbcc0df6e94463713b754fe293eaa03da99befb9a5bd", size = 207746, upload-time = "2025-10-14T04:41:33.773Z" }, + { url = "https://files.pythonhosted.org/packages/10/9a/97c8d48ef10d6cd4fcead2415523221624bf58bcf68a802721a6bc807c8f/charset_normalizer-3.4.4-cp314-cp314-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:8af65f14dc14a79b924524b1e7fffe304517b2bff5a58bf64f30b98bbc5079eb", size = 147889, upload-time = "2025-10-14T04:41:34.897Z" }, + { url = "https://files.pythonhosted.org/packages/10/bf/979224a919a1b606c82bd2c5fa49b5c6d5727aa47b4312bb27b1734f53cd/charset_normalizer-3.4.4-cp314-cp314-manylinux2014_armv7l.manylinux_2_17_armv7l.manylinux_2_31_armv7l.whl", hash = "sha256:74664978bb272435107de04e36db5a9735e78232b85b77d45cfb38f758efd33e", size = 143641, upload-time = "2025-10-14T04:41:36.116Z" }, + { url = "https://files.pythonhosted.org/packages/ba/33/0ad65587441fc730dc7bd90e9716b30b4702dc7b617e6ba4997dc8651495/charset_normalizer-3.4.4-cp314-cp314-manylinux2014_ppc64le.manylinux_2_17_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:752944c7ffbfdd10c074dc58ec2d5a8a4cd9493b314d367c14d24c17684ddd14", size = 160779, upload-time = "2025-10-14T04:41:37.229Z" }, + { url = "https://files.pythonhosted.org/packages/67/ed/331d6b249259ee71ddea93f6f2f0a56cfebd46938bde6fcc6f7b9a3d0e09/charset_normalizer-3.4.4-cp314-cp314-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:d1f13550535ad8cff21b8d757a3257963e951d96e20ec82ab44bc64aeb62a191", size = 159035, upload-time = "2025-10-14T04:41:38.368Z" }, + { url = "https://files.pythonhosted.org/packages/67/ff/f6b948ca32e4f2a4576aa129d8bed61f2e0543bf9f5f2b7fc3758ed005c9/charset_normalizer-3.4.4-cp314-cp314-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:ecaae4149d99b1c9e7b88bb03e3221956f68fd6d50be2ef061b2381b61d20838", size = 152542, upload-time = "2025-10-14T04:41:39.862Z" }, + { url = "https://files.pythonhosted.org/packages/16/85/276033dcbcc369eb176594de22728541a925b2632f9716428c851b149e83/charset_normalizer-3.4.4-cp314-cp314-manylinux_2_31_riscv64.manylinux_2_39_riscv64.whl", hash = "sha256:cb6254dc36b47a990e59e1068afacdcd02958bdcce30bb50cc1700a8b9d624a6", size = 149524, upload-time = "2025-10-14T04:41:41.319Z" }, + { url = "https://files.pythonhosted.org/packages/9e/f2/6a2a1f722b6aba37050e626530a46a68f74e63683947a8acff92569f979a/charset_normalizer-3.4.4-cp314-cp314-musllinux_1_2_aarch64.whl", hash = "sha256:c8ae8a0f02f57a6e61203a31428fa1d677cbe50c93622b4149d5c0f319c1d19e", size = 150395, upload-time = "2025-10-14T04:41:42.539Z" }, + { url = "https://files.pythonhosted.org/packages/60/bb/2186cb2f2bbaea6338cad15ce23a67f9b0672929744381e28b0592676824/charset_normalizer-3.4.4-cp314-cp314-musllinux_1_2_armv7l.whl", hash = "sha256:47cc91b2f4dd2833fddaedd2893006b0106129d4b94fdb6af1f4ce5a9965577c", size = 143680, upload-time = "2025-10-14T04:41:43.661Z" }, + { url = "https://files.pythonhosted.org/packages/7d/a5/bf6f13b772fbb2a90360eb620d52ed8f796f3c5caee8398c3b2eb7b1c60d/charset_normalizer-3.4.4-cp314-cp314-musllinux_1_2_ppc64le.whl", hash = "sha256:82004af6c302b5d3ab2cfc4cc5f29db16123b1a8417f2e25f9066f91d4411090", size = 162045, upload-time = "2025-10-14T04:41:44.821Z" }, + { url = "https://files.pythonhosted.org/packages/df/c5/d1be898bf0dc3ef9030c3825e5d3b83f2c528d207d246cbabe245966808d/charset_normalizer-3.4.4-cp314-cp314-musllinux_1_2_riscv64.whl", hash = "sha256:2b7d8f6c26245217bd2ad053761201e9f9680f8ce52f0fcd8d0755aeae5b2152", size = 149687, upload-time = "2025-10-14T04:41:46.442Z" }, + { url = "https://files.pythonhosted.org/packages/a5/42/90c1f7b9341eef50c8a1cb3f098ac43b0508413f33affd762855f67a410e/charset_normalizer-3.4.4-cp314-cp314-musllinux_1_2_s390x.whl", hash = "sha256:799a7a5e4fb2d5898c60b640fd4981d6a25f1c11790935a44ce38c54e985f828", size = 160014, upload-time = "2025-10-14T04:41:47.631Z" }, + { url = "https://files.pythonhosted.org/packages/76/be/4d3ee471e8145d12795ab655ece37baed0929462a86e72372fd25859047c/charset_normalizer-3.4.4-cp314-cp314-musllinux_1_2_x86_64.whl", hash = "sha256:99ae2cffebb06e6c22bdc25801d7b30f503cc87dbd283479e7b606f70aff57ec", size = 154044, upload-time = "2025-10-14T04:41:48.81Z" }, + { url = "https://files.pythonhosted.org/packages/b0/6f/8f7af07237c34a1defe7defc565a9bc1807762f672c0fde711a4b22bf9c0/charset_normalizer-3.4.4-cp314-cp314-win32.whl", hash = "sha256:f9d332f8c2a2fcbffe1378594431458ddbef721c1769d78e2cbc06280d8155f9", size = 99940, upload-time = "2025-10-14T04:41:49.946Z" }, + { url = "https://files.pythonhosted.org/packages/4b/51/8ade005e5ca5b0d80fb4aff72a3775b325bdc3d27408c8113811a7cbe640/charset_normalizer-3.4.4-cp314-cp314-win_amd64.whl", hash = "sha256:8a6562c3700cce886c5be75ade4a5db4214fda19fede41d9792d100288d8f94c", size = 107104, upload-time = "2025-10-14T04:41:51.051Z" }, + { url = "https://files.pythonhosted.org/packages/da/5f/6b8f83a55bb8278772c5ae54a577f3099025f9ade59d0136ac24a0df4bde/charset_normalizer-3.4.4-cp314-cp314-win_arm64.whl", hash = "sha256:de00632ca48df9daf77a2c65a484531649261ec9f25489917f09e455cb09ddb2", size = 100743, upload-time = "2025-10-14T04:41:52.122Z" }, + { url = "https://files.pythonhosted.org/packages/0a/4c/925909008ed5a988ccbb72dcc897407e5d6d3bd72410d69e051fc0c14647/charset_normalizer-3.4.4-py3-none-any.whl", hash = "sha256:7a32c560861a02ff789ad905a2fe94e3f840803362c84fecf1851cb4cf3dc37f", size = 53402, upload-time = "2025-10-14T04:42:31.76Z" }, +] + +[[package]] +name = "colorama" +version = "0.4.6" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/d8/53/6f443c9a4a8358a93a6792e2acffb9d9d5cb0a5cfd8802644b7b1c9a02e4/colorama-0.4.6.tar.gz", hash = "sha256:08695f5cb7ed6e0531a20572697297273c47b8cae5a63ffc6d6ed5c201be6e44", size = 27697, upload-time = "2022-10-25T02:36:22.414Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/d1/d6/3965ed04c63042e047cb6a3e6ed1a63a35087b6a609aa3a15ed8ac56c221/colorama-0.4.6-py2.py3-none-any.whl", hash = "sha256:4f1d9991f5acc0ca119f9d443620b77f9d6b33703e51011c16baf57afb285fc6", size = 25335, upload-time = "2022-10-25T02:36:20.889Z" }, +] + +[[package]] +name = "comm" +version = "0.2.3" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/4c/13/7d740c5849255756bc17888787313b61fd38a0a8304fc4f073dfc46122aa/comm-0.2.3.tar.gz", hash = "sha256:2dc8048c10962d55d7ad693be1e7045d891b7ce8d999c97963a5e3e99c055971", size = 6319, upload-time = "2025-07-25T14:02:04.452Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/60/97/891a0971e1e4a8c5d2b20bbe0e524dc04548d2307fee33cdeba148fd4fc7/comm-0.2.3-py3-none-any.whl", hash = "sha256:c615d91d75f7f04f095b30d1c1711babd43bdc6419c1be9886a85f2f4e489417", size = 7294, upload-time = "2025-07-25T14:02:02.896Z" }, +] + +[[package]] +name = "contourpy" +version = "1.3.3" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "numpy" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/58/01/1253e6698a07380cd31a736d248a3f2a50a7c88779a1813da27503cadc2a/contourpy-1.3.3.tar.gz", hash = "sha256:083e12155b210502d0bca491432bb04d56dc3432f95a979b429f2848c3dbe880", size = 13466174, upload-time = "2025-07-26T12:03:12.549Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/91/2e/c4390a31919d8a78b90e8ecf87cd4b4c4f05a5b48d05ec17db8e5404c6f4/contourpy-1.3.3-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:709a48ef9a690e1343202916450bc48b9e51c049b089c7f79a267b46cffcdaa1", size = 288773, upload-time = "2025-07-26T12:01:02.277Z" }, + { url = "https://files.pythonhosted.org/packages/0d/44/c4b0b6095fef4dc9c420e041799591e3b63e9619e3044f7f4f6c21c0ab24/contourpy-1.3.3-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:23416f38bfd74d5d28ab8429cc4d63fa67d5068bd711a85edb1c3fb0c3e2f381", size = 270149, upload-time = "2025-07-26T12:01:04.072Z" }, + { url = "https://files.pythonhosted.org/packages/30/2e/dd4ced42fefac8470661d7cb7e264808425e6c5d56d175291e93890cce09/contourpy-1.3.3-cp311-cp311-manylinux_2_26_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:929ddf8c4c7f348e4c0a5a3a714b5c8542ffaa8c22954862a46ca1813b667ee7", size = 329222, upload-time = "2025-07-26T12:01:05.688Z" }, + { url = "https://files.pythonhosted.org/packages/f2/74/cc6ec2548e3d276c71389ea4802a774b7aa3558223b7bade3f25787fafc2/contourpy-1.3.3-cp311-cp311-manylinux_2_26_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:9e999574eddae35f1312c2b4b717b7885d4edd6cb46700e04f7f02db454e67c1", size = 377234, upload-time = "2025-07-26T12:01:07.054Z" }, + { url = "https://files.pythonhosted.org/packages/03/b3/64ef723029f917410f75c09da54254c5f9ea90ef89b143ccadb09df14c15/contourpy-1.3.3-cp311-cp311-manylinux_2_26_s390x.manylinux_2_28_s390x.whl", hash = "sha256:0bf67e0e3f482cb69779dd3061b534eb35ac9b17f163d851e2a547d56dba0a3a", size = 380555, upload-time = "2025-07-26T12:01:08.801Z" }, + { url = "https://files.pythonhosted.org/packages/5f/4b/6157f24ca425b89fe2eb7e7be642375711ab671135be21e6faa100f7448c/contourpy-1.3.3-cp311-cp311-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:51e79c1f7470158e838808d4a996fa9bac72c498e93d8ebe5119bc1e6becb0db", size = 355238, upload-time = "2025-07-26T12:01:10.319Z" }, + { url = "https://files.pythonhosted.org/packages/98/56/f914f0dd678480708a04cfd2206e7c382533249bc5001eb9f58aa693e200/contourpy-1.3.3-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:598c3aaece21c503615fd59c92a3598b428b2f01bfb4b8ca9c4edeecc2438620", size = 1326218, upload-time = "2025-07-26T12:01:12.659Z" }, + { url = "https://files.pythonhosted.org/packages/fb/d7/4a972334a0c971acd5172389671113ae82aa7527073980c38d5868ff1161/contourpy-1.3.3-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:322ab1c99b008dad206d406bb61d014cf0174df491ae9d9d0fac6a6fda4f977f", size = 1392867, upload-time = "2025-07-26T12:01:15.533Z" }, + { url = "https://files.pythonhosted.org/packages/75/3e/f2cc6cd56dc8cff46b1a56232eabc6feea52720083ea71ab15523daab796/contourpy-1.3.3-cp311-cp311-win32.whl", hash = "sha256:fd907ae12cd483cd83e414b12941c632a969171bf90fc937d0c9f268a31cafff", size = 183677, upload-time = "2025-07-26T12:01:17.088Z" }, + { url = "https://files.pythonhosted.org/packages/98/4b/9bd370b004b5c9d8045c6c33cf65bae018b27aca550a3f657cdc99acdbd8/contourpy-1.3.3-cp311-cp311-win_amd64.whl", hash = "sha256:3519428f6be58431c56581f1694ba8e50626f2dd550af225f82fb5f5814d2a42", size = 225234, upload-time = "2025-07-26T12:01:18.256Z" }, + { url = "https://files.pythonhosted.org/packages/d9/b6/71771e02c2e004450c12b1120a5f488cad2e4d5b590b1af8bad060360fe4/contourpy-1.3.3-cp311-cp311-win_arm64.whl", hash = "sha256:15ff10bfada4bf92ec8b31c62bf7c1834c244019b4a33095a68000d7075df470", size = 193123, upload-time = "2025-07-26T12:01:19.848Z" }, + { url = "https://files.pythonhosted.org/packages/be/45/adfee365d9ea3d853550b2e735f9d66366701c65db7855cd07621732ccfc/contourpy-1.3.3-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:b08a32ea2f8e42cf1d4be3169a98dd4be32bafe4f22b6c4cb4ba810fa9e5d2cb", size = 293419, upload-time = "2025-07-26T12:01:21.16Z" }, + { url = "https://files.pythonhosted.org/packages/53/3e/405b59cfa13021a56bba395a6b3aca8cec012b45bf177b0eaf7a202cde2c/contourpy-1.3.3-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:556dba8fb6f5d8742f2923fe9457dbdd51e1049c4a43fd3986a0b14a1d815fc6", size = 273979, upload-time = "2025-07-26T12:01:22.448Z" }, + { url = "https://files.pythonhosted.org/packages/d4/1c/a12359b9b2ca3a845e8f7f9ac08bdf776114eb931392fcad91743e2ea17b/contourpy-1.3.3-cp312-cp312-manylinux_2_26_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:92d9abc807cf7d0e047b95ca5d957cf4792fcd04e920ca70d48add15c1a90ea7", size = 332653, upload-time = "2025-07-26T12:01:24.155Z" }, + { url = "https://files.pythonhosted.org/packages/63/12/897aeebfb475b7748ea67b61e045accdfcf0d971f8a588b67108ed7f5512/contourpy-1.3.3-cp312-cp312-manylinux_2_26_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:b2e8faa0ed68cb29af51edd8e24798bb661eac3bd9f65420c1887b6ca89987c8", size = 379536, upload-time = "2025-07-26T12:01:25.91Z" }, + { url = "https://files.pythonhosted.org/packages/43/8a/a8c584b82deb248930ce069e71576fc09bd7174bbd35183b7943fb1064fd/contourpy-1.3.3-cp312-cp312-manylinux_2_26_s390x.manylinux_2_28_s390x.whl", hash = "sha256:626d60935cf668e70a5ce6ff184fd713e9683fb458898e4249b63be9e28286ea", size = 384397, upload-time = "2025-07-26T12:01:27.152Z" }, + { url = "https://files.pythonhosted.org/packages/cc/8f/ec6289987824b29529d0dfda0d74a07cec60e54b9c92f3c9da4c0ac732de/contourpy-1.3.3-cp312-cp312-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:4d00e655fcef08aba35ec9610536bfe90267d7ab5ba944f7032549c55a146da1", size = 362601, upload-time = "2025-07-26T12:01:28.808Z" }, + { url = "https://files.pythonhosted.org/packages/05/0a/a3fe3be3ee2dceb3e615ebb4df97ae6f3828aa915d3e10549ce016302bd1/contourpy-1.3.3-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:451e71b5a7d597379ef572de31eeb909a87246974d960049a9848c3bc6c41bf7", size = 1331288, upload-time = "2025-07-26T12:01:31.198Z" }, + { url = "https://files.pythonhosted.org/packages/33/1d/acad9bd4e97f13f3e2b18a3977fe1b4a37ecf3d38d815333980c6c72e963/contourpy-1.3.3-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:459c1f020cd59fcfe6650180678a9993932d80d44ccde1fa1868977438f0b411", size = 1403386, upload-time = "2025-07-26T12:01:33.947Z" }, + { url = "https://files.pythonhosted.org/packages/cf/8f/5847f44a7fddf859704217a99a23a4f6417b10e5ab1256a179264561540e/contourpy-1.3.3-cp312-cp312-win32.whl", hash = "sha256:023b44101dfe49d7d53932be418477dba359649246075c996866106da069af69", size = 185018, upload-time = "2025-07-26T12:01:35.64Z" }, + { url = "https://files.pythonhosted.org/packages/19/e8/6026ed58a64563186a9ee3f29f41261fd1828f527dd93d33b60feca63352/contourpy-1.3.3-cp312-cp312-win_amd64.whl", hash = "sha256:8153b8bfc11e1e4d75bcb0bff1db232f9e10b274e0929de9d608027e0d34ff8b", size = 226567, upload-time = "2025-07-26T12:01:36.804Z" }, + { url = "https://files.pythonhosted.org/packages/d1/e2/f05240d2c39a1ed228d8328a78b6f44cd695f7ef47beb3e684cf93604f86/contourpy-1.3.3-cp312-cp312-win_arm64.whl", hash = "sha256:07ce5ed73ecdc4a03ffe3e1b3e3c1166db35ae7584be76f65dbbe28a7791b0cc", size = 193655, upload-time = "2025-07-26T12:01:37.999Z" }, + { url = "https://files.pythonhosted.org/packages/68/35/0167aad910bbdb9599272bd96d01a9ec6852f36b9455cf2ca67bd4cc2d23/contourpy-1.3.3-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:177fb367556747a686509d6fef71d221a4b198a3905fe824430e5ea0fda54eb5", size = 293257, upload-time = "2025-07-26T12:01:39.367Z" }, + { url = "https://files.pythonhosted.org/packages/96/e4/7adcd9c8362745b2210728f209bfbcf7d91ba868a2c5f40d8b58f54c509b/contourpy-1.3.3-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:d002b6f00d73d69333dac9d0b8d5e84d9724ff9ef044fd63c5986e62b7c9e1b1", size = 274034, upload-time = "2025-07-26T12:01:40.645Z" }, + { url = "https://files.pythonhosted.org/packages/73/23/90e31ceeed1de63058a02cb04b12f2de4b40e3bef5e082a7c18d9c8ae281/contourpy-1.3.3-cp313-cp313-manylinux_2_26_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:348ac1f5d4f1d66d3322420f01d42e43122f43616e0f194fc1c9f5d830c5b286", size = 334672, upload-time = "2025-07-26T12:01:41.942Z" }, + { url = "https://files.pythonhosted.org/packages/ed/93/b43d8acbe67392e659e1d984700e79eb67e2acb2bd7f62012b583a7f1b55/contourpy-1.3.3-cp313-cp313-manylinux_2_26_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:655456777ff65c2c548b7c454af9c6f33f16c8884f11083244b5819cc214f1b5", size = 381234, upload-time = "2025-07-26T12:01:43.499Z" }, + { url = "https://files.pythonhosted.org/packages/46/3b/bec82a3ea06f66711520f75a40c8fc0b113b2a75edb36aa633eb11c4f50f/contourpy-1.3.3-cp313-cp313-manylinux_2_26_s390x.manylinux_2_28_s390x.whl", hash = "sha256:644a6853d15b2512d67881586bd03f462c7ab755db95f16f14d7e238f2852c67", size = 385169, upload-time = "2025-07-26T12:01:45.219Z" }, + { url = "https://files.pythonhosted.org/packages/4b/32/e0f13a1c5b0f8572d0ec6ae2f6c677b7991fafd95da523159c19eff0696a/contourpy-1.3.3-cp313-cp313-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:4debd64f124ca62069f313a9cb86656ff087786016d76927ae2cf37846b006c9", size = 362859, upload-time = "2025-07-26T12:01:46.519Z" }, + { url = "https://files.pythonhosted.org/packages/33/71/e2a7945b7de4e58af42d708a219f3b2f4cff7386e6b6ab0a0fa0033c49a9/contourpy-1.3.3-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:a15459b0f4615b00bbd1e91f1b9e19b7e63aea7483d03d804186f278c0af2659", size = 1332062, upload-time = "2025-07-26T12:01:48.964Z" }, + { url = "https://files.pythonhosted.org/packages/12/fc/4e87ac754220ccc0e807284f88e943d6d43b43843614f0a8afa469801db0/contourpy-1.3.3-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:ca0fdcd73925568ca027e0b17ab07aad764be4706d0a925b89227e447d9737b7", size = 1403932, upload-time = "2025-07-26T12:01:51.979Z" }, + { url = "https://files.pythonhosted.org/packages/a6/2e/adc197a37443f934594112222ac1aa7dc9a98faf9c3842884df9a9d8751d/contourpy-1.3.3-cp313-cp313-win32.whl", hash = "sha256:b20c7c9a3bf701366556e1b1984ed2d0cedf999903c51311417cf5f591d8c78d", size = 185024, upload-time = "2025-07-26T12:01:53.245Z" }, + { url = "https://files.pythonhosted.org/packages/18/0b/0098c214843213759692cc638fce7de5c289200a830e5035d1791d7a2338/contourpy-1.3.3-cp313-cp313-win_amd64.whl", hash = "sha256:1cadd8b8969f060ba45ed7c1b714fe69185812ab43bd6b86a9123fe8f99c3263", size = 226578, upload-time = "2025-07-26T12:01:54.422Z" }, + { url = "https://files.pythonhosted.org/packages/8a/9a/2f6024a0c5995243cd63afdeb3651c984f0d2bc727fd98066d40e141ad73/contourpy-1.3.3-cp313-cp313-win_arm64.whl", hash = "sha256:fd914713266421b7536de2bfa8181aa8c699432b6763a0ea64195ebe28bff6a9", size = 193524, upload-time = "2025-07-26T12:01:55.73Z" }, + { url = "https://files.pythonhosted.org/packages/c0/b3/f8a1a86bd3298513f500e5b1f5fd92b69896449f6cab6a146a5d52715479/contourpy-1.3.3-cp313-cp313t-macosx_10_13_x86_64.whl", hash = "sha256:88df9880d507169449d434c293467418b9f6cbe82edd19284aa0409e7fdb933d", size = 306730, upload-time = "2025-07-26T12:01:57.051Z" }, + { url = "https://files.pythonhosted.org/packages/3f/11/4780db94ae62fc0c2053909b65dc3246bd7cecfc4f8a20d957ad43aa4ad8/contourpy-1.3.3-cp313-cp313t-macosx_11_0_arm64.whl", hash = "sha256:d06bb1f751ba5d417047db62bca3c8fde202b8c11fb50742ab3ab962c81e8216", size = 287897, upload-time = "2025-07-26T12:01:58.663Z" }, + { url = "https://files.pythonhosted.org/packages/ae/15/e59f5f3ffdd6f3d4daa3e47114c53daabcb18574a26c21f03dc9e4e42ff0/contourpy-1.3.3-cp313-cp313t-manylinux_2_26_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:e4e6b05a45525357e382909a4c1600444e2a45b4795163d3b22669285591c1ae", size = 326751, upload-time = "2025-07-26T12:02:00.343Z" }, + { url = "https://files.pythonhosted.org/packages/0f/81/03b45cfad088e4770b1dcf72ea78d3802d04200009fb364d18a493857210/contourpy-1.3.3-cp313-cp313t-manylinux_2_26_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:ab3074b48c4e2cf1a960e6bbeb7f04566bf36b1861d5c9d4d8ac04b82e38ba20", size = 375486, upload-time = "2025-07-26T12:02:02.128Z" }, + { url = "https://files.pythonhosted.org/packages/0c/ba/49923366492ffbdd4486e970d421b289a670ae8cf539c1ea9a09822b371a/contourpy-1.3.3-cp313-cp313t-manylinux_2_26_s390x.manylinux_2_28_s390x.whl", hash = "sha256:6c3d53c796f8647d6deb1abe867daeb66dcc8a97e8455efa729516b997b8ed99", size = 388106, upload-time = "2025-07-26T12:02:03.615Z" }, + { url = "https://files.pythonhosted.org/packages/9f/52/5b00ea89525f8f143651f9f03a0df371d3cbd2fccd21ca9b768c7a6500c2/contourpy-1.3.3-cp313-cp313t-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:50ed930df7289ff2a8d7afeb9603f8289e5704755c7e5c3bbd929c90c817164b", size = 352548, upload-time = "2025-07-26T12:02:05.165Z" }, + { url = "https://files.pythonhosted.org/packages/32/1d/a209ec1a3a3452d490f6b14dd92e72280c99ae3d1e73da74f8277d4ee08f/contourpy-1.3.3-cp313-cp313t-musllinux_1_2_aarch64.whl", hash = "sha256:4feffb6537d64b84877da813a5c30f1422ea5739566abf0bd18065ac040e120a", size = 1322297, upload-time = "2025-07-26T12:02:07.379Z" }, + { url = "https://files.pythonhosted.org/packages/bc/9e/46f0e8ebdd884ca0e8877e46a3f4e633f6c9c8c4f3f6e72be3fe075994aa/contourpy-1.3.3-cp313-cp313t-musllinux_1_2_x86_64.whl", hash = "sha256:2b7e9480ffe2b0cd2e787e4df64270e3a0440d9db8dc823312e2c940c167df7e", size = 1391023, upload-time = "2025-07-26T12:02:10.171Z" }, + { url = "https://files.pythonhosted.org/packages/b9/70/f308384a3ae9cd2209e0849f33c913f658d3326900d0ff5d378d6a1422d2/contourpy-1.3.3-cp313-cp313t-win32.whl", hash = "sha256:283edd842a01e3dcd435b1c5116798d661378d83d36d337b8dde1d16a5fc9ba3", size = 196157, upload-time = "2025-07-26T12:02:11.488Z" }, + { url = "https://files.pythonhosted.org/packages/b2/dd/880f890a6663b84d9e34a6f88cded89d78f0091e0045a284427cb6b18521/contourpy-1.3.3-cp313-cp313t-win_amd64.whl", hash = "sha256:87acf5963fc2b34825e5b6b048f40e3635dd547f590b04d2ab317c2619ef7ae8", size = 240570, upload-time = "2025-07-26T12:02:12.754Z" }, + { url = "https://files.pythonhosted.org/packages/80/99/2adc7d8ffead633234817ef8e9a87115c8a11927a94478f6bb3d3f4d4f7d/contourpy-1.3.3-cp313-cp313t-win_arm64.whl", hash = "sha256:3c30273eb2a55024ff31ba7d052dde990d7d8e5450f4bbb6e913558b3d6c2301", size = 199713, upload-time = "2025-07-26T12:02:14.4Z" }, + { url = "https://files.pythonhosted.org/packages/72/8b/4546f3ab60f78c514ffb7d01a0bd743f90de36f0019d1be84d0a708a580a/contourpy-1.3.3-cp314-cp314-macosx_10_13_x86_64.whl", hash = "sha256:fde6c716d51c04b1c25d0b90364d0be954624a0ee9d60e23e850e8d48353d07a", size = 292189, upload-time = "2025-07-26T12:02:16.095Z" }, + { url = "https://files.pythonhosted.org/packages/fd/e1/3542a9cb596cadd76fcef413f19c79216e002623158befe6daa03dbfa88c/contourpy-1.3.3-cp314-cp314-macosx_11_0_arm64.whl", hash = "sha256:cbedb772ed74ff5be440fa8eee9bd49f64f6e3fc09436d9c7d8f1c287b121d77", size = 273251, upload-time = "2025-07-26T12:02:17.524Z" }, + { url = "https://files.pythonhosted.org/packages/b1/71/f93e1e9471d189f79d0ce2497007731c1e6bf9ef6d1d61b911430c3db4e5/contourpy-1.3.3-cp314-cp314-manylinux_2_26_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:22e9b1bd7a9b1d652cd77388465dc358dafcd2e217d35552424aa4f996f524f5", size = 335810, upload-time = "2025-07-26T12:02:18.9Z" }, + { url = "https://files.pythonhosted.org/packages/91/f9/e35f4c1c93f9275d4e38681a80506b5510e9327350c51f8d4a5a724d178c/contourpy-1.3.3-cp314-cp314-manylinux_2_26_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:a22738912262aa3e254e4f3cb079a95a67132fc5a063890e224393596902f5a4", size = 382871, upload-time = "2025-07-26T12:02:20.418Z" }, + { url = "https://files.pythonhosted.org/packages/b5/71/47b512f936f66a0a900d81c396a7e60d73419868fba959c61efed7a8ab46/contourpy-1.3.3-cp314-cp314-manylinux_2_26_s390x.manylinux_2_28_s390x.whl", hash = "sha256:afe5a512f31ee6bd7d0dda52ec9864c984ca3d66664444f2d72e0dc4eb832e36", size = 386264, upload-time = "2025-07-26T12:02:21.916Z" }, + { url = "https://files.pythonhosted.org/packages/04/5f/9ff93450ba96b09c7c2b3f81c94de31c89f92292f1380261bd7195bea4ea/contourpy-1.3.3-cp314-cp314-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:f64836de09927cba6f79dcd00fdd7d5329f3fccc633468507079c829ca4db4e3", size = 363819, upload-time = "2025-07-26T12:02:23.759Z" }, + { url = "https://files.pythonhosted.org/packages/3e/a6/0b185d4cc480ee494945cde102cb0149ae830b5fa17bf855b95f2e70ad13/contourpy-1.3.3-cp314-cp314-musllinux_1_2_aarch64.whl", hash = "sha256:1fd43c3be4c8e5fd6e4f2baeae35ae18176cf2e5cced681cca908addf1cdd53b", size = 1333650, upload-time = "2025-07-26T12:02:26.181Z" }, + { url = "https://files.pythonhosted.org/packages/43/d7/afdc95580ca56f30fbcd3060250f66cedbde69b4547028863abd8aa3b47e/contourpy-1.3.3-cp314-cp314-musllinux_1_2_x86_64.whl", hash = "sha256:6afc576f7b33cf00996e5c1102dc2a8f7cc89e39c0b55df93a0b78c1bd992b36", size = 1404833, upload-time = "2025-07-26T12:02:28.782Z" }, + { url = "https://files.pythonhosted.org/packages/e2/e2/366af18a6d386f41132a48f033cbd2102e9b0cf6345d35ff0826cd984566/contourpy-1.3.3-cp314-cp314-win32.whl", hash = "sha256:66c8a43a4f7b8df8b71ee1840e4211a3c8d93b214b213f590e18a1beca458f7d", size = 189692, upload-time = "2025-07-26T12:02:30.128Z" }, + { url = "https://files.pythonhosted.org/packages/7d/c2/57f54b03d0f22d4044b8afb9ca0e184f8b1afd57b4f735c2fa70883dc601/contourpy-1.3.3-cp314-cp314-win_amd64.whl", hash = "sha256:cf9022ef053f2694e31d630feaacb21ea24224be1c3ad0520b13d844274614fd", size = 232424, upload-time = "2025-07-26T12:02:31.395Z" }, + { url = "https://files.pythonhosted.org/packages/18/79/a9416650df9b525737ab521aa181ccc42d56016d2123ddcb7b58e926a42c/contourpy-1.3.3-cp314-cp314-win_arm64.whl", hash = "sha256:95b181891b4c71de4bb404c6621e7e2390745f887f2a026b2d99e92c17892339", size = 198300, upload-time = "2025-07-26T12:02:32.956Z" }, + { url = "https://files.pythonhosted.org/packages/1f/42/38c159a7d0f2b7b9c04c64ab317042bb6952b713ba875c1681529a2932fe/contourpy-1.3.3-cp314-cp314t-macosx_10_13_x86_64.whl", hash = "sha256:33c82d0138c0a062380332c861387650c82e4cf1747aaa6938b9b6516762e772", size = 306769, upload-time = "2025-07-26T12:02:34.2Z" }, + { url = "https://files.pythonhosted.org/packages/c3/6c/26a8205f24bca10974e77460de68d3d7c63e282e23782f1239f226fcae6f/contourpy-1.3.3-cp314-cp314t-macosx_11_0_arm64.whl", hash = "sha256:ea37e7b45949df430fe649e5de8351c423430046a2af20b1c1961cae3afcda77", size = 287892, upload-time = "2025-07-26T12:02:35.807Z" }, + { url = "https://files.pythonhosted.org/packages/66/06/8a475c8ab718ebfd7925661747dbb3c3ee9c82ac834ccb3570be49d129f4/contourpy-1.3.3-cp314-cp314t-manylinux_2_26_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:d304906ecc71672e9c89e87c4675dc5c2645e1f4269a5063b99b0bb29f232d13", size = 326748, upload-time = "2025-07-26T12:02:37.193Z" }, + { url = "https://files.pythonhosted.org/packages/b4/a3/c5ca9f010a44c223f098fccd8b158bb1cb287378a31ac141f04730dc49be/contourpy-1.3.3-cp314-cp314t-manylinux_2_26_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:ca658cd1a680a5c9ea96dc61cdbae1e85c8f25849843aa799dfd3cb370ad4fbe", size = 375554, upload-time = "2025-07-26T12:02:38.894Z" }, + { url = "https://files.pythonhosted.org/packages/80/5b/68bd33ae63fac658a4145088c1e894405e07584a316738710b636c6d0333/contourpy-1.3.3-cp314-cp314t-manylinux_2_26_s390x.manylinux_2_28_s390x.whl", hash = "sha256:ab2fd90904c503739a75b7c8c5c01160130ba67944a7b77bbf36ef8054576e7f", size = 388118, upload-time = "2025-07-26T12:02:40.642Z" }, + { url = "https://files.pythonhosted.org/packages/40/52/4c285a6435940ae25d7410a6c36bda5145839bc3f0beb20c707cda18b9d2/contourpy-1.3.3-cp314-cp314t-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:b7301b89040075c30e5768810bc96a8e8d78085b47d8be6e4c3f5a0b4ed478a0", size = 352555, upload-time = "2025-07-26T12:02:42.25Z" }, + { url = "https://files.pythonhosted.org/packages/24/ee/3e81e1dd174f5c7fefe50e85d0892de05ca4e26ef1c9a59c2a57e43b865a/contourpy-1.3.3-cp314-cp314t-musllinux_1_2_aarch64.whl", hash = "sha256:2a2a8b627d5cc6b7c41a4beff6c5ad5eb848c88255fda4a8745f7e901b32d8e4", size = 1322295, upload-time = "2025-07-26T12:02:44.668Z" }, + { url = "https://files.pythonhosted.org/packages/3c/b2/6d913d4d04e14379de429057cd169e5e00f6c2af3bb13e1710bcbdb5da12/contourpy-1.3.3-cp314-cp314t-musllinux_1_2_x86_64.whl", hash = "sha256:fd6ec6be509c787f1caf6b247f0b1ca598bef13f4ddeaa126b7658215529ba0f", size = 1391027, upload-time = "2025-07-26T12:02:47.09Z" }, + { url = "https://files.pythonhosted.org/packages/93/8a/68a4ec5c55a2971213d29a9374913f7e9f18581945a7a31d1a39b5d2dfe5/contourpy-1.3.3-cp314-cp314t-win32.whl", hash = "sha256:e74a9a0f5e3fff48fb5a7f2fd2b9b70a3fe014a67522f79b7cca4c0c7e43c9ae", size = 202428, upload-time = "2025-07-26T12:02:48.691Z" }, + { url = "https://files.pythonhosted.org/packages/fa/96/fd9f641ffedc4fa3ace923af73b9d07e869496c9cc7a459103e6e978992f/contourpy-1.3.3-cp314-cp314t-win_amd64.whl", hash = "sha256:13b68d6a62db8eafaebb8039218921399baf6e47bf85006fd8529f2a08ef33fc", size = 250331, upload-time = "2025-07-26T12:02:50.137Z" }, + { url = "https://files.pythonhosted.org/packages/ae/8c/469afb6465b853afff216f9528ffda78a915ff880ed58813ba4faf4ba0b6/contourpy-1.3.3-cp314-cp314t-win_arm64.whl", hash = "sha256:b7448cb5a725bb1e35ce88771b86fba35ef418952474492cf7c764059933ff8b", size = 203831, upload-time = "2025-07-26T12:02:51.449Z" }, + { url = "https://files.pythonhosted.org/packages/a5/29/8dcfe16f0107943fa92388c23f6e05cff0ba58058c4c95b00280d4c75a14/contourpy-1.3.3-pp311-pypy311_pp73-macosx_10_15_x86_64.whl", hash = "sha256:cd5dfcaeb10f7b7f9dc8941717c6c2ade08f587be2226222c12b25f0483ed497", size = 278809, upload-time = "2025-07-26T12:02:52.74Z" }, + { url = "https://files.pythonhosted.org/packages/85/a9/8b37ef4f7dafeb335daee3c8254645ef5725be4d9c6aa70b50ec46ef2f7e/contourpy-1.3.3-pp311-pypy311_pp73-macosx_11_0_arm64.whl", hash = "sha256:0c1fc238306b35f246d61a1d416a627348b5cf0648648a031e14bb8705fcdfe8", size = 261593, upload-time = "2025-07-26T12:02:54.037Z" }, + { url = "https://files.pythonhosted.org/packages/0a/59/ebfb8c677c75605cc27f7122c90313fd2f375ff3c8d19a1694bda74aaa63/contourpy-1.3.3-pp311-pypy311_pp73-manylinux_2_26_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:70f9aad7de812d6541d29d2bbf8feb22ff7e1c299523db288004e3157ff4674e", size = 302202, upload-time = "2025-07-26T12:02:55.947Z" }, + { url = "https://files.pythonhosted.org/packages/3c/37/21972a15834d90bfbfb009b9d004779bd5a07a0ec0234e5ba8f64d5736f4/contourpy-1.3.3-pp311-pypy311_pp73-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:5ed3657edf08512fc3fe81b510e35c2012fbd3081d2e26160f27ca28affec989", size = 329207, upload-time = "2025-07-26T12:02:57.468Z" }, + { url = "https://files.pythonhosted.org/packages/0c/58/bd257695f39d05594ca4ad60df5bcb7e32247f9951fd09a9b8edb82d1daa/contourpy-1.3.3-pp311-pypy311_pp73-win_amd64.whl", hash = "sha256:3d1a3799d62d45c18bafd41c5fa05120b96a28079f2393af559b843d1a966a77", size = 225315, upload-time = "2025-07-26T12:02:58.801Z" }, +] + +[[package]] +name = "coverage" +version = "7.13.4" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/24/56/95b7e30fa389756cb56630faa728da46a27b8c6eb46f9d557c68fff12b65/coverage-7.13.4.tar.gz", hash = "sha256:e5c8f6ed1e61a8b2dcdf31eb0b9bbf0130750ca79c1c49eb898e2ad86f5ccc91", size = 827239, upload-time = "2026-02-09T12:59:03.86Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/b4/ad/b59e5b451cf7172b8d1043dc0fa718f23aab379bc1521ee13d4bd9bfa960/coverage-7.13.4-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:d490ba50c3f35dd7c17953c68f3270e7ccd1c6642e2d2afe2d8e720b98f5a053", size = 219278, upload-time = "2026-02-09T12:56:31.673Z" }, + { url = "https://files.pythonhosted.org/packages/f1/17/0cb7ca3de72e5f4ef2ec2fa0089beafbcaaaead1844e8b8a63d35173d77d/coverage-7.13.4-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:19bc3c88078789f8ef36acb014d7241961dbf883fd2533d18cb1e7a5b4e28b11", size = 219783, upload-time = "2026-02-09T12:56:33.104Z" }, + { url = "https://files.pythonhosted.org/packages/ab/63/325d8e5b11e0eaf6d0f6a44fad444ae58820929a9b0de943fa377fe73e85/coverage-7.13.4-cp311-cp311-manylinux1_i686.manylinux_2_28_i686.manylinux_2_5_i686.whl", hash = "sha256:3998e5a32e62fdf410c0dbd3115df86297995d6e3429af80b8798aad894ca7aa", size = 250200, upload-time = "2026-02-09T12:56:34.474Z" }, + { url = "https://files.pythonhosted.org/packages/76/53/c16972708cbb79f2942922571a687c52bd109a7bd51175aeb7558dff2236/coverage-7.13.4-cp311-cp311-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl", hash = "sha256:8e264226ec98e01a8e1054314af91ee6cde0eacac4f465cc93b03dbe0bce2fd7", size = 252114, upload-time = "2026-02-09T12:56:35.749Z" }, + { url = "https://files.pythonhosted.org/packages/eb/c2/7ab36d8b8cc412bec9ea2d07c83c48930eb4ba649634ba00cb7e4e0f9017/coverage-7.13.4-cp311-cp311-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:a3aa4e7b9e416774b21797365b358a6e827ffadaaca81b69ee02946852449f00", size = 254220, upload-time = "2026-02-09T12:56:37.796Z" }, + { url = "https://files.pythonhosted.org/packages/d6/4d/cf52c9a3322c89a0e6febdfbc83bb45c0ed3c64ad14081b9503adee702e7/coverage-7.13.4-cp311-cp311-manylinux2014_ppc64le.manylinux_2_17_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:71ca20079dd8f27fcf808817e281e90220475cd75115162218d0e27549f95fef", size = 256164, upload-time = "2026-02-09T12:56:39.016Z" }, + { url = "https://files.pythonhosted.org/packages/78/e9/eb1dd17bd6de8289df3580e967e78294f352a5df8a57ff4671ee5fc3dcd0/coverage-7.13.4-cp311-cp311-manylinux_2_31_riscv64.manylinux_2_39_riscv64.whl", hash = "sha256:e2f25215f1a359ab17320b47bcdaca3e6e6356652e8256f2441e4ef972052903", size = 250325, upload-time = "2026-02-09T12:56:40.668Z" }, + { url = "https://files.pythonhosted.org/packages/71/07/8c1542aa873728f72267c07278c5cc0ec91356daf974df21335ccdb46368/coverage-7.13.4-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:d65b2d373032411e86960604dc4edac91fdfb5dca539461cf2cbe78327d1e64f", size = 251913, upload-time = "2026-02-09T12:56:41.97Z" }, + { url = "https://files.pythonhosted.org/packages/74/d7/c62e2c5e4483a748e27868e4c32ad3daa9bdddbba58e1bc7a15e252baa74/coverage-7.13.4-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:94eb63f9b363180aff17de3e7c8760c3ba94664ea2695c52f10111244d16a299", size = 249974, upload-time = "2026-02-09T12:56:43.323Z" }, + { url = "https://files.pythonhosted.org/packages/98/9f/4c5c015a6e98ced54efd0f5cf8d31b88e5504ecb6857585fc0161bb1e600/coverage-7.13.4-cp311-cp311-musllinux_1_2_ppc64le.whl", hash = "sha256:e856bf6616714c3a9fbc270ab54103f4e685ba236fa98c054e8f87f266c93505", size = 253741, upload-time = "2026-02-09T12:56:45.155Z" }, + { url = "https://files.pythonhosted.org/packages/bd/59/0f4eef89b9f0fcd9633b5d350016f54126ab49426a70ff4c4e87446cabdc/coverage-7.13.4-cp311-cp311-musllinux_1_2_riscv64.whl", hash = "sha256:65dfcbe305c3dfe658492df2d85259e0d79ead4177f9ae724b6fb245198f55d6", size = 249695, upload-time = "2026-02-09T12:56:46.636Z" }, + { url = "https://files.pythonhosted.org/packages/b5/2c/b7476f938deb07166f3eb281a385c262675d688ff4659ad56c6c6b8e2e70/coverage-7.13.4-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:b507778ae8a4c915436ed5c2e05b4a6cecfa70f734e19c22a005152a11c7b6a9", size = 250599, upload-time = "2026-02-09T12:56:48.13Z" }, + { url = "https://files.pythonhosted.org/packages/b8/34/c3420709d9846ee3785b9f2831b4d94f276f38884032dca1457fa83f7476/coverage-7.13.4-cp311-cp311-win32.whl", hash = "sha256:784fc3cf8be001197b652d51d3fd259b1e2262888693a4636e18879f613a62a9", size = 221780, upload-time = "2026-02-09T12:56:50.479Z" }, + { url = "https://files.pythonhosted.org/packages/61/08/3d9c8613079d2b11c185b865de9a4c1a68850cfda2b357fae365cf609f29/coverage-7.13.4-cp311-cp311-win_amd64.whl", hash = "sha256:2421d591f8ca05b308cf0092807308b2facbefe54af7c02ac22548b88b95c98f", size = 222715, upload-time = "2026-02-09T12:56:51.815Z" }, + { url = "https://files.pythonhosted.org/packages/18/1a/54c3c80b2f056164cc0a6cdcb040733760c7c4be9d780fe655f356f433e4/coverage-7.13.4-cp311-cp311-win_arm64.whl", hash = "sha256:79e73a76b854d9c6088fe5d8b2ebe745f8681c55f7397c3c0a016192d681045f", size = 221385, upload-time = "2026-02-09T12:56:53.194Z" }, + { url = "https://files.pythonhosted.org/packages/d1/81/4ce2fdd909c5a0ed1f6dedb88aa57ab79b6d1fbd9b588c1ac7ef45659566/coverage-7.13.4-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:02231499b08dabbe2b96612993e5fc34217cdae907a51b906ac7fca8027a4459", size = 219449, upload-time = "2026-02-09T12:56:54.889Z" }, + { url = "https://files.pythonhosted.org/packages/5d/96/5238b1efc5922ddbdc9b0db9243152c09777804fb7c02ad1741eb18a11c0/coverage-7.13.4-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:40aa8808140e55dc022b15d8aa7f651b6b3d68b365ea0398f1441e0b04d859c3", size = 219810, upload-time = "2026-02-09T12:56:56.33Z" }, + { url = "https://files.pythonhosted.org/packages/78/72/2f372b726d433c9c35e56377cf1d513b4c16fe51841060d826b95caacec1/coverage-7.13.4-cp312-cp312-manylinux1_i686.manylinux_2_28_i686.manylinux_2_5_i686.whl", hash = "sha256:5b856a8ccf749480024ff3bd7310adaef57bf31fd17e1bfc404b7940b6986634", size = 251308, upload-time = "2026-02-09T12:56:57.858Z" }, + { url = "https://files.pythonhosted.org/packages/5d/a0/2ea570925524ef4e00bb6c82649f5682a77fac5ab910a65c9284de422600/coverage-7.13.4-cp312-cp312-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl", hash = "sha256:2c048ea43875fbf8b45d476ad79f179809c590ec7b79e2035c662e7afa3192e3", size = 254052, upload-time = "2026-02-09T12:56:59.754Z" }, + { url = "https://files.pythonhosted.org/packages/e8/ac/45dc2e19a1939098d783c846e130b8f862fbb50d09e0af663988f2f21973/coverage-7.13.4-cp312-cp312-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:b7b38448866e83176e28086674fe7368ab8590e4610fb662b44e345b86d63ffa", size = 255165, upload-time = "2026-02-09T12:57:01.287Z" }, + { url = "https://files.pythonhosted.org/packages/2d/4d/26d236ff35abc3b5e63540d3386e4c3b192168c1d96da5cb2f43c640970f/coverage-7.13.4-cp312-cp312-manylinux2014_ppc64le.manylinux_2_17_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:de6defc1c9badbf8b9e67ae90fd00519186d6ab64e5cc5f3d21359c2a9b2c1d3", size = 257432, upload-time = "2026-02-09T12:57:02.637Z" }, + { url = "https://files.pythonhosted.org/packages/ec/55/14a966c757d1348b2e19caf699415a2a4c4f7feaa4bbc6326a51f5c7dd1b/coverage-7.13.4-cp312-cp312-manylinux_2_31_riscv64.manylinux_2_39_riscv64.whl", hash = "sha256:7eda778067ad7ffccd23ecffce537dface96212576a07924cbf0d8799d2ded5a", size = 251716, upload-time = "2026-02-09T12:57:04.056Z" }, + { url = "https://files.pythonhosted.org/packages/77/33/50116647905837c66d28b2af1321b845d5f5d19be9655cb84d4a0ea806b4/coverage-7.13.4-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:e87f6c587c3f34356c3759f0420693e35e7eb0e2e41e4c011cb6ec6ecbbf1db7", size = 253089, upload-time = "2026-02-09T12:57:05.503Z" }, + { url = "https://files.pythonhosted.org/packages/c2/b4/8efb11a46e3665d92635a56e4f2d4529de6d33f2cb38afd47d779d15fc99/coverage-7.13.4-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:8248977c2e33aecb2ced42fef99f2d319e9904a36e55a8a68b69207fb7e43edc", size = 251232, upload-time = "2026-02-09T12:57:06.879Z" }, + { url = "https://files.pythonhosted.org/packages/51/24/8cd73dd399b812cc76bb0ac260e671c4163093441847ffe058ac9fda1e32/coverage-7.13.4-cp312-cp312-musllinux_1_2_ppc64le.whl", hash = "sha256:25381386e80ae727608e662474db537d4df1ecd42379b5ba33c84633a2b36d47", size = 255299, upload-time = "2026-02-09T12:57:08.245Z" }, + { url = "https://files.pythonhosted.org/packages/03/94/0a4b12f1d0e029ce1ccc1c800944a9984cbe7d678e470bb6d3c6bc38a0da/coverage-7.13.4-cp312-cp312-musllinux_1_2_riscv64.whl", hash = "sha256:ee756f00726693e5ba94d6df2bdfd64d4852d23b09bb0bc700e3b30e6f333985", size = 250796, upload-time = "2026-02-09T12:57:10.142Z" }, + { url = "https://files.pythonhosted.org/packages/73/44/6002fbf88f6698ca034360ce474c406be6d5a985b3fdb3401128031eef6b/coverage-7.13.4-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:fdfc1e28e7c7cdce44985b3043bc13bbd9c747520f94a4d7164af8260b3d91f0", size = 252673, upload-time = "2026-02-09T12:57:12.197Z" }, + { url = "https://files.pythonhosted.org/packages/de/c6/a0279f7c00e786be75a749a5674e6fa267bcbd8209cd10c9a450c655dfa7/coverage-7.13.4-cp312-cp312-win32.whl", hash = "sha256:01d4cbc3c283a17fc1e42d614a119f7f438eabb593391283adca8dc86eff1246", size = 221990, upload-time = "2026-02-09T12:57:14.085Z" }, + { url = "https://files.pythonhosted.org/packages/77/4e/c0a25a425fcf5557d9abd18419c95b63922e897bc86c1f327f155ef234a9/coverage-7.13.4-cp312-cp312-win_amd64.whl", hash = "sha256:9401ebc7ef522f01d01d45532c68c5ac40fb27113019b6b7d8b208f6e9baa126", size = 222800, upload-time = "2026-02-09T12:57:15.944Z" }, + { url = "https://files.pythonhosted.org/packages/47/ac/92da44ad9a6f4e3a7debd178949d6f3769bedca33830ce9b1dcdab589a37/coverage-7.13.4-cp312-cp312-win_arm64.whl", hash = "sha256:b1ec7b6b6e93255f952e27ab58fbc68dcc468844b16ecbee881aeb29b6ab4d8d", size = 221415, upload-time = "2026-02-09T12:57:17.497Z" }, + { url = "https://files.pythonhosted.org/packages/db/23/aad45061a31677d68e47499197a131eea55da4875d16c1f42021ab963503/coverage-7.13.4-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:b66a2da594b6068b48b2692f043f35d4d3693fb639d5ea8b39533c2ad9ac3ab9", size = 219474, upload-time = "2026-02-09T12:57:19.332Z" }, + { url = "https://files.pythonhosted.org/packages/a5/70/9b8b67a0945f3dfec1fd896c5cefb7c19d5a3a6d74630b99a895170999ae/coverage-7.13.4-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:3599eb3992d814d23b35c536c28df1a882caa950f8f507cef23d1cbf334995ac", size = 219844, upload-time = "2026-02-09T12:57:20.66Z" }, + { url = "https://files.pythonhosted.org/packages/97/fd/7e859f8fab324cef6c4ad7cff156ca7c489fef9179d5749b0c8d321281c2/coverage-7.13.4-cp313-cp313-manylinux1_i686.manylinux_2_28_i686.manylinux_2_5_i686.whl", hash = "sha256:93550784d9281e374fb5a12bf1324cc8a963fd63b2d2f223503ef0fd4aa339ea", size = 250832, upload-time = "2026-02-09T12:57:22.007Z" }, + { url = "https://files.pythonhosted.org/packages/e4/dc/b2442d10020c2f52617828862d8b6ee337859cd8f3a1f13d607dddda9cf7/coverage-7.13.4-cp313-cp313-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl", hash = "sha256:b720ce6a88a2755f7c697c23268ddc47a571b88052e6b155224347389fdf6a3b", size = 253434, upload-time = "2026-02-09T12:57:23.339Z" }, + { url = "https://files.pythonhosted.org/packages/5a/88/6728a7ad17428b18d836540630487231f5470fb82454871149502f5e5aa2/coverage-7.13.4-cp313-cp313-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:7b322db1284a2ed3aa28ffd8ebe3db91c929b7a333c0820abec3d838ef5b3525", size = 254676, upload-time = "2026-02-09T12:57:24.774Z" }, + { url = "https://files.pythonhosted.org/packages/7c/bc/21244b1b8cedf0dff0a2b53b208015fe798d5f2a8d5348dbfece04224fff/coverage-7.13.4-cp313-cp313-manylinux2014_ppc64le.manylinux_2_17_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:f4594c67d8a7c89cf922d9df0438c7c7bb022ad506eddb0fdb2863359ff78242", size = 256807, upload-time = "2026-02-09T12:57:26.125Z" }, + { url = "https://files.pythonhosted.org/packages/97/a0/ddba7ed3251cff51006737a727d84e05b61517d1784a9988a846ba508877/coverage-7.13.4-cp313-cp313-manylinux_2_31_riscv64.manylinux_2_39_riscv64.whl", hash = "sha256:53d133df809c743eb8bce33b24bcababb371f4441340578cd406e084d94a6148", size = 251058, upload-time = "2026-02-09T12:57:27.614Z" }, + { url = "https://files.pythonhosted.org/packages/9b/55/e289addf7ff54d3a540526f33751951bf0878f3809b47f6dfb3def69c6f7/coverage-7.13.4-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:76451d1978b95ba6507a039090ba076105c87cc76fc3efd5d35d72093964d49a", size = 252805, upload-time = "2026-02-09T12:57:29.066Z" }, + { url = "https://files.pythonhosted.org/packages/13/4e/cc276b1fa4a59be56d96f1dabddbdc30f4ba22e3b1cd42504c37b3313255/coverage-7.13.4-cp313-cp313-musllinux_1_2_i686.whl", hash = "sha256:7f57b33491e281e962021de110b451ab8a24182589be17e12a22c79047935e23", size = 250766, upload-time = "2026-02-09T12:57:30.522Z" }, + { url = "https://files.pythonhosted.org/packages/94/44/1093b8f93018f8b41a8cf29636c9292502f05e4a113d4d107d14a3acd044/coverage-7.13.4-cp313-cp313-musllinux_1_2_ppc64le.whl", hash = "sha256:1731dc33dc276dafc410a885cbf5992f1ff171393e48a21453b78727d090de80", size = 254923, upload-time = "2026-02-09T12:57:31.946Z" }, + { url = "https://files.pythonhosted.org/packages/8b/55/ea2796da2d42257f37dbea1aab239ba9263b31bd91d5527cdd6db5efe174/coverage-7.13.4-cp313-cp313-musllinux_1_2_riscv64.whl", hash = "sha256:bd60d4fe2f6fa7dff9223ca1bbc9f05d2b6697bc5961072e5d3b952d46e1b1ea", size = 250591, upload-time = "2026-02-09T12:57:33.842Z" }, + { url = "https://files.pythonhosted.org/packages/d4/fa/7c4bb72aacf8af5020675aa633e59c1fbe296d22aed191b6a5b711eb2bc7/coverage-7.13.4-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:9181a3ccead280b828fae232df12b16652702b49d41e99d657f46cc7b1f6ec7a", size = 252364, upload-time = "2026-02-09T12:57:35.743Z" }, + { url = "https://files.pythonhosted.org/packages/5c/38/a8d2ec0146479c20bbaa7181b5b455a0c41101eed57f10dd19a78ab44c80/coverage-7.13.4-cp313-cp313-win32.whl", hash = "sha256:f53d492307962561ac7de4cd1de3e363589b000ab69617c6156a16ba7237998d", size = 222010, upload-time = "2026-02-09T12:57:37.25Z" }, + { url = "https://files.pythonhosted.org/packages/e2/0c/dbfafbe90a185943dcfbc766fe0e1909f658811492d79b741523a414a6cc/coverage-7.13.4-cp313-cp313-win_amd64.whl", hash = "sha256:e6f70dec1cc557e52df5306d051ef56003f74d56e9c4dd7ddb07e07ef32a84dd", size = 222818, upload-time = "2026-02-09T12:57:38.734Z" }, + { url = "https://files.pythonhosted.org/packages/04/d1/934918a138c932c90d78301f45f677fb05c39a3112b96fd2c8e60503cdc7/coverage-7.13.4-cp313-cp313-win_arm64.whl", hash = "sha256:fb07dc5da7e849e2ad31a5d74e9bece81f30ecf5a42909d0a695f8bd1874d6af", size = 221438, upload-time = "2026-02-09T12:57:40.223Z" }, + { url = "https://files.pythonhosted.org/packages/52/57/ee93ced533bcb3e6df961c0c6e42da2fc6addae53fb95b94a89b1e33ebd7/coverage-7.13.4-cp313-cp313t-macosx_10_13_x86_64.whl", hash = "sha256:40d74da8e6c4b9ac18b15331c4b5ebc35a17069410cad462ad4f40dcd2d50c0d", size = 220165, upload-time = "2026-02-09T12:57:41.639Z" }, + { url = "https://files.pythonhosted.org/packages/c5/e0/969fc285a6fbdda49d91af278488d904dcd7651b2693872f0ff94e40e84a/coverage-7.13.4-cp313-cp313t-macosx_11_0_arm64.whl", hash = "sha256:4223b4230a376138939a9173f1bdd6521994f2aff8047fae100d6d94d50c5a12", size = 220516, upload-time = "2026-02-09T12:57:44.215Z" }, + { url = "https://files.pythonhosted.org/packages/b1/b8/9531944e16267e2735a30a9641ff49671f07e8138ecf1ca13db9fd2560c7/coverage-7.13.4-cp313-cp313t-manylinux1_i686.manylinux_2_28_i686.manylinux_2_5_i686.whl", hash = "sha256:1d4be36a5114c499f9f1f9195e95ebf979460dbe2d88e6816ea202010ba1c34b", size = 261804, upload-time = "2026-02-09T12:57:45.989Z" }, + { url = "https://files.pythonhosted.org/packages/8a/f3/e63df6d500314a2a60390d1989240d5f27318a7a68fa30ad3806e2a9323e/coverage-7.13.4-cp313-cp313t-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl", hash = "sha256:200dea7d1e8095cc6e98cdabe3fd1d21ab17d3cee6dab00cadbb2fe35d9c15b9", size = 263885, upload-time = "2026-02-09T12:57:47.42Z" }, + { url = "https://files.pythonhosted.org/packages/f3/67/7654810de580e14b37670b60a09c599fa348e48312db5b216d730857ffe6/coverage-7.13.4-cp313-cp313t-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:b8eb931ee8e6d8243e253e5ed7336deea6904369d2fd8ae6e43f68abbf167092", size = 266308, upload-time = "2026-02-09T12:57:49.345Z" }, + { url = "https://files.pythonhosted.org/packages/37/6f/39d41eca0eab3cc82115953ad41c4e77935286c930e8fad15eaed1389d83/coverage-7.13.4-cp313-cp313t-manylinux2014_ppc64le.manylinux_2_17_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:75eab1ebe4f2f64d9509b984f9314d4aa788540368218b858dad56dc8f3e5eb9", size = 267452, upload-time = "2026-02-09T12:57:50.811Z" }, + { url = "https://files.pythonhosted.org/packages/50/6d/39c0fbb8fc5cd4d2090811e553c2108cf5112e882f82505ee7495349a6bf/coverage-7.13.4-cp313-cp313t-manylinux_2_31_riscv64.manylinux_2_39_riscv64.whl", hash = "sha256:c35eb28c1d085eb7d8c9b3296567a1bebe03ce72962e932431b9a61f28facf26", size = 261057, upload-time = "2026-02-09T12:57:52.447Z" }, + { url = "https://files.pythonhosted.org/packages/a4/a2/60010c669df5fa603bb5a97fb75407e191a846510da70ac657eb696b7fce/coverage-7.13.4-cp313-cp313t-musllinux_1_2_aarch64.whl", hash = "sha256:eb88b316ec33760714a4720feb2816a3a59180fd58c1985012054fa7aebee4c2", size = 263875, upload-time = "2026-02-09T12:57:53.938Z" }, + { url = "https://files.pythonhosted.org/packages/3e/d9/63b22a6bdbd17f1f96e9ed58604c2a6b0e72a9133e37d663bef185877cf6/coverage-7.13.4-cp313-cp313t-musllinux_1_2_i686.whl", hash = "sha256:7d41eead3cc673cbd38a4417deb7fd0b4ca26954ff7dc6078e33f6ff97bed940", size = 261500, upload-time = "2026-02-09T12:57:56.012Z" }, + { url = "https://files.pythonhosted.org/packages/70/bf/69f86ba1ad85bc3ad240e4c0e57a2e620fbc0e1645a47b5c62f0e941ad7f/coverage-7.13.4-cp313-cp313t-musllinux_1_2_ppc64le.whl", hash = "sha256:fb26a934946a6afe0e326aebe0730cdff393a8bc0bbb65a2f41e30feddca399c", size = 265212, upload-time = "2026-02-09T12:57:57.5Z" }, + { url = "https://files.pythonhosted.org/packages/ae/f2/5f65a278a8c2148731831574c73e42f57204243d33bedaaf18fa79c5958f/coverage-7.13.4-cp313-cp313t-musllinux_1_2_riscv64.whl", hash = "sha256:dae88bc0fc77edaa65c14be099bd57ee140cf507e6bfdeea7938457ab387efb0", size = 260398, upload-time = "2026-02-09T12:57:59.027Z" }, + { url = "https://files.pythonhosted.org/packages/ef/80/6e8280a350ee9fea92f14b8357448a242dcaa243cb2c72ab0ca591f66c8c/coverage-7.13.4-cp313-cp313t-musllinux_1_2_x86_64.whl", hash = "sha256:845f352911777a8e722bfce168958214951e07e47e5d5d9744109fa5fe77f79b", size = 262584, upload-time = "2026-02-09T12:58:01.129Z" }, + { url = "https://files.pythonhosted.org/packages/22/63/01ff182fc95f260b539590fb12c11ad3e21332c15f9799cb5e2386f71d9f/coverage-7.13.4-cp313-cp313t-win32.whl", hash = "sha256:2fa8d5f8de70688a28240de9e139fa16b153cc3cbb01c5f16d88d6505ebdadf9", size = 222688, upload-time = "2026-02-09T12:58:02.736Z" }, + { url = "https://files.pythonhosted.org/packages/a9/43/89de4ef5d3cd53b886afa114065f7e9d3707bdb3e5efae13535b46ae483d/coverage-7.13.4-cp313-cp313t-win_amd64.whl", hash = "sha256:9351229c8c8407645840edcc277f4a2d44814d1bc34a2128c11c2a031d45a5dd", size = 223746, upload-time = "2026-02-09T12:58:05.362Z" }, + { url = "https://files.pythonhosted.org/packages/35/39/7cf0aa9a10d470a5309b38b289b9bb07ddeac5d61af9b664fe9775a4cb3e/coverage-7.13.4-cp313-cp313t-win_arm64.whl", hash = "sha256:30b8d0512f2dc8c8747557e8fb459d6176a2c9e5731e2b74d311c03b78451997", size = 222003, upload-time = "2026-02-09T12:58:06.952Z" }, + { url = "https://files.pythonhosted.org/packages/92/11/a9cf762bb83386467737d32187756a42094927150c3e107df4cb078e8590/coverage-7.13.4-cp314-cp314-macosx_10_15_x86_64.whl", hash = "sha256:300deaee342f90696ed186e3a00c71b5b3d27bffe9e827677954f4ee56969601", size = 219522, upload-time = "2026-02-09T12:58:08.623Z" }, + { url = "https://files.pythonhosted.org/packages/d3/28/56e6d892b7b052236d67c95f1936b6a7cf7c3e2634bf27610b8cbd7f9c60/coverage-7.13.4-cp314-cp314-macosx_11_0_arm64.whl", hash = "sha256:29e3220258d682b6226a9b0925bc563ed9a1ebcff3cad30f043eceea7eaf2689", size = 219855, upload-time = "2026-02-09T12:58:10.176Z" }, + { url = "https://files.pythonhosted.org/packages/e5/69/233459ee9eb0c0d10fcc2fe425a029b3fa5ce0f040c966ebce851d030c70/coverage-7.13.4-cp314-cp314-manylinux1_i686.manylinux_2_28_i686.manylinux_2_5_i686.whl", hash = "sha256:391ee8f19bef69210978363ca930f7328081c6a0152f1166c91f0b5fdd2a773c", size = 250887, upload-time = "2026-02-09T12:58:12.503Z" }, + { url = "https://files.pythonhosted.org/packages/06/90/2cdab0974b9b5bbc1623f7876b73603aecac11b8d95b85b5b86b32de5eab/coverage-7.13.4-cp314-cp314-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl", hash = "sha256:0dd7ab8278f0d58a0128ba2fca25824321f05d059c1441800e934ff2efa52129", size = 253396, upload-time = "2026-02-09T12:58:14.615Z" }, + { url = "https://files.pythonhosted.org/packages/ac/15/ea4da0f85bf7d7b27635039e649e99deb8173fe551096ea15017f7053537/coverage-7.13.4-cp314-cp314-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:78cdf0d578b15148b009ccf18c686aa4f719d887e76e6b40c38ffb61d264a552", size = 254745, upload-time = "2026-02-09T12:58:16.162Z" }, + { url = "https://files.pythonhosted.org/packages/99/11/bb356e86920c655ca4d61daee4e2bbc7258f0a37de0be32d233b561134ff/coverage-7.13.4-cp314-cp314-manylinux2014_ppc64le.manylinux_2_17_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:48685fee12c2eb3b27c62f2658e7ea21e9c3239cba5a8a242801a0a3f6a8c62a", size = 257055, upload-time = "2026-02-09T12:58:17.892Z" }, + { url = "https://files.pythonhosted.org/packages/c9/0f/9ae1f8cb17029e09da06ca4e28c9e1d5c1c0a511c7074592e37e0836c915/coverage-7.13.4-cp314-cp314-manylinux_2_31_riscv64.manylinux_2_39_riscv64.whl", hash = "sha256:4e83efc079eb39480e6346a15a1bcb3e9b04759c5202d157e1dd4303cd619356", size = 250911, upload-time = "2026-02-09T12:58:19.495Z" }, + { url = "https://files.pythonhosted.org/packages/89/3a/adfb68558fa815cbc29747b553bc833d2150228f251b127f1ce97e48547c/coverage-7.13.4-cp314-cp314-musllinux_1_2_aarch64.whl", hash = "sha256:ecae9737b72408d6a950f7e525f30aca12d4bd8dd95e37342e5beb3a2a8c4f71", size = 252754, upload-time = "2026-02-09T12:58:21.064Z" }, + { url = "https://files.pythonhosted.org/packages/32/b1/540d0c27c4e748bd3cd0bd001076ee416eda993c2bae47a73b7cc9357931/coverage-7.13.4-cp314-cp314-musllinux_1_2_i686.whl", hash = "sha256:ae4578f8528569d3cf303fef2ea569c7f4c4059a38c8667ccef15c6e1f118aa5", size = 250720, upload-time = "2026-02-09T12:58:22.622Z" }, + { url = "https://files.pythonhosted.org/packages/c7/95/383609462b3ffb1fe133014a7c84fc0dd01ed55ac6140fa1093b5af7ebb1/coverage-7.13.4-cp314-cp314-musllinux_1_2_ppc64le.whl", hash = "sha256:6fdef321fdfbb30a197efa02d48fcd9981f0d8ad2ae8903ac318adc653f5df98", size = 254994, upload-time = "2026-02-09T12:58:24.548Z" }, + { url = "https://files.pythonhosted.org/packages/f7/ba/1761138e86c81680bfc3c49579d66312865457f9fe405b033184e5793cb3/coverage-7.13.4-cp314-cp314-musllinux_1_2_riscv64.whl", hash = "sha256:2b0f6ccf3dbe577170bebfce1318707d0e8c3650003cb4b3a9dd744575daa8b5", size = 250531, upload-time = "2026-02-09T12:58:26.271Z" }, + { url = "https://files.pythonhosted.org/packages/f8/8e/05900df797a9c11837ab59c4d6fe94094e029582aab75c3309a93e6fb4e3/coverage-7.13.4-cp314-cp314-musllinux_1_2_x86_64.whl", hash = "sha256:75fcd519f2a5765db3f0e391eb3b7d150cce1a771bf4c9f861aeab86c767a3c0", size = 252189, upload-time = "2026-02-09T12:58:27.807Z" }, + { url = "https://files.pythonhosted.org/packages/00/bd/29c9f2db9ea4ed2738b8a9508c35626eb205d51af4ab7bf56a21a2e49926/coverage-7.13.4-cp314-cp314-win32.whl", hash = "sha256:8e798c266c378da2bd819b0677df41ab46d78065fb2a399558f3f6cae78b2fbb", size = 222258, upload-time = "2026-02-09T12:58:29.441Z" }, + { url = "https://files.pythonhosted.org/packages/a7/4d/1f8e723f6829977410efeb88f73673d794075091c8c7c18848d273dc9d73/coverage-7.13.4-cp314-cp314-win_amd64.whl", hash = "sha256:245e37f664d89861cf2329c9afa2c1fe9e6d4e1a09d872c947e70718aeeac505", size = 223073, upload-time = "2026-02-09T12:58:31.026Z" }, + { url = "https://files.pythonhosted.org/packages/51/5b/84100025be913b44e082ea32abcf1afbf4e872f5120b7a1cab1d331b1e13/coverage-7.13.4-cp314-cp314-win_arm64.whl", hash = "sha256:ad27098a189e5838900ce4c2a99f2fe42a0bf0c2093c17c69b45a71579e8d4a2", size = 221638, upload-time = "2026-02-09T12:58:32.599Z" }, + { url = "https://files.pythonhosted.org/packages/a7/e4/c884a405d6ead1370433dad1e3720216b4f9fd8ef5b64bfd984a2a60a11a/coverage-7.13.4-cp314-cp314t-macosx_10_15_x86_64.whl", hash = "sha256:85480adfb35ffc32d40918aad81b89c69c9cc5661a9b8a81476d3e645321a056", size = 220246, upload-time = "2026-02-09T12:58:34.181Z" }, + { url = "https://files.pythonhosted.org/packages/81/5c/4d7ed8b23b233b0fffbc9dfec53c232be2e695468523242ea9fd30f97ad2/coverage-7.13.4-cp314-cp314t-macosx_11_0_arm64.whl", hash = "sha256:79be69cf7f3bf9b0deeeb062eab7ac7f36cd4cc4c4dd694bd28921ba4d8596cc", size = 220514, upload-time = "2026-02-09T12:58:35.704Z" }, + { url = "https://files.pythonhosted.org/packages/2f/6f/3284d4203fd2f28edd73034968398cd2d4cb04ab192abc8cff007ea35679/coverage-7.13.4-cp314-cp314t-manylinux1_i686.manylinux_2_28_i686.manylinux_2_5_i686.whl", hash = "sha256:caa421e2684e382c5d8973ac55e4f36bed6821a9bad5c953494de960c74595c9", size = 261877, upload-time = "2026-02-09T12:58:37.864Z" }, + { url = "https://files.pythonhosted.org/packages/09/aa/b672a647bbe1556a85337dc95bfd40d146e9965ead9cc2fe81bde1e5cbce/coverage-7.13.4-cp314-cp314t-manylinux1_x86_64.manylinux_2_28_x86_64.manylinux_2_5_x86_64.whl", hash = "sha256:14375934243ee05f56c45393fe2ce81fe5cc503c07cee2bdf1725fb8bef3ffaf", size = 264004, upload-time = "2026-02-09T12:58:39.492Z" }, + { url = "https://files.pythonhosted.org/packages/79/a1/aa384dbe9181f98bba87dd23dda436f0c6cf2e148aecbb4e50fc51c1a656/coverage-7.13.4-cp314-cp314t-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:25a41c3104d08edb094d9db0d905ca54d0cd41c928bb6be3c4c799a54753af55", size = 266408, upload-time = "2026-02-09T12:58:41.852Z" }, + { url = "https://files.pythonhosted.org/packages/53/5e/5150bf17b4019bc600799f376bb9606941e55bd5a775dc1e096b6ffea952/coverage-7.13.4-cp314-cp314t-manylinux2014_ppc64le.manylinux_2_17_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:6f01afcff62bf9a08fb32b2c1d6e924236c0383c02c790732b6537269e466a72", size = 267544, upload-time = "2026-02-09T12:58:44.093Z" }, + { url = "https://files.pythonhosted.org/packages/e0/ed/f1de5c675987a4a7a672250d2c5c9d73d289dbf13410f00ed7181d8017dd/coverage-7.13.4-cp314-cp314t-manylinux_2_31_riscv64.manylinux_2_39_riscv64.whl", hash = "sha256:eb9078108fbf0bcdde37c3f4779303673c2fa1fe8f7956e68d447d0dd426d38a", size = 260980, upload-time = "2026-02-09T12:58:45.721Z" }, + { url = "https://files.pythonhosted.org/packages/b3/e3/fe758d01850aa172419a6743fe76ba8b92c29d181d4f676ffe2dae2ba631/coverage-7.13.4-cp314-cp314t-musllinux_1_2_aarch64.whl", hash = "sha256:0e086334e8537ddd17e5f16a344777c1ab8194986ec533711cbe6c41cde841b6", size = 263871, upload-time = "2026-02-09T12:58:47.334Z" }, + { url = "https://files.pythonhosted.org/packages/b6/76/b829869d464115e22499541def9796b25312b8cf235d3bb00b39f1675395/coverage-7.13.4-cp314-cp314t-musllinux_1_2_i686.whl", hash = "sha256:725d985c5ab621268b2edb8e50dfe57633dc69bda071abc470fed55a14935fd3", size = 261472, upload-time = "2026-02-09T12:58:48.995Z" }, + { url = "https://files.pythonhosted.org/packages/14/9e/caedb1679e73e2f6ad240173f55218488bfe043e38da577c4ec977489915/coverage-7.13.4-cp314-cp314t-musllinux_1_2_ppc64le.whl", hash = "sha256:3c06f0f1337c667b971ca2f975523347e63ec5e500b9aa5882d91931cd3ef750", size = 265210, upload-time = "2026-02-09T12:58:51.178Z" }, + { url = "https://files.pythonhosted.org/packages/3a/10/0dd02cb009b16ede425b49ec344aba13a6ae1dc39600840ea6abcb085ac4/coverage-7.13.4-cp314-cp314t-musllinux_1_2_riscv64.whl", hash = "sha256:590c0ed4bf8e85f745e6b805b2e1c457b2e33d5255dd9729743165253bc9ad39", size = 260319, upload-time = "2026-02-09T12:58:53.081Z" }, + { url = "https://files.pythonhosted.org/packages/92/8e/234d2c927af27c6d7a5ffad5bd2cf31634c46a477b4c7adfbfa66baf7ebb/coverage-7.13.4-cp314-cp314t-musllinux_1_2_x86_64.whl", hash = "sha256:eb30bf180de3f632cd043322dad5751390e5385108b2807368997d1a92a509d0", size = 262638, upload-time = "2026-02-09T12:58:55.258Z" }, + { url = "https://files.pythonhosted.org/packages/2f/64/e5547c8ff6964e5965c35a480855911b61509cce544f4d442caa759a0702/coverage-7.13.4-cp314-cp314t-win32.whl", hash = "sha256:c4240e7eded42d131a2d2c4dec70374b781b043ddc79a9de4d55ca71f8e98aea", size = 223040, upload-time = "2026-02-09T12:58:56.936Z" }, + { url = "https://files.pythonhosted.org/packages/c7/96/38086d58a181aac86d503dfa9c47eb20715a79c3e3acbdf786e92e5c09a8/coverage-7.13.4-cp314-cp314t-win_amd64.whl", hash = "sha256:4c7d3cc01e7350f2f0f6f7036caaf5673fb56b6998889ccfe9e1c1fe75a9c932", size = 224148, upload-time = "2026-02-09T12:58:58.645Z" }, + { url = "https://files.pythonhosted.org/packages/ce/72/8d10abd3740a0beb98c305e0c3faf454366221c0f37a8bcf8f60020bb65a/coverage-7.13.4-cp314-cp314t-win_arm64.whl", hash = "sha256:23e3f687cf945070d1c90f85db66d11e3025665d8dafa831301a0e0038f3db9b", size = 222172, upload-time = "2026-02-09T12:59:00.396Z" }, + { url = "https://files.pythonhosted.org/packages/0d/4a/331fe2caf6799d591109bb9c08083080f6de90a823695d412a935622abb2/coverage-7.13.4-py3-none-any.whl", hash = "sha256:1af1641e57cf7ba1bd67d677c9abdbcd6cc2ab7da3bca7fa1e2b7e50e65f2ad0", size = 211242, upload-time = "2026-02-09T12:59:02.032Z" }, +] + +[[package]] +name = "cryptography" +version = "46.0.5" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "cffi", marker = "platform_python_implementation != 'PyPy'" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/60/04/ee2a9e8542e4fa2773b81771ff8349ff19cdd56b7258a0cc442639052edb/cryptography-46.0.5.tar.gz", hash = "sha256:abace499247268e3757271b2f1e244b36b06f8515cf27c4d49468fc9eb16e93d", size = 750064, upload-time = "2026-02-10T19:18:38.255Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/ff/9e/6b4397a3e3d15123de3b1806ef342522393d50736c13b20ec4c9ea6693a6/cryptography-46.0.5-cp311-abi3-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:c18ff11e86df2e28854939acde2d003f7984f721eba450b56a200ad90eeb0e6b", size = 4275637, upload-time = "2026-02-10T19:17:10.53Z" }, + { url = "https://files.pythonhosted.org/packages/63/e7/471ab61099a3920b0c77852ea3f0ea611c9702f651600397ac567848b897/cryptography-46.0.5-cp311-abi3-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:4d7e3d356b8cd4ea5aff04f129d5f66ebdc7b6f8eae802b93739ed520c47c79b", size = 4424742, upload-time = "2026-02-10T19:17:12.388Z" }, + { url = "https://files.pythonhosted.org/packages/37/53/a18500f270342d66bf7e4d9f091114e31e5ee9e7375a5aba2e85a91e0044/cryptography-46.0.5-cp311-abi3-manylinux_2_28_aarch64.whl", hash = "sha256:50bfb6925eff619c9c023b967d5b77a54e04256c4281b0e21336a130cd7fc263", size = 4277528, upload-time = "2026-02-10T19:17:13.853Z" }, + { url = "https://files.pythonhosted.org/packages/22/29/c2e812ebc38c57b40e7c583895e73c8c5adb4d1e4a0cc4c5a4fdab2b1acc/cryptography-46.0.5-cp311-abi3-manylinux_2_28_ppc64le.whl", hash = "sha256:803812e111e75d1aa73690d2facc295eaefd4439be1023fefc4995eaea2af90d", size = 4947993, upload-time = "2026-02-10T19:17:15.618Z" }, + { url = "https://files.pythonhosted.org/packages/6b/e7/237155ae19a9023de7e30ec64e5d99a9431a567407ac21170a046d22a5a3/cryptography-46.0.5-cp311-abi3-manylinux_2_28_x86_64.whl", hash = "sha256:3ee190460e2fbe447175cda91b88b84ae8322a104fc27766ad09428754a618ed", size = 4456855, upload-time = "2026-02-10T19:17:17.221Z" }, + { url = "https://files.pythonhosted.org/packages/2d/87/fc628a7ad85b81206738abbd213b07702bcbdada1dd43f72236ef3cffbb5/cryptography-46.0.5-cp311-abi3-manylinux_2_31_armv7l.whl", hash = "sha256:f145bba11b878005c496e93e257c1e88f154d278d2638e6450d17e0f31e558d2", size = 3984635, upload-time = "2026-02-10T19:17:18.792Z" }, + { url = "https://files.pythonhosted.org/packages/84/29/65b55622bde135aedf4565dc509d99b560ee4095e56989e815f8fd2aa910/cryptography-46.0.5-cp311-abi3-manylinux_2_34_aarch64.whl", hash = "sha256:e9251e3be159d1020c4030bd2e5f84d6a43fe54b6c19c12f51cde9542a2817b2", size = 4277038, upload-time = "2026-02-10T19:17:20.256Z" }, + { url = "https://files.pythonhosted.org/packages/bc/36/45e76c68d7311432741faf1fbf7fac8a196a0a735ca21f504c75d37e2558/cryptography-46.0.5-cp311-abi3-manylinux_2_34_ppc64le.whl", hash = "sha256:47fb8a66058b80e509c47118ef8a75d14c455e81ac369050f20ba0d23e77fee0", size = 4912181, upload-time = "2026-02-10T19:17:21.825Z" }, + { url = "https://files.pythonhosted.org/packages/6d/1a/c1ba8fead184d6e3d5afcf03d569acac5ad063f3ac9fb7258af158f7e378/cryptography-46.0.5-cp311-abi3-manylinux_2_34_x86_64.whl", hash = "sha256:4c3341037c136030cb46e4b1e17b7418ea4cbd9dd207e4a6f3b2b24e0d4ac731", size = 4456482, upload-time = "2026-02-10T19:17:25.133Z" }, + { url = "https://files.pythonhosted.org/packages/f9/e5/3fb22e37f66827ced3b902cf895e6a6bc1d095b5b26be26bd13c441fdf19/cryptography-46.0.5-cp311-abi3-musllinux_1_2_aarch64.whl", hash = "sha256:890bcb4abd5a2d3f852196437129eb3667d62630333aacc13dfd470fad3aaa82", size = 4405497, upload-time = "2026-02-10T19:17:26.66Z" }, + { url = "https://files.pythonhosted.org/packages/1a/df/9d58bb32b1121a8a2f27383fabae4d63080c7ca60b9b5c88be742be04ee7/cryptography-46.0.5-cp311-abi3-musllinux_1_2_x86_64.whl", hash = "sha256:80a8d7bfdf38f87ca30a5391c0c9ce4ed2926918e017c29ddf643d0ed2778ea1", size = 4667819, upload-time = "2026-02-10T19:17:28.569Z" }, + { url = "https://files.pythonhosted.org/packages/67/c8/581a6702e14f0898a0848105cbefd20c058099e2c2d22ef4e476dfec75d7/cryptography-46.0.5-cp314-cp314t-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:5be7bf2fb40769e05739dd0046e7b26f9d4670badc7b032d6ce4db64dddc0678", size = 4265728, upload-time = "2026-02-10T19:17:35.569Z" }, + { url = "https://files.pythonhosted.org/packages/dd/4a/ba1a65ce8fc65435e5a849558379896c957870dd64fecea97b1ad5f46a37/cryptography-46.0.5-cp314-cp314t-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:fe346b143ff9685e40192a4960938545c699054ba11d4f9029f94751e3f71d87", size = 4408287, upload-time = "2026-02-10T19:17:36.938Z" }, + { url = "https://files.pythonhosted.org/packages/f8/67/8ffdbf7b65ed1ac224d1c2df3943553766914a8ca718747ee3871da6107e/cryptography-46.0.5-cp314-cp314t-manylinux_2_28_aarch64.whl", hash = "sha256:c69fd885df7d089548a42d5ec05be26050ebcd2283d89b3d30676eb32ff87dee", size = 4270291, upload-time = "2026-02-10T19:17:38.748Z" }, + { url = "https://files.pythonhosted.org/packages/f8/e5/f52377ee93bc2f2bba55a41a886fd208c15276ffbd2569f2ddc89d50e2c5/cryptography-46.0.5-cp314-cp314t-manylinux_2_28_ppc64le.whl", hash = "sha256:8293f3dea7fc929ef7240796ba231413afa7b68ce38fd21da2995549f5961981", size = 4927539, upload-time = "2026-02-10T19:17:40.241Z" }, + { url = "https://files.pythonhosted.org/packages/3b/02/cfe39181b02419bbbbcf3abdd16c1c5c8541f03ca8bda240debc467d5a12/cryptography-46.0.5-cp314-cp314t-manylinux_2_28_x86_64.whl", hash = "sha256:1abfdb89b41c3be0365328a410baa9df3ff8a9110fb75e7b52e66803ddabc9a9", size = 4442199, upload-time = "2026-02-10T19:17:41.789Z" }, + { url = "https://files.pythonhosted.org/packages/c0/96/2fcaeb4873e536cf71421a388a6c11b5bc846e986b2b069c79363dc1648e/cryptography-46.0.5-cp314-cp314t-manylinux_2_31_armv7l.whl", hash = "sha256:d66e421495fdb797610a08f43b05269e0a5ea7f5e652a89bfd5a7d3c1dee3648", size = 3960131, upload-time = "2026-02-10T19:17:43.379Z" }, + { url = "https://files.pythonhosted.org/packages/d8/d2/b27631f401ddd644e94c5cf33c9a4069f72011821cf3dc7309546b0642a0/cryptography-46.0.5-cp314-cp314t-manylinux_2_34_aarch64.whl", hash = "sha256:4e817a8920bfbcff8940ecfd60f23d01836408242b30f1a708d93198393a80b4", size = 4270072, upload-time = "2026-02-10T19:17:45.481Z" }, + { url = "https://files.pythonhosted.org/packages/f4/a7/60d32b0370dae0b4ebe55ffa10e8599a2a59935b5ece1b9f06edb73abdeb/cryptography-46.0.5-cp314-cp314t-manylinux_2_34_ppc64le.whl", hash = "sha256:68f68d13f2e1cb95163fa3b4db4bf9a159a418f5f6e7242564fc75fcae667fd0", size = 4892170, upload-time = "2026-02-10T19:17:46.997Z" }, + { url = "https://files.pythonhosted.org/packages/d2/b9/cf73ddf8ef1164330eb0b199a589103c363afa0cf794218c24d524a58eab/cryptography-46.0.5-cp314-cp314t-manylinux_2_34_x86_64.whl", hash = "sha256:a3d1fae9863299076f05cb8a778c467578262fae09f9dc0ee9b12eb4268ce663", size = 4441741, upload-time = "2026-02-10T19:17:48.661Z" }, + { url = "https://files.pythonhosted.org/packages/5f/eb/eee00b28c84c726fe8fa0158c65afe312d9c3b78d9d01daf700f1f6e37ff/cryptography-46.0.5-cp314-cp314t-musllinux_1_2_aarch64.whl", hash = "sha256:c4143987a42a2397f2fc3b4d7e3a7d313fbe684f67ff443999e803dd75a76826", size = 4396728, upload-time = "2026-02-10T19:17:50.058Z" }, + { url = "https://files.pythonhosted.org/packages/65/f4/6bc1a9ed5aef7145045114b75b77c2a8261b4d38717bd8dea111a63c3442/cryptography-46.0.5-cp314-cp314t-musllinux_1_2_x86_64.whl", hash = "sha256:7d731d4b107030987fd61a7f8ab512b25b53cef8f233a97379ede116f30eb67d", size = 4652001, upload-time = "2026-02-10T19:17:51.54Z" }, + { url = "https://files.pythonhosted.org/packages/0f/04/c85bdeab78c8bc77b701bf0d9bdcf514c044e18a46dcff330df5448631b0/cryptography-46.0.5-cp38-abi3-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:7d1f30a86d2757199cb2d56e48cce14deddf1f9c95f1ef1b64ee91ea43fe2e18", size = 4275349, upload-time = "2026-02-10T19:17:58.419Z" }, + { url = "https://files.pythonhosted.org/packages/5c/32/9b87132a2f91ee7f5223b091dc963055503e9b442c98fc0b8a5ca765fab0/cryptography-46.0.5-cp38-abi3-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:039917b0dc418bb9f6edce8a906572d69e74bd330b0b3fea4f79dab7f8ddd235", size = 4420667, upload-time = "2026-02-10T19:18:00.619Z" }, + { url = "https://files.pythonhosted.org/packages/a1/a6/a7cb7010bec4b7c5692ca6f024150371b295ee1c108bdc1c400e4c44562b/cryptography-46.0.5-cp38-abi3-manylinux_2_28_aarch64.whl", hash = "sha256:ba2a27ff02f48193fc4daeadf8ad2590516fa3d0adeeb34336b96f7fa64c1e3a", size = 4276980, upload-time = "2026-02-10T19:18:02.379Z" }, + { url = "https://files.pythonhosted.org/packages/8e/7c/c4f45e0eeff9b91e3f12dbd0e165fcf2a38847288fcfd889deea99fb7b6d/cryptography-46.0.5-cp38-abi3-manylinux_2_28_ppc64le.whl", hash = "sha256:61aa400dce22cb001a98014f647dc21cda08f7915ceb95df0c9eaf84b4b6af76", size = 4939143, upload-time = "2026-02-10T19:18:03.964Z" }, + { url = "https://files.pythonhosted.org/packages/37/19/e1b8f964a834eddb44fa1b9a9976f4e414cbb7aa62809b6760c8803d22d1/cryptography-46.0.5-cp38-abi3-manylinux_2_28_x86_64.whl", hash = "sha256:3ce58ba46e1bc2aac4f7d9290223cead56743fa6ab94a5d53292ffaac6a91614", size = 4453674, upload-time = "2026-02-10T19:18:05.588Z" }, + { url = "https://files.pythonhosted.org/packages/db/ed/db15d3956f65264ca204625597c410d420e26530c4e2943e05a0d2f24d51/cryptography-46.0.5-cp38-abi3-manylinux_2_31_armv7l.whl", hash = "sha256:420d0e909050490d04359e7fdb5ed7e667ca5c3c402b809ae2563d7e66a92229", size = 3978801, upload-time = "2026-02-10T19:18:07.167Z" }, + { url = "https://files.pythonhosted.org/packages/41/e2/df40a31d82df0a70a0daf69791f91dbb70e47644c58581d654879b382d11/cryptography-46.0.5-cp38-abi3-manylinux_2_34_aarch64.whl", hash = "sha256:582f5fcd2afa31622f317f80426a027f30dc792e9c80ffee87b993200ea115f1", size = 4276755, upload-time = "2026-02-10T19:18:09.813Z" }, + { url = "https://files.pythonhosted.org/packages/33/45/726809d1176959f4a896b86907b98ff4391a8aa29c0aaaf9450a8a10630e/cryptography-46.0.5-cp38-abi3-manylinux_2_34_ppc64le.whl", hash = "sha256:bfd56bb4b37ed4f330b82402f6f435845a5f5648edf1ad497da51a8452d5d62d", size = 4901539, upload-time = "2026-02-10T19:18:11.263Z" }, + { url = "https://files.pythonhosted.org/packages/99/0f/a3076874e9c88ecb2ecc31382f6e7c21b428ede6f55aafa1aa272613e3cd/cryptography-46.0.5-cp38-abi3-manylinux_2_34_x86_64.whl", hash = "sha256:a3d507bb6a513ca96ba84443226af944b0f7f47dcc9a399d110cd6146481d24c", size = 4452794, upload-time = "2026-02-10T19:18:12.914Z" }, + { url = "https://files.pythonhosted.org/packages/02/ef/ffeb542d3683d24194a38f66ca17c0a4b8bf10631feef44a7ef64e631b1a/cryptography-46.0.5-cp38-abi3-musllinux_1_2_aarch64.whl", hash = "sha256:9f16fbdf4da055efb21c22d81b89f155f02ba420558db21288b3d0035bafd5f4", size = 4404160, upload-time = "2026-02-10T19:18:14.375Z" }, + { url = "https://files.pythonhosted.org/packages/96/93/682d2b43c1d5f1406ed048f377c0fc9fc8f7b0447a478d5c65ab3d3a66eb/cryptography-46.0.5-cp38-abi3-musllinux_1_2_x86_64.whl", hash = "sha256:ced80795227d70549a411a4ab66e8ce307899fad2220ce5ab2f296e687eacde9", size = 4667123, upload-time = "2026-02-10T19:18:15.886Z" }, + { url = "https://files.pythonhosted.org/packages/e9/6f/6cc6cc9955caa6eaf83660b0da2b077c7fe8ff9950a3c5e45d605038d439/cryptography-46.0.5-pp311-pypy311_pp73-manylinux_2_28_aarch64.whl", hash = "sha256:bc84e875994c3b445871ea7181d424588171efec3e185dced958dad9e001950a", size = 4218321, upload-time = "2026-02-10T19:18:22.349Z" }, + { url = "https://files.pythonhosted.org/packages/3e/5d/c4da701939eeee699566a6c1367427ab91a8b7088cc2328c09dbee940415/cryptography-46.0.5-pp311-pypy311_pp73-manylinux_2_28_x86_64.whl", hash = "sha256:2ae6971afd6246710480e3f15824ed3029a60fc16991db250034efd0b9fb4356", size = 4381786, upload-time = "2026-02-10T19:18:24.529Z" }, + { url = "https://files.pythonhosted.org/packages/ac/97/a538654732974a94ff96c1db621fa464f455c02d4bb7d2652f4edc21d600/cryptography-46.0.5-pp311-pypy311_pp73-manylinux_2_34_aarch64.whl", hash = "sha256:d861ee9e76ace6cf36a6a89b959ec08e7bc2493ee39d07ffe5acb23ef46d27da", size = 4217990, upload-time = "2026-02-10T19:18:25.957Z" }, + { url = "https://files.pythonhosted.org/packages/ae/11/7e500d2dd3ba891197b9efd2da5454b74336d64a7cc419aa7327ab74e5f6/cryptography-46.0.5-pp311-pypy311_pp73-manylinux_2_34_x86_64.whl", hash = "sha256:2b7a67c9cd56372f3249b39699f2ad479f6991e62ea15800973b956f4b73e257", size = 4381252, upload-time = "2026-02-10T19:18:27.496Z" }, +] + +[[package]] +name = "cycler" +version = "0.12.1" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/a9/95/a3dbbb5028f35eafb79008e7522a75244477d2838f38cbb722248dabc2a8/cycler-0.12.1.tar.gz", hash = "sha256:88bb128f02ba341da8ef447245a9e138fae777f6a23943da4540077d3601eb1c", size = 7615, upload-time = "2023-10-07T05:32:18.335Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/e7/05/c19819d5e3d95294a6f5947fb9b9629efb316b96de511b418c53d245aae6/cycler-0.12.1-py3-none-any.whl", hash = "sha256:85cef7cff222d8644161529808465972e51340599459b8ac3ccbac5a854e0d30", size = 8321, upload-time = "2023-10-07T05:32:16.783Z" }, +] + +[[package]] +name = "debugpy" +version = "1.8.20" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/e0/b7/cd8080344452e4874aae67c40d8940e2b4d47b01601a8fd9f44786c757c7/debugpy-1.8.20.tar.gz", hash = "sha256:55bc8701714969f1ab89a6d5f2f3d40c36f91b2cbe2f65d98bf8196f6a6a2c33", size = 1645207, upload-time = "2026-01-29T23:03:28.199Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/51/56/c3baf5cbe4dd77427fd9aef99fcdade259ad128feeb8a786c246adb838e5/debugpy-1.8.20-cp311-cp311-macosx_15_0_universal2.whl", hash = "sha256:eada6042ad88fa1571b74bd5402ee8b86eded7a8f7b827849761700aff171f1b", size = 2208318, upload-time = "2026-01-29T23:03:36.481Z" }, + { url = "https://files.pythonhosted.org/packages/9a/7d/4fa79a57a8e69fe0d9763e98d1110320f9ecd7f1f362572e3aafd7417c9d/debugpy-1.8.20-cp311-cp311-manylinux_2_34_x86_64.whl", hash = "sha256:7de0b7dfeedc504421032afba845ae2a7bcc32ddfb07dae2c3ca5442f821c344", size = 3171493, upload-time = "2026-01-29T23:03:37.775Z" }, + { url = "https://files.pythonhosted.org/packages/7d/f2/1e8f8affe51e12a26f3a8a8a4277d6e60aa89d0a66512f63b1e799d424a4/debugpy-1.8.20-cp311-cp311-win32.whl", hash = "sha256:773e839380cf459caf73cc533ea45ec2737a5cc184cf1b3b796cd4fd98504fec", size = 5209240, upload-time = "2026-01-29T23:03:39.109Z" }, + { url = "https://files.pythonhosted.org/packages/d5/92/1cb532e88560cbee973396254b21bece8c5d7c2ece958a67afa08c9f10dc/debugpy-1.8.20-cp311-cp311-win_amd64.whl", hash = "sha256:1f7650546e0eded1902d0f6af28f787fa1f1dbdbc97ddabaf1cd963a405930cb", size = 5233481, upload-time = "2026-01-29T23:03:40.659Z" }, + { url = "https://files.pythonhosted.org/packages/14/57/7f34f4736bfb6e00f2e4c96351b07805d83c9a7b33d28580ae01374430f7/debugpy-1.8.20-cp312-cp312-macosx_15_0_universal2.whl", hash = "sha256:4ae3135e2089905a916909ef31922b2d733d756f66d87345b3e5e52b7a55f13d", size = 2550686, upload-time = "2026-01-29T23:03:42.023Z" }, + { url = "https://files.pythonhosted.org/packages/ab/78/b193a3975ca34458f6f0e24aaf5c3e3da72f5401f6054c0dfd004b41726f/debugpy-1.8.20-cp312-cp312-manylinux_2_34_x86_64.whl", hash = "sha256:88f47850a4284b88bd2bfee1f26132147d5d504e4e86c22485dfa44b97e19b4b", size = 4310588, upload-time = "2026-01-29T23:03:43.314Z" }, + { url = "https://files.pythonhosted.org/packages/c1/55/f14deb95eaf4f30f07ef4b90a8590fc05d9e04df85ee379712f6fb6736d7/debugpy-1.8.20-cp312-cp312-win32.whl", hash = "sha256:4057ac68f892064e5f98209ab582abfee3b543fb55d2e87610ddc133a954d390", size = 5331372, upload-time = "2026-01-29T23:03:45.526Z" }, + { url = "https://files.pythonhosted.org/packages/a1/39/2bef246368bd42f9bd7cba99844542b74b84dacbdbea0833e610f384fee8/debugpy-1.8.20-cp312-cp312-win_amd64.whl", hash = "sha256:a1a8f851e7cf171330679ef6997e9c579ef6dd33c9098458bd9986a0f4ca52e3", size = 5372835, upload-time = "2026-01-29T23:03:47.245Z" }, + { url = "https://files.pythonhosted.org/packages/15/e2/fc500524cc6f104a9d049abc85a0a8b3f0d14c0a39b9c140511c61e5b40b/debugpy-1.8.20-cp313-cp313-macosx_15_0_universal2.whl", hash = "sha256:5dff4bb27027821fdfcc9e8f87309a28988231165147c31730128b1c983e282a", size = 2539560, upload-time = "2026-01-29T23:03:48.738Z" }, + { url = "https://files.pythonhosted.org/packages/90/83/fb33dcea789ed6018f8da20c5a9bc9d82adc65c0c990faed43f7c955da46/debugpy-1.8.20-cp313-cp313-manylinux_2_34_x86_64.whl", hash = "sha256:84562982dd7cf5ebebfdea667ca20a064e096099997b175fe204e86817f64eaf", size = 4293272, upload-time = "2026-01-29T23:03:50.169Z" }, + { url = "https://files.pythonhosted.org/packages/a6/25/b1e4a01bfb824d79a6af24b99ef291e24189080c93576dfd9b1a2815cd0f/debugpy-1.8.20-cp313-cp313-win32.whl", hash = "sha256:da11dea6447b2cadbf8ce2bec59ecea87cc18d2c574980f643f2d2dfe4862393", size = 5331208, upload-time = "2026-01-29T23:03:51.547Z" }, + { url = "https://files.pythonhosted.org/packages/13/f7/a0b368ce54ffff9e9028c098bd2d28cfc5b54f9f6c186929083d4c60ba58/debugpy-1.8.20-cp313-cp313-win_amd64.whl", hash = "sha256:eb506e45943cab2efb7c6eafdd65b842f3ae779f020c82221f55aca9de135ed7", size = 5372930, upload-time = "2026-01-29T23:03:53.585Z" }, + { url = "https://files.pythonhosted.org/packages/33/2e/f6cb9a8a13f5058f0a20fe09711a7b726232cd5a78c6a7c05b2ec726cff9/debugpy-1.8.20-cp314-cp314-macosx_15_0_universal2.whl", hash = "sha256:9c74df62fc064cd5e5eaca1353a3ef5a5d50da5eb8058fcef63106f7bebe6173", size = 2538066, upload-time = "2026-01-29T23:03:54.999Z" }, + { url = "https://files.pythonhosted.org/packages/c5/56/6ddca50b53624e1ca3ce1d1e49ff22db46c47ea5fb4c0cc5c9b90a616364/debugpy-1.8.20-cp314-cp314-manylinux_2_34_x86_64.whl", hash = "sha256:077a7447589ee9bc1ff0cdf443566d0ecf540ac8aa7333b775ebcb8ce9f4ecad", size = 4269425, upload-time = "2026-01-29T23:03:56.518Z" }, + { url = "https://files.pythonhosted.org/packages/c5/d9/d64199c14a0d4c476df46c82470a3ce45c8d183a6796cfb5e66533b3663c/debugpy-1.8.20-cp314-cp314-win32.whl", hash = "sha256:352036a99dd35053b37b7803f748efc456076f929c6a895556932eaf2d23b07f", size = 5331407, upload-time = "2026-01-29T23:03:58.481Z" }, + { url = "https://files.pythonhosted.org/packages/e0/d9/1f07395b54413432624d61524dfd98c1a7c7827d2abfdb8829ac92638205/debugpy-1.8.20-cp314-cp314-win_amd64.whl", hash = "sha256:a98eec61135465b062846112e5ecf2eebb855305acc1dfbae43b72903b8ab5be", size = 5372521, upload-time = "2026-01-29T23:03:59.864Z" }, + { url = "https://files.pythonhosted.org/packages/e0/c3/7f67dea8ccf8fdcb9c99033bbe3e90b9e7395415843accb81428c441be2d/debugpy-1.8.20-py2.py3-none-any.whl", hash = "sha256:5be9bed9ae3be00665a06acaa48f8329d2b9632f15fd09f6a9a8c8d9907e54d7", size = 5337658, upload-time = "2026-01-29T23:04:17.404Z" }, +] + +[[package]] +name = "decorator" +version = "5.2.1" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/43/fa/6d96a0978d19e17b68d634497769987b16c8f4cd0a7a05048bec693caa6b/decorator-5.2.1.tar.gz", hash = "sha256:65f266143752f734b0a7cc83c46f4618af75b8c5911b00ccb61d0ac9b6da0360", size = 56711, upload-time = "2025-02-24T04:41:34.073Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/4e/8c/f3147f5c4b73e7550fe5f9352eaa956ae838d5c51eb58e7a25b9f3e2643b/decorator-5.2.1-py3-none-any.whl", hash = "sha256:d316bb415a2d9e2d2b3abcc4084c6502fc09240e292cd76a76afc106a1c8e04a", size = 9190, upload-time = "2025-02-24T04:41:32.565Z" }, +] + +[[package]] +name = "defusedxml" +version = "0.7.1" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/0f/d5/c66da9b79e5bdb124974bfe172b4daf3c984ebd9c2a06e2b8a4dc7331c72/defusedxml-0.7.1.tar.gz", hash = "sha256:1bb3032db185915b62d7c6209c5a8792be6a32ab2fedacc84e01b52c51aa3e69", size = 75520, upload-time = "2021-03-08T10:59:26.269Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/07/6c/aa3f2f849e01cb6a001cd8554a88d4c77c5c1a31c95bdf1cf9301e6d9ef4/defusedxml-0.7.1-py2.py3-none-any.whl", hash = "sha256:a352e7e428770286cc899e2542b6cdaedb2b4953ff269a210103ec58f6198a61", size = 25604, upload-time = "2021-03-08T10:59:24.45Z" }, +] + +[[package]] +name = "distlib" +version = "0.4.0" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/96/8e/709914eb2b5749865801041647dc7f4e6d00b549cfe88b65ca192995f07c/distlib-0.4.0.tar.gz", hash = "sha256:feec40075be03a04501a973d81f633735b4b69f98b05450592310c0f401a4e0d", size = 614605, upload-time = "2025-07-17T16:52:00.465Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/33/6b/e0547afaf41bf2c42e52430072fa5658766e3d65bd4b03a563d1b6336f57/distlib-0.4.0-py2.py3-none-any.whl", hash = "sha256:9659f7d87e46584a30b5780e43ac7a2143098441670ff0a49d5f9034c54a6c16", size = 469047, upload-time = "2025-07-17T16:51:58.613Z" }, +] + +[[package]] +name = "docutils" +version = "0.22.4" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/ae/b6/03bb70946330e88ffec97aefd3ea75ba575cb2e762061e0e62a213befee8/docutils-0.22.4.tar.gz", hash = "sha256:4db53b1fde9abecbb74d91230d32ab626d94f6badfc575d6db9194a49df29968", size = 2291750, upload-time = "2025-12-18T19:00:26.443Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/02/10/5da547df7a391dcde17f59520a231527b8571e6f46fc8efb02ccb370ab12/docutils-0.22.4-py3-none-any.whl", hash = "sha256:d0013f540772d1420576855455d050a2180186c91c15779301ac2ccb3eeb68de", size = 633196, upload-time = "2025-12-18T19:00:18.077Z" }, +] + +[[package]] +name = "donfig" +version = "0.8.1.post1" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "pyyaml" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/25/71/80cc718ff6d7abfbabacb1f57aaa42e9c1552bfdd01e64ddd704e4a03638/donfig-0.8.1.post1.tar.gz", hash = "sha256:3bef3413a4c1c601b585e8d297256d0c1470ea012afa6e8461dc28bfb7c23f52", size = 19506, upload-time = "2024-05-23T14:14:31.513Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/0c/d5/c5db1ea3394c6e1732fb3286b3bd878b59507a8f77d32a2cebda7d7b7cd4/donfig-0.8.1.post1-py3-none-any.whl", hash = "sha256:2a3175ce74a06109ff9307d90a230f81215cbac9a751f4d1c6194644b8204f9d", size = 21592, upload-time = "2024-05-23T14:13:55.283Z" }, +] + +[[package]] +name = "executing" +version = "2.2.1" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/cc/28/c14e053b6762b1044f34a13aab6859bbf40456d37d23aa286ac24cfd9a5d/executing-2.2.1.tar.gz", hash = "sha256:3632cc370565f6648cc328b32435bd120a1e4ebb20c77e3fdde9a13cd1e533c4", size = 1129488, upload-time = "2025-09-01T09:48:10.866Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/c1/ea/53f2148663b321f21b5a606bd5f191517cf40b7072c0497d3c92c4a13b1e/executing-2.2.1-py2.py3-none-any.whl", hash = "sha256:760643d3452b4d777d295bb167ccc74c64a81df23fb5e08eff250c425a4b2017", size = 28317, upload-time = "2025-09-01T09:48:08.5Z" }, +] + +[[package]] +name = "fast-array-utils" +version = "1.3.1" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "numpy", marker = "python_full_version >= '3.12'" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/1e/ff/93edc904b05a3260d5a690ac6dcdcd3cce10065b6fb56cdc683f80969456/fast_array_utils-1.3.1.tar.gz", hash = "sha256:34d175a63e9208c6fcbcb3cc18f75480ecdeaeed248759da0e74ab8fbcf55808", size = 330367, upload-time = "2025-11-18T10:20:32.016Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/5f/cb/ddcf4ad63ba88df95025837e35faf6ea6862bab1327f836801ba02140a22/fast_array_utils-1.3.1-py3-none-any.whl", hash = "sha256:7617322b29c9f3a8e4c046355ecf653bbee581245787243ea06212a1a56fa611", size = 36518, upload-time = "2025-11-18T10:20:30.777Z" }, +] + +[package.optional-dependencies] +accel = [ + { name = "numba", marker = "python_full_version >= '3.12'" }, +] +sparse = [ + { name = "scipy", marker = "python_full_version >= '3.12'" }, +] + +[[package]] +name = "fastjsonschema" +version = "2.21.2" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/20/b5/23b216d9d985a956623b6bd12d4086b60f0059b27799f23016af04a74ea1/fastjsonschema-2.21.2.tar.gz", hash = "sha256:b1eb43748041c880796cd077f1a07c3d94e93ae84bba5ed36800a33554ae05de", size = 374130, upload-time = "2025-08-14T18:49:36.666Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/cb/a8/20d0723294217e47de6d9e2e40fd4a9d2f7c4b6ef974babd482a59743694/fastjsonschema-2.21.2-py3-none-any.whl", hash = "sha256:1c797122d0a86c5cace2e54bf4e819c36223b552017172f32c5c024a6b77e463", size = 24024, upload-time = "2025-08-14T18:49:34.776Z" }, +] + +[[package]] +name = "filelock" +version = "3.24.3" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/73/92/a8e2479937ff39185d20dd6a851c1a63e55849e447a55e798cc2e1f49c65/filelock-3.24.3.tar.gz", hash = "sha256:011a5644dc937c22699943ebbfc46e969cdde3e171470a6e40b9533e5a72affa", size = 37935, upload-time = "2026-02-19T00:48:20.543Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/9c/0f/5d0c71a1aefeb08efff26272149e07ab922b64f46c63363756224bd6872e/filelock-3.24.3-py3-none-any.whl", hash = "sha256:426e9a4660391f7f8a810d71b0555bce9008b0a1cc342ab1f6947d37639e002d", size = 24331, upload-time = "2026-02-19T00:48:18.465Z" }, +] + +[[package]] +name = "flit" +version = "3.12.0" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "docutils" }, + { name = "flit-core" }, + { name = "pip" }, + { name = "requests" }, + { name = "tomli-w" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/50/9c/0608c91a5b6c013c63548515ae31cff6399cd9ce891bd9daee8c103da09b/flit-3.12.0.tar.gz", hash = "sha256:1c80f34dd96992e7758b40423d2809f48f640ca285d0b7821825e50745ec3740", size = 155038, upload-time = "2025-03-25T08:03:22.505Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/f5/82/ce1d3bb380b227e26e517655d1de7b32a72aad61fa21ff9bd91a2e2db6ee/flit-3.12.0-py3-none-any.whl", hash = "sha256:2b4e7171dc22881fa6adc2dbf083e5ecc72520be3cd7587d2a803da94d6ef431", size = 50657, upload-time = "2025-03-25T08:03:19.031Z" }, +] + +[[package]] +name = "flit-core" +version = "3.12.0" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/69/59/b6fc2188dfc7ea4f936cd12b49d707f66a1cb7a1d2c16172963534db741b/flit_core-3.12.0.tar.gz", hash = "sha256:18f63100d6f94385c6ed57a72073443e1a71a4acb4339491615d0f16d6ff01b2", size = 53690, upload-time = "2025-03-25T08:03:23.969Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/f2/65/b6ba90634c984a4fcc02c7e3afe523fef500c4980fec67cc27536ee50acf/flit_core-3.12.0-py3-none-any.whl", hash = "sha256:e7a0304069ea895172e3c7bb703292e992c5d1555dd1233ab7b5621b5b69e62c", size = 45594, upload-time = "2025-03-25T08:03:20.772Z" }, +] + +[[package]] +name = "fonttools" +version = "4.61.1" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/ec/ca/cf17b88a8df95691275a3d77dc0a5ad9907f328ae53acbe6795da1b2f5ed/fonttools-4.61.1.tar.gz", hash = "sha256:6675329885c44657f826ef01d9e4fb33b9158e9d93c537d84ad8399539bc6f69", size = 3565756, upload-time = "2025-12-12T17:31:24.246Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/69/12/bf9f4eaa2fad039356cc627587e30ed008c03f1cebd3034376b5ee8d1d44/fonttools-4.61.1-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:c6604b735bb12fef8e0efd5578c9fb5d3d8532d5001ea13a19cddf295673ee09", size = 2852213, upload-time = "2025-12-12T17:29:46.675Z" }, + { url = "https://files.pythonhosted.org/packages/ac/49/4138d1acb6261499bedde1c07f8c2605d1d8f9d77a151e5507fd3ef084b6/fonttools-4.61.1-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:5ce02f38a754f207f2f06557523cd39a06438ba3aafc0639c477ac409fc64e37", size = 2401689, upload-time = "2025-12-12T17:29:48.769Z" }, + { url = "https://files.pythonhosted.org/packages/e5/fe/e6ce0fe20a40e03aef906af60aa87668696f9e4802fa283627d0b5ed777f/fonttools-4.61.1-cp311-cp311-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:77efb033d8d7ff233385f30c62c7c79271c8885d5c9657d967ede124671bbdfb", size = 5058809, upload-time = "2025-12-12T17:29:51.701Z" }, + { url = "https://files.pythonhosted.org/packages/79/61/1ca198af22f7dd22c17ab86e9024ed3c06299cfdb08170640e9996d501a0/fonttools-4.61.1-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:75c1a6dfac6abd407634420c93864a1e274ebc1c7531346d9254c0d8f6ca00f9", size = 5036039, upload-time = "2025-12-12T17:29:53.659Z" }, + { url = "https://files.pythonhosted.org/packages/99/cc/fa1801e408586b5fce4da9f5455af8d770f4fc57391cd5da7256bb364d38/fonttools-4.61.1-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:0de30bfe7745c0d1ffa2b0b7048fb7123ad0d71107e10ee090fa0b16b9452e87", size = 5034714, upload-time = "2025-12-12T17:29:55.592Z" }, + { url = "https://files.pythonhosted.org/packages/bf/aa/b7aeafe65adb1b0a925f8f25725e09f078c635bc22754f3fecb7456955b0/fonttools-4.61.1-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:58b0ee0ab5b1fc9921eccfe11d1435added19d6494dde14e323f25ad2bc30c56", size = 5158648, upload-time = "2025-12-12T17:29:57.861Z" }, + { url = "https://files.pythonhosted.org/packages/99/f9/08ea7a38663328881384c6e7777bbefc46fd7d282adfd87a7d2b84ec9d50/fonttools-4.61.1-cp311-cp311-win32.whl", hash = "sha256:f79b168428351d11e10c5aeb61a74e1851ec221081299f4cf56036a95431c43a", size = 2280681, upload-time = "2025-12-12T17:29:59.943Z" }, + { url = "https://files.pythonhosted.org/packages/07/ad/37dd1ae5fa6e01612a1fbb954f0927681f282925a86e86198ccd7b15d515/fonttools-4.61.1-cp311-cp311-win_amd64.whl", hash = "sha256:fe2efccb324948a11dd09d22136fe2ac8a97d6c1347cf0b58a911dcd529f66b7", size = 2331951, upload-time = "2025-12-12T17:30:02.254Z" }, + { url = "https://files.pythonhosted.org/packages/6f/16/7decaa24a1bd3a70c607b2e29f0adc6159f36a7e40eaba59846414765fd4/fonttools-4.61.1-cp312-cp312-macosx_10_13_universal2.whl", hash = "sha256:f3cb4a569029b9f291f88aafc927dd53683757e640081ca8c412781ea144565e", size = 2851593, upload-time = "2025-12-12T17:30:04.225Z" }, + { url = "https://files.pythonhosted.org/packages/94/98/3c4cb97c64713a8cf499b3245c3bf9a2b8fd16a3e375feff2aed78f96259/fonttools-4.61.1-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:41a7170d042e8c0024703ed13b71893519a1a6d6e18e933e3ec7507a2c26a4b2", size = 2400231, upload-time = "2025-12-12T17:30:06.47Z" }, + { url = "https://files.pythonhosted.org/packages/b7/37/82dbef0f6342eb01f54bca073ac1498433d6ce71e50c3c3282b655733b31/fonttools-4.61.1-cp312-cp312-manylinux1_x86_64.manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_5_x86_64.whl", hash = "sha256:10d88e55330e092940584774ee5e8a6971b01fc2f4d3466a1d6c158230880796", size = 4954103, upload-time = "2025-12-12T17:30:08.432Z" }, + { url = "https://files.pythonhosted.org/packages/6c/44/f3aeac0fa98e7ad527f479e161aca6c3a1e47bb6996b053d45226fe37bf2/fonttools-4.61.1-cp312-cp312-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:15acc09befd16a0fb8a8f62bc147e1a82817542d72184acca9ce6e0aeda9fa6d", size = 5004295, upload-time = "2025-12-12T17:30:10.56Z" }, + { url = "https://files.pythonhosted.org/packages/14/e8/7424ced75473983b964d09f6747fa09f054a6d656f60e9ac9324cf40c743/fonttools-4.61.1-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:e6bcdf33aec38d16508ce61fd81838f24c83c90a1d1b8c68982857038673d6b8", size = 4944109, upload-time = "2025-12-12T17:30:12.874Z" }, + { url = "https://files.pythonhosted.org/packages/c8/8b/6391b257fa3d0b553d73e778f953a2f0154292a7a7a085e2374b111e5410/fonttools-4.61.1-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:5fade934607a523614726119164ff621e8c30e8fa1ffffbbd358662056ba69f0", size = 5093598, upload-time = "2025-12-12T17:30:15.79Z" }, + { url = "https://files.pythonhosted.org/packages/d9/71/fd2ea96cdc512d92da5678a1c98c267ddd4d8c5130b76d0f7a80f9a9fde8/fonttools-4.61.1-cp312-cp312-win32.whl", hash = "sha256:75da8f28eff26defba42c52986de97b22106cb8f26515b7c22443ebc9c2d3261", size = 2269060, upload-time = "2025-12-12T17:30:18.058Z" }, + { url = "https://files.pythonhosted.org/packages/80/3b/a3e81b71aed5a688e89dfe0e2694b26b78c7d7f39a5ffd8a7d75f54a12a8/fonttools-4.61.1-cp312-cp312-win_amd64.whl", hash = "sha256:497c31ce314219888c0e2fce5ad9178ca83fe5230b01a5006726cdf3ac9f24d9", size = 2319078, upload-time = "2025-12-12T17:30:22.862Z" }, + { url = "https://files.pythonhosted.org/packages/4b/cf/00ba28b0990982530addb8dc3e9e6f2fa9cb5c20df2abdda7baa755e8fe1/fonttools-4.61.1-cp313-cp313-macosx_10_13_universal2.whl", hash = "sha256:8c56c488ab471628ff3bfa80964372fc13504ece601e0d97a78ee74126b2045c", size = 2846454, upload-time = "2025-12-12T17:30:24.938Z" }, + { url = "https://files.pythonhosted.org/packages/5a/ca/468c9a8446a2103ae645d14fee3f610567b7042aba85031c1c65e3ef7471/fonttools-4.61.1-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:dc492779501fa723b04d0ab1f5be046797fee17d27700476edc7ee9ae535a61e", size = 2398191, upload-time = "2025-12-12T17:30:27.343Z" }, + { url = "https://files.pythonhosted.org/packages/a3/4b/d67eedaed19def5967fade3297fed8161b25ba94699efc124b14fb68cdbc/fonttools-4.61.1-cp313-cp313-manylinux1_x86_64.manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_5_x86_64.whl", hash = "sha256:64102ca87e84261419c3747a0d20f396eb024bdbeb04c2bfb37e2891f5fadcb5", size = 4928410, upload-time = "2025-12-12T17:30:29.771Z" }, + { url = "https://files.pythonhosted.org/packages/b0/8d/6fb3494dfe61a46258cd93d979cf4725ded4eb46c2a4ca35e4490d84daea/fonttools-4.61.1-cp313-cp313-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:4c1b526c8d3f615a7b1867f38a9410849c8f4aef078535742198e942fba0e9bd", size = 4984460, upload-time = "2025-12-12T17:30:32.073Z" }, + { url = "https://files.pythonhosted.org/packages/f7/f1/a47f1d30b3dc00d75e7af762652d4cbc3dff5c2697a0dbd5203c81afd9c3/fonttools-4.61.1-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:41ed4b5ec103bd306bb68f81dc166e77409e5209443e5773cb4ed837bcc9b0d3", size = 4925800, upload-time = "2025-12-12T17:30:34.339Z" }, + { url = "https://files.pythonhosted.org/packages/a7/01/e6ae64a0981076e8a66906fab01539799546181e32a37a0257b77e4aa88b/fonttools-4.61.1-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:b501c862d4901792adaec7c25b1ecc749e2662543f68bb194c42ba18d6eec98d", size = 5067859, upload-time = "2025-12-12T17:30:36.593Z" }, + { url = "https://files.pythonhosted.org/packages/73/aa/28e40b8d6809a9b5075350a86779163f074d2b617c15d22343fce81918db/fonttools-4.61.1-cp313-cp313-win32.whl", hash = "sha256:4d7092bb38c53bbc78e9255a59158b150bcdc115a1e3b3ce0b5f267dc35dd63c", size = 2267821, upload-time = "2025-12-12T17:30:38.478Z" }, + { url = "https://files.pythonhosted.org/packages/1a/59/453c06d1d83dc0951b69ef692d6b9f1846680342927df54e9a1ca91c6f90/fonttools-4.61.1-cp313-cp313-win_amd64.whl", hash = "sha256:21e7c8d76f62ab13c9472ccf74515ca5b9a761d1bde3265152a6dc58700d895b", size = 2318169, upload-time = "2025-12-12T17:30:40.951Z" }, + { url = "https://files.pythonhosted.org/packages/32/8f/4e7bf82c0cbb738d3c2206c920ca34ca74ef9dabde779030145d28665104/fonttools-4.61.1-cp314-cp314-macosx_10_15_universal2.whl", hash = "sha256:fff4f534200a04b4a36e7ae3cb74493afe807b517a09e99cb4faa89a34ed6ecd", size = 2846094, upload-time = "2025-12-12T17:30:43.511Z" }, + { url = "https://files.pythonhosted.org/packages/71/09/d44e45d0a4f3a651f23a1e9d42de43bc643cce2971b19e784cc67d823676/fonttools-4.61.1-cp314-cp314-macosx_10_15_x86_64.whl", hash = "sha256:d9203500f7c63545b4ce3799319fe4d9feb1a1b89b28d3cb5abd11b9dd64147e", size = 2396589, upload-time = "2025-12-12T17:30:45.681Z" }, + { url = "https://files.pythonhosted.org/packages/89/18/58c64cafcf8eb677a99ef593121f719e6dcbdb7d1c594ae5a10d4997ca8a/fonttools-4.61.1-cp314-cp314-manylinux1_x86_64.manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_5_x86_64.whl", hash = "sha256:fa646ecec9528bef693415c79a86e733c70a4965dd938e9a226b0fc64c9d2e6c", size = 4877892, upload-time = "2025-12-12T17:30:47.709Z" }, + { url = "https://files.pythonhosted.org/packages/8a/ec/9e6b38c7ba1e09eb51db849d5450f4c05b7e78481f662c3b79dbde6f3d04/fonttools-4.61.1-cp314-cp314-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:11f35ad7805edba3aac1a3710d104592df59f4b957e30108ae0ba6c10b11dd75", size = 4972884, upload-time = "2025-12-12T17:30:49.656Z" }, + { url = "https://files.pythonhosted.org/packages/5e/87/b5339da8e0256734ba0dbbf5b6cdebb1dd79b01dc8c270989b7bcd465541/fonttools-4.61.1-cp314-cp314-musllinux_1_2_aarch64.whl", hash = "sha256:b931ae8f62db78861b0ff1ac017851764602288575d65b8e8ff1963fed419063", size = 4924405, upload-time = "2025-12-12T17:30:51.735Z" }, + { url = "https://files.pythonhosted.org/packages/0b/47/e3409f1e1e69c073a3a6fd8cb886eb18c0bae0ee13db2c8d5e7f8495e8b7/fonttools-4.61.1-cp314-cp314-musllinux_1_2_x86_64.whl", hash = "sha256:b148b56f5de675ee16d45e769e69f87623a4944f7443850bf9a9376e628a89d2", size = 5035553, upload-time = "2025-12-12T17:30:54.823Z" }, + { url = "https://files.pythonhosted.org/packages/bf/b6/1f6600161b1073a984294c6c031e1a56ebf95b6164249eecf30012bb2e38/fonttools-4.61.1-cp314-cp314-win32.whl", hash = "sha256:9b666a475a65f4e839d3d10473fad6d47e0a9db14a2f4a224029c5bfde58ad2c", size = 2271915, upload-time = "2025-12-12T17:30:57.913Z" }, + { url = "https://files.pythonhosted.org/packages/52/7b/91e7b01e37cc8eb0e1f770d08305b3655e4f002fc160fb82b3390eabacf5/fonttools-4.61.1-cp314-cp314-win_amd64.whl", hash = "sha256:4f5686e1fe5fce75d82d93c47a438a25bf0d1319d2843a926f741140b2b16e0c", size = 2323487, upload-time = "2025-12-12T17:30:59.804Z" }, + { url = "https://files.pythonhosted.org/packages/39/5c/908ad78e46c61c3e3ed70c3b58ff82ab48437faf84ec84f109592cabbd9f/fonttools-4.61.1-cp314-cp314t-macosx_10_15_universal2.whl", hash = "sha256:e76ce097e3c57c4bcb67c5aa24a0ecdbd9f74ea9219997a707a4061fbe2707aa", size = 2929571, upload-time = "2025-12-12T17:31:02.574Z" }, + { url = "https://files.pythonhosted.org/packages/bd/41/975804132c6dea64cdbfbaa59f3518a21c137a10cccf962805b301ac6ab2/fonttools-4.61.1-cp314-cp314t-macosx_10_15_x86_64.whl", hash = "sha256:9cfef3ab326780c04d6646f68d4b4742aae222e8b8ea1d627c74e38afcbc9d91", size = 2435317, upload-time = "2025-12-12T17:31:04.974Z" }, + { url = "https://files.pythonhosted.org/packages/b0/5a/aef2a0a8daf1ebaae4cfd83f84186d4a72ee08fd6a8451289fcd03ffa8a4/fonttools-4.61.1-cp314-cp314t-manylinux1_x86_64.manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_5_x86_64.whl", hash = "sha256:a75c301f96db737e1c5ed5fd7d77d9c34466de16095a266509e13da09751bd19", size = 4882124, upload-time = "2025-12-12T17:31:07.456Z" }, + { url = "https://files.pythonhosted.org/packages/80/33/d6db3485b645b81cea538c9d1c9219d5805f0877fda18777add4671c5240/fonttools-4.61.1-cp314-cp314t-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:91669ccac46bbc1d09e9273546181919064e8df73488ea087dcac3e2968df9ba", size = 5100391, upload-time = "2025-12-12T17:31:09.732Z" }, + { url = "https://files.pythonhosted.org/packages/6c/d6/675ba631454043c75fcf76f0ca5463eac8eb0666ea1d7badae5fea001155/fonttools-4.61.1-cp314-cp314t-musllinux_1_2_aarch64.whl", hash = "sha256:c33ab3ca9d3ccd581d58e989d67554e42d8d4ded94ab3ade3508455fe70e65f7", size = 4978800, upload-time = "2025-12-12T17:31:11.681Z" }, + { url = "https://files.pythonhosted.org/packages/7f/33/d3ec753d547a8d2bdaedd390d4a814e8d5b45a093d558f025c6b990b554c/fonttools-4.61.1-cp314-cp314t-musllinux_1_2_x86_64.whl", hash = "sha256:664c5a68ec406f6b1547946683008576ef8b38275608e1cee6c061828171c118", size = 5006426, upload-time = "2025-12-12T17:31:13.764Z" }, + { url = "https://files.pythonhosted.org/packages/b4/40/cc11f378b561a67bea850ab50063366a0d1dd3f6d0a30ce0f874b0ad5664/fonttools-4.61.1-cp314-cp314t-win32.whl", hash = "sha256:aed04cabe26f30c1647ef0e8fbb207516fd40fe9472e9439695f5c6998e60ac5", size = 2335377, upload-time = "2025-12-12T17:31:16.49Z" }, + { url = "https://files.pythonhosted.org/packages/e4/ff/c9a2b66b39f8628531ea58b320d66d951267c98c6a38684daa8f50fb02f8/fonttools-4.61.1-cp314-cp314t-win_amd64.whl", hash = "sha256:2180f14c141d2f0f3da43f3a81bc8aa4684860f6b0e6f9e165a4831f24e6a23b", size = 2400613, upload-time = "2025-12-12T17:31:18.769Z" }, + { url = "https://files.pythonhosted.org/packages/c7/4e/ce75a57ff3aebf6fc1f4e9d508b8e5810618a33d900ad6c19eb30b290b97/fonttools-4.61.1-py3-none-any.whl", hash = "sha256:17d2bf5d541add43822bcf0c43d7d847b160c9bb01d15d5007d84e2217aaa371", size = 1148996, upload-time = "2025-12-12T17:31:21.03Z" }, +] + +[[package]] +name = "furo" +version = "2025.12.19" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "accessible-pygments" }, + { name = "beautifulsoup4" }, + { name = "pygments" }, + { name = "sphinx", version = "9.0.4", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.12'" }, + { name = "sphinx", version = "9.1.0", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.12'" }, + { name = "sphinx-basic-ng" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/ec/20/5f5ad4da6a5a27c80f2ed2ee9aee3f9e36c66e56e21c00fde467b2f8f88f/furo-2025.12.19.tar.gz", hash = "sha256:188d1f942037d8b37cd3985b955839fea62baa1730087dc29d157677c857e2a7", size = 1661473, upload-time = "2025-12-19T17:34:40.889Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/f4/b2/50e9b292b5cac13e9e81272c7171301abc753a60460d21505b606e15cf21/furo-2025.12.19-py3-none-any.whl", hash = "sha256:bb0ead5309f9500130665a26bee87693c41ce4dbdff864dbfb6b0dae4673d24f", size = 339262, upload-time = "2025-12-19T17:34:38.905Z" }, +] + +[[package]] +name = "google-crc32c" +version = "1.8.0" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/03/41/4b9c02f99e4c5fb477122cd5437403b552873f014616ac1d19ac8221a58d/google_crc32c-1.8.0.tar.gz", hash = "sha256:a428e25fb7691024de47fecfbff7ff957214da51eddded0da0ae0e0f03a2cf79", size = 14192, upload-time = "2025-12-16T00:35:25.142Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/5d/ef/21ccfaab3d5078d41efe8612e0ed0bfc9ce22475de074162a91a25f7980d/google_crc32c-1.8.0-cp311-cp311-macosx_12_0_arm64.whl", hash = "sha256:014a7e68d623e9a4222d663931febc3033c5c7c9730785727de2a81f87d5bab8", size = 31298, upload-time = "2025-12-16T00:20:32.241Z" }, + { url = "https://files.pythonhosted.org/packages/c5/b8/f8413d3f4b676136e965e764ceedec904fe38ae8de0cdc52a12d8eb1096e/google_crc32c-1.8.0-cp311-cp311-macosx_12_0_x86_64.whl", hash = "sha256:86cfc00fe45a0ac7359e5214a1704e51a99e757d0272554874f419f79838c5f7", size = 30872, upload-time = "2025-12-16T00:33:58.785Z" }, + { url = "https://files.pythonhosted.org/packages/f6/fd/33aa4ec62b290477181c55bb1c9302c9698c58c0ce9a6ab4874abc8b0d60/google_crc32c-1.8.0-cp311-cp311-manylinux1_x86_64.manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_5_x86_64.whl", hash = "sha256:19b40d637a54cb71e0829179f6cb41835f0fbd9e8eb60552152a8b52c36cbe15", size = 33243, upload-time = "2025-12-16T00:40:21.46Z" }, + { url = "https://files.pythonhosted.org/packages/71/03/4820b3bd99c9653d1a5210cb32f9ba4da9681619b4d35b6a052432df4773/google_crc32c-1.8.0-cp311-cp311-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:17446feb05abddc187e5441a45971b8394ea4c1b6efd88ab0af393fd9e0a156a", size = 33608, upload-time = "2025-12-16T00:40:22.204Z" }, + { url = "https://files.pythonhosted.org/packages/7c/43/acf61476a11437bf9733fb2f70599b1ced11ec7ed9ea760fdd9a77d0c619/google_crc32c-1.8.0-cp311-cp311-win_amd64.whl", hash = "sha256:71734788a88f551fbd6a97be9668a0020698e07b2bf5b3aa26a36c10cdfb27b2", size = 34439, upload-time = "2025-12-16T00:35:20.458Z" }, + { url = "https://files.pythonhosted.org/packages/e9/5f/7307325b1198b59324c0fa9807cafb551afb65e831699f2ce211ad5c8240/google_crc32c-1.8.0-cp312-cp312-macosx_12_0_arm64.whl", hash = "sha256:4b8286b659c1335172e39563ab0a768b8015e88e08329fa5321f774275fc3113", size = 31300, upload-time = "2025-12-16T00:21:56.723Z" }, + { url = "https://files.pythonhosted.org/packages/21/8e/58c0d5d86e2220e6a37befe7e6a94dd2f6006044b1a33edf1ff6d9f7e319/google_crc32c-1.8.0-cp312-cp312-macosx_12_0_x86_64.whl", hash = "sha256:2a3dc3318507de089c5384cc74d54318401410f82aa65b2d9cdde9d297aca7cb", size = 30867, upload-time = "2025-12-16T00:38:31.302Z" }, + { url = "https://files.pythonhosted.org/packages/ce/a9/a780cc66f86335a6019f557a8aaca8fbb970728f0efd2430d15ff1beae0e/google_crc32c-1.8.0-cp312-cp312-manylinux1_x86_64.manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_5_x86_64.whl", hash = "sha256:14f87e04d613dfa218d6135e81b78272c3b904e2a7053b841481b38a7d901411", size = 33364, upload-time = "2025-12-16T00:40:22.96Z" }, + { url = "https://files.pythonhosted.org/packages/21/3f/3457ea803db0198c9aaca2dd373750972ce28a26f00544b6b85088811939/google_crc32c-1.8.0-cp312-cp312-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:cb5c869c2923d56cb0c8e6bcdd73c009c36ae39b652dbe46a05eb4ef0ad01454", size = 33740, upload-time = "2025-12-16T00:40:23.96Z" }, + { url = "https://files.pythonhosted.org/packages/df/c0/87c2073e0c72515bb8733d4eef7b21548e8d189f094b5dad20b0ecaf64f6/google_crc32c-1.8.0-cp312-cp312-win_amd64.whl", hash = "sha256:3cc0c8912038065eafa603b238abf252e204accab2a704c63b9e14837a854962", size = 34437, upload-time = "2025-12-16T00:35:21.395Z" }, + { url = "https://files.pythonhosted.org/packages/d1/db/000f15b41724589b0e7bc24bc7a8967898d8d3bc8caf64c513d91ef1f6c0/google_crc32c-1.8.0-cp313-cp313-macosx_12_0_arm64.whl", hash = "sha256:3ebb04528e83b2634857f43f9bb8ef5b2bbe7f10f140daeb01b58f972d04736b", size = 31297, upload-time = "2025-12-16T00:23:20.709Z" }, + { url = "https://files.pythonhosted.org/packages/d7/0d/8ebed0c39c53a7e838e2a486da8abb0e52de135f1b376ae2f0b160eb4c1a/google_crc32c-1.8.0-cp313-cp313-macosx_12_0_x86_64.whl", hash = "sha256:450dc98429d3e33ed2926fc99ee81001928d63460f8538f21a5d6060912a8e27", size = 30867, upload-time = "2025-12-16T00:43:14.628Z" }, + { url = "https://files.pythonhosted.org/packages/ce/42/b468aec74a0354b34c8cbf748db20d6e350a68a2b0912e128cabee49806c/google_crc32c-1.8.0-cp313-cp313-manylinux1_x86_64.manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_5_x86_64.whl", hash = "sha256:3b9776774b24ba76831609ffbabce8cdf6fa2bd5e9df37b594221c7e333a81fa", size = 33344, upload-time = "2025-12-16T00:40:24.742Z" }, + { url = "https://files.pythonhosted.org/packages/1c/e8/b33784d6fc77fb5062a8a7854e43e1e618b87d5ddf610a88025e4de6226e/google_crc32c-1.8.0-cp313-cp313-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:89c17d53d75562edfff86679244830599ee0a48efc216200691de8b02ab6b2b8", size = 33694, upload-time = "2025-12-16T00:40:25.505Z" }, + { url = "https://files.pythonhosted.org/packages/92/b1/d3cbd4d988afb3d8e4db94ca953df429ed6db7282ed0e700d25e6c7bfc8d/google_crc32c-1.8.0-cp313-cp313-win_amd64.whl", hash = "sha256:57a50a9035b75643996fbf224d6661e386c7162d1dfdab9bc4ca790947d1007f", size = 34435, upload-time = "2025-12-16T00:35:22.107Z" }, + { url = "https://files.pythonhosted.org/packages/21/88/8ecf3c2b864a490b9e7010c84fd203ec8cf3b280651106a3a74dd1b0ca72/google_crc32c-1.8.0-cp314-cp314-macosx_12_0_arm64.whl", hash = "sha256:e6584b12cb06796d285d09e33f63309a09368b9d806a551d8036a4207ea43697", size = 31301, upload-time = "2025-12-16T00:24:48.527Z" }, + { url = "https://files.pythonhosted.org/packages/36/c6/f7ff6c11f5ca215d9f43d3629163727a272eabc356e5c9b2853df2bfe965/google_crc32c-1.8.0-cp314-cp314-macosx_12_0_x86_64.whl", hash = "sha256:f4b51844ef67d6cf2e9425983274da75f18b1597bb2c998e1c0a0e8d46f8f651", size = 30868, upload-time = "2025-12-16T00:48:12.163Z" }, + { url = "https://files.pythonhosted.org/packages/56/15/c25671c7aad70f8179d858c55a6ae8404902abe0cdcf32a29d581792b491/google_crc32c-1.8.0-cp314-cp314-manylinux1_x86_64.manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_5_x86_64.whl", hash = "sha256:b0d1a7afc6e8e4635564ba8aa5c0548e3173e41b6384d7711a9123165f582de2", size = 33381, upload-time = "2025-12-16T00:40:26.268Z" }, + { url = "https://files.pythonhosted.org/packages/42/fa/f50f51260d7b0ef5d4898af122d8a7ec5a84e2984f676f746445f783705f/google_crc32c-1.8.0-cp314-cp314-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:8b3f68782f3cbd1bce027e48768293072813469af6a61a86f6bb4977a4380f21", size = 33734, upload-time = "2025-12-16T00:40:27.028Z" }, + { url = "https://files.pythonhosted.org/packages/08/a5/7b059810934a09fb3ccb657e0843813c1fee1183d3bc2c8041800374aa2c/google_crc32c-1.8.0-cp314-cp314-win_amd64.whl", hash = "sha256:d511b3153e7011a27ab6ee6bb3a5404a55b994dc1a7322c0b87b29606d9790e2", size = 34878, upload-time = "2025-12-16T00:35:23.142Z" }, + { url = "https://files.pythonhosted.org/packages/52/c5/c171e4d8c44fec1422d801a6d2e5d7ddabd733eeda505c79730ee9607f07/google_crc32c-1.8.0-pp311-pypy311_pp73-manylinux1_x86_64.manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_5_x86_64.whl", hash = "sha256:87fa445064e7db928226b2e6f0d5304ab4cd0339e664a4e9a25029f384d9bb93", size = 28615, upload-time = "2025-12-16T00:40:29.298Z" }, + { url = "https://files.pythonhosted.org/packages/9c/97/7d75fe37a7a6ed171a2cf17117177e7aab7e6e0d115858741b41e9dd4254/google_crc32c-1.8.0-pp311-pypy311_pp73-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:f639065ea2042d5c034bf258a9f085eaa7af0cd250667c0635a3118e8f92c69c", size = 28800, upload-time = "2025-12-16T00:40:30.322Z" }, +] + +[[package]] +name = "h5py" +version = "3.15.1" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "numpy" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/4d/6a/0d79de0b025aa85dc8864de8e97659c94cf3d23148394a954dc5ca52f8c8/h5py-3.15.1.tar.gz", hash = "sha256:c86e3ed45c4473564de55aa83b6fc9e5ead86578773dfbd93047380042e26b69", size = 426236, upload-time = "2025-10-16T10:35:27.404Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/41/fd/8349b48b15b47768042cff06ad6e1c229f0a4bd89225bf6b6894fea27e6d/h5py-3.15.1-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:5aaa330bcbf2830150c50897ea5dcbed30b5b6d56897289846ac5b9e529ec243", size = 3434135, upload-time = "2025-10-16T10:33:47.954Z" }, + { url = "https://files.pythonhosted.org/packages/c1/b0/1c628e26a0b95858f54aba17e1599e7f6cd241727596cc2580b72cb0a9bf/h5py-3.15.1-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:c970fb80001fffabb0109eaf95116c8e7c0d3ca2de854e0901e8a04c1f098509", size = 2870958, upload-time = "2025-10-16T10:33:50.907Z" }, + { url = "https://files.pythonhosted.org/packages/f9/e3/c255cafc9b85e6ea04e2ad1bba1416baa1d7f57fc98a214be1144087690c/h5py-3.15.1-cp311-cp311-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:80e5bb5b9508d5d9da09f81fd00abbb3f85da8143e56b1585d59bc8ceb1dba8b", size = 4504770, upload-time = "2025-10-16T10:33:54.357Z" }, + { url = "https://files.pythonhosted.org/packages/8b/23/4ab1108e87851ccc69694b03b817d92e142966a6c4abd99e17db77f2c066/h5py-3.15.1-cp311-cp311-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:5b849ba619a066196169763c33f9f0f02e381156d61c03e000bb0100f9950faf", size = 4700329, upload-time = "2025-10-16T10:33:57.616Z" }, + { url = "https://files.pythonhosted.org/packages/a4/e4/932a3a8516e4e475b90969bf250b1924dbe3612a02b897e426613aed68f4/h5py-3.15.1-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:e7f6c841efd4e6e5b7e82222eaf90819927b6d256ab0f3aca29675601f654f3c", size = 4152456, upload-time = "2025-10-16T10:34:00.843Z" }, + { url = "https://files.pythonhosted.org/packages/2a/0a/f74d589883b13737021b2049ac796328f188dbb60c2ed35b101f5b95a3fc/h5py-3.15.1-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:ca8a3a22458956ee7b40d8e39c9a9dc01f82933e4c030c964f8b875592f4d831", size = 4617295, upload-time = "2025-10-16T10:34:04.154Z" }, + { url = "https://files.pythonhosted.org/packages/23/95/499b4e56452ef8b6c95a271af0dde08dac4ddb70515a75f346d4f400579b/h5py-3.15.1-cp311-cp311-win_amd64.whl", hash = "sha256:550e51131376889656feec4aff2170efc054a7fe79eb1da3bb92e1625d1ac878", size = 2882129, upload-time = "2025-10-16T10:34:06.886Z" }, + { url = "https://files.pythonhosted.org/packages/ce/bb/cfcc70b8a42222ba3ad4478bcef1791181ea908e2adbd7d53c66395edad5/h5py-3.15.1-cp311-cp311-win_arm64.whl", hash = "sha256:b39239947cb36a819147fc19e86b618dcb0953d1cd969f5ed71fc0de60392427", size = 2477121, upload-time = "2025-10-16T10:34:09.579Z" }, + { url = "https://files.pythonhosted.org/packages/62/b8/c0d9aa013ecfa8b7057946c080c0c07f6fa41e231d2e9bd306a2f8110bdc/h5py-3.15.1-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:316dd0f119734f324ca7ed10b5627a2de4ea42cc4dfbcedbee026aaa361c238c", size = 3399089, upload-time = "2025-10-16T10:34:12.135Z" }, + { url = "https://files.pythonhosted.org/packages/a4/5e/3c6f6e0430813c7aefe784d00c6711166f46225f5d229546eb53032c3707/h5py-3.15.1-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:b51469890e58e85d5242e43aab29f5e9c7e526b951caab354f3ded4ac88e7b76", size = 2847803, upload-time = "2025-10-16T10:34:14.564Z" }, + { url = "https://files.pythonhosted.org/packages/00/69/ba36273b888a4a48d78f9268d2aee05787e4438557450a8442946ab8f3ec/h5py-3.15.1-cp312-cp312-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:8a33bfd5dfcea037196f7778534b1ff7e36a7f40a89e648c8f2967292eb6898e", size = 4914884, upload-time = "2025-10-16T10:34:18.452Z" }, + { url = "https://files.pythonhosted.org/packages/3a/30/d1c94066343a98bb2cea40120873193a4fed68c4ad7f8935c11caf74c681/h5py-3.15.1-cp312-cp312-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:25c8843fec43b2cc368aa15afa1cdf83fc5e17b1c4e10cd3771ef6c39b72e5ce", size = 5109965, upload-time = "2025-10-16T10:34:21.853Z" }, + { url = "https://files.pythonhosted.org/packages/81/3d/d28172116eafc3bc9f5991b3cb3fd2c8a95f5984f50880adfdf991de9087/h5py-3.15.1-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:a308fd8681a864c04423c0324527237a0484e2611e3441f8089fd00ed56a8171", size = 4561870, upload-time = "2025-10-16T10:34:26.69Z" }, + { url = "https://files.pythonhosted.org/packages/a5/83/393a7226024238b0f51965a7156004eaae1fcf84aa4bfecf7e582676271b/h5py-3.15.1-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:f4a016df3f4a8a14d573b496e4d1964deb380e26031fc85fb40e417e9131888a", size = 5037161, upload-time = "2025-10-16T10:34:30.383Z" }, + { url = "https://files.pythonhosted.org/packages/cf/51/329e7436bf87ca6b0fe06dd0a3795c34bebe4ed8d6c44450a20565d57832/h5py-3.15.1-cp312-cp312-win_amd64.whl", hash = "sha256:59b25cf02411bf12e14f803fef0b80886444c7fe21a5ad17c6a28d3f08098a1e", size = 2874165, upload-time = "2025-10-16T10:34:33.461Z" }, + { url = "https://files.pythonhosted.org/packages/09/a8/2d02b10a66747c54446e932171dd89b8b4126c0111b440e6bc05a7c852ec/h5py-3.15.1-cp312-cp312-win_arm64.whl", hash = "sha256:61d5a58a9851e01ee61c932bbbb1c98fe20aba0a5674776600fb9a361c0aa652", size = 2458214, upload-time = "2025-10-16T10:34:35.733Z" }, + { url = "https://files.pythonhosted.org/packages/88/b3/40207e0192415cbff7ea1d37b9f24b33f6d38a5a2f5d18a678de78f967ae/h5py-3.15.1-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:c8440fd8bee9500c235ecb7aa1917a0389a2adb80c209fa1cc485bd70e0d94a5", size = 3376511, upload-time = "2025-10-16T10:34:38.596Z" }, + { url = "https://files.pythonhosted.org/packages/31/96/ba99a003c763998035b0de4c299598125df5fc6c9ccf834f152ddd60e0fb/h5py-3.15.1-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:ab2219dbc6fcdb6932f76b548e2b16f34a1f52b7666e998157a4dfc02e2c4123", size = 2826143, upload-time = "2025-10-16T10:34:41.342Z" }, + { url = "https://files.pythonhosted.org/packages/6a/c2/fc6375d07ea3962df7afad7d863fe4bde18bb88530678c20d4c90c18de1d/h5py-3.15.1-cp313-cp313-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:d8cb02c3a96255149ed3ac811eeea25b655d959c6dd5ce702c9a95ff11859eb5", size = 4908316, upload-time = "2025-10-16T10:34:44.619Z" }, + { url = "https://files.pythonhosted.org/packages/d9/69/4402ea66272dacc10b298cca18ed73e1c0791ff2ae9ed218d3859f9698ac/h5py-3.15.1-cp313-cp313-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:121b2b7a4c1915d63737483b7bff14ef253020f617c2fb2811f67a4bed9ac5e8", size = 5103710, upload-time = "2025-10-16T10:34:48.639Z" }, + { url = "https://files.pythonhosted.org/packages/e0/f6/11f1e2432d57d71322c02a97a5567829a75f223a8c821764a0e71a65cde8/h5py-3.15.1-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:59b0d63b318bf3cc06687def2b45afd75926bbc006f7b8cd2b1a231299fc8599", size = 4556042, upload-time = "2025-10-16T10:34:51.841Z" }, + { url = "https://files.pythonhosted.org/packages/18/88/3eda3ef16bfe7a7dbc3d8d6836bbaa7986feb5ff091395e140dc13927bcc/h5py-3.15.1-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:e02fe77a03f652500d8bff288cbf3675f742fc0411f5a628fa37116507dc7cc0", size = 5030639, upload-time = "2025-10-16T10:34:55.257Z" }, + { url = "https://files.pythonhosted.org/packages/e5/ea/fbb258a98863f99befb10ed727152b4ae659f322e1d9c0576f8a62754e81/h5py-3.15.1-cp313-cp313-win_amd64.whl", hash = "sha256:dea78b092fd80a083563ed79a3171258d4a4d307492e7cf8b2313d464c82ba52", size = 2864363, upload-time = "2025-10-16T10:34:58.099Z" }, + { url = "https://files.pythonhosted.org/packages/5d/c9/35021cc9cd2b2915a7da3026e3d77a05bed1144a414ff840953b33937fb9/h5py-3.15.1-cp313-cp313-win_arm64.whl", hash = "sha256:c256254a8a81e2bddc0d376e23e2a6d2dc8a1e8a2261835ed8c1281a0744cd97", size = 2449570, upload-time = "2025-10-16T10:35:00.473Z" }, + { url = "https://files.pythonhosted.org/packages/a0/2c/926eba1514e4d2e47d0e9eb16c784e717d8b066398ccfca9b283917b1bfb/h5py-3.15.1-cp314-cp314-macosx_10_15_x86_64.whl", hash = "sha256:5f4fb0567eb8517c3ecd6b3c02c4f4e9da220c8932604960fd04e24ee1254763", size = 3380368, upload-time = "2025-10-16T10:35:03.117Z" }, + { url = "https://files.pythonhosted.org/packages/65/4b/d715ed454d3baa5f6ae1d30b7eca4c7a1c1084f6a2edead9e801a1541d62/h5py-3.15.1-cp314-cp314-macosx_11_0_arm64.whl", hash = "sha256:954e480433e82d3872503104f9b285d369048c3a788b2b1a00e53d1c47c98dd2", size = 2833793, upload-time = "2025-10-16T10:35:05.623Z" }, + { url = "https://files.pythonhosted.org/packages/ef/d4/ef386c28e4579314610a8bffebbee3b69295b0237bc967340b7c653c6c10/h5py-3.15.1-cp314-cp314-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:fd125c131889ebbef0849f4a0e29cf363b48aba42f228d08b4079913b576bb3a", size = 4903199, upload-time = "2025-10-16T10:35:08.972Z" }, + { url = "https://files.pythonhosted.org/packages/33/5d/65c619e195e0b5e54ea5a95c1bb600c8ff8715e0d09676e4cce56d89f492/h5py-3.15.1-cp314-cp314-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:28a20e1a4082a479b3d7db2169f3a5034af010b90842e75ebbf2e9e49eb4183e", size = 5097224, upload-time = "2025-10-16T10:35:12.808Z" }, + { url = "https://files.pythonhosted.org/packages/30/30/5273218400bf2da01609e1292f562c94b461fcb73c7a9e27fdadd43abc0a/h5py-3.15.1-cp314-cp314-musllinux_1_2_aarch64.whl", hash = "sha256:fa8df5267f545b4946df8ca0d93d23382191018e4cda2deda4c2cedf9a010e13", size = 4551207, upload-time = "2025-10-16T10:35:16.24Z" }, + { url = "https://files.pythonhosted.org/packages/d3/39/a7ef948ddf4d1c556b0b2b9559534777bccc318543b3f5a1efdf6b556c9c/h5py-3.15.1-cp314-cp314-musllinux_1_2_x86_64.whl", hash = "sha256:99d374a21f7321a4c6ab327c4ab23bd925ad69821aeb53a1e75dd809d19f67fa", size = 5025426, upload-time = "2025-10-16T10:35:19.831Z" }, + { url = "https://files.pythonhosted.org/packages/b6/d8/7368679b8df6925b8415f9dcc9ab1dab01ddc384d2b2c24aac9191bd9ceb/h5py-3.15.1-cp314-cp314-win_amd64.whl", hash = "sha256:9c73d1d7cdb97d5b17ae385153472ce118bed607e43be11e9a9deefaa54e0734", size = 2865704, upload-time = "2025-10-16T10:35:22.658Z" }, + { url = "https://files.pythonhosted.org/packages/d3/b7/4a806f85d62c20157e62e58e03b27513dc9c55499768530acc4f4c5ce4be/h5py-3.15.1-cp314-cp314-win_arm64.whl", hash = "sha256:a6d8c5a05a76aca9a494b4c53ce8a9c29023b7f64f625c6ce1841e92a362ccdf", size = 2465544, upload-time = "2025-10-16T10:35:25.695Z" }, +] + +[[package]] +name = "id" +version = "1.6.1" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "urllib3" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/6d/04/c2156091427636080787aac190019dc64096e56a23b7364d3c1764ee3a06/id-1.6.1.tar.gz", hash = "sha256:d0732d624fb46fd4e7bc4e5152f00214450953b9e772c182c1c22964def1a069", size = 18088, upload-time = "2026-02-04T16:19:41.26Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/42/77/de194443bf38daed9452139e960c632b0ef9f9a5dd9ce605fdf18ca9f1b1/id-1.6.1-py3-none-any.whl", hash = "sha256:f5ec41ed2629a508f5d0988eda142e190c9c6da971100612c4de9ad9f9b237ca", size = 14689, upload-time = "2026-02-04T16:19:40.051Z" }, +] + +[[package]] +name = "identify" +version = "2.6.16" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/5b/8d/e8b97e6bd3fb6fb271346f7981362f1e04d6a7463abd0de79e1fda17c067/identify-2.6.16.tar.gz", hash = "sha256:846857203b5511bbe94d5a352a48ef2359532bc8f6727b5544077a0dcfb24980", size = 99360, upload-time = "2026-01-12T18:58:58.201Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/b8/58/40fbbcefeda82364720eba5cf2270f98496bdfa19ea75b4cccae79c698e6/identify-2.6.16-py2.py3-none-any.whl", hash = "sha256:391ee4d77741d994189522896270b787aed8670389bfd60f326d677d64a6dfb0", size = 99202, upload-time = "2026-01-12T18:58:56.627Z" }, +] + +[[package]] +name = "idna" +version = "3.11" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/6f/6d/0703ccc57f3a7233505399edb88de3cbd678da106337b9fcde432b65ed60/idna-3.11.tar.gz", hash = "sha256:795dafcc9c04ed0c1fb032c2aa73654d8e8c5023a7df64a53f39190ada629902", size = 194582, upload-time = "2025-10-12T14:55:20.501Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/0e/61/66938bbb5fc52dbdf84594873d5b51fb1f7c7794e9c0f5bd885f30bc507b/idna-3.11-py3-none-any.whl", hash = "sha256:771a87f49d9defaf64091e6e6fe9c18d4833f140bd19464795bc32d966ca37ea", size = 71008, upload-time = "2025-10-12T14:55:18.883Z" }, +] + +[[package]] +name = "igraph" +version = "1.0.0" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "texttable" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/23/be/56bef1919005b4caf1f71522b300d359f7faeb7ae93a3b0baa9b4f146a87/igraph-1.0.0.tar.gz", hash = "sha256:2414d0be2e4d77ee5357807d100974b40f6082bb1bb71988ec46cfb6728651ee", size = 5077105, upload-time = "2025-10-23T12:22:50.127Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/a5/03/3278ad0ceb3ea0e84d8ae3a85bdded4d0e57853aeb802a200feb43847b93/igraph-1.0.0-cp39-abi3-macosx_10_15_x86_64.whl", hash = "sha256:c2cbc415e02523e5a241eecee82319080bf928a70b1ba299f3b3e25bf029b6d4", size = 2257415, upload-time = "2025-10-23T12:22:27.246Z" }, + { url = "https://files.pythonhosted.org/packages/0d/bc/6281ec7f9baaf71ee57c3b1748da2d3148d15d253e1a03006f204aa68ca5/igraph-1.0.0-cp39-abi3-macosx_11_0_arm64.whl", hash = "sha256:1a27753cd80680a8f676c2d5a467aaa4a95e510b30748398ec4e4aeb982130e8", size = 2048555, upload-time = "2025-10-23T12:22:29.49Z" }, + { url = "https://files.pythonhosted.org/packages/2a/38/3cd6428a4ed4c09a56df05998438e7774fd1d799ee4fb8fc481674f5f7fc/igraph-1.0.0-cp39-abi3-manylinux_2_28_aarch64.whl", hash = "sha256:a55dc3a2a4e3fc3eba42479910c1511bfc3ecb33cdf5f0406891fd85f14b5aee", size = 5314141, upload-time = "2025-10-23T12:22:31.023Z" }, + { url = "https://files.pythonhosted.org/packages/7d/da/dd2867c25adbb41563720f14b5fc895c98bf88be682a3faff4f7b3118d2a/igraph-1.0.0-cp39-abi3-manylinux_2_28_x86_64.whl", hash = "sha256:2d04c2c76f686fb1f554ee35dfd3085f5e73b7965ba6b4cf06d53e66b1955522", size = 5683134, upload-time = "2025-10-23T12:22:32.423Z" }, + { url = "https://files.pythonhosted.org/packages/e5/40/243c118d34ab80382d7009c4dcb99b887384c3d2ce84d29eeac19e2a007a/igraph-1.0.0-cp39-abi3-musllinux_1_2_aarch64.whl", hash = "sha256:f2b52dc1757fff0fed29a9f7a276d971a11db4211569ed78b9eab36288dfcc9d", size = 6211583, upload-time = "2025-10-23T12:22:34.238Z" }, + { url = "https://files.pythonhosted.org/packages/1d/b7/88f433819c54b496cb0315fce28e658970cb20ff5dbd52a5a605ce2888de/igraph-1.0.0-cp39-abi3-musllinux_1_2_x86_64.whl", hash = "sha256:05c79a2a8fca695b2f217a6fa7f2549f896f757d4db41be32a055400cb19cc30", size = 6594509, upload-time = "2025-10-23T12:22:35.831Z" }, + { url = "https://files.pythonhosted.org/packages/7b/5d/8f7f6f619d374e959aa3664ebc4b24c10abc90c2e8efbed97f2623fadaf5/igraph-1.0.0-cp39-abi3-win32.whl", hash = "sha256:c2bce3cd472fec3dd9c4d8a3ea5b6b9be65fb30edf760beb4850760dd4f2d479", size = 2725406, upload-time = "2025-10-23T12:22:37.588Z" }, + { url = "https://files.pythonhosted.org/packages/af/77/a85b3745cf40a0572bae2de8cd9c2a2a8af78e5cf3e880fc0a249114e609/igraph-1.0.0-cp39-abi3-win_amd64.whl", hash = "sha256:faeff8ede0cf15eb4ded44b0fcea6e1886740146e60504c24ad2da14e0939563", size = 3221663, upload-time = "2025-10-23T12:22:39.404Z" }, + { url = "https://files.pythonhosted.org/packages/ef/7e/5df541c37bdf6493035e89c22bd53f30d99b291bcda6c78e9a8afeecec2b/igraph-1.0.0-cp39-abi3-win_arm64.whl", hash = "sha256:b607cafc24b10a615e713ee96e58208ef27e0764af80140c7cc45d4724a3f2df", size = 2785701, upload-time = "2025-10-23T12:22:41.03Z" }, + { url = "https://files.pythonhosted.org/packages/b9/73/bf1d4dbbc9123435b3ca14bb608b243a50a4f158ecea564bf196715248d9/igraph-1.0.0-pp311-pypy311_pp73-macosx_10_15_x86_64.whl", hash = "sha256:3189c1a8e8a8f58009f3f729040eb3701254d074ed37245691d529869ec940c5", size = 2246636, upload-time = "2025-10-23T12:22:42.314Z" }, + { url = "https://files.pythonhosted.org/packages/59/ac/28482f2af45cc0a0ca88a69d17a6ea694f58bdbd22cc876e7273a0379282/igraph-1.0.0-pp311-pypy311_pp73-macosx_11_0_arm64.whl", hash = "sha256:ebe9502689b946301584b3cfacdbc70c58c4d664d804e39b6daa31be5c20bf46", size = 2036101, upload-time = "2025-10-23T12:22:43.957Z" }, + { url = "https://files.pythonhosted.org/packages/56/80/806a093df1d1ddc3b30d0418b1ee56388ae7018f8ae288677ee2b3a1abaf/igraph-1.0.0-pp311-pypy311_pp73-manylinux_2_28_aarch64.whl", hash = "sha256:f117683108c54330d6dc67a708e3724c13c9989885122a29781296872989a222", size = 3053403, upload-time = "2025-10-23T12:22:45.573Z" }, + { url = "https://files.pythonhosted.org/packages/56/bf/cf7aeff230a4368c0b8bc6b02f3ea27db41db33714b51e1e8a7c1458f31b/igraph-1.0.0-pp311-pypy311_pp73-manylinux_2_28_x86_64.whl", hash = "sha256:077dbff0edb8b4ce0f9fefdf325200346d9d5db02de31872b41743de08e67a16", size = 3262472, upload-time = "2025-10-23T12:22:47.248Z" }, + { url = "https://files.pythonhosted.org/packages/d8/ca/dbc06072d5eea402a6dc81f387afb1b7e0c415f1d8a75232943fc4d1bfdb/igraph-1.0.0-pp311-pypy311_pp73-win_amd64.whl", hash = "sha256:fe7c693b2a84a4e03ca31e65aa05a2ecd8728137fa9909ccbf6453b4200b856d", size = 3218861, upload-time = "2025-10-23T12:22:48.46Z" }, +] + +[[package]] +name = "imagesize" +version = "1.4.1" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/a7/84/62473fb57d61e31fef6e36d64a179c8781605429fd927b5dd608c997be31/imagesize-1.4.1.tar.gz", hash = "sha256:69150444affb9cb0d5cc5a92b3676f0b2fb7cd9ae39e947a5e11a36b4497cd4a", size = 1280026, upload-time = "2022-07-01T12:21:05.687Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/ff/62/85c4c919272577931d407be5ba5d71c20f0b616d31a0befe0ae45bb79abd/imagesize-1.4.1-py2.py3-none-any.whl", hash = "sha256:0d8d18d08f840c19d0ee7ca1fd82490fdc3729b7ac93f49870406ddde8ef8d8b", size = 8769, upload-time = "2022-07-01T12:21:02.467Z" }, +] + +[[package]] +name = "importlib-metadata" +version = "8.7.1" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "zipp", marker = "python_full_version < '3.12'" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/f3/49/3b30cad09e7771a4982d9975a8cbf64f00d4a1ececb53297f1d9a7be1b10/importlib_metadata-8.7.1.tar.gz", hash = "sha256:49fef1ae6440c182052f407c8d34a68f72efc36db9ca90dc0113398f2fdde8bb", size = 57107, upload-time = "2025-12-21T10:00:19.278Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/fa/5e/f8e9a1d23b9c20a551a8a02ea3637b4642e22c2626e3a13a9a29cdea99eb/importlib_metadata-8.7.1-py3-none-any.whl", hash = "sha256:5a1f80bf1daa489495071efbb095d75a634cf28a8bc299581244063b53176151", size = 27865, upload-time = "2025-12-21T10:00:18.329Z" }, +] + +[[package]] +name = "iniconfig" +version = "2.3.0" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/72/34/14ca021ce8e5dfedc35312d08ba8bf51fdd999c576889fc2c24cb97f4f10/iniconfig-2.3.0.tar.gz", hash = "sha256:c76315c77db068650d49c5b56314774a7804df16fee4402c1f19d6d15d8c4730", size = 20503, upload-time = "2025-10-18T21:55:43.219Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/cb/b1/3846dd7f199d53cb17f49cba7e651e9ce294d8497c8c150530ed11865bb8/iniconfig-2.3.0-py3-none-any.whl", hash = "sha256:f631c04d2c48c52b84d0d0549c99ff3859c98df65b3101406327ecc7d53fbf12", size = 7484, upload-time = "2025-10-18T21:55:41.639Z" }, +] + +[[package]] +name = "ipykernel" +version = "7.2.0" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "appnope", marker = "sys_platform == 'darwin'" }, + { name = "comm" }, + { name = "debugpy" }, + { name = "ipython" }, + { name = "jupyter-client" }, + { name = "jupyter-core" }, + { name = "matplotlib-inline" }, + { name = "nest-asyncio" }, + { name = "packaging" }, + { name = "psutil" }, + { name = "pyzmq" }, + { name = "tornado" }, + { name = "traitlets" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/ca/8d/b68b728e2d06b9e0051019640a40a9eb7a88fcd82c2e1b5ce70bef5ff044/ipykernel-7.2.0.tar.gz", hash = "sha256:18ed160b6dee2cbb16e5f3575858bc19d8f1fe6046a9a680c708494ce31d909e", size = 176046, upload-time = "2026-02-06T16:43:27.403Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/82/b9/e73d5d9f405cba7706c539aa8b311b49d4c2f3d698d9c12f815231169c71/ipykernel-7.2.0-py3-none-any.whl", hash = "sha256:3bbd4420d2b3cc105cbdf3756bfc04500b1e52f090a90716851f3916c62e1661", size = 118788, upload-time = "2026-02-06T16:43:25.149Z" }, +] + +[[package]] +name = "ipython" +version = "9.10.0" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "colorama", marker = "sys_platform == 'win32'" }, + { name = "decorator" }, + { name = "ipython-pygments-lexers" }, + { name = "jedi" }, + { name = "matplotlib-inline" }, + { name = "pexpect", marker = "sys_platform != 'emscripten' and sys_platform != 'win32'" }, + { name = "prompt-toolkit" }, + { name = "pygments" }, + { name = "stack-data" }, + { name = "traitlets" }, + { name = "typing-extensions", marker = "python_full_version < '3.12'" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/a6/60/2111715ea11f39b1535bed6024b7dec7918b71e5e5d30855a5b503056b50/ipython-9.10.0.tar.gz", hash = "sha256:cd9e656be97618a0676d058134cd44e6dc7012c0e5cb36a9ce96a8c904adaf77", size = 4426526, upload-time = "2026-02-02T10:00:33.594Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/3d/aa/898dec789a05731cd5a9f50605b7b44a72bd198fd0d4528e11fc610177cc/ipython-9.10.0-py3-none-any.whl", hash = "sha256:c6ab68cc23bba8c7e18e9b932797014cc61ea7fd6f19de180ab9ba73e65ee58d", size = 622774, upload-time = "2026-02-02T10:00:31.503Z" }, +] + +[[package]] +name = "ipython-pygments-lexers" +version = "1.1.1" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "pygments" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/ef/4c/5dd1d8af08107f88c7f741ead7a40854b8ac24ddf9ae850afbcf698aa552/ipython_pygments_lexers-1.1.1.tar.gz", hash = "sha256:09c0138009e56b6854f9535736f4171d855c8c08a563a0dcd8022f78355c7e81", size = 8393, upload-time = "2025-01-17T11:24:34.505Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/d9/33/1f075bf72b0b747cb3288d011319aaf64083cf2efef8354174e3ed4540e2/ipython_pygments_lexers-1.1.1-py3-none-any.whl", hash = "sha256:a9462224a505ade19a605f71f8fa63c2048833ce50abc86768a0d81d876dc81c", size = 8074, upload-time = "2025-01-17T11:24:33.271Z" }, +] + +[[package]] +name = "ipywidgets" +version = "8.1.8" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "comm" }, + { name = "ipython" }, + { name = "jupyterlab-widgets" }, + { name = "traitlets" }, + { name = "widgetsnbextension" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/4c/ae/c5ce1edc1afe042eadb445e95b0671b03cee61895264357956e61c0d2ac0/ipywidgets-8.1.8.tar.gz", hash = "sha256:61f969306b95f85fba6b6986b7fe45d73124d1d9e3023a8068710d47a22ea668", size = 116739, upload-time = "2025-11-01T21:18:12.393Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/56/6d/0d9848617b9f753b87f214f1c682592f7ca42de085f564352f10f0843026/ipywidgets-8.1.8-py3-none-any.whl", hash = "sha256:ecaca67aed704a338f88f67b1181b58f821ab5dc89c1f0f5ef99db43c1c2921e", size = 139808, upload-time = "2025-11-01T21:18:10.956Z" }, +] + +[[package]] +name = "jaraco-classes" +version = "3.4.0" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "more-itertools" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/06/c0/ed4a27bc5571b99e3cff68f8a9fa5b56ff7df1c2251cc715a652ddd26402/jaraco.classes-3.4.0.tar.gz", hash = "sha256:47a024b51d0239c0dd8c8540c6c7f484be3b8fcf0b2d85c13825780d3b3f3acd", size = 11780, upload-time = "2024-03-31T07:27:36.643Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/7f/66/b15ce62552d84bbfcec9a4873ab79d993a1dd4edb922cbfccae192bd5b5f/jaraco.classes-3.4.0-py3-none-any.whl", hash = "sha256:f662826b6bed8cace05e7ff873ce0f9283b5c924470fe664fff1c2f00f581790", size = 6777, upload-time = "2024-03-31T07:27:34.792Z" }, +] + +[[package]] +name = "jaraco-context" +version = "6.1.0" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "backports-tarfile", marker = "python_full_version < '3.12'" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/cb/9c/a788f5bb29c61e456b8ee52ce76dbdd32fd72cd73dd67bc95f42c7a8d13c/jaraco_context-6.1.0.tar.gz", hash = "sha256:129a341b0a85a7db7879e22acd66902fda67882db771754574338898b2d5d86f", size = 15850, upload-time = "2026-01-13T02:53:53.847Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/8d/48/aa685dbf1024c7bd82bede569e3a85f82c32fd3d79ba5fea578f0159571a/jaraco_context-6.1.0-py3-none-any.whl", hash = "sha256:a43b5ed85815223d0d3cfdb6d7ca0d2bc8946f28f30b6f3216bda070f68badda", size = 7065, upload-time = "2026-01-13T02:53:53.031Z" }, +] + +[[package]] +name = "jaraco-functools" +version = "4.4.0" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "more-itertools" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/0f/27/056e0638a86749374d6f57d0b0db39f29509cce9313cf91bdc0ac4d91084/jaraco_functools-4.4.0.tar.gz", hash = "sha256:da21933b0417b89515562656547a77b4931f98176eb173644c0d35032a33d6bb", size = 19943, upload-time = "2025-12-21T09:29:43.6Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/fd/c4/813bb09f0985cb21e959f21f2464169eca882656849adf727ac7bb7e1767/jaraco_functools-4.4.0-py3-none-any.whl", hash = "sha256:9eec1e36f45c818d9bf307c8948eb03b2b56cd44087b3cdc989abca1f20b9176", size = 10481, upload-time = "2025-12-21T09:29:42.27Z" }, +] + +[[package]] +name = "jedi" +version = "0.19.2" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "parso" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/72/3a/79a912fbd4d8dd6fbb02bf69afd3bb72cf0c729bb3063c6f4498603db17a/jedi-0.19.2.tar.gz", hash = "sha256:4770dc3de41bde3966b02eb84fbcf557fb33cce26ad23da12c742fb50ecb11f0", size = 1231287, upload-time = "2024-11-11T01:41:42.873Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/c0/5a/9cac0c82afec3d09ccd97c8b6502d48f165f9124db81b4bcb90b4af974ee/jedi-0.19.2-py2.py3-none-any.whl", hash = "sha256:a8ef22bde8490f57fe5c7681a3c83cb58874daf72b4784de3cce5b6ef6edb5b9", size = 1572278, upload-time = "2024-11-11T01:41:40.175Z" }, +] + +[[package]] +name = "jeepney" +version = "0.9.0" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/7b/6f/357efd7602486741aa73ffc0617fb310a29b588ed0fd69c2399acbb85b0c/jeepney-0.9.0.tar.gz", hash = "sha256:cf0e9e845622b81e4a28df94c40345400256ec608d0e55bb8a3feaa9163f5732", size = 106758, upload-time = "2025-02-27T18:51:01.684Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/b2/a3/e137168c9c44d18eff0376253da9f1e9234d0239e0ee230d2fee6cea8e55/jeepney-0.9.0-py3-none-any.whl", hash = "sha256:97e5714520c16fc0a45695e5365a2e11b81ea79bba796e26f9f1d178cb182683", size = 49010, upload-time = "2025-02-27T18:51:00.104Z" }, +] + +[[package]] +name = "jinja2" +version = "3.1.6" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "markupsafe" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/df/bf/f7da0350254c0ed7c72f3e33cef02e048281fec7ecec5f032d4aac52226b/jinja2-3.1.6.tar.gz", hash = "sha256:0137fb05990d35f1275a587e9aee6d56da821fc83491a0fb838183be43f66d6d", size = 245115, upload-time = "2025-03-05T20:05:02.478Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/62/a1/3d680cbfd5f4b8f15abc1d571870c5fc3e594bb582bc3b64ea099db13e56/jinja2-3.1.6-py3-none-any.whl", hash = "sha256:85ece4451f492d0c13c5dd7c13a64681a86afae63a5f347908daf103ce6d2f67", size = 134899, upload-time = "2025-03-05T20:05:00.369Z" }, +] + +[[package]] +name = "joblib" +version = "1.5.3" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/41/f2/d34e8b3a08a9cc79a50b2208a93dce981fe615b64d5a4d4abee421d898df/joblib-1.5.3.tar.gz", hash = "sha256:8561a3269e6801106863fd0d6d84bb737be9e7631e33aaed3fb9ce5953688da3", size = 331603, upload-time = "2025-12-15T08:41:46.427Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/7b/91/984aca2ec129e2757d1e4e3c81c3fcda9d0f85b74670a094cc443d9ee949/joblib-1.5.3-py3-none-any.whl", hash = "sha256:5fc3c5039fc5ca8c0276333a188bbd59d6b7ab37fe6632daa76bc7f9ec18e713", size = 309071, upload-time = "2025-12-15T08:41:44.973Z" }, +] + +[[package]] +name = "jsonschema" +version = "4.26.0" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "attrs" }, + { name = "jsonschema-specifications" }, + { name = "referencing" }, + { name = "rpds-py" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/b3/fc/e067678238fa451312d4c62bf6e6cf5ec56375422aee02f9cb5f909b3047/jsonschema-4.26.0.tar.gz", hash = "sha256:0c26707e2efad8aa1bfc5b7ce170f3fccc2e4918ff85989ba9ffa9facb2be326", size = 366583, upload-time = "2026-01-07T13:41:07.246Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/69/90/f63fb5873511e014207a475e2bb4e8b2e570d655b00ac19a9a0ca0a385ee/jsonschema-4.26.0-py3-none-any.whl", hash = "sha256:d489f15263b8d200f8387e64b4c3a75f06629559fb73deb8fdfb525f2dab50ce", size = 90630, upload-time = "2026-01-07T13:41:05.306Z" }, +] + +[[package]] +name = "jsonschema-specifications" +version = "2025.9.1" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "referencing" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/19/74/a633ee74eb36c44aa6d1095e7cc5569bebf04342ee146178e2d36600708b/jsonschema_specifications-2025.9.1.tar.gz", hash = "sha256:b540987f239e745613c7a9176f3edb72b832a4ac465cf02712288397832b5e8d", size = 32855, upload-time = "2025-09-08T01:34:59.186Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/41/45/1a4ed80516f02155c51f51e8cedb3c1902296743db0bbc66608a0db2814f/jsonschema_specifications-2025.9.1-py3-none-any.whl", hash = "sha256:98802fee3a11ee76ecaca44429fda8a41bff98b00a0f2838151b113f210cc6fe", size = 18437, upload-time = "2025-09-08T01:34:57.871Z" }, +] + +[[package]] +name = "jupyter-client" +version = "8.8.0" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "jupyter-core" }, + { name = "python-dateutil" }, + { name = "pyzmq" }, + { name = "tornado" }, + { name = "traitlets" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/05/e4/ba649102a3bc3fbca54e7239fb924fd434c766f855693d86de0b1f2bec81/jupyter_client-8.8.0.tar.gz", hash = "sha256:d556811419a4f2d96c869af34e854e3f059b7cc2d6d01a9cd9c85c267691be3e", size = 348020, upload-time = "2026-01-08T13:55:47.938Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/2d/0b/ceb7694d864abc0a047649aec263878acb9f792e1fec3e676f22dc9015e3/jupyter_client-8.8.0-py3-none-any.whl", hash = "sha256:f93a5b99c5e23a507b773d3a1136bd6e16c67883ccdbd9a829b0bbdb98cd7d7a", size = 107371, upload-time = "2026-01-08T13:55:45.562Z" }, +] + +[[package]] +name = "jupyter-core" +version = "5.9.1" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "platformdirs" }, + { name = "traitlets" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/02/49/9d1284d0dc65e2c757b74c6687b6d319b02f822ad039e5c512df9194d9dd/jupyter_core-5.9.1.tar.gz", hash = "sha256:4d09aaff303b9566c3ce657f580bd089ff5c91f5f89cf7d8846c3cdf465b5508", size = 89814, upload-time = "2025-10-16T19:19:18.444Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/e7/e7/80988e32bf6f73919a113473a604f5a8f09094de312b9d52b79c2df7612b/jupyter_core-5.9.1-py3-none-any.whl", hash = "sha256:ebf87fdc6073d142e114c72c9e29a9d7ca03fad818c5d300ce2adc1fb0743407", size = 29032, upload-time = "2025-10-16T19:19:16.783Z" }, +] + +[[package]] +name = "jupyterlab-pygments" +version = "0.3.0" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/90/51/9187be60d989df97f5f0aba133fa54e7300f17616e065d1ada7d7646b6d6/jupyterlab_pygments-0.3.0.tar.gz", hash = "sha256:721aca4d9029252b11cfa9d185e5b5af4d54772bb8072f9b7036f4170054d35d", size = 512900, upload-time = "2023-11-23T09:26:37.44Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/b1/dd/ead9d8ea85bf202d90cc513b533f9c363121c7792674f78e0d8a854b63b4/jupyterlab_pygments-0.3.0-py3-none-any.whl", hash = "sha256:841a89020971da1d8693f1a99997aefc5dc424bb1b251fd6322462a1b8842780", size = 15884, upload-time = "2023-11-23T09:26:34.325Z" }, +] + +[[package]] +name = "jupyterlab-widgets" +version = "3.0.16" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/26/2d/ef58fed122b268c69c0aa099da20bc67657cdfb2e222688d5731bd5b971d/jupyterlab_widgets-3.0.16.tar.gz", hash = "sha256:423da05071d55cf27a9e602216d35a3a65a3e41cdf9c5d3b643b814ce38c19e0", size = 897423, upload-time = "2025-11-01T21:11:29.724Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/ab/b5/36c712098e6191d1b4e349304ef73a8d06aed77e56ceaac8c0a306c7bda1/jupyterlab_widgets-3.0.16-py3-none-any.whl", hash = "sha256:45fa36d9c6422cf2559198e4db481aa243c7a32d9926b500781c830c80f7ecf8", size = 914926, upload-time = "2025-11-01T21:11:28.008Z" }, +] + +[[package]] +name = "keyring" +version = "25.7.0" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "importlib-metadata", marker = "python_full_version < '3.12'" }, + { name = "jaraco-classes" }, + { name = "jaraco-context" }, + { name = "jaraco-functools" }, + { name = "jeepney", marker = "sys_platform == 'linux'" }, + { name = "pywin32-ctypes", marker = "sys_platform == 'win32'" }, + { name = "secretstorage", marker = "sys_platform == 'linux'" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/43/4b/674af6ef2f97d56f0ab5153bf0bfa28ccb6c3ed4d1babf4305449668807b/keyring-25.7.0.tar.gz", hash = "sha256:fe01bd85eb3f8fb3dd0405defdeac9a5b4f6f0439edbb3149577f244a2e8245b", size = 63516, upload-time = "2025-11-16T16:26:09.482Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/81/db/e655086b7f3a705df045bf0933bdd9c2f79bb3c97bfef1384598bb79a217/keyring-25.7.0-py3-none-any.whl", hash = "sha256:be4a0b195f149690c166e850609a477c532ddbfbaed96a404d4e43f8d5e2689f", size = 39160, upload-time = "2025-11-16T16:26:08.402Z" }, +] + +[[package]] +name = "kiwisolver" +version = "1.4.9" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/5c/3c/85844f1b0feb11ee581ac23fe5fce65cd049a200c1446708cc1b7f922875/kiwisolver-1.4.9.tar.gz", hash = "sha256:c3b22c26c6fd6811b0ae8363b95ca8ce4ea3c202d3d0975b2914310ceb1bcc4d", size = 97564, upload-time = "2025-08-10T21:27:49.279Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/6f/ab/c80b0d5a9d8a1a65f4f815f2afff9798b12c3b9f31f1d304dd233dd920e2/kiwisolver-1.4.9-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:eb14a5da6dc7642b0f3a18f13654847cd8b7a2550e2645a5bda677862b03ba16", size = 124167, upload-time = "2025-08-10T21:25:53.403Z" }, + { url = "https://files.pythonhosted.org/packages/a0/c0/27fe1a68a39cf62472a300e2879ffc13c0538546c359b86f149cc19f6ac3/kiwisolver-1.4.9-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:39a219e1c81ae3b103643d2aedb90f1ef22650deb266ff12a19e7773f3e5f089", size = 66579, upload-time = "2025-08-10T21:25:54.79Z" }, + { url = "https://files.pythonhosted.org/packages/31/a2/a12a503ac1fd4943c50f9822678e8015a790a13b5490354c68afb8489814/kiwisolver-1.4.9-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:2405a7d98604b87f3fc28b1716783534b1b4b8510d8142adca34ee0bc3c87543", size = 65309, upload-time = "2025-08-10T21:25:55.76Z" }, + { url = "https://files.pythonhosted.org/packages/66/e1/e533435c0be77c3f64040d68d7a657771194a63c279f55573188161e81ca/kiwisolver-1.4.9-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:dc1ae486f9abcef254b5618dfb4113dd49f94c68e3e027d03cf0143f3f772b61", size = 1435596, upload-time = "2025-08-10T21:25:56.861Z" }, + { url = "https://files.pythonhosted.org/packages/67/1e/51b73c7347f9aabdc7215aa79e8b15299097dc2f8e67dee2b095faca9cb0/kiwisolver-1.4.9-cp311-cp311-manylinux_2_24_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:8a1f570ce4d62d718dce3f179ee78dac3b545ac16c0c04bb363b7607a949c0d1", size = 1246548, upload-time = "2025-08-10T21:25:58.246Z" }, + { url = "https://files.pythonhosted.org/packages/21/aa/72a1c5d1e430294f2d32adb9542719cfb441b5da368d09d268c7757af46c/kiwisolver-1.4.9-cp311-cp311-manylinux_2_24_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:cb27e7b78d716c591e88e0a09a2139c6577865d7f2e152488c2cc6257f460872", size = 1263618, upload-time = "2025-08-10T21:25:59.857Z" }, + { url = "https://files.pythonhosted.org/packages/a3/af/db1509a9e79dbf4c260ce0cfa3903ea8945f6240e9e59d1e4deb731b1a40/kiwisolver-1.4.9-cp311-cp311-manylinux_2_24_s390x.manylinux_2_28_s390x.whl", hash = "sha256:15163165efc2f627eb9687ea5f3a28137217d217ac4024893d753f46bce9de26", size = 1317437, upload-time = "2025-08-10T21:26:01.105Z" }, + { url = "https://files.pythonhosted.org/packages/e0/f2/3ea5ee5d52abacdd12013a94130436e19969fa183faa1e7c7fbc89e9a42f/kiwisolver-1.4.9-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:bdee92c56a71d2b24c33a7d4c2856bd6419d017e08caa7802d2963870e315028", size = 2195742, upload-time = "2025-08-10T21:26:02.675Z" }, + { url = "https://files.pythonhosted.org/packages/6f/9b/1efdd3013c2d9a2566aa6a337e9923a00590c516add9a1e89a768a3eb2fc/kiwisolver-1.4.9-cp311-cp311-musllinux_1_2_ppc64le.whl", hash = "sha256:412f287c55a6f54b0650bd9b6dce5aceddb95864a1a90c87af16979d37c89771", size = 2290810, upload-time = "2025-08-10T21:26:04.009Z" }, + { url = "https://files.pythonhosted.org/packages/fb/e5/cfdc36109ae4e67361f9bc5b41323648cb24a01b9ade18784657e022e65f/kiwisolver-1.4.9-cp311-cp311-musllinux_1_2_s390x.whl", hash = "sha256:2c93f00dcba2eea70af2be5f11a830a742fe6b579a1d4e00f47760ef13be247a", size = 2461579, upload-time = "2025-08-10T21:26:05.317Z" }, + { url = "https://files.pythonhosted.org/packages/62/86/b589e5e86c7610842213994cdea5add00960076bef4ae290c5fa68589cac/kiwisolver-1.4.9-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:f117e1a089d9411663a3207ba874f31be9ac8eaa5b533787024dc07aeb74f464", size = 2268071, upload-time = "2025-08-10T21:26:06.686Z" }, + { url = "https://files.pythonhosted.org/packages/3b/c6/f8df8509fd1eee6c622febe54384a96cfaf4d43bf2ccec7a0cc17e4715c9/kiwisolver-1.4.9-cp311-cp311-win_amd64.whl", hash = "sha256:be6a04e6c79819c9a8c2373317d19a96048e5a3f90bec587787e86a1153883c2", size = 73840, upload-time = "2025-08-10T21:26:07.94Z" }, + { url = "https://files.pythonhosted.org/packages/e2/2d/16e0581daafd147bc11ac53f032a2b45eabac897f42a338d0a13c1e5c436/kiwisolver-1.4.9-cp311-cp311-win_arm64.whl", hash = "sha256:0ae37737256ba2de764ddc12aed4956460277f00c4996d51a197e72f62f5eec7", size = 65159, upload-time = "2025-08-10T21:26:09.048Z" }, + { url = "https://files.pythonhosted.org/packages/86/c9/13573a747838aeb1c76e3267620daa054f4152444d1f3d1a2324b78255b5/kiwisolver-1.4.9-cp312-cp312-macosx_10_13_universal2.whl", hash = "sha256:ac5a486ac389dddcc5bef4f365b6ae3ffff2c433324fb38dd35e3fab7c957999", size = 123686, upload-time = "2025-08-10T21:26:10.034Z" }, + { url = "https://files.pythonhosted.org/packages/51/ea/2ecf727927f103ffd1739271ca19c424d0e65ea473fbaeea1c014aea93f6/kiwisolver-1.4.9-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:f2ba92255faa7309d06fe44c3a4a97efe1c8d640c2a79a5ef728b685762a6fd2", size = 66460, upload-time = "2025-08-10T21:26:11.083Z" }, + { url = "https://files.pythonhosted.org/packages/5b/5a/51f5464373ce2aeb5194508298a508b6f21d3867f499556263c64c621914/kiwisolver-1.4.9-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:4a2899935e724dd1074cb568ce7ac0dce28b2cd6ab539c8e001a8578eb106d14", size = 64952, upload-time = "2025-08-10T21:26:12.058Z" }, + { url = "https://files.pythonhosted.org/packages/70/90/6d240beb0f24b74371762873e9b7f499f1e02166a2d9c5801f4dbf8fa12e/kiwisolver-1.4.9-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:f6008a4919fdbc0b0097089f67a1eb55d950ed7e90ce2cc3e640abadd2757a04", size = 1474756, upload-time = "2025-08-10T21:26:13.096Z" }, + { url = "https://files.pythonhosted.org/packages/12/42/f36816eaf465220f683fb711efdd1bbf7a7005a2473d0e4ed421389bd26c/kiwisolver-1.4.9-cp312-cp312-manylinux_2_24_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:67bb8b474b4181770f926f7b7d2f8c0248cbcb78b660fdd41a47054b28d2a752", size = 1276404, upload-time = "2025-08-10T21:26:14.457Z" }, + { url = "https://files.pythonhosted.org/packages/2e/64/bc2de94800adc830c476dce44e9b40fd0809cddeef1fde9fcf0f73da301f/kiwisolver-1.4.9-cp312-cp312-manylinux_2_24_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:2327a4a30d3ee07d2fbe2e7933e8a37c591663b96ce42a00bc67461a87d7df77", size = 1294410, upload-time = "2025-08-10T21:26:15.73Z" }, + { url = "https://files.pythonhosted.org/packages/5f/42/2dc82330a70aa8e55b6d395b11018045e58d0bb00834502bf11509f79091/kiwisolver-1.4.9-cp312-cp312-manylinux_2_24_s390x.manylinux_2_28_s390x.whl", hash = "sha256:7a08b491ec91b1d5053ac177afe5290adacf1f0f6307d771ccac5de30592d198", size = 1343631, upload-time = "2025-08-10T21:26:17.045Z" }, + { url = "https://files.pythonhosted.org/packages/22/fd/f4c67a6ed1aab149ec5a8a401c323cee7a1cbe364381bb6c9c0d564e0e20/kiwisolver-1.4.9-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:d8fc5c867c22b828001b6a38d2eaeb88160bf5783c6cb4a5e440efc981ce286d", size = 2224963, upload-time = "2025-08-10T21:26:18.737Z" }, + { url = "https://files.pythonhosted.org/packages/45/aa/76720bd4cb3713314677d9ec94dcc21ced3f1baf4830adde5bb9b2430a5f/kiwisolver-1.4.9-cp312-cp312-musllinux_1_2_ppc64le.whl", hash = "sha256:3b3115b2581ea35bb6d1f24a4c90af37e5d9b49dcff267eeed14c3893c5b86ab", size = 2321295, upload-time = "2025-08-10T21:26:20.11Z" }, + { url = "https://files.pythonhosted.org/packages/80/19/d3ec0d9ab711242f56ae0dc2fc5d70e298bb4a1f9dfab44c027668c673a1/kiwisolver-1.4.9-cp312-cp312-musllinux_1_2_s390x.whl", hash = "sha256:858e4c22fb075920b96a291928cb7dea5644e94c0ee4fcd5af7e865655e4ccf2", size = 2487987, upload-time = "2025-08-10T21:26:21.49Z" }, + { url = "https://files.pythonhosted.org/packages/39/e9/61e4813b2c97e86b6fdbd4dd824bf72d28bcd8d4849b8084a357bc0dd64d/kiwisolver-1.4.9-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:ed0fecd28cc62c54b262e3736f8bb2512d8dcfdc2bcf08be5f47f96bf405b145", size = 2291817, upload-time = "2025-08-10T21:26:22.812Z" }, + { url = "https://files.pythonhosted.org/packages/a0/41/85d82b0291db7504da3c2defe35c9a8a5c9803a730f297bd823d11d5fb77/kiwisolver-1.4.9-cp312-cp312-win_amd64.whl", hash = "sha256:f68208a520c3d86ea51acf688a3e3002615a7f0238002cccc17affecc86a8a54", size = 73895, upload-time = "2025-08-10T21:26:24.37Z" }, + { url = "https://files.pythonhosted.org/packages/e2/92/5f3068cf15ee5cb624a0c7596e67e2a0bb2adee33f71c379054a491d07da/kiwisolver-1.4.9-cp312-cp312-win_arm64.whl", hash = "sha256:2c1a4f57df73965f3f14df20b80ee29e6a7930a57d2d9e8491a25f676e197c60", size = 64992, upload-time = "2025-08-10T21:26:25.732Z" }, + { url = "https://files.pythonhosted.org/packages/31/c1/c2686cda909742ab66c7388e9a1a8521a59eb89f8bcfbee28fc980d07e24/kiwisolver-1.4.9-cp313-cp313-macosx_10_13_universal2.whl", hash = "sha256:a5d0432ccf1c7ab14f9949eec60c5d1f924f17c037e9f8b33352fa05799359b8", size = 123681, upload-time = "2025-08-10T21:26:26.725Z" }, + { url = "https://files.pythonhosted.org/packages/ca/f0/f44f50c9f5b1a1860261092e3bc91ecdc9acda848a8b8c6abfda4a24dd5c/kiwisolver-1.4.9-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:efb3a45b35622bb6c16dbfab491a8f5a391fe0e9d45ef32f4df85658232ca0e2", size = 66464, upload-time = "2025-08-10T21:26:27.733Z" }, + { url = "https://files.pythonhosted.org/packages/2d/7a/9d90a151f558e29c3936b8a47ac770235f436f2120aca41a6d5f3d62ae8d/kiwisolver-1.4.9-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:1a12cf6398e8a0a001a059747a1cbf24705e18fe413bc22de7b3d15c67cffe3f", size = 64961, upload-time = "2025-08-10T21:26:28.729Z" }, + { url = "https://files.pythonhosted.org/packages/e9/e9/f218a2cb3a9ffbe324ca29a9e399fa2d2866d7f348ec3a88df87fc248fc5/kiwisolver-1.4.9-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:b67e6efbf68e077dd71d1a6b37e43e1a99d0bff1a3d51867d45ee8908b931098", size = 1474607, upload-time = "2025-08-10T21:26:29.798Z" }, + { url = "https://files.pythonhosted.org/packages/d9/28/aac26d4c882f14de59041636292bc838db8961373825df23b8eeb807e198/kiwisolver-1.4.9-cp313-cp313-manylinux_2_24_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:5656aa670507437af0207645273ccdfee4f14bacd7f7c67a4306d0dcaeaf6eed", size = 1276546, upload-time = "2025-08-10T21:26:31.401Z" }, + { url = "https://files.pythonhosted.org/packages/8b/ad/8bfc1c93d4cc565e5069162f610ba2f48ff39b7de4b5b8d93f69f30c4bed/kiwisolver-1.4.9-cp313-cp313-manylinux_2_24_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:bfc08add558155345129c7803b3671cf195e6a56e7a12f3dde7c57d9b417f525", size = 1294482, upload-time = "2025-08-10T21:26:32.721Z" }, + { url = "https://files.pythonhosted.org/packages/da/f1/6aca55ff798901d8ce403206d00e033191f63d82dd708a186e0ed2067e9c/kiwisolver-1.4.9-cp313-cp313-manylinux_2_24_s390x.manylinux_2_28_s390x.whl", hash = "sha256:40092754720b174e6ccf9e845d0d8c7d8e12c3d71e7fc35f55f3813e96376f78", size = 1343720, upload-time = "2025-08-10T21:26:34.032Z" }, + { url = "https://files.pythonhosted.org/packages/d1/91/eed031876c595c81d90d0f6fc681ece250e14bf6998c3d7c419466b523b7/kiwisolver-1.4.9-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:497d05f29a1300d14e02e6441cf0f5ee81c1ff5a304b0d9fb77423974684e08b", size = 2224907, upload-time = "2025-08-10T21:26:35.824Z" }, + { url = "https://files.pythonhosted.org/packages/e9/ec/4d1925f2e49617b9cca9c34bfa11adefad49d00db038e692a559454dfb2e/kiwisolver-1.4.9-cp313-cp313-musllinux_1_2_ppc64le.whl", hash = "sha256:bdd1a81a1860476eb41ac4bc1e07b3f07259e6d55bbf739b79c8aaedcf512799", size = 2321334, upload-time = "2025-08-10T21:26:37.534Z" }, + { url = "https://files.pythonhosted.org/packages/43/cb/450cd4499356f68802750c6ddc18647b8ea01ffa28f50d20598e0befe6e9/kiwisolver-1.4.9-cp313-cp313-musllinux_1_2_s390x.whl", hash = "sha256:e6b93f13371d341afee3be9f7c5964e3fe61d5fa30f6a30eb49856935dfe4fc3", size = 2488313, upload-time = "2025-08-10T21:26:39.191Z" }, + { url = "https://files.pythonhosted.org/packages/71/67/fc76242bd99f885651128a5d4fa6083e5524694b7c88b489b1b55fdc491d/kiwisolver-1.4.9-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:d75aa530ccfaa593da12834b86a0724f58bff12706659baa9227c2ccaa06264c", size = 2291970, upload-time = "2025-08-10T21:26:40.828Z" }, + { url = "https://files.pythonhosted.org/packages/75/bd/f1a5d894000941739f2ae1b65a32892349423ad49c2e6d0771d0bad3fae4/kiwisolver-1.4.9-cp313-cp313-win_amd64.whl", hash = "sha256:dd0a578400839256df88c16abddf9ba14813ec5f21362e1fe65022e00c883d4d", size = 73894, upload-time = "2025-08-10T21:26:42.33Z" }, + { url = "https://files.pythonhosted.org/packages/95/38/dce480814d25b99a391abbddadc78f7c117c6da34be68ca8b02d5848b424/kiwisolver-1.4.9-cp313-cp313-win_arm64.whl", hash = "sha256:d4188e73af84ca82468f09cadc5ac4db578109e52acb4518d8154698d3a87ca2", size = 64995, upload-time = "2025-08-10T21:26:43.889Z" }, + { url = "https://files.pythonhosted.org/packages/e2/37/7d218ce5d92dadc5ebdd9070d903e0c7cf7edfe03f179433ac4d13ce659c/kiwisolver-1.4.9-cp313-cp313t-macosx_10_13_universal2.whl", hash = "sha256:5a0f2724dfd4e3b3ac5a82436a8e6fd16baa7d507117e4279b660fe8ca38a3a1", size = 126510, upload-time = "2025-08-10T21:26:44.915Z" }, + { url = "https://files.pythonhosted.org/packages/23/b0/e85a2b48233daef4b648fb657ebbb6f8367696a2d9548a00b4ee0eb67803/kiwisolver-1.4.9-cp313-cp313t-macosx_10_13_x86_64.whl", hash = "sha256:1b11d6a633e4ed84fc0ddafd4ebfd8ea49b3f25082c04ad12b8315c11d504dc1", size = 67903, upload-time = "2025-08-10T21:26:45.934Z" }, + { url = "https://files.pythonhosted.org/packages/44/98/f2425bc0113ad7de24da6bb4dae1343476e95e1d738be7c04d31a5d037fd/kiwisolver-1.4.9-cp313-cp313t-macosx_11_0_arm64.whl", hash = "sha256:61874cdb0a36016354853593cffc38e56fc9ca5aa97d2c05d3dcf6922cd55a11", size = 66402, upload-time = "2025-08-10T21:26:47.101Z" }, + { url = "https://files.pythonhosted.org/packages/98/d8/594657886df9f34c4177cc353cc28ca7e6e5eb562d37ccc233bff43bbe2a/kiwisolver-1.4.9-cp313-cp313t-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:60c439763a969a6af93b4881db0eed8fadf93ee98e18cbc35bc8da868d0c4f0c", size = 1582135, upload-time = "2025-08-10T21:26:48.665Z" }, + { url = "https://files.pythonhosted.org/packages/5c/c6/38a115b7170f8b306fc929e166340c24958347308ea3012c2b44e7e295db/kiwisolver-1.4.9-cp313-cp313t-manylinux_2_24_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:92a2f997387a1b79a75e7803aa7ded2cfbe2823852ccf1ba3bcf613b62ae3197", size = 1389409, upload-time = "2025-08-10T21:26:50.335Z" }, + { url = "https://files.pythonhosted.org/packages/bf/3b/e04883dace81f24a568bcee6eb3001da4ba05114afa622ec9b6fafdc1f5e/kiwisolver-1.4.9-cp313-cp313t-manylinux_2_24_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:a31d512c812daea6d8b3be3b2bfcbeb091dbb09177706569bcfc6240dcf8b41c", size = 1401763, upload-time = "2025-08-10T21:26:51.867Z" }, + { url = "https://files.pythonhosted.org/packages/9f/80/20ace48e33408947af49d7d15c341eaee69e4e0304aab4b7660e234d6288/kiwisolver-1.4.9-cp313-cp313t-manylinux_2_24_s390x.manylinux_2_28_s390x.whl", hash = "sha256:52a15b0f35dad39862d376df10c5230155243a2c1a436e39eb55623ccbd68185", size = 1453643, upload-time = "2025-08-10T21:26:53.592Z" }, + { url = "https://files.pythonhosted.org/packages/64/31/6ce4380a4cd1f515bdda976a1e90e547ccd47b67a1546d63884463c92ca9/kiwisolver-1.4.9-cp313-cp313t-musllinux_1_2_aarch64.whl", hash = "sha256:a30fd6fdef1430fd9e1ba7b3398b5ee4e2887783917a687d86ba69985fb08748", size = 2330818, upload-time = "2025-08-10T21:26:55.051Z" }, + { url = "https://files.pythonhosted.org/packages/fa/e9/3f3fcba3bcc7432c795b82646306e822f3fd74df0ee81f0fa067a1f95668/kiwisolver-1.4.9-cp313-cp313t-musllinux_1_2_ppc64le.whl", hash = "sha256:cc9617b46837c6468197b5945e196ee9ca43057bb7d9d1ae688101e4e1dddf64", size = 2419963, upload-time = "2025-08-10T21:26:56.421Z" }, + { url = "https://files.pythonhosted.org/packages/99/43/7320c50e4133575c66e9f7dadead35ab22d7c012a3b09bb35647792b2a6d/kiwisolver-1.4.9-cp313-cp313t-musllinux_1_2_s390x.whl", hash = "sha256:0ab74e19f6a2b027ea4f845a78827969af45ce790e6cb3e1ebab71bdf9f215ff", size = 2594639, upload-time = "2025-08-10T21:26:57.882Z" }, + { url = "https://files.pythonhosted.org/packages/65/d6/17ae4a270d4a987ef8a385b906d2bdfc9fce502d6dc0d3aea865b47f548c/kiwisolver-1.4.9-cp313-cp313t-musllinux_1_2_x86_64.whl", hash = "sha256:dba5ee5d3981160c28d5490f0d1b7ed730c22470ff7f6cc26cfcfaacb9896a07", size = 2391741, upload-time = "2025-08-10T21:26:59.237Z" }, + { url = "https://files.pythonhosted.org/packages/2a/8f/8f6f491d595a9e5912971f3f863d81baddccc8a4d0c3749d6a0dd9ffc9df/kiwisolver-1.4.9-cp313-cp313t-win_arm64.whl", hash = "sha256:0749fd8f4218ad2e851e11cc4dc05c7cbc0cbc4267bdfdb31782e65aace4ee9c", size = 68646, upload-time = "2025-08-10T21:27:00.52Z" }, + { url = "https://files.pythonhosted.org/packages/6b/32/6cc0fbc9c54d06c2969faa9c1d29f5751a2e51809dd55c69055e62d9b426/kiwisolver-1.4.9-cp314-cp314-macosx_10_13_universal2.whl", hash = "sha256:9928fe1eb816d11ae170885a74d074f57af3a0d65777ca47e9aeb854a1fba386", size = 123806, upload-time = "2025-08-10T21:27:01.537Z" }, + { url = "https://files.pythonhosted.org/packages/b2/dd/2bfb1d4a4823d92e8cbb420fe024b8d2167f72079b3bb941207c42570bdf/kiwisolver-1.4.9-cp314-cp314-macosx_10_13_x86_64.whl", hash = "sha256:d0005b053977e7b43388ddec89fa567f43d4f6d5c2c0affe57de5ebf290dc552", size = 66605, upload-time = "2025-08-10T21:27:03.335Z" }, + { url = "https://files.pythonhosted.org/packages/f7/69/00aafdb4e4509c2ca6064646cba9cd4b37933898f426756adb2cb92ebbed/kiwisolver-1.4.9-cp314-cp314-macosx_11_0_arm64.whl", hash = "sha256:2635d352d67458b66fd0667c14cb1d4145e9560d503219034a18a87e971ce4f3", size = 64925, upload-time = "2025-08-10T21:27:04.339Z" }, + { url = "https://files.pythonhosted.org/packages/43/dc/51acc6791aa14e5cb6d8a2e28cefb0dc2886d8862795449d021334c0df20/kiwisolver-1.4.9-cp314-cp314-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:767c23ad1c58c9e827b649a9ab7809fd5fd9db266a9cf02b0e926ddc2c680d58", size = 1472414, upload-time = "2025-08-10T21:27:05.437Z" }, + { url = "https://files.pythonhosted.org/packages/3d/bb/93fa64a81db304ac8a246f834d5094fae4b13baf53c839d6bb6e81177129/kiwisolver-1.4.9-cp314-cp314-manylinux_2_24_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:72d0eb9fba308b8311685c2268cf7d0a0639a6cd027d8128659f72bdd8a024b4", size = 1281272, upload-time = "2025-08-10T21:27:07.063Z" }, + { url = "https://files.pythonhosted.org/packages/70/e6/6df102916960fb8d05069d4bd92d6d9a8202d5a3e2444494e7cd50f65b7a/kiwisolver-1.4.9-cp314-cp314-manylinux_2_24_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:f68e4f3eeca8fb22cc3d731f9715a13b652795ef657a13df1ad0c7dc0e9731df", size = 1298578, upload-time = "2025-08-10T21:27:08.452Z" }, + { url = "https://files.pythonhosted.org/packages/7c/47/e142aaa612f5343736b087864dbaebc53ea8831453fb47e7521fa8658f30/kiwisolver-1.4.9-cp314-cp314-manylinux_2_24_s390x.manylinux_2_28_s390x.whl", hash = "sha256:d84cd4061ae292d8ac367b2c3fa3aad11cb8625a95d135fe93f286f914f3f5a6", size = 1345607, upload-time = "2025-08-10T21:27:10.125Z" }, + { url = "https://files.pythonhosted.org/packages/54/89/d641a746194a0f4d1a3670fb900d0dbaa786fb98341056814bc3f058fa52/kiwisolver-1.4.9-cp314-cp314-musllinux_1_2_aarch64.whl", hash = "sha256:a60ea74330b91bd22a29638940d115df9dc00af5035a9a2a6ad9399ffb4ceca5", size = 2230150, upload-time = "2025-08-10T21:27:11.484Z" }, + { url = "https://files.pythonhosted.org/packages/aa/6b/5ee1207198febdf16ac11f78c5ae40861b809cbe0e6d2a8d5b0b3044b199/kiwisolver-1.4.9-cp314-cp314-musllinux_1_2_ppc64le.whl", hash = "sha256:ce6a3a4e106cf35c2d9c4fa17c05ce0b180db622736845d4315519397a77beaf", size = 2325979, upload-time = "2025-08-10T21:27:12.917Z" }, + { url = "https://files.pythonhosted.org/packages/fc/ff/b269eefd90f4ae14dcc74973d5a0f6d28d3b9bb1afd8c0340513afe6b39a/kiwisolver-1.4.9-cp314-cp314-musllinux_1_2_s390x.whl", hash = "sha256:77937e5e2a38a7b48eef0585114fe7930346993a88060d0bf886086d2aa49ef5", size = 2491456, upload-time = "2025-08-10T21:27:14.353Z" }, + { url = "https://files.pythonhosted.org/packages/fc/d4/10303190bd4d30de547534601e259a4fbf014eed94aae3e5521129215086/kiwisolver-1.4.9-cp314-cp314-musllinux_1_2_x86_64.whl", hash = "sha256:24c175051354f4a28c5d6a31c93906dc653e2bf234e8a4bbfb964892078898ce", size = 2294621, upload-time = "2025-08-10T21:27:15.808Z" }, + { url = "https://files.pythonhosted.org/packages/28/e0/a9a90416fce5c0be25742729c2ea52105d62eda6c4be4d803c2a7be1fa50/kiwisolver-1.4.9-cp314-cp314-win_amd64.whl", hash = "sha256:0763515d4df10edf6d06a3c19734e2566368980d21ebec439f33f9eb936c07b7", size = 75417, upload-time = "2025-08-10T21:27:17.436Z" }, + { url = "https://files.pythonhosted.org/packages/1f/10/6949958215b7a9a264299a7db195564e87900f709db9245e4ebdd3c70779/kiwisolver-1.4.9-cp314-cp314-win_arm64.whl", hash = "sha256:0e4e2bf29574a6a7b7f6cb5fa69293b9f96c928949ac4a53ba3f525dffb87f9c", size = 66582, upload-time = "2025-08-10T21:27:18.436Z" }, + { url = "https://files.pythonhosted.org/packages/ec/79/60e53067903d3bc5469b369fe0dfc6b3482e2133e85dae9daa9527535991/kiwisolver-1.4.9-cp314-cp314t-macosx_10_13_universal2.whl", hash = "sha256:d976bbb382b202f71c67f77b0ac11244021cfa3f7dfd9e562eefcea2df711548", size = 126514, upload-time = "2025-08-10T21:27:19.465Z" }, + { url = "https://files.pythonhosted.org/packages/25/d1/4843d3e8d46b072c12a38c97c57fab4608d36e13fe47d47ee96b4d61ba6f/kiwisolver-1.4.9-cp314-cp314t-macosx_10_13_x86_64.whl", hash = "sha256:2489e4e5d7ef9a1c300a5e0196e43d9c739f066ef23270607d45aba368b91f2d", size = 67905, upload-time = "2025-08-10T21:27:20.51Z" }, + { url = "https://files.pythonhosted.org/packages/8c/ae/29ffcbd239aea8b93108de1278271ae764dfc0d803a5693914975f200596/kiwisolver-1.4.9-cp314-cp314t-macosx_11_0_arm64.whl", hash = "sha256:e2ea9f7ab7fbf18fffb1b5434ce7c69a07582f7acc7717720f1d69f3e806f90c", size = 66399, upload-time = "2025-08-10T21:27:21.496Z" }, + { url = "https://files.pythonhosted.org/packages/a1/ae/d7ba902aa604152c2ceba5d352d7b62106bedbccc8e95c3934d94472bfa3/kiwisolver-1.4.9-cp314-cp314t-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:b34e51affded8faee0dfdb705416153819d8ea9250bbbf7ea1b249bdeb5f1122", size = 1582197, upload-time = "2025-08-10T21:27:22.604Z" }, + { url = "https://files.pythonhosted.org/packages/f2/41/27c70d427eddb8bc7e4f16420a20fefc6f480312122a59a959fdfe0445ad/kiwisolver-1.4.9-cp314-cp314t-manylinux_2_24_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:d8aacd3d4b33b772542b2e01beb50187536967b514b00003bdda7589722d2a64", size = 1390125, upload-time = "2025-08-10T21:27:24.036Z" }, + { url = "https://files.pythonhosted.org/packages/41/42/b3799a12bafc76d962ad69083f8b43b12bf4fe78b097b12e105d75c9b8f1/kiwisolver-1.4.9-cp314-cp314t-manylinux_2_24_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:7cf974dd4e35fa315563ac99d6287a1024e4dc2077b8a7d7cd3d2fb65d283134", size = 1402612, upload-time = "2025-08-10T21:27:25.773Z" }, + { url = "https://files.pythonhosted.org/packages/d2/b5/a210ea073ea1cfaca1bb5c55a62307d8252f531beb364e18aa1e0888b5a0/kiwisolver-1.4.9-cp314-cp314t-manylinux_2_24_s390x.manylinux_2_28_s390x.whl", hash = "sha256:85bd218b5ecfbee8c8a82e121802dcb519a86044c9c3b2e4aef02fa05c6da370", size = 1453990, upload-time = "2025-08-10T21:27:27.089Z" }, + { url = "https://files.pythonhosted.org/packages/5f/ce/a829eb8c033e977d7ea03ed32fb3c1781b4fa0433fbadfff29e39c676f32/kiwisolver-1.4.9-cp314-cp314t-musllinux_1_2_aarch64.whl", hash = "sha256:0856e241c2d3df4efef7c04a1e46b1936b6120c9bcf36dd216e3acd84bc4fb21", size = 2331601, upload-time = "2025-08-10T21:27:29.343Z" }, + { url = "https://files.pythonhosted.org/packages/e0/4b/b5e97eb142eb9cd0072dacfcdcd31b1c66dc7352b0f7c7255d339c0edf00/kiwisolver-1.4.9-cp314-cp314t-musllinux_1_2_ppc64le.whl", hash = "sha256:9af39d6551f97d31a4deebeac6f45b156f9755ddc59c07b402c148f5dbb6482a", size = 2422041, upload-time = "2025-08-10T21:27:30.754Z" }, + { url = "https://files.pythonhosted.org/packages/40/be/8eb4cd53e1b85ba4edc3a9321666f12b83113a178845593307a3e7891f44/kiwisolver-1.4.9-cp314-cp314t-musllinux_1_2_s390x.whl", hash = "sha256:bb4ae2b57fc1d8cbd1cf7b1d9913803681ffa903e7488012be5b76dedf49297f", size = 2594897, upload-time = "2025-08-10T21:27:32.803Z" }, + { url = "https://files.pythonhosted.org/packages/99/dd/841e9a66c4715477ea0abc78da039832fbb09dac5c35c58dc4c41a407b8a/kiwisolver-1.4.9-cp314-cp314t-musllinux_1_2_x86_64.whl", hash = "sha256:aedff62918805fb62d43a4aa2ecd4482c380dc76cd31bd7c8878588a61bd0369", size = 2391835, upload-time = "2025-08-10T21:27:34.23Z" }, + { url = "https://files.pythonhosted.org/packages/0c/28/4b2e5c47a0da96896fdfdb006340ade064afa1e63675d01ea5ac222b6d52/kiwisolver-1.4.9-cp314-cp314t-win_amd64.whl", hash = "sha256:1fa333e8b2ce4d9660f2cda9c0e1b6bafcfb2457a9d259faa82289e73ec24891", size = 79988, upload-time = "2025-08-10T21:27:35.587Z" }, + { url = "https://files.pythonhosted.org/packages/80/be/3578e8afd18c88cdf9cb4cffde75a96d2be38c5a903f1ed0ceec061bd09e/kiwisolver-1.4.9-cp314-cp314t-win_arm64.whl", hash = "sha256:4a48a2ce79d65d363597ef7b567ce3d14d68783d2b2263d98db3d9477805ba32", size = 70260, upload-time = "2025-08-10T21:27:36.606Z" }, + { url = "https://files.pythonhosted.org/packages/a3/0f/36d89194b5a32c054ce93e586d4049b6c2c22887b0eb229c61c68afd3078/kiwisolver-1.4.9-pp311-pypy311_pp73-macosx_10_15_x86_64.whl", hash = "sha256:720e05574713db64c356e86732c0f3c5252818d05f9df320f0ad8380641acea5", size = 60104, upload-time = "2025-08-10T21:27:43.287Z" }, + { url = "https://files.pythonhosted.org/packages/52/ba/4ed75f59e4658fd21fe7dde1fee0ac397c678ec3befba3fe6482d987af87/kiwisolver-1.4.9-pp311-pypy311_pp73-macosx_11_0_arm64.whl", hash = "sha256:17680d737d5335b552994a2008fab4c851bcd7de33094a82067ef3a576ff02fa", size = 58592, upload-time = "2025-08-10T21:27:44.314Z" }, + { url = "https://files.pythonhosted.org/packages/33/01/a8ea7c5ea32a9b45ceeaee051a04c8ed4320f5add3c51bfa20879b765b70/kiwisolver-1.4.9-pp311-pypy311_pp73-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:85b5352f94e490c028926ea567fc569c52ec79ce131dadb968d3853e809518c2", size = 80281, upload-time = "2025-08-10T21:27:45.369Z" }, + { url = "https://files.pythonhosted.org/packages/da/e3/dbd2ecdce306f1d07a1aaf324817ee993aab7aee9db47ceac757deabafbe/kiwisolver-1.4.9-pp311-pypy311_pp73-manylinux_2_24_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:464415881e4801295659462c49461a24fb107c140de781d55518c4b80cb6790f", size = 78009, upload-time = "2025-08-10T21:27:46.376Z" }, + { url = "https://files.pythonhosted.org/packages/da/e9/0d4add7873a73e462aeb45c036a2dead2562b825aa46ba326727b3f31016/kiwisolver-1.4.9-pp311-pypy311_pp73-win_amd64.whl", hash = "sha256:fb940820c63a9590d31d88b815e7a3aa5915cad3ce735ab45f0c730b39547de1", size = 73929, upload-time = "2025-08-10T21:27:48.236Z" }, +] + +[[package]] +name = "latexcodec" +version = "3.0.1" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/27/dd/4270b2c5e2ee49316c3859e62293bd2ea8e382339d63ab7bbe9f39c0ec3b/latexcodec-3.0.1.tar.gz", hash = "sha256:e78a6911cd72f9dec35031c6ec23584de6842bfbc4610a9678868d14cdfb0357", size = 31222, upload-time = "2025-06-17T18:47:34.051Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/b5/40/23569737873cc9637fd488606347e9dd92b9fa37ba4fcda1f98ee5219a97/latexcodec-3.0.1-py3-none-any.whl", hash = "sha256:a9eb8200bff693f0437a69581f7579eb6bca25c4193515c09900ce76451e452e", size = 18532, upload-time = "2025-06-17T18:47:30.726Z" }, +] + +[[package]] +name = "legacy-api-wrap" +version = "1.5" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/58/49/f06f94048c8974205730d40beca879e43b6eee08efb0101cfb8623e60f41/legacy_api_wrap-1.5.tar.gz", hash = "sha256:b41ba6532f3ebfe3a897a35a7f97dec3be04b92a450f6c2bcf89f1b91c9cadf2", size = 11610, upload-time = "2025-11-03T13:21:12.437Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/41/5b/058db09c45ba58a7321bdf2294cae651b37d6fec68117265af90cde043b0/legacy_api_wrap-1.5-py3-none-any.whl", hash = "sha256:5a8ea50e3e3bcbcdec3447b77034fd0d32cb2cf4089db799238708e4d7e0098d", size = 10182, upload-time = "2025-11-03T13:21:11.102Z" }, +] + +[[package]] +name = "llvmlite" +version = "0.46.0" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/74/cd/08ae687ba099c7e3d21fe2ea536500563ef1943c5105bf6ab4ee3829f68e/llvmlite-0.46.0.tar.gz", hash = "sha256:227c9fd6d09dce2783c18b754b7cd9d9b3b3515210c46acc2d3c5badd9870ceb", size = 193456, upload-time = "2025-12-08T18:15:36.295Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/7a/a1/2ad4b2367915faeebe8447f0a057861f646dbf5fbbb3561db42c65659cf3/llvmlite-0.46.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:82f3d39b16f19aa1a56d5fe625883a6ab600d5cc9ea8906cca70ce94cabba067", size = 37232766, upload-time = "2025-12-08T18:14:48.836Z" }, + { url = "https://files.pythonhosted.org/packages/12/b5/99cf8772fdd846c07da4fd70f07812a3c8fd17ea2409522c946bb0f2b277/llvmlite-0.46.0-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:a3df43900119803bbc52720e758c76f316a9a0f34612a886862dfe0a5591a17e", size = 56275175, upload-time = "2025-12-08T18:14:51.604Z" }, + { url = "https://files.pythonhosted.org/packages/38/f2/ed806f9c003563732da156139c45d970ee435bd0bfa5ed8de87ba972b452/llvmlite-0.46.0-cp311-cp311-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:de183fefc8022d21b0aa37fc3e90410bc3524aed8617f0ff76732fc6c3af5361", size = 55128630, upload-time = "2025-12-08T18:14:55.107Z" }, + { url = "https://files.pythonhosted.org/packages/19/0c/8f5a37a65fc9b7b17408508145edd5f86263ad69c19d3574e818f533a0eb/llvmlite-0.46.0-cp311-cp311-win_amd64.whl", hash = "sha256:e8b10bc585c58bdffec9e0c309bb7d51be1f2f15e169a4b4d42f2389e431eb93", size = 38138652, upload-time = "2025-12-08T18:14:58.171Z" }, + { url = "https://files.pythonhosted.org/packages/2b/f8/4db016a5e547d4e054ff2f3b99203d63a497465f81ab78ec8eb2ff7b2304/llvmlite-0.46.0-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:6b9588ad4c63b4f0175a3984b85494f0c927c6b001e3a246a3a7fb3920d9a137", size = 37232767, upload-time = "2025-12-08T18:15:00.737Z" }, + { url = "https://files.pythonhosted.org/packages/aa/85/4890a7c14b4fa54400945cb52ac3cd88545bbdb973c440f98ca41591cdc5/llvmlite-0.46.0-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:3535bd2bb6a2d7ae4012681ac228e5132cdb75fefb1bcb24e33f2f3e0c865ed4", size = 56275176, upload-time = "2025-12-08T18:15:03.936Z" }, + { url = "https://files.pythonhosted.org/packages/6a/07/3d31d39c1a1a08cd5337e78299fca77e6aebc07c059fbd0033e3edfab45c/llvmlite-0.46.0-cp312-cp312-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:4cbfd366e60ff87ea6cc62f50bc4cd800ebb13ed4c149466f50cf2163a473d1e", size = 55128630, upload-time = "2025-12-08T18:15:07.196Z" }, + { url = "https://files.pythonhosted.org/packages/2a/6b/d139535d7590a1bba1ceb68751bef22fadaa5b815bbdf0e858e3875726b2/llvmlite-0.46.0-cp312-cp312-win_amd64.whl", hash = "sha256:398b39db462c39563a97b912d4f2866cd37cba60537975a09679b28fbbc0fb38", size = 38138940, upload-time = "2025-12-08T18:15:10.162Z" }, + { url = "https://files.pythonhosted.org/packages/e6/ff/3eba7eb0aed4b6fca37125387cd417e8c458e750621fce56d2c541f67fa8/llvmlite-0.46.0-cp313-cp313-macosx_12_0_arm64.whl", hash = "sha256:30b60892d034bc560e0ec6654737aaa74e5ca327bd8114d82136aa071d611172", size = 37232767, upload-time = "2025-12-08T18:15:13.22Z" }, + { url = "https://files.pythonhosted.org/packages/0e/54/737755c0a91558364b9200702c3c9c15d70ed63f9b98a2c32f1c2aa1f3ba/llvmlite-0.46.0-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:6cc19b051753368a9c9f31dc041299059ee91aceec81bd57b0e385e5d5bf1a54", size = 56275176, upload-time = "2025-12-08T18:15:16.339Z" }, + { url = "https://files.pythonhosted.org/packages/e6/91/14f32e1d70905c1c0aa4e6609ab5d705c3183116ca02ac6df2091868413a/llvmlite-0.46.0-cp313-cp313-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:bca185892908f9ede48c0acd547fe4dc1bafefb8a4967d47db6cf664f9332d12", size = 55128629, upload-time = "2025-12-08T18:15:19.493Z" }, + { url = "https://files.pythonhosted.org/packages/4a/a7/d526ae86708cea531935ae777b6dbcabe7db52718e6401e0fb9c5edea80e/llvmlite-0.46.0-cp313-cp313-win_amd64.whl", hash = "sha256:67438fd30e12349ebb054d86a5a1a57fd5e87d264d2451bcfafbbbaa25b82a35", size = 38138941, upload-time = "2025-12-08T18:15:22.536Z" }, + { url = "https://files.pythonhosted.org/packages/95/ae/af0ffb724814cc2ea64445acad05f71cff5f799bb7efb22e47ee99340dbc/llvmlite-0.46.0-cp314-cp314-macosx_12_0_arm64.whl", hash = "sha256:d252edfb9f4ac1fcf20652258e3f102b26b03eef738dc8a6ffdab7d7d341d547", size = 37232768, upload-time = "2025-12-08T18:15:25.055Z" }, + { url = "https://files.pythonhosted.org/packages/c9/19/5018e5352019be753b7b07f7759cdabb69ca5779fea2494be8839270df4c/llvmlite-0.46.0-cp314-cp314-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:379fdd1c59badeff8982cb47e4694a6143bec3bb49aa10a466e095410522064d", size = 56275173, upload-time = "2025-12-08T18:15:28.109Z" }, + { url = "https://files.pythonhosted.org/packages/9f/c9/d57877759d707e84c082163c543853245f91b70c804115a5010532890f18/llvmlite-0.46.0-cp314-cp314-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:2e8cbfff7f6db0fa2c771ad24154e2a7e457c2444d7673e6de06b8b698c3b269", size = 55128628, upload-time = "2025-12-08T18:15:31.098Z" }, + { url = "https://files.pythonhosted.org/packages/30/a8/e61a8c2b3cc7a597073d9cde1fcbb567e9d827f1db30c93cf80422eac70d/llvmlite-0.46.0-cp314-cp314-win_amd64.whl", hash = "sha256:7821eda3ec1f18050f981819756631d60b6d7ab1a6cf806d9efefbe3f4082d61", size = 39153056, upload-time = "2025-12-08T18:15:33.938Z" }, +] + +[[package]] +name = "markdown-it-py" +version = "4.0.0" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "mdurl" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/5b/f5/4ec618ed16cc4f8fb3b701563655a69816155e79e24a17b651541804721d/markdown_it_py-4.0.0.tar.gz", hash = "sha256:cb0a2b4aa34f932c007117b194e945bd74e0ec24133ceb5bac59009cda1cb9f3", size = 73070, upload-time = "2025-08-11T12:57:52.854Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/94/54/e7d793b573f298e1c9013b8c4dade17d481164aa517d1d7148619c2cedbf/markdown_it_py-4.0.0-py3-none-any.whl", hash = "sha256:87327c59b172c5011896038353a81343b6754500a08cd7a4973bb48c6d578147", size = 87321, upload-time = "2025-08-11T12:57:51.923Z" }, +] + +[[package]] +name = "markupsafe" +version = "3.0.3" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/7e/99/7690b6d4034fffd95959cbe0c02de8deb3098cc577c67bb6a24fe5d7caa7/markupsafe-3.0.3.tar.gz", hash = "sha256:722695808f4b6457b320fdc131280796bdceb04ab50fe1795cd540799ebe1698", size = 80313, upload-time = "2025-09-27T18:37:40.426Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/08/db/fefacb2136439fc8dd20e797950e749aa1f4997ed584c62cfb8ef7c2be0e/markupsafe-3.0.3-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:1cc7ea17a6824959616c525620e387f6dd30fec8cb44f649e31712db02123dad", size = 11631, upload-time = "2025-09-27T18:36:18.185Z" }, + { url = "https://files.pythonhosted.org/packages/e1/2e/5898933336b61975ce9dc04decbc0a7f2fee78c30353c5efba7f2d6ff27a/markupsafe-3.0.3-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:4bd4cd07944443f5a265608cc6aab442e4f74dff8088b0dfc8238647b8f6ae9a", size = 12058, upload-time = "2025-09-27T18:36:19.444Z" }, + { url = "https://files.pythonhosted.org/packages/1d/09/adf2df3699d87d1d8184038df46a9c80d78c0148492323f4693df54e17bb/markupsafe-3.0.3-cp311-cp311-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:6b5420a1d9450023228968e7e6a9ce57f65d148ab56d2313fcd589eee96a7a50", size = 24287, upload-time = "2025-09-27T18:36:20.768Z" }, + { url = "https://files.pythonhosted.org/packages/30/ac/0273f6fcb5f42e314c6d8cd99effae6a5354604d461b8d392b5ec9530a54/markupsafe-3.0.3-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:0bf2a864d67e76e5c9a34dc26ec616a66b9888e25e7b9460e1c76d3293bd9dbf", size = 22940, upload-time = "2025-09-27T18:36:22.249Z" }, + { url = "https://files.pythonhosted.org/packages/19/ae/31c1be199ef767124c042c6c3e904da327a2f7f0cd63a0337e1eca2967a8/markupsafe-3.0.3-cp311-cp311-manylinux_2_31_riscv64.manylinux_2_39_riscv64.whl", hash = "sha256:bc51efed119bc9cfdf792cdeaa4d67e8f6fcccab66ed4bfdd6bde3e59bfcbb2f", size = 21887, upload-time = "2025-09-27T18:36:23.535Z" }, + { url = "https://files.pythonhosted.org/packages/b2/76/7edcab99d5349a4532a459e1fe64f0b0467a3365056ae550d3bcf3f79e1e/markupsafe-3.0.3-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:068f375c472b3e7acbe2d5318dea141359e6900156b5b2ba06a30b169086b91a", size = 23692, upload-time = "2025-09-27T18:36:24.823Z" }, + { url = "https://files.pythonhosted.org/packages/a4/28/6e74cdd26d7514849143d69f0bf2399f929c37dc2b31e6829fd2045b2765/markupsafe-3.0.3-cp311-cp311-musllinux_1_2_riscv64.whl", hash = "sha256:7be7b61bb172e1ed687f1754f8e7484f1c8019780f6f6b0786e76bb01c2ae115", size = 21471, upload-time = "2025-09-27T18:36:25.95Z" }, + { url = "https://files.pythonhosted.org/packages/62/7e/a145f36a5c2945673e590850a6f8014318d5577ed7e5920a4b3448e0865d/markupsafe-3.0.3-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:f9e130248f4462aaa8e2552d547f36ddadbeaa573879158d721bbd33dfe4743a", size = 22923, upload-time = "2025-09-27T18:36:27.109Z" }, + { url = "https://files.pythonhosted.org/packages/0f/62/d9c46a7f5c9adbeeeda52f5b8d802e1094e9717705a645efc71b0913a0a8/markupsafe-3.0.3-cp311-cp311-win32.whl", hash = "sha256:0db14f5dafddbb6d9208827849fad01f1a2609380add406671a26386cdf15a19", size = 14572, upload-time = "2025-09-27T18:36:28.045Z" }, + { url = "https://files.pythonhosted.org/packages/83/8a/4414c03d3f891739326e1783338e48fb49781cc915b2e0ee052aa490d586/markupsafe-3.0.3-cp311-cp311-win_amd64.whl", hash = "sha256:de8a88e63464af587c950061a5e6a67d3632e36df62b986892331d4620a35c01", size = 15077, upload-time = "2025-09-27T18:36:29.025Z" }, + { url = "https://files.pythonhosted.org/packages/35/73/893072b42e6862f319b5207adc9ae06070f095b358655f077f69a35601f0/markupsafe-3.0.3-cp311-cp311-win_arm64.whl", hash = "sha256:3b562dd9e9ea93f13d53989d23a7e775fdfd1066c33494ff43f5418bc8c58a5c", size = 13876, upload-time = "2025-09-27T18:36:29.954Z" }, + { url = "https://files.pythonhosted.org/packages/5a/72/147da192e38635ada20e0a2e1a51cf8823d2119ce8883f7053879c2199b5/markupsafe-3.0.3-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:d53197da72cc091b024dd97249dfc7794d6a56530370992a5e1a08983ad9230e", size = 11615, upload-time = "2025-09-27T18:36:30.854Z" }, + { url = "https://files.pythonhosted.org/packages/9a/81/7e4e08678a1f98521201c3079f77db69fb552acd56067661f8c2f534a718/markupsafe-3.0.3-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:1872df69a4de6aead3491198eaf13810b565bdbeec3ae2dc8780f14458ec73ce", size = 12020, upload-time = "2025-09-27T18:36:31.971Z" }, + { url = "https://files.pythonhosted.org/packages/1e/2c/799f4742efc39633a1b54a92eec4082e4f815314869865d876824c257c1e/markupsafe-3.0.3-cp312-cp312-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:3a7e8ae81ae39e62a41ec302f972ba6ae23a5c5396c8e60113e9066ef893da0d", size = 24332, upload-time = "2025-09-27T18:36:32.813Z" }, + { url = "https://files.pythonhosted.org/packages/3c/2e/8d0c2ab90a8c1d9a24f0399058ab8519a3279d1bd4289511d74e909f060e/markupsafe-3.0.3-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:d6dd0be5b5b189d31db7cda48b91d7e0a9795f31430b7f271219ab30f1d3ac9d", size = 22947, upload-time = "2025-09-27T18:36:33.86Z" }, + { url = "https://files.pythonhosted.org/packages/2c/54/887f3092a85238093a0b2154bd629c89444f395618842e8b0c41783898ea/markupsafe-3.0.3-cp312-cp312-manylinux_2_31_riscv64.manylinux_2_39_riscv64.whl", hash = "sha256:94c6f0bb423f739146aec64595853541634bde58b2135f27f61c1ffd1cd4d16a", size = 21962, upload-time = "2025-09-27T18:36:35.099Z" }, + { url = "https://files.pythonhosted.org/packages/c9/2f/336b8c7b6f4a4d95e91119dc8521402461b74a485558d8f238a68312f11c/markupsafe-3.0.3-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:be8813b57049a7dc738189df53d69395eba14fb99345e0a5994914a3864c8a4b", size = 23760, upload-time = "2025-09-27T18:36:36.001Z" }, + { url = "https://files.pythonhosted.org/packages/32/43/67935f2b7e4982ffb50a4d169b724d74b62a3964bc1a9a527f5ac4f1ee2b/markupsafe-3.0.3-cp312-cp312-musllinux_1_2_riscv64.whl", hash = "sha256:83891d0e9fb81a825d9a6d61e3f07550ca70a076484292a70fde82c4b807286f", size = 21529, upload-time = "2025-09-27T18:36:36.906Z" }, + { url = "https://files.pythonhosted.org/packages/89/e0/4486f11e51bbba8b0c041098859e869e304d1c261e59244baa3d295d47b7/markupsafe-3.0.3-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:77f0643abe7495da77fb436f50f8dab76dbc6e5fd25d39589a0f1fe6548bfa2b", size = 23015, upload-time = "2025-09-27T18:36:37.868Z" }, + { url = "https://files.pythonhosted.org/packages/2f/e1/78ee7a023dac597a5825441ebd17170785a9dab23de95d2c7508ade94e0e/markupsafe-3.0.3-cp312-cp312-win32.whl", hash = "sha256:d88b440e37a16e651bda4c7c2b930eb586fd15ca7406cb39e211fcff3bf3017d", size = 14540, upload-time = "2025-09-27T18:36:38.761Z" }, + { url = "https://files.pythonhosted.org/packages/aa/5b/bec5aa9bbbb2c946ca2733ef9c4ca91c91b6a24580193e891b5f7dbe8e1e/markupsafe-3.0.3-cp312-cp312-win_amd64.whl", hash = "sha256:26a5784ded40c9e318cfc2bdb30fe164bdb8665ded9cd64d500a34fb42067b1c", size = 15105, upload-time = "2025-09-27T18:36:39.701Z" }, + { url = "https://files.pythonhosted.org/packages/e5/f1/216fc1bbfd74011693a4fd837e7026152e89c4bcf3e77b6692fba9923123/markupsafe-3.0.3-cp312-cp312-win_arm64.whl", hash = "sha256:35add3b638a5d900e807944a078b51922212fb3dedb01633a8defc4b01a3c85f", size = 13906, upload-time = "2025-09-27T18:36:40.689Z" }, + { url = "https://files.pythonhosted.org/packages/38/2f/907b9c7bbba283e68f20259574b13d005c121a0fa4c175f9bed27c4597ff/markupsafe-3.0.3-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:e1cf1972137e83c5d4c136c43ced9ac51d0e124706ee1c8aa8532c1287fa8795", size = 11622, upload-time = "2025-09-27T18:36:41.777Z" }, + { url = "https://files.pythonhosted.org/packages/9c/d9/5f7756922cdd676869eca1c4e3c0cd0df60ed30199ffd775e319089cb3ed/markupsafe-3.0.3-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:116bb52f642a37c115f517494ea5feb03889e04df47eeff5b130b1808ce7c219", size = 12029, upload-time = "2025-09-27T18:36:43.257Z" }, + { url = "https://files.pythonhosted.org/packages/00/07/575a68c754943058c78f30db02ee03a64b3c638586fba6a6dd56830b30a3/markupsafe-3.0.3-cp313-cp313-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:133a43e73a802c5562be9bbcd03d090aa5a1fe899db609c29e8c8d815c5f6de6", size = 24374, upload-time = "2025-09-27T18:36:44.508Z" }, + { url = "https://files.pythonhosted.org/packages/a9/21/9b05698b46f218fc0e118e1f8168395c65c8a2c750ae2bab54fc4bd4e0e8/markupsafe-3.0.3-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:ccfcd093f13f0f0b7fdd0f198b90053bf7b2f02a3927a30e63f3ccc9df56b676", size = 22980, upload-time = "2025-09-27T18:36:45.385Z" }, + { url = "https://files.pythonhosted.org/packages/7f/71/544260864f893f18b6827315b988c146b559391e6e7e8f7252839b1b846a/markupsafe-3.0.3-cp313-cp313-manylinux_2_31_riscv64.manylinux_2_39_riscv64.whl", hash = "sha256:509fa21c6deb7a7a273d629cf5ec029bc209d1a51178615ddf718f5918992ab9", size = 21990, upload-time = "2025-09-27T18:36:46.916Z" }, + { url = "https://files.pythonhosted.org/packages/c2/28/b50fc2f74d1ad761af2f5dcce7492648b983d00a65b8c0e0cb457c82ebbe/markupsafe-3.0.3-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:a4afe79fb3de0b7097d81da19090f4df4f8d3a2b3adaa8764138aac2e44f3af1", size = 23784, upload-time = "2025-09-27T18:36:47.884Z" }, + { url = "https://files.pythonhosted.org/packages/ed/76/104b2aa106a208da8b17a2fb72e033a5a9d7073c68f7e508b94916ed47a9/markupsafe-3.0.3-cp313-cp313-musllinux_1_2_riscv64.whl", hash = "sha256:795e7751525cae078558e679d646ae45574b47ed6e7771863fcc079a6171a0fc", size = 21588, upload-time = "2025-09-27T18:36:48.82Z" }, + { url = "https://files.pythonhosted.org/packages/b5/99/16a5eb2d140087ebd97180d95249b00a03aa87e29cc224056274f2e45fd6/markupsafe-3.0.3-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:8485f406a96febb5140bfeca44a73e3ce5116b2501ac54fe953e488fb1d03b12", size = 23041, upload-time = "2025-09-27T18:36:49.797Z" }, + { url = "https://files.pythonhosted.org/packages/19/bc/e7140ed90c5d61d77cea142eed9f9c303f4c4806f60a1044c13e3f1471d0/markupsafe-3.0.3-cp313-cp313-win32.whl", hash = "sha256:bdd37121970bfd8be76c5fb069c7751683bdf373db1ed6c010162b2a130248ed", size = 14543, upload-time = "2025-09-27T18:36:51.584Z" }, + { url = "https://files.pythonhosted.org/packages/05/73/c4abe620b841b6b791f2edc248f556900667a5a1cf023a6646967ae98335/markupsafe-3.0.3-cp313-cp313-win_amd64.whl", hash = "sha256:9a1abfdc021a164803f4d485104931fb8f8c1efd55bc6b748d2f5774e78b62c5", size = 15113, upload-time = "2025-09-27T18:36:52.537Z" }, + { url = "https://files.pythonhosted.org/packages/f0/3a/fa34a0f7cfef23cf9500d68cb7c32dd64ffd58a12b09225fb03dd37d5b80/markupsafe-3.0.3-cp313-cp313-win_arm64.whl", hash = "sha256:7e68f88e5b8799aa49c85cd116c932a1ac15caaa3f5db09087854d218359e485", size = 13911, upload-time = "2025-09-27T18:36:53.513Z" }, + { url = "https://files.pythonhosted.org/packages/e4/d7/e05cd7efe43a88a17a37b3ae96e79a19e846f3f456fe79c57ca61356ef01/markupsafe-3.0.3-cp313-cp313t-macosx_10_13_x86_64.whl", hash = "sha256:218551f6df4868a8d527e3062d0fb968682fe92054e89978594c28e642c43a73", size = 11658, upload-time = "2025-09-27T18:36:54.819Z" }, + { url = "https://files.pythonhosted.org/packages/99/9e/e412117548182ce2148bdeacdda3bb494260c0b0184360fe0d56389b523b/markupsafe-3.0.3-cp313-cp313t-macosx_11_0_arm64.whl", hash = "sha256:3524b778fe5cfb3452a09d31e7b5adefeea8c5be1d43c4f810ba09f2ceb29d37", size = 12066, upload-time = "2025-09-27T18:36:55.714Z" }, + { url = "https://files.pythonhosted.org/packages/bc/e6/fa0ffcda717ef64a5108eaa7b4f5ed28d56122c9a6d70ab8b72f9f715c80/markupsafe-3.0.3-cp313-cp313t-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:4e885a3d1efa2eadc93c894a21770e4bc67899e3543680313b09f139e149ab19", size = 25639, upload-time = "2025-09-27T18:36:56.908Z" }, + { url = "https://files.pythonhosted.org/packages/96/ec/2102e881fe9d25fc16cb4b25d5f5cde50970967ffa5dddafdb771237062d/markupsafe-3.0.3-cp313-cp313t-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:8709b08f4a89aa7586de0aadc8da56180242ee0ada3999749b183aa23df95025", size = 23569, upload-time = "2025-09-27T18:36:57.913Z" }, + { url = "https://files.pythonhosted.org/packages/4b/30/6f2fce1f1f205fc9323255b216ca8a235b15860c34b6798f810f05828e32/markupsafe-3.0.3-cp313-cp313t-manylinux_2_31_riscv64.manylinux_2_39_riscv64.whl", hash = "sha256:b8512a91625c9b3da6f127803b166b629725e68af71f8184ae7e7d54686a56d6", size = 23284, upload-time = "2025-09-27T18:36:58.833Z" }, + { url = "https://files.pythonhosted.org/packages/58/47/4a0ccea4ab9f5dcb6f79c0236d954acb382202721e704223a8aafa38b5c8/markupsafe-3.0.3-cp313-cp313t-musllinux_1_2_aarch64.whl", hash = "sha256:9b79b7a16f7fedff2495d684f2b59b0457c3b493778c9eed31111be64d58279f", size = 24801, upload-time = "2025-09-27T18:36:59.739Z" }, + { url = "https://files.pythonhosted.org/packages/6a/70/3780e9b72180b6fecb83a4814d84c3bf4b4ae4bf0b19c27196104149734c/markupsafe-3.0.3-cp313-cp313t-musllinux_1_2_riscv64.whl", hash = "sha256:12c63dfb4a98206f045aa9563db46507995f7ef6d83b2f68eda65c307c6829eb", size = 22769, upload-time = "2025-09-27T18:37:00.719Z" }, + { url = "https://files.pythonhosted.org/packages/98/c5/c03c7f4125180fc215220c035beac6b9cb684bc7a067c84fc69414d315f5/markupsafe-3.0.3-cp313-cp313t-musllinux_1_2_x86_64.whl", hash = "sha256:8f71bc33915be5186016f675cd83a1e08523649b0e33efdb898db577ef5bb009", size = 23642, upload-time = "2025-09-27T18:37:01.673Z" }, + { url = "https://files.pythonhosted.org/packages/80/d6/2d1b89f6ca4bff1036499b1e29a1d02d282259f3681540e16563f27ebc23/markupsafe-3.0.3-cp313-cp313t-win32.whl", hash = "sha256:69c0b73548bc525c8cb9a251cddf1931d1db4d2258e9599c28c07ef3580ef354", size = 14612, upload-time = "2025-09-27T18:37:02.639Z" }, + { url = "https://files.pythonhosted.org/packages/2b/98/e48a4bfba0a0ffcf9925fe2d69240bfaa19c6f7507b8cd09c70684a53c1e/markupsafe-3.0.3-cp313-cp313t-win_amd64.whl", hash = "sha256:1b4b79e8ebf6b55351f0d91fe80f893b4743f104bff22e90697db1590e47a218", size = 15200, upload-time = "2025-09-27T18:37:03.582Z" }, + { url = "https://files.pythonhosted.org/packages/0e/72/e3cc540f351f316e9ed0f092757459afbc595824ca724cbc5a5d4263713f/markupsafe-3.0.3-cp313-cp313t-win_arm64.whl", hash = "sha256:ad2cf8aa28b8c020ab2fc8287b0f823d0a7d8630784c31e9ee5edea20f406287", size = 13973, upload-time = "2025-09-27T18:37:04.929Z" }, + { url = "https://files.pythonhosted.org/packages/33/8a/8e42d4838cd89b7dde187011e97fe6c3af66d8c044997d2183fbd6d31352/markupsafe-3.0.3-cp314-cp314-macosx_10_13_x86_64.whl", hash = "sha256:eaa9599de571d72e2daf60164784109f19978b327a3910d3e9de8c97b5b70cfe", size = 11619, upload-time = "2025-09-27T18:37:06.342Z" }, + { url = "https://files.pythonhosted.org/packages/b5/64/7660f8a4a8e53c924d0fa05dc3a55c9cee10bbd82b11c5afb27d44b096ce/markupsafe-3.0.3-cp314-cp314-macosx_11_0_arm64.whl", hash = "sha256:c47a551199eb8eb2121d4f0f15ae0f923d31350ab9280078d1e5f12b249e0026", size = 12029, upload-time = "2025-09-27T18:37:07.213Z" }, + { url = "https://files.pythonhosted.org/packages/da/ef/e648bfd021127bef5fa12e1720ffed0c6cbb8310c8d9bea7266337ff06de/markupsafe-3.0.3-cp314-cp314-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:f34c41761022dd093b4b6896d4810782ffbabe30f2d443ff5f083e0cbbb8c737", size = 24408, upload-time = "2025-09-27T18:37:09.572Z" }, + { url = "https://files.pythonhosted.org/packages/41/3c/a36c2450754618e62008bf7435ccb0f88053e07592e6028a34776213d877/markupsafe-3.0.3-cp314-cp314-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:457a69a9577064c05a97c41f4e65148652db078a3a509039e64d3467b9e7ef97", size = 23005, upload-time = "2025-09-27T18:37:10.58Z" }, + { url = "https://files.pythonhosted.org/packages/bc/20/b7fdf89a8456b099837cd1dc21974632a02a999ec9bf7ca3e490aacd98e7/markupsafe-3.0.3-cp314-cp314-manylinux_2_31_riscv64.manylinux_2_39_riscv64.whl", hash = "sha256:e8afc3f2ccfa24215f8cb28dcf43f0113ac3c37c2f0f0806d8c70e4228c5cf4d", size = 22048, upload-time = "2025-09-27T18:37:11.547Z" }, + { url = "https://files.pythonhosted.org/packages/9a/a7/591f592afdc734f47db08a75793a55d7fbcc6902a723ae4cfbab61010cc5/markupsafe-3.0.3-cp314-cp314-musllinux_1_2_aarch64.whl", hash = "sha256:ec15a59cf5af7be74194f7ab02d0f59a62bdcf1a537677ce67a2537c9b87fcda", size = 23821, upload-time = "2025-09-27T18:37:12.48Z" }, + { url = "https://files.pythonhosted.org/packages/7d/33/45b24e4f44195b26521bc6f1a82197118f74df348556594bd2262bda1038/markupsafe-3.0.3-cp314-cp314-musllinux_1_2_riscv64.whl", hash = "sha256:0eb9ff8191e8498cca014656ae6b8d61f39da5f95b488805da4bb029cccbfbaf", size = 21606, upload-time = "2025-09-27T18:37:13.485Z" }, + { url = "https://files.pythonhosted.org/packages/ff/0e/53dfaca23a69fbfbbf17a4b64072090e70717344c52eaaaa9c5ddff1e5f0/markupsafe-3.0.3-cp314-cp314-musllinux_1_2_x86_64.whl", hash = "sha256:2713baf880df847f2bece4230d4d094280f4e67b1e813eec43b4c0e144a34ffe", size = 23043, upload-time = "2025-09-27T18:37:14.408Z" }, + { url = "https://files.pythonhosted.org/packages/46/11/f333a06fc16236d5238bfe74daccbca41459dcd8d1fa952e8fbd5dccfb70/markupsafe-3.0.3-cp314-cp314-win32.whl", hash = "sha256:729586769a26dbceff69f7a7dbbf59ab6572b99d94576a5592625d5b411576b9", size = 14747, upload-time = "2025-09-27T18:37:15.36Z" }, + { url = "https://files.pythonhosted.org/packages/28/52/182836104b33b444e400b14f797212f720cbc9ed6ba34c800639d154e821/markupsafe-3.0.3-cp314-cp314-win_amd64.whl", hash = "sha256:bdc919ead48f234740ad807933cdf545180bfbe9342c2bb451556db2ed958581", size = 15341, upload-time = "2025-09-27T18:37:16.496Z" }, + { url = "https://files.pythonhosted.org/packages/6f/18/acf23e91bd94fd7b3031558b1f013adfa21a8e407a3fdb32745538730382/markupsafe-3.0.3-cp314-cp314-win_arm64.whl", hash = "sha256:5a7d5dc5140555cf21a6fefbdbf8723f06fcd2f63ef108f2854de715e4422cb4", size = 14073, upload-time = "2025-09-27T18:37:17.476Z" }, + { url = "https://files.pythonhosted.org/packages/3c/f0/57689aa4076e1b43b15fdfa646b04653969d50cf30c32a102762be2485da/markupsafe-3.0.3-cp314-cp314t-macosx_10_13_x86_64.whl", hash = "sha256:1353ef0c1b138e1907ae78e2f6c63ff67501122006b0f9abad68fda5f4ffc6ab", size = 11661, upload-time = "2025-09-27T18:37:18.453Z" }, + { url = "https://files.pythonhosted.org/packages/89/c3/2e67a7ca217c6912985ec766c6393b636fb0c2344443ff9d91404dc4c79f/markupsafe-3.0.3-cp314-cp314t-macosx_11_0_arm64.whl", hash = "sha256:1085e7fbddd3be5f89cc898938f42c0b3c711fdcb37d75221de2666af647c175", size = 12069, upload-time = "2025-09-27T18:37:19.332Z" }, + { url = "https://files.pythonhosted.org/packages/f0/00/be561dce4e6ca66b15276e184ce4b8aec61fe83662cce2f7d72bd3249d28/markupsafe-3.0.3-cp314-cp314t-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:1b52b4fb9df4eb9ae465f8d0c228a00624de2334f216f178a995ccdcf82c4634", size = 25670, upload-time = "2025-09-27T18:37:20.245Z" }, + { url = "https://files.pythonhosted.org/packages/50/09/c419f6f5a92e5fadde27efd190eca90f05e1261b10dbd8cbcb39cd8ea1dc/markupsafe-3.0.3-cp314-cp314t-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:fed51ac40f757d41b7c48425901843666a6677e3e8eb0abcff09e4ba6e664f50", size = 23598, upload-time = "2025-09-27T18:37:21.177Z" }, + { url = "https://files.pythonhosted.org/packages/22/44/a0681611106e0b2921b3033fc19bc53323e0b50bc70cffdd19f7d679bb66/markupsafe-3.0.3-cp314-cp314t-manylinux_2_31_riscv64.manylinux_2_39_riscv64.whl", hash = "sha256:f190daf01f13c72eac4efd5c430a8de82489d9cff23c364c3ea822545032993e", size = 23261, upload-time = "2025-09-27T18:37:22.167Z" }, + { url = "https://files.pythonhosted.org/packages/5f/57/1b0b3f100259dc9fffe780cfb60d4be71375510e435efec3d116b6436d43/markupsafe-3.0.3-cp314-cp314t-musllinux_1_2_aarch64.whl", hash = "sha256:e56b7d45a839a697b5eb268c82a71bd8c7f6c94d6fd50c3d577fa39a9f1409f5", size = 24835, upload-time = "2025-09-27T18:37:23.296Z" }, + { url = "https://files.pythonhosted.org/packages/26/6a/4bf6d0c97c4920f1597cc14dd720705eca0bf7c787aebc6bb4d1bead5388/markupsafe-3.0.3-cp314-cp314t-musllinux_1_2_riscv64.whl", hash = "sha256:f3e98bb3798ead92273dc0e5fd0f31ade220f59a266ffd8a4f6065e0a3ce0523", size = 22733, upload-time = "2025-09-27T18:37:24.237Z" }, + { url = "https://files.pythonhosted.org/packages/14/c7/ca723101509b518797fedc2fdf79ba57f886b4aca8a7d31857ba3ee8281f/markupsafe-3.0.3-cp314-cp314t-musllinux_1_2_x86_64.whl", hash = "sha256:5678211cb9333a6468fb8d8be0305520aa073f50d17f089b5b4b477ea6e67fdc", size = 23672, upload-time = "2025-09-27T18:37:25.271Z" }, + { url = "https://files.pythonhosted.org/packages/fb/df/5bd7a48c256faecd1d36edc13133e51397e41b73bb77e1a69deab746ebac/markupsafe-3.0.3-cp314-cp314t-win32.whl", hash = "sha256:915c04ba3851909ce68ccc2b8e2cd691618c4dc4c4232fb7982bca3f41fd8c3d", size = 14819, upload-time = "2025-09-27T18:37:26.285Z" }, + { url = "https://files.pythonhosted.org/packages/1a/8a/0402ba61a2f16038b48b39bccca271134be00c5c9f0f623208399333c448/markupsafe-3.0.3-cp314-cp314t-win_amd64.whl", hash = "sha256:4faffd047e07c38848ce017e8725090413cd80cbc23d86e55c587bf979e579c9", size = 15426, upload-time = "2025-09-27T18:37:27.316Z" }, + { url = "https://files.pythonhosted.org/packages/70/bc/6f1c2f612465f5fa89b95bead1f44dcb607670fd42891d8fdcd5d039f4f4/markupsafe-3.0.3-cp314-cp314t-win_arm64.whl", hash = "sha256:32001d6a8fc98c8cb5c947787c5d08b0a50663d139f1305bac5885d98d9b40fa", size = 14146, upload-time = "2025-09-27T18:37:28.327Z" }, +] + +[[package]] +name = "matplotlib" +version = "3.10.8" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "contourpy" }, + { name = "cycler" }, + { name = "fonttools" }, + { name = "kiwisolver" }, + { name = "numpy" }, + { name = "packaging" }, + { name = "pillow" }, + { name = "pyparsing" }, + { name = "python-dateutil" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/8a/76/d3c6e3a13fe484ebe7718d14e269c9569c4eb0020a968a327acb3b9a8fe6/matplotlib-3.10.8.tar.gz", hash = "sha256:2299372c19d56bcd35cf05a2738308758d32b9eaed2371898d8f5bd33f084aa3", size = 34806269, upload-time = "2025-12-10T22:56:51.155Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/f8/86/de7e3a1cdcfc941483af70609edc06b83e7c8a0e0dc9ac325200a3f4d220/matplotlib-3.10.8-cp311-cp311-macosx_10_12_x86_64.whl", hash = "sha256:6be43b667360fef5c754dda5d25a32e6307a03c204f3c0fc5468b78fa87b4160", size = 8251215, upload-time = "2025-12-10T22:55:16.175Z" }, + { url = "https://files.pythonhosted.org/packages/fd/14/baad3222f424b19ce6ad243c71de1ad9ec6b2e4eb1e458a48fdc6d120401/matplotlib-3.10.8-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:a2b336e2d91a3d7006864e0990c83b216fcdca64b5a6484912902cef87313d78", size = 8139625, upload-time = "2025-12-10T22:55:17.712Z" }, + { url = "https://files.pythonhosted.org/packages/8f/a0/7024215e95d456de5883e6732e708d8187d9753a21d32f8ddb3befc0c445/matplotlib-3.10.8-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:efb30e3baaea72ce5928e32bab719ab4770099079d66726a62b11b1ef7273be4", size = 8712614, upload-time = "2025-12-10T22:55:20.8Z" }, + { url = "https://files.pythonhosted.org/packages/5a/f4/b8347351da9a5b3f41e26cf547252d861f685c6867d179a7c9d60ad50189/matplotlib-3.10.8-cp311-cp311-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:d56a1efd5bfd61486c8bc968fa18734464556f0fb8e51690f4ac25d85cbbbbc2", size = 9540997, upload-time = "2025-12-10T22:55:23.258Z" }, + { url = "https://files.pythonhosted.org/packages/9e/c0/c7b914e297efe0bc36917bf216b2acb91044b91e930e878ae12981e461e5/matplotlib-3.10.8-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:238b7ce5717600615c895050239ec955d91f321c209dd110db988500558e70d6", size = 9596825, upload-time = "2025-12-10T22:55:25.217Z" }, + { url = "https://files.pythonhosted.org/packages/6f/d3/a4bbc01c237ab710a1f22b4da72f4ff6d77eb4c7735ea9811a94ae239067/matplotlib-3.10.8-cp311-cp311-win_amd64.whl", hash = "sha256:18821ace09c763ec93aef5eeff087ee493a24051936d7b9ebcad9662f66501f9", size = 8135090, upload-time = "2025-12-10T22:55:27.162Z" }, + { url = "https://files.pythonhosted.org/packages/89/dd/a0b6588f102beab33ca6f5218b31725216577b2a24172f327eaf6417d5c9/matplotlib-3.10.8-cp311-cp311-win_arm64.whl", hash = "sha256:bab485bcf8b1c7d2060b4fcb6fc368a9e6f4cd754c9c2fea281f4be21df394a2", size = 8012377, upload-time = "2025-12-10T22:55:29.185Z" }, + { url = "https://files.pythonhosted.org/packages/9e/67/f997cdcbb514012eb0d10cd2b4b332667997fb5ebe26b8d41d04962fa0e6/matplotlib-3.10.8-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:64fcc24778ca0404ce0cb7b6b77ae1f4c7231cdd60e6778f999ee05cbd581b9a", size = 8260453, upload-time = "2025-12-10T22:55:30.709Z" }, + { url = "https://files.pythonhosted.org/packages/7e/65/07d5f5c7f7c994f12c768708bd2e17a4f01a2b0f44a1c9eccad872433e2e/matplotlib-3.10.8-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:b9a5ca4ac220a0cdd1ba6bcba3608547117d30468fefce49bb26f55c1a3d5c58", size = 8148321, upload-time = "2025-12-10T22:55:33.265Z" }, + { url = "https://files.pythonhosted.org/packages/3e/f3/c5195b1ae57ef85339fd7285dfb603b22c8b4e79114bae5f4f0fcf688677/matplotlib-3.10.8-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:3ab4aabc72de4ff77b3ec33a6d78a68227bf1123465887f9905ba79184a1cc04", size = 8716944, upload-time = "2025-12-10T22:55:34.922Z" }, + { url = "https://files.pythonhosted.org/packages/00/f9/7638f5cc82ec8a7aa005de48622eecc3ed7c9854b96ba15bd76b7fd27574/matplotlib-3.10.8-cp312-cp312-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:24d50994d8c5816ddc35411e50a86ab05f575e2530c02752e02538122613371f", size = 9550099, upload-time = "2025-12-10T22:55:36.789Z" }, + { url = "https://files.pythonhosted.org/packages/57/61/78cd5920d35b29fd2a0fe894de8adf672ff52939d2e9b43cb83cd5ce1bc7/matplotlib-3.10.8-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:99eefd13c0dc3b3c1b4d561c1169e65fe47aab7b8158754d7c084088e2329466", size = 9613040, upload-time = "2025-12-10T22:55:38.715Z" }, + { url = "https://files.pythonhosted.org/packages/30/4e/c10f171b6e2f44d9e3a2b96efa38b1677439d79c99357600a62cc1e9594e/matplotlib-3.10.8-cp312-cp312-win_amd64.whl", hash = "sha256:dd80ecb295460a5d9d260df63c43f4afbdd832d725a531f008dad1664f458adf", size = 8142717, upload-time = "2025-12-10T22:55:41.103Z" }, + { url = "https://files.pythonhosted.org/packages/f1/76/934db220026b5fef85f45d51a738b91dea7d70207581063cd9bd8fafcf74/matplotlib-3.10.8-cp312-cp312-win_arm64.whl", hash = "sha256:3c624e43ed56313651bc18a47f838b60d7b8032ed348911c54906b130b20071b", size = 8012751, upload-time = "2025-12-10T22:55:42.684Z" }, + { url = "https://files.pythonhosted.org/packages/3d/b9/15fd5541ef4f5b9a17eefd379356cf12175fe577424e7b1d80676516031a/matplotlib-3.10.8-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:3f2e409836d7f5ac2f1c013110a4d50b9f7edc26328c108915f9075d7d7a91b6", size = 8261076, upload-time = "2025-12-10T22:55:44.648Z" }, + { url = "https://files.pythonhosted.org/packages/8d/a0/2ba3473c1b66b9c74dc7107c67e9008cb1782edbe896d4c899d39ae9cf78/matplotlib-3.10.8-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:56271f3dac49a88d7fca5060f004d9d22b865f743a12a23b1e937a0be4818ee1", size = 8148794, upload-time = "2025-12-10T22:55:46.252Z" }, + { url = "https://files.pythonhosted.org/packages/75/97/a471f1c3eb1fd6f6c24a31a5858f443891d5127e63a7788678d14e249aea/matplotlib-3.10.8-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:a0a7f52498f72f13d4a25ea70f35f4cb60642b466cbb0a9be951b5bc3f45a486", size = 8718474, upload-time = "2025-12-10T22:55:47.864Z" }, + { url = "https://files.pythonhosted.org/packages/01/be/cd478f4b66f48256f42927d0acbcd63a26a893136456cd079c0cc24fbabf/matplotlib-3.10.8-cp313-cp313-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:646d95230efb9ca614a7a594d4fcacde0ac61d25e37dd51710b36477594963ce", size = 9549637, upload-time = "2025-12-10T22:55:50.048Z" }, + { url = "https://files.pythonhosted.org/packages/5d/7c/8dc289776eae5109e268c4fb92baf870678dc048a25d4ac903683b86d5bf/matplotlib-3.10.8-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:f89c151aab2e2e23cb3fe0acad1e8b82841fd265379c4cecd0f3fcb34c15e0f6", size = 9613678, upload-time = "2025-12-10T22:55:52.21Z" }, + { url = "https://files.pythonhosted.org/packages/64/40/37612487cc8a437d4dd261b32ca21fe2d79510fe74af74e1f42becb1bdb8/matplotlib-3.10.8-cp313-cp313-win_amd64.whl", hash = "sha256:e8ea3e2d4066083e264e75c829078f9e149fa119d27e19acd503de65e0b13149", size = 8142686, upload-time = "2025-12-10T22:55:54.253Z" }, + { url = "https://files.pythonhosted.org/packages/66/52/8d8a8730e968185514680c2a6625943f70269509c3dcfc0dcf7d75928cb8/matplotlib-3.10.8-cp313-cp313-win_arm64.whl", hash = "sha256:c108a1d6fa78a50646029cb6d49808ff0fc1330fda87fa6f6250c6b5369b6645", size = 8012917, upload-time = "2025-12-10T22:55:56.268Z" }, + { url = "https://files.pythonhosted.org/packages/b5/27/51fe26e1062f298af5ef66343d8ef460e090a27fea73036c76c35821df04/matplotlib-3.10.8-cp313-cp313t-macosx_10_13_x86_64.whl", hash = "sha256:ad3d9833a64cf48cc4300f2b406c3d0f4f4724a91c0bd5640678a6ba7c102077", size = 8305679, upload-time = "2025-12-10T22:55:57.856Z" }, + { url = "https://files.pythonhosted.org/packages/2c/1e/4de865bc591ac8e3062e835f42dd7fe7a93168d519557837f0e37513f629/matplotlib-3.10.8-cp313-cp313t-macosx_11_0_arm64.whl", hash = "sha256:eb3823f11823deade26ce3b9f40dcb4a213da7a670013929f31d5f5ed1055b22", size = 8198336, upload-time = "2025-12-10T22:55:59.371Z" }, + { url = "https://files.pythonhosted.org/packages/c6/cb/2f7b6e75fb4dce87ef91f60cac4f6e34f4c145ab036a22318ec837971300/matplotlib-3.10.8-cp313-cp313t-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:d9050fee89a89ed57b4fb2c1bfac9a3d0c57a0d55aed95949eedbc42070fea39", size = 8731653, upload-time = "2025-12-10T22:56:01.032Z" }, + { url = "https://files.pythonhosted.org/packages/46/b3/bd9c57d6ba670a37ab31fb87ec3e8691b947134b201f881665b28cc039ff/matplotlib-3.10.8-cp313-cp313t-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:b44d07310e404ba95f8c25aa5536f154c0a8ec473303535949e52eb71d0a1565", size = 9561356, upload-time = "2025-12-10T22:56:02.95Z" }, + { url = "https://files.pythonhosted.org/packages/c0/3d/8b94a481456dfc9dfe6e39e93b5ab376e50998cddfd23f4ae3b431708f16/matplotlib-3.10.8-cp313-cp313t-musllinux_1_2_x86_64.whl", hash = "sha256:0a33deb84c15ede243aead39f77e990469fff93ad1521163305095b77b72ce4a", size = 9614000, upload-time = "2025-12-10T22:56:05.411Z" }, + { url = "https://files.pythonhosted.org/packages/bd/cd/bc06149fe5585ba800b189a6a654a75f1f127e8aab02fd2be10df7fa500c/matplotlib-3.10.8-cp313-cp313t-win_amd64.whl", hash = "sha256:3a48a78d2786784cc2413e57397981fb45c79e968d99656706018d6e62e57958", size = 8220043, upload-time = "2025-12-10T22:56:07.551Z" }, + { url = "https://files.pythonhosted.org/packages/e3/de/b22cf255abec916562cc04eef457c13e58a1990048de0c0c3604d082355e/matplotlib-3.10.8-cp313-cp313t-win_arm64.whl", hash = "sha256:15d30132718972c2c074cd14638c7f4592bd98719e2308bccea40e0538bc0cb5", size = 8062075, upload-time = "2025-12-10T22:56:09.178Z" }, + { url = "https://files.pythonhosted.org/packages/3c/43/9c0ff7a2f11615e516c3b058e1e6e8f9614ddeca53faca06da267c48345d/matplotlib-3.10.8-cp314-cp314-macosx_10_13_x86_64.whl", hash = "sha256:b53285e65d4fa4c86399979e956235deb900be5baa7fc1218ea67fbfaeaadd6f", size = 8262481, upload-time = "2025-12-10T22:56:10.885Z" }, + { url = "https://files.pythonhosted.org/packages/6f/ca/e8ae28649fcdf039fda5ef554b40a95f50592a3c47e6f7270c9561c12b07/matplotlib-3.10.8-cp314-cp314-macosx_11_0_arm64.whl", hash = "sha256:32f8dce744be5569bebe789e46727946041199030db8aeb2954d26013a0eb26b", size = 8151473, upload-time = "2025-12-10T22:56:12.377Z" }, + { url = "https://files.pythonhosted.org/packages/f1/6f/009d129ae70b75e88cbe7e503a12a4c0670e08ed748a902c2568909e9eb5/matplotlib-3.10.8-cp314-cp314-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:4cf267add95b1c88300d96ca837833d4112756045364f5c734a2276038dae27d", size = 9553896, upload-time = "2025-12-10T22:56:14.432Z" }, + { url = "https://files.pythonhosted.org/packages/f5/26/4221a741eb97967bc1fd5e4c52b9aa5a91b2f4ec05b59f6def4d820f9df9/matplotlib-3.10.8-cp314-cp314-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:2cf5bd12cecf46908f286d7838b2abc6c91cda506c0445b8223a7c19a00df008", size = 9824193, upload-time = "2025-12-10T22:56:16.29Z" }, + { url = "https://files.pythonhosted.org/packages/1f/f3/3abf75f38605772cf48a9daf5821cd4f563472f38b4b828c6fba6fa6d06e/matplotlib-3.10.8-cp314-cp314-musllinux_1_2_x86_64.whl", hash = "sha256:41703cc95688f2516b480f7f339d8851a6035f18e100ee6a32bc0b8536a12a9c", size = 9615444, upload-time = "2025-12-10T22:56:18.155Z" }, + { url = "https://files.pythonhosted.org/packages/93/a5/de89ac80f10b8dc615807ee1133cd99ac74082581196d4d9590bea10690d/matplotlib-3.10.8-cp314-cp314-win_amd64.whl", hash = "sha256:83d282364ea9f3e52363da262ce32a09dfe241e4080dcedda3c0db059d3c1f11", size = 8272719, upload-time = "2025-12-10T22:56:20.366Z" }, + { url = "https://files.pythonhosted.org/packages/69/ce/b006495c19ccc0a137b48083168a37bd056392dee02f87dba0472f2797fe/matplotlib-3.10.8-cp314-cp314-win_arm64.whl", hash = "sha256:2c1998e92cd5999e295a731bcb2911c75f597d937341f3030cc24ef2733d78a8", size = 8144205, upload-time = "2025-12-10T22:56:22.239Z" }, + { url = "https://files.pythonhosted.org/packages/68/d9/b31116a3a855bd313c6fcdb7226926d59b041f26061c6c5b1be66a08c826/matplotlib-3.10.8-cp314-cp314t-macosx_10_13_x86_64.whl", hash = "sha256:b5a2b97dbdc7d4f353ebf343744f1d1f1cca8aa8bfddb4262fcf4306c3761d50", size = 8305785, upload-time = "2025-12-10T22:56:24.218Z" }, + { url = "https://files.pythonhosted.org/packages/1e/90/6effe8103f0272685767ba5f094f453784057072f49b393e3ea178fe70a5/matplotlib-3.10.8-cp314-cp314t-macosx_11_0_arm64.whl", hash = "sha256:3f5c3e4da343bba819f0234186b9004faba952cc420fbc522dc4e103c1985908", size = 8198361, upload-time = "2025-12-10T22:56:26.787Z" }, + { url = "https://files.pythonhosted.org/packages/d7/65/a73188711bea603615fc0baecca1061429ac16940e2385433cc778a9d8e7/matplotlib-3.10.8-cp314-cp314t-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:5f62550b9a30afde8c1c3ae450e5eb547d579dd69b25c2fc7a1c67f934c1717a", size = 9561357, upload-time = "2025-12-10T22:56:28.953Z" }, + { url = "https://files.pythonhosted.org/packages/f4/3d/b5c5d5d5be8ce63292567f0e2c43dde9953d3ed86ac2de0a72e93c8f07a1/matplotlib-3.10.8-cp314-cp314t-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:495672de149445ec1b772ff2c9ede9b769e3cb4f0d0aa7fa730d7f59e2d4e1c1", size = 9823610, upload-time = "2025-12-10T22:56:31.455Z" }, + { url = "https://files.pythonhosted.org/packages/4d/4b/e7beb6bbd49f6bae727a12b270a2654d13c397576d25bd6786e47033300f/matplotlib-3.10.8-cp314-cp314t-musllinux_1_2_x86_64.whl", hash = "sha256:595ba4d8fe983b88f0eec8c26a241e16d6376fe1979086232f481f8f3f67494c", size = 9614011, upload-time = "2025-12-10T22:56:33.85Z" }, + { url = "https://files.pythonhosted.org/packages/7c/e6/76f2813d31f032e65f6f797e3f2f6e4aab95b65015924b1c51370395c28a/matplotlib-3.10.8-cp314-cp314t-win_amd64.whl", hash = "sha256:25d380fe8b1dc32cf8f0b1b448470a77afb195438bafdf1d858bfb876f3edf7b", size = 8362801, upload-time = "2025-12-10T22:56:36.107Z" }, + { url = "https://files.pythonhosted.org/packages/5d/49/d651878698a0b67f23aa28e17f45a6d6dd3d3f933fa29087fa4ce5947b5a/matplotlib-3.10.8-cp314-cp314t-win_arm64.whl", hash = "sha256:113bb52413ea508ce954a02c10ffd0d565f9c3bc7f2eddc27dfe1731e71c7b5f", size = 8192560, upload-time = "2025-12-10T22:56:38.008Z" }, + { url = "https://files.pythonhosted.org/packages/04/30/3afaa31c757f34b7725ab9d2ba8b48b5e89c2019c003e7d0ead143aabc5a/matplotlib-3.10.8-pp311-pypy311_pp73-macosx_10_15_x86_64.whl", hash = "sha256:6da7c2ce169267d0d066adcf63758f0604aa6c3eebf67458930f9d9b79ad1db1", size = 8249198, upload-time = "2025-12-10T22:56:45.584Z" }, + { url = "https://files.pythonhosted.org/packages/48/2f/6334aec331f57485a642a7c8be03cb286f29111ae71c46c38b363230063c/matplotlib-3.10.8-pp311-pypy311_pp73-macosx_11_0_arm64.whl", hash = "sha256:9153c3292705be9f9c64498a8872118540c3f4123d1a1c840172edf262c8be4a", size = 8136817, upload-time = "2025-12-10T22:56:47.339Z" }, + { url = "https://files.pythonhosted.org/packages/73/e4/6d6f14b2a759c622f191b2d67e9075a3f56aaccb3be4bb9bb6890030d0a0/matplotlib-3.10.8-pp311-pypy311_pp73-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:1ae029229a57cd1e8fe542485f27e7ca7b23aa9e8944ddb4985d0bc444f1eca2", size = 8713867, upload-time = "2025-12-10T22:56:48.954Z" }, +] + +[[package]] +name = "matplotlib-inline" +version = "0.2.1" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "traitlets" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/c7/74/97e72a36efd4ae2bccb3463284300f8953f199b5ffbc04cbbb0ec78f74b1/matplotlib_inline-0.2.1.tar.gz", hash = "sha256:e1ee949c340d771fc39e241ea75683deb94762c8fa5f2927ec57c83c4dffa9fe", size = 8110, upload-time = "2025-10-23T09:00:22.126Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/af/33/ee4519fa02ed11a94aef9559552f3b17bb863f2ecfe1a35dc7f548cde231/matplotlib_inline-0.2.1-py3-none-any.whl", hash = "sha256:d56ce5156ba6085e00a9d54fead6ed29a9c47e215cd1bba2e976ef39f5710a76", size = 9516, upload-time = "2025-10-23T09:00:20.675Z" }, +] + +[[package]] +name = "matplotlib-sankey" +version = "0.3.2" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "matplotlib" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/71/43/676dd09556fcd8c778e66606ca9707b94aa7fff10d8df7ba33e094dabf5b/matplotlib_sankey-0.3.2.tar.gz", hash = "sha256:4244853b32e38bc1569dd23fe782731486faa6e74bdc97f48154ef2180a2070b", size = 9359, upload-time = "2026-02-11T20:49:35.318Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/e5/c9/d1022fd88a64566b9ef5c90097c8204e56dff05f264b9c761b4d1c08e3d2/matplotlib_sankey-0.3.2-py3-none-any.whl", hash = "sha256:db7a579e1999c42534f6f54a6ffd4402dea0197920a945adce2f968df24099cd", size = 11246, upload-time = "2026-02-11T20:49:34.541Z" }, +] + +[[package]] +name = "mdit-py-plugins" +version = "0.5.0" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "markdown-it-py" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/b2/fd/a756d36c0bfba5f6e39a1cdbdbfdd448dc02692467d83816dff4592a1ebc/mdit_py_plugins-0.5.0.tar.gz", hash = "sha256:f4918cb50119f50446560513a8e311d574ff6aaed72606ddae6d35716fe809c6", size = 44655, upload-time = "2025-08-11T07:25:49.083Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/fb/86/dd6e5db36df29e76c7a7699123569a4a18c1623ce68d826ed96c62643cae/mdit_py_plugins-0.5.0-py3-none-any.whl", hash = "sha256:07a08422fc1936a5d26d146759e9155ea466e842f5ab2f7d2266dd084c8dab1f", size = 57205, upload-time = "2025-08-11T07:25:47.597Z" }, +] + +[[package]] +name = "mdurl" +version = "0.1.2" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/d6/54/cfe61301667036ec958cb99bd3efefba235e65cdeb9c84d24a8293ba1d90/mdurl-0.1.2.tar.gz", hash = "sha256:bb413d29f5eea38f31dd4754dd7377d4465116fb207585f97bf925588687c1ba", size = 8729, upload-time = "2022-08-14T12:40:10.846Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/b3/38/89ba8ad64ae25be8de66a6d463314cf1eb366222074cfda9ee839c56a4b4/mdurl-0.1.2-py3-none-any.whl", hash = "sha256:84008a41e51615a49fc9966191ff91509e3c40b939176e643fd50a5c2196b8f8", size = 9979, upload-time = "2022-08-14T12:40:09.779Z" }, +] + +[[package]] +name = "mistune" +version = "3.2.0" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/9d/55/d01f0c4b45ade6536c51170b9043db8b2ec6ddf4a35c7ea3f5f559ac935b/mistune-3.2.0.tar.gz", hash = "sha256:708487c8a8cdd99c9d90eb3ed4c3ed961246ff78ac82f03418f5183ab70e398a", size = 95467, upload-time = "2025-12-23T11:36:34.994Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/9b/f7/4a5e785ec9fbd65146a27b6b70b6cdc161a66f2024e4b04ac06a67f5578b/mistune-3.2.0-py3-none-any.whl", hash = "sha256:febdc629a3c78616b94393c6580551e0e34cc289987ec6c35ed3f4be42d0eee1", size = 53598, upload-time = "2025-12-23T11:36:33.211Z" }, +] + +[[package]] +name = "more-itertools" +version = "10.8.0" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/ea/5d/38b681d3fce7a266dd9ab73c66959406d565b3e85f21d5e66e1181d93721/more_itertools-10.8.0.tar.gz", hash = "sha256:f638ddf8a1a0d134181275fb5d58b086ead7c6a72429ad725c67503f13ba30bd", size = 137431, upload-time = "2025-09-02T15:23:11.018Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/a4/8e/469e5a4a2f5855992e425f3cb33804cc07bf18d48f2db061aec61ce50270/more_itertools-10.8.0-py3-none-any.whl", hash = "sha256:52d4362373dcf7c52546bc4af9a86ee7c4579df9a8dc268be0a2f949d376cc9b", size = 69667, upload-time = "2025-09-02T15:23:09.635Z" }, +] + +[[package]] +name = "myst-parser" +version = "5.0.0" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "docutils" }, + { name = "jinja2" }, + { name = "markdown-it-py" }, + { name = "mdit-py-plugins" }, + { name = "pyyaml" }, + { name = "sphinx", version = "9.0.4", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.12'" }, + { name = "sphinx", version = "9.1.0", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.12'" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/33/fa/7b45eef11b7971f0beb29d27b7bfe0d747d063aa29e170d9edd004733c8a/myst_parser-5.0.0.tar.gz", hash = "sha256:f6f231452c56e8baa662cc352c548158f6a16fcbd6e3800fc594978002b94f3a", size = 98535, upload-time = "2026-01-15T09:08:18.036Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/d3/ac/686789b9145413f1a61878c407210e41bfdb097976864e0913078b24098c/myst_parser-5.0.0-py3-none-any.whl", hash = "sha256:ab31e516024918296e169139072b81592336f2fef55b8986aa31c9f04b5f7211", size = 84533, upload-time = "2026-01-15T09:08:16.788Z" }, +] + +[[package]] +name = "natsort" +version = "8.4.0" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/e2/a9/a0c57aee75f77794adaf35322f8b6404cbd0f89ad45c87197a937764b7d0/natsort-8.4.0.tar.gz", hash = "sha256:45312c4a0e5507593da193dedd04abb1469253b601ecaf63445ad80f0a1ea581", size = 76575, upload-time = "2023-06-20T04:17:19.925Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/ef/82/7a9d0550484a62c6da82858ee9419f3dd1ccc9aa1c26a1e43da3ecd20b0d/natsort-8.4.0-py3-none-any.whl", hash = "sha256:4732914fb471f56b5cce04d7bae6f164a592c7712e1c85f9ef585e197299521c", size = 38268, upload-time = "2023-06-20T04:17:17.522Z" }, +] + +[[package]] +name = "nbclient" +version = "0.10.4" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "jupyter-client" }, + { name = "jupyter-core" }, + { name = "nbformat" }, + { name = "traitlets" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/56/91/1c1d5a4b9a9ebba2b4e32b8c852c2975c872aec1fe42ab5e516b2cecd193/nbclient-0.10.4.tar.gz", hash = "sha256:1e54091b16e6da39e297b0ece3e10f6f29f4ac4e8ee515d29f8a7099bd6553c9", size = 62554, upload-time = "2025-12-23T07:45:46.369Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/83/a0/5b0c2f11142ed1dddec842457d3f65eaf71a0080894eb6f018755b319c3a/nbclient-0.10.4-py3-none-any.whl", hash = "sha256:9162df5a7373d70d606527300a95a975a47c137776cd942e52d9c7e29ff83440", size = 25465, upload-time = "2025-12-23T07:45:44.51Z" }, +] + +[[package]] +name = "nbconvert" +version = "7.17.0" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "beautifulsoup4" }, + { name = "bleach", extra = ["css"] }, + { name = "defusedxml" }, + { name = "jinja2" }, + { name = "jupyter-core" }, + { name = "jupyterlab-pygments" }, + { name = "markupsafe" }, + { name = "mistune" }, + { name = "nbclient" }, + { name = "nbformat" }, + { name = "packaging" }, + { name = "pandocfilters" }, + { name = "pygments" }, + { name = "traitlets" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/38/47/81f886b699450d0569f7bc551df2b1673d18df7ff25cc0c21ca36ed8a5ff/nbconvert-7.17.0.tar.gz", hash = "sha256:1b2696f1b5be12309f6c7d707c24af604b87dfaf6d950794c7b07acab96dda78", size = 862855, upload-time = "2026-01-29T16:37:48.478Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/0d/4b/8d5f796a792f8a25f6925a96032f098789f448571eb92011df1ae59e8ea8/nbconvert-7.17.0-py3-none-any.whl", hash = "sha256:4f99a63b337b9a23504347afdab24a11faa7d86b405e5c8f9881cd313336d518", size = 261510, upload-time = "2026-01-29T16:37:46.322Z" }, +] + +[[package]] +name = "nbformat" +version = "5.10.4" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "fastjsonschema" }, + { name = "jsonschema" }, + { name = "jupyter-core" }, + { name = "traitlets" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/6d/fd/91545e604bc3dad7dca9ed03284086039b294c6b3d75c0d2fa45f9e9caf3/nbformat-5.10.4.tar.gz", hash = "sha256:322168b14f937a5d11362988ecac2a4952d3d8e3a2cbeb2319584631226d5b3a", size = 142749, upload-time = "2024-04-04T11:20:37.371Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/a9/82/0340caa499416c78e5d8f5f05947ae4bc3cba53c9f038ab6e9ed964e22f1/nbformat-5.10.4-py3-none-any.whl", hash = "sha256:3b48d6c8fbca4b299bf3982ea7db1af21580e4fec269ad087b9e81588891200b", size = 78454, upload-time = "2024-04-04T11:20:34.895Z" }, +] + +[[package]] +name = "nbsphinx" +version = "0.9.8" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "docutils" }, + { name = "jinja2" }, + { name = "nbconvert" }, + { name = "nbformat" }, + { name = "sphinx", version = "9.0.4", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.12'" }, + { name = "sphinx", version = "9.1.0", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.12'" }, + { name = "traitlets" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/e7/d1/82081750f8a78ad0399c6ed831d42623b891904e8e7b8a75878225cf1dce/nbsphinx-0.9.8.tar.gz", hash = "sha256:d0765908399a8ee2b57be7ae881cf2ea58d66db3af7bbf33e6eb48f83bea5495", size = 417469, upload-time = "2025-11-28T17:41:02.336Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/03/78/843bcf0cf31f88d2f8a9a063d2d80817b1901657d83d65b89b3aa835732e/nbsphinx-0.9.8-py3-none-any.whl", hash = "sha256:92d95ee91784e56bc633b60b767a6b6f23a0445f891e24641ce3c3f004759ccf", size = 31961, upload-time = "2025-11-28T17:41:00.796Z" }, +] + +[[package]] +name = "nest-asyncio" +version = "1.6.0" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/83/f8/51569ac65d696c8ecbee95938f89d4abf00f47d58d48f6fbabfe8f0baefe/nest_asyncio-1.6.0.tar.gz", hash = "sha256:6f172d5449aca15afd6c646851f4e31e02c598d553a667e38cafa997cfec55fe", size = 7418, upload-time = "2024-01-21T14:25:19.227Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/a0/c4/c2971a3ba4c6103a3d10c4b0f24f461ddc027f0f09763220cf35ca1401b3/nest_asyncio-1.6.0-py3-none-any.whl", hash = "sha256:87af6efd6b5e897c81050477ef65c62e2b2f35d51703cae01aff2905b1852e1c", size = 5195, upload-time = "2024-01-21T14:25:17.223Z" }, +] + +[[package]] +name = "networkx" +version = "3.6.1" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/6a/51/63fe664f3908c97be9d2e4f1158eb633317598cfa6e1fc14af5383f17512/networkx-3.6.1.tar.gz", hash = "sha256:26b7c357accc0c8cde558ad486283728b65b6a95d85ee1cd66bafab4c8168509", size = 2517025, upload-time = "2025-12-08T17:02:39.908Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/9e/c9/b2622292ea83fbb4ec318f5b9ab867d0a28ab43c5717bb85b0a5f6b3b0a4/networkx-3.6.1-py3-none-any.whl", hash = "sha256:d47fbf302e7d9cbbb9e2555a0d267983d2aa476bac30e90dfbe5669bd57f3762", size = 2068504, upload-time = "2025-12-08T17:02:38.159Z" }, +] + +[[package]] +name = "nh3" +version = "0.3.3" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/cc/37/ab55eb2b05e334ff9a1ad52c556ace1f9c20a3f63613a165d384d5387657/nh3-0.3.3.tar.gz", hash = "sha256:185ed41b88c910b9ca8edc89ca3b4be688a12cb9de129d84befa2f74a0039fee", size = 18968, upload-time = "2026-02-14T09:35:15.664Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/e7/a4/834f0ebd80844ce67e1bdb011d6f844f61cdb4c1d7cdc56a982bc054cc00/nh3-0.3.3-cp314-cp314t-macosx_10_12_x86_64.macosx_11_0_arm64.macosx_10_12_universal2.whl", hash = "sha256:21b058cd20d9f0919421a820a2843fdb5e1749c0bf57a6247ab8f4ba6723c9fc", size = 1428680, upload-time = "2026-02-14T09:34:33.015Z" }, + { url = "https://files.pythonhosted.org/packages/7f/1a/a7d72e750f74c6b71befbeebc4489579fe783466889d41f32e34acde0b6b/nh3-0.3.3-cp314-cp314t-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f4400a73c2a62859e769f9d36d1b5a7a5c65c4179d1dddd2f6f3095b2db0cbfc", size = 799003, upload-time = "2026-02-14T09:34:35.108Z" }, + { url = "https://files.pythonhosted.org/packages/58/d5/089eb6d65da139dc2223b83b2627e00872eccb5e1afdf5b1d76eb6ad3fcc/nh3-0.3.3-cp314-cp314t-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:1ef87f8e916321a88b45f2d597f29bd56e560ed4568a50f0f1305afab86b7189", size = 846818, upload-time = "2026-02-14T09:34:37Z" }, + { url = "https://files.pythonhosted.org/packages/9b/c6/44a0b65fc7b213a3a725f041ef986534b100e58cd1a2e00f0fd3c9603893/nh3-0.3.3-cp314-cp314t-musllinux_1_2_aarch64.whl", hash = "sha256:a446eae598987f49ee97ac2f18eafcce4e62e7574bd1eb23782e4702e54e217d", size = 1012537, upload-time = "2026-02-14T09:34:38.515Z" }, + { url = "https://files.pythonhosted.org/packages/94/3a/91bcfcc0a61b286b8b25d39e288b9c0ba91c3290d402867d1cd705169844/nh3-0.3.3-cp314-cp314t-musllinux_1_2_armv7l.whl", hash = "sha256:0d5eb734a78ac364af1797fef718340a373f626a9ff6b4fb0b4badf7927e7b81", size = 1095435, upload-time = "2026-02-14T09:34:40.022Z" }, + { url = "https://files.pythonhosted.org/packages/fd/fd/4617a19d80cf9f958e65724ff5e97bc2f76f2f4c5194c740016606c87bd1/nh3-0.3.3-cp314-cp314t-musllinux_1_2_i686.whl", hash = "sha256:92a958e6f6d0100e025a5686aafd67e3c98eac67495728f8bb64fbeb3e474493", size = 1056344, upload-time = "2026-02-14T09:34:41.469Z" }, + { url = "https://files.pythonhosted.org/packages/bd/7d/5bcbbc56e71b7dda7ef1d6008098da9c5426d6334137ef32bb2b9c496984/nh3-0.3.3-cp314-cp314t-musllinux_1_2_x86_64.whl", hash = "sha256:9ed40cf8449a59a03aa465114fedce1ff7ac52561688811d047917cc878b19ca", size = 1034533, upload-time = "2026-02-14T09:34:43.313Z" }, + { url = "https://files.pythonhosted.org/packages/3f/9c/054eff8a59a8b23b37f0f4ac84cdd688ee84cf5251664c0e14e5d30a8a67/nh3-0.3.3-cp314-cp314t-win32.whl", hash = "sha256:b50c3770299fb2a7c1113751501e8878d525d15160a4c05194d7fe62b758aad8", size = 608305, upload-time = "2026-02-14T09:34:44.622Z" }, + { url = "https://files.pythonhosted.org/packages/d7/b0/64667b8d522c7b859717a02b1a66ba03b529ca1df623964e598af8db1ed5/nh3-0.3.3-cp314-cp314t-win_amd64.whl", hash = "sha256:21a63ccb18ddad3f784bb775955839b8b80e347e597726f01e43ca1abcc5c808", size = 620633, upload-time = "2026-02-14T09:34:46.069Z" }, + { url = "https://files.pythonhosted.org/packages/91/b5/ae9909e4ddfd86ee076c4d6d62ba69e9b31061da9d2f722936c52df8d556/nh3-0.3.3-cp314-cp314t-win_arm64.whl", hash = "sha256:f508ddd4e2433fdcb78c790fc2d24e3a349ba775e5fa904af89891321d4844a3", size = 607027, upload-time = "2026-02-14T09:34:47.91Z" }, + { url = "https://files.pythonhosted.org/packages/13/3e/aef8cf8e0419b530c95e96ae93a5078e9b36c1e6613eeb1df03a80d5194e/nh3-0.3.3-cp38-abi3-macosx_10_12_x86_64.macosx_11_0_arm64.macosx_10_12_universal2.whl", hash = "sha256:e8ee96156f7dfc6e30ecda650e480c5ae0a7d38f0c6fafc3c1c655e2500421d9", size = 1448640, upload-time = "2026-02-14T09:34:49.316Z" }, + { url = "https://files.pythonhosted.org/packages/ca/43/d2011a4f6c0272cb122eeff40062ee06bb2b6e57eabc3a5e057df0d582df/nh3-0.3.3-cp38-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:45fe0d6a607264910daec30360c8a3b5b1500fd832d21b2da608256287bcb92d", size = 839405, upload-time = "2026-02-14T09:34:50.779Z" }, + { url = "https://files.pythonhosted.org/packages/f8/f3/965048510c1caf2a34ed04411a46a04a06eb05563cd06f1aa57b71eb2bc8/nh3-0.3.3-cp38-abi3-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:5bc1d4b30ba1ba896669d944b6003630592665974bd11a3dc2f661bde92798a7", size = 825849, upload-time = "2026-02-14T09:34:52.622Z" }, + { url = "https://files.pythonhosted.org/packages/78/99/b4bbc6ad16329d8db2c2c320423f00b549ca3b129c2b2f9136be2606dbb0/nh3-0.3.3-cp38-abi3-manylinux_2_17_ppc64.manylinux2014_ppc64.whl", hash = "sha256:f433a2dd66545aad4a720ad1b2150edcdca75bfff6f4e6f378ade1ec138d5e77", size = 1068303, upload-time = "2026-02-14T09:34:54.179Z" }, + { url = "https://files.pythonhosted.org/packages/3f/34/3420d97065aab1b35f3e93ce9c96c8ebd423ce86fe84dee3126790421a2a/nh3-0.3.3-cp38-abi3-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:52e973cb742e95b9ae1b35822ce23992428750f4b46b619fe86eba4205255b30", size = 1029316, upload-time = "2026-02-14T09:34:56.186Z" }, + { url = "https://files.pythonhosted.org/packages/f1/9a/99eda757b14e596fdb2ca5f599a849d9554181aa899274d0d183faef4493/nh3-0.3.3-cp38-abi3-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:4c730617bdc15d7092dcc0469dc2826b914c8f874996d105b4bc3842a41c1cd9", size = 919944, upload-time = "2026-02-14T09:34:57.886Z" }, + { url = "https://files.pythonhosted.org/packages/6f/84/c0dc75c7fb596135f999e59a410d9f45bdabb989f1cb911f0016d22b747b/nh3-0.3.3-cp38-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:e98fa3dbfd54e25487e36ba500bc29bca3a4cab4ffba18cfb1a35a2d02624297", size = 811461, upload-time = "2026-02-14T09:34:59.65Z" }, + { url = "https://files.pythonhosted.org/packages/7e/ec/b1bf57cab6230eec910e4863528dc51dcf21b57aaf7c88ee9190d62c9185/nh3-0.3.3-cp38-abi3-manylinux_2_31_riscv64.whl", hash = "sha256:3a62b8ae7c235481715055222e54c682422d0495a5c73326807d4e44c5d14691", size = 840360, upload-time = "2026-02-14T09:35:01.444Z" }, + { url = "https://files.pythonhosted.org/packages/37/5e/326ae34e904dde09af1de51219a611ae914111f0970f2f111f4f0188f57e/nh3-0.3.3-cp38-abi3-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:fc305a2264868ec8fa16548296f803d8fd9c1fa66cd28b88b605b1bd06667c0b", size = 859872, upload-time = "2026-02-14T09:35:03.348Z" }, + { url = "https://files.pythonhosted.org/packages/09/38/7eba529ce17ab4d3790205da37deabb4cb6edcba15f27b8562e467f2fc97/nh3-0.3.3-cp38-abi3-musllinux_1_2_aarch64.whl", hash = "sha256:90126a834c18af03bfd6ff9a027bfa6bbf0e238527bc780a24de6bd7cc1041e2", size = 1023550, upload-time = "2026-02-14T09:35:04.829Z" }, + { url = "https://files.pythonhosted.org/packages/05/a2/556fdecd37c3681b1edee2cf795a6799c6ed0a5551b2822636960d7e7651/nh3-0.3.3-cp38-abi3-musllinux_1_2_armv7l.whl", hash = "sha256:24769a428e9e971e4ccfb24628f83aaa7dc3c8b41b130c8ddc1835fa1c924489", size = 1105212, upload-time = "2026-02-14T09:35:06.821Z" }, + { url = "https://files.pythonhosted.org/packages/dd/e3/5db0b0ad663234967d83702277094687baf7c498831a2d3ad3451c11770f/nh3-0.3.3-cp38-abi3-musllinux_1_2_i686.whl", hash = "sha256:b7a18ee057761e455d58b9d31445c3e4b2594cff4ddb84d2e331c011ef46f462", size = 1069970, upload-time = "2026-02-14T09:35:08.504Z" }, + { url = "https://files.pythonhosted.org/packages/79/b2/2ea21b79c6e869581ce5f51549b6e185c4762233591455bf2a326fb07f3b/nh3-0.3.3-cp38-abi3-musllinux_1_2_x86_64.whl", hash = "sha256:5a4b2c1f3e6f3cbe7048e17f4fefad3f8d3e14cc0fd08fb8599e0d5653f6b181", size = 1047588, upload-time = "2026-02-14T09:35:09.911Z" }, + { url = "https://files.pythonhosted.org/packages/e2/92/2e434619e658c806d9c096eed2cdff9a883084299b7b19a3f0824eb8e63d/nh3-0.3.3-cp38-abi3-win32.whl", hash = "sha256:e974850b131fdffa75e7ad8e0d9c7a855b96227b093417fdf1bd61656e530f37", size = 616179, upload-time = "2026-02-14T09:35:11.366Z" }, + { url = "https://files.pythonhosted.org/packages/73/88/1ce287ef8649dc51365b5094bd3713b76454838140a32ab4f8349973883c/nh3-0.3.3-cp38-abi3-win_amd64.whl", hash = "sha256:2efd17c0355d04d39e6d79122b42662277ac10a17ea48831d90b46e5ef7e4fc0", size = 631159, upload-time = "2026-02-14T09:35:12.77Z" }, + { url = "https://files.pythonhosted.org/packages/31/f1/b4835dbde4fb06f29db89db027576d6014081cd278d9b6751facc3e69e43/nh3-0.3.3-cp38-abi3-win_arm64.whl", hash = "sha256:b838e619f483531483d26d889438e53a880510e832d2aafe73f93b7b1ac2bce2", size = 616645, upload-time = "2026-02-14T09:35:14.062Z" }, +] + +[[package]] +name = "nodeenv" +version = "1.10.0" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/24/bf/d1bda4f6168e0b2e9e5958945e01910052158313224ada5ce1fb2e1113b8/nodeenv-1.10.0.tar.gz", hash = "sha256:996c191ad80897d076bdfba80a41994c2b47c68e224c542b48feba42ba00f8bb", size = 55611, upload-time = "2025-12-20T14:08:54.006Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/88/b2/d0896bdcdc8d28a7fc5717c305f1a861c26e18c05047949fb371034d98bd/nodeenv-1.10.0-py2.py3-none-any.whl", hash = "sha256:5bb13e3eed2923615535339b3c620e76779af4cb4c6a90deccc9e36b274d3827", size = 23438, upload-time = "2025-12-20T14:08:52.782Z" }, +] + +[[package]] +name = "numba" +version = "0.64.0" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "llvmlite" }, + { name = "numpy" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/23/c9/a0fb41787d01d621046138da30f6c2100d80857bf34b3390dd68040f27a3/numba-0.64.0.tar.gz", hash = "sha256:95e7300af648baa3308127b1955b52ce6d11889d16e8cfe637b4f85d2fca52b1", size = 2765679, upload-time = "2026-02-18T18:41:20.974Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/89/a3/1a4286a1c16136c8896d8e2090d950e79b3ec626d3a8dc9620f6234d5a38/numba-0.64.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:766156ee4b8afeeb2b2e23c81307c5d19031f18d5ce76ae2c5fb1429e72fa92b", size = 2682938, upload-time = "2026-02-18T18:40:52.897Z" }, + { url = "https://files.pythonhosted.org/packages/19/16/aa6e3ba3cd45435c117d1101b278b646444ed05b7c712af631b91353f573/numba-0.64.0-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:d17071b4ffc9d39b75d8e6c101a36f0c81b646123859898c9799cb31807c8f78", size = 3747376, upload-time = "2026-02-18T18:40:54.925Z" }, + { url = "https://files.pythonhosted.org/packages/c0/f1/dd2f25e18d75fdf897f730b78c5a7b00cc4450f2405564dbebfaf359f21f/numba-0.64.0-cp311-cp311-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:4ead5630434133bac87fa67526eacb264535e4e9a2d5ec780e0b4fc381a7d275", size = 3453292, upload-time = "2026-02-18T18:40:56.818Z" }, + { url = "https://files.pythonhosted.org/packages/31/29/e09d5630578a50a2b3fa154990b6b839cf95327aa0709e2d50d0b6816cd1/numba-0.64.0-cp311-cp311-win_amd64.whl", hash = "sha256:f2b1fd93e7aaac07d6fbaed059c00679f591f2423885c206d8c1b55d65ca3f2d", size = 2749824, upload-time = "2026-02-18T18:40:58.392Z" }, + { url = "https://files.pythonhosted.org/packages/70/a6/9fc52cb4f0d5e6d8b5f4d81615bc01012e3cf24e1052a60f17a68deb8092/numba-0.64.0-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:69440a8e8bc1a81028446f06b363e28635aa67bd51b1e498023f03b812e0ce68", size = 2683418, upload-time = "2026-02-18T18:40:59.886Z" }, + { url = "https://files.pythonhosted.org/packages/9b/89/1a74ea99b180b7a5587b0301ed1b183a2937c4b4b67f7994689b5d36fc34/numba-0.64.0-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:f13721011f693ba558b8dd4e4db7f2640462bba1b855bdc804be45bbeb55031a", size = 3804087, upload-time = "2026-02-18T18:41:01.699Z" }, + { url = "https://files.pythonhosted.org/packages/91/e1/583c647404b15f807410510fec1eb9b80cb8474165940b7749f026f21cbc/numba-0.64.0-cp312-cp312-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:e0b180b1133f2b5d8b3f09d96b6d7a9e51a7da5dda3c09e998b5bcfac85d222c", size = 3504309, upload-time = "2026-02-18T18:41:03.252Z" }, + { url = "https://files.pythonhosted.org/packages/85/23/0fce5789b8a5035e7ace21216a468143f3144e02013252116616c58339aa/numba-0.64.0-cp312-cp312-win_amd64.whl", hash = "sha256:e63dc94023b47894849b8b106db28ccb98b49d5498b98878fac1a38f83ac007a", size = 2752740, upload-time = "2026-02-18T18:41:05.097Z" }, + { url = "https://files.pythonhosted.org/packages/52/80/2734de90f9300a6e2503b35ee50d9599926b90cbb7ac54f9e40074cd07f1/numba-0.64.0-cp313-cp313-macosx_12_0_arm64.whl", hash = "sha256:3bab2c872194dcd985f1153b70782ec0fbbe348fffef340264eacd3a76d59fd6", size = 2683392, upload-time = "2026-02-18T18:41:06.563Z" }, + { url = "https://files.pythonhosted.org/packages/42/e8/14b5853ebefd5b37723ef365c5318a30ce0702d39057eaa8d7d76392859d/numba-0.64.0-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:703a246c60832cad231d2e73c1182f25bf3cc8b699759ec8fe58a2dbc689a70c", size = 3812245, upload-time = "2026-02-18T18:41:07.963Z" }, + { url = "https://files.pythonhosted.org/packages/8a/a2/f60dc6c96d19b7185144265a5fbf01c14993d37ff4cd324b09d0212aa7ce/numba-0.64.0-cp313-cp313-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:7e2e49a7900ee971d32af7609adc0cfe6aa7477c6f6cccdf6d8138538cf7756f", size = 3511328, upload-time = "2026-02-18T18:41:09.504Z" }, + { url = "https://files.pythonhosted.org/packages/9c/2a/fe7003ea7e7237ee7014f8eaeeb7b0d228a2db22572ca85bab2648cf52cb/numba-0.64.0-cp313-cp313-win_amd64.whl", hash = "sha256:396f43c3f77e78d7ec84cdfc6b04969c78f8f169351b3c4db814b97e7acf4245", size = 2752668, upload-time = "2026-02-18T18:41:11.455Z" }, + { url = "https://files.pythonhosted.org/packages/3d/8a/77d26afe0988c592dd97cb8d4e80bfb3dfc7dbdacfca7d74a7c5c81dd8c2/numba-0.64.0-cp314-cp314-macosx_12_0_arm64.whl", hash = "sha256:f565d55eaeff382cbc86c63c8c610347453af3d1e7afb2b6569aac1c9b5c93ce", size = 2683590, upload-time = "2026-02-18T18:41:12.897Z" }, + { url = "https://files.pythonhosted.org/packages/8e/4b/600b8b7cdbc7f9cebee9ea3d13bb70052a79baf28944024ffcb59f0712e3/numba-0.64.0-cp314-cp314-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:9b55169b18892c783f85e9ad9e6f5297a6d12967e4414e6b71361086025ff0bb", size = 3781163, upload-time = "2026-02-18T18:41:15.377Z" }, + { url = "https://files.pythonhosted.org/packages/ff/73/53f2d32bfa45b7175e9944f6b816d8c32840178c3eee9325033db5bf838e/numba-0.64.0-cp314-cp314-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:196bcafa02c9dd1707e068434f6d5cedde0feb787e3432f7f1f0e993cc336c4c", size = 3481172, upload-time = "2026-02-18T18:41:17.281Z" }, + { url = "https://files.pythonhosted.org/packages/b5/00/aebd2f7f1e11e38814bb96e95a27580817a7b340608d3ac085fdbab83174/numba-0.64.0-cp314-cp314-win_amd64.whl", hash = "sha256:213e9acbe7f1c05090592e79020315c1749dd52517b90e94c517dca3f014d4a1", size = 2754700, upload-time = "2026-02-18T18:41:19.277Z" }, +] + +[[package]] +name = "numcodecs" +version = "0.16.5" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "numpy" }, + { name = "typing-extensions" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/44/bd/8a391e7c356366224734efd24da929cc4796fff468bfb179fe1af6548535/numcodecs-0.16.5.tar.gz", hash = "sha256:0d0fb60852f84c0bd9543cc4d2ab9eefd37fc8efcc410acd4777e62a1d300318", size = 6276387, upload-time = "2025-11-21T02:49:48.986Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/af/85/1ac101a40ead81eaa1c7dc49a8827a30e2e436211b43ebdc63c590eb1347/numcodecs-0.16.5-cp311-cp311-macosx_10_13_x86_64.whl", hash = "sha256:78382dcea50622f2ef1e6e7a71dbe7f861d8fe376b27b7c297c26907304fef1e", size = 1621795, upload-time = "2025-11-21T02:49:17.418Z" }, + { url = "https://files.pythonhosted.org/packages/0e/cc/0d97ef55dda48cb0f93d7b92d761208e7a99bd2eea6b0e859426e6a99a21/numcodecs-0.16.5-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:e2d04a19cb57a3c519b4127ac377cca6471aee1990d7c18f5b1e3a4fe1306689", size = 1153030, upload-time = "2025-11-21T02:49:19.089Z" }, + { url = "https://files.pythonhosted.org/packages/5e/41/e120ee1b390730ac5987cde2afd82e2b8442cec315ab40b94b0373e93e73/numcodecs-0.16.5-cp311-cp311-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:c043af648eb280cd61785c99c22ff5c3c3460f906eb51a8511327c4f5111b283", size = 8510503, upload-time = "2025-11-21T02:49:20.324Z" }, + { url = "https://files.pythonhosted.org/packages/54/4b/195ac84cc8f6077b4f0f421e8daee21b7f1bd88cb7716414234379fe68ec/numcodecs-0.16.5-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:c398919ef2eb0e56b8e97456f622640bfd3deed06de3acc976989cbcb22628a3", size = 9123428, upload-time = "2025-11-21T02:49:22.328Z" }, + { url = "https://files.pythonhosted.org/packages/0f/5b/af02c417954f46e5c7bd5163ac251f535877d909fce54861c99ae197f6f6/numcodecs-0.16.5-cp311-cp311-win_amd64.whl", hash = "sha256:3820860ed302d4d84a1c66e70981ff959d5eb712555be4e7d8ced49888594773", size = 801542, upload-time = "2025-11-21T02:49:24.265Z" }, + { url = "https://files.pythonhosted.org/packages/75/cc/55420f3641a67f78392dc0bc5d02cb9eb0a9dcebf2848d1ac77253ca61fa/numcodecs-0.16.5-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:24e675dc8d1550cd976a99479b87d872cb142632c75cc402fea04c08c4898523", size = 1656287, upload-time = "2025-11-21T02:49:25.755Z" }, + { url = "https://files.pythonhosted.org/packages/f5/6c/86644987505dcb90ba6d627d6989c27bafb0699f9fd00187e06d05ea8594/numcodecs-0.16.5-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:94ddfa4341d1a3ab99989d13b01b5134abb687d3dab2ead54b450aefe4ad5bd6", size = 1148899, upload-time = "2025-11-21T02:49:26.87Z" }, + { url = "https://files.pythonhosted.org/packages/97/1e/98aaddf272552d9fef1f0296a9939d1487914a239e98678f6b20f8b0a5c8/numcodecs-0.16.5-cp312-cp312-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:b554ab9ecf69de7ca2b6b5e8bc696bd9747559cb4dd5127bd08d7a28bec59c3a", size = 8534814, upload-time = "2025-11-21T02:49:28.547Z" }, + { url = "https://files.pythonhosted.org/packages/fb/53/78c98ef5c8b2b784453487f3e4d6c017b20747c58b470393e230c78d18e8/numcodecs-0.16.5-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:ad1a379a45bd3491deab8ae6548313946744f868c21d5340116977ea3be5b1d6", size = 9173471, upload-time = "2025-11-21T02:49:30.444Z" }, + { url = "https://files.pythonhosted.org/packages/1c/20/2fdec87fc7f8cec950d2b0bea603c12dc9f05b4966dc5924ba5a36a61bf6/numcodecs-0.16.5-cp312-cp312-win_amd64.whl", hash = "sha256:845a9857886ffe4a3172ba1c537ae5bcc01e65068c31cf1fce1a844bd1da050f", size = 801412, upload-time = "2025-11-21T02:49:32.123Z" }, + { url = "https://files.pythonhosted.org/packages/38/38/071ced5a5fd1c85ba0e14ba721b66b053823e5176298c2f707e50bed11d9/numcodecs-0.16.5-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:25be3a516ab677dad890760d357cfe081a371d9c0a2e9a204562318ac5969de3", size = 1654359, upload-time = "2025-11-21T02:49:33.673Z" }, + { url = "https://files.pythonhosted.org/packages/d1/c0/5f84ba7525577c1b9909fc2d06ef11314825fc4ad4378f61d0e4c9883b4a/numcodecs-0.16.5-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:0107e839ef75b854e969cb577e140b1aadb9847893937636582d23a2a4c6ce50", size = 1144237, upload-time = "2025-11-21T02:49:35.294Z" }, + { url = "https://files.pythonhosted.org/packages/0b/00/787ea5f237b8ea7bc67140c99155f9c00b5baf11c49afc5f3bfefa298f95/numcodecs-0.16.5-cp313-cp313-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:015a7c859ecc2a06e2a548f64008c0ec3aaecabc26456c2c62f4278d8fc20597", size = 8483064, upload-time = "2025-11-21T02:49:36.454Z" }, + { url = "https://files.pythonhosted.org/packages/c4/e6/d359fdd37498e74d26a167f7a51e54542e642ea47181eb4e643a69a066c3/numcodecs-0.16.5-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:84230b4b9dad2392f2a84242bd6e3e659ac137b5a1ce3571d6965fca673e0903", size = 9126063, upload-time = "2025-11-21T02:49:38.018Z" }, + { url = "https://files.pythonhosted.org/packages/27/72/6663cc0382ddbb866136c255c837bcb96cc7ce5e83562efec55e1b995941/numcodecs-0.16.5-cp313-cp313-win_amd64.whl", hash = "sha256:5088145502ad1ebf677ec47d00eb6f0fd600658217db3e0c070c321c85d6cf3d", size = 799275, upload-time = "2025-11-21T02:49:39.558Z" }, + { url = "https://files.pythonhosted.org/packages/3c/9e/38e7ca8184c958b51f45d56a4aeceb1134ecde2d8bd157efadc98502cc42/numcodecs-0.16.5-cp314-cp314-macosx_10_13_x86_64.whl", hash = "sha256:b05647b8b769e6bc8016e9fd4843c823ce5c9f2337c089fb5c9c4da05e5275de", size = 1654721, upload-time = "2025-11-21T02:49:40.602Z" }, + { url = "https://files.pythonhosted.org/packages/a1/37/260fa42e7b2b08e6e00ad632f8dd620961a60a459426c26cea390f8c68d0/numcodecs-0.16.5-cp314-cp314-macosx_11_0_arm64.whl", hash = "sha256:3832bd1b5af8bb3e413076b7d93318c8e7d7b68935006b9fa36ca057d1725a8f", size = 1146887, upload-time = "2025-11-21T02:49:41.721Z" }, + { url = "https://files.pythonhosted.org/packages/4e/15/e2e1151b5a8b14a15dfd4bb4abccce7fff7580f39bc34092780088835f3a/numcodecs-0.16.5-cp314-cp314-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:49f7b7d24f103187f53135bed28bb9f0ed6b2e14c604664726487bb6d7c882e1", size = 8476987, upload-time = "2025-11-21T02:49:43.363Z" }, + { url = "https://files.pythonhosted.org/packages/6d/30/16a57fc4d9fb0ba06c600408bd6634f2f1753c54a7a351c99c5e09b51ee2/numcodecs-0.16.5-cp314-cp314-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:aec9736d81b70f337d89c4070ee3ffeff113f386fd789492fa152d26a15043e4", size = 9102377, upload-time = "2025-11-21T02:49:45.508Z" }, + { url = "https://files.pythonhosted.org/packages/31/a5/a0425af36c20d55a3ea884db4b4efca25a43bea9214ba69ca7932dd997b4/numcodecs-0.16.5-cp314-cp314-win_amd64.whl", hash = "sha256:b16a14303800e9fb88abc39463ab4706c037647ac17e49e297faa5f7d7dbbf1d", size = 819022, upload-time = "2025-11-21T02:49:47.39Z" }, +] + +[[package]] +name = "numpy" +version = "2.4.2" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/57/fd/0005efbd0af48e55eb3c7208af93f2862d4b1a56cd78e84309a2d959208d/numpy-2.4.2.tar.gz", hash = "sha256:659a6107e31a83c4e33f763942275fd278b21d095094044eb35569e86a21ddae", size = 20723651, upload-time = "2026-01-31T23:13:10.135Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/d3/44/71852273146957899753e69986246d6a176061ea183407e95418c2aa4d9a/numpy-2.4.2-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:e7e88598032542bd49af7c4747541422884219056c268823ef6e5e89851c8825", size = 16955478, upload-time = "2026-01-31T23:10:25.623Z" }, + { url = "https://files.pythonhosted.org/packages/74/41/5d17d4058bd0cd96bcbd4d9ff0fb2e21f52702aab9a72e4a594efa18692f/numpy-2.4.2-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:7edc794af8b36ca37ef5fcb5e0d128c7e0595c7b96a2318d1badb6fcd8ee86b1", size = 14965467, upload-time = "2026-01-31T23:10:28.186Z" }, + { url = "https://files.pythonhosted.org/packages/49/48/fb1ce8136c19452ed15f033f8aee91d5defe515094e330ce368a0647846f/numpy-2.4.2-cp311-cp311-macosx_14_0_arm64.whl", hash = "sha256:6e9f61981ace1360e42737e2bae58b27bf28a1b27e781721047d84bd754d32e7", size = 5475172, upload-time = "2026-01-31T23:10:30.848Z" }, + { url = "https://files.pythonhosted.org/packages/40/a9/3feb49f17bbd1300dd2570432961f5c8a4ffeff1db6f02c7273bd020a4c9/numpy-2.4.2-cp311-cp311-macosx_14_0_x86_64.whl", hash = "sha256:cb7bbb88aa74908950d979eeaa24dbdf1a865e3c7e45ff0121d8f70387b55f73", size = 6805145, upload-time = "2026-01-31T23:10:32.352Z" }, + { url = "https://files.pythonhosted.org/packages/3f/39/fdf35cbd6d6e2fcad42fcf85ac04a85a0d0fbfbf34b30721c98d602fd70a/numpy-2.4.2-cp311-cp311-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:4f069069931240b3fc703f1e23df63443dbd6390614c8c44a87d96cd0ec81eb1", size = 15966084, upload-time = "2026-01-31T23:10:34.502Z" }, + { url = "https://files.pythonhosted.org/packages/1b/46/6fa4ea94f1ddf969b2ee941290cca6f1bfac92b53c76ae5f44afe17ceb69/numpy-2.4.2-cp311-cp311-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:c02ef4401a506fb60b411467ad501e1429a3487abca4664871d9ae0b46c8ba32", size = 16899477, upload-time = "2026-01-31T23:10:37.075Z" }, + { url = "https://files.pythonhosted.org/packages/09/a1/2a424e162b1a14a5bd860a464ab4e07513916a64ab1683fae262f735ccd2/numpy-2.4.2-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:2653de5c24910e49c2b106499803124dde62a5a1fe0eedeaecf4309a5f639390", size = 17323429, upload-time = "2026-01-31T23:10:39.704Z" }, + { url = "https://files.pythonhosted.org/packages/ce/a2/73014149ff250628df72c58204822ac01d768697913881aacf839ff78680/numpy-2.4.2-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:1ae241bbfc6ae276f94a170b14785e561cb5e7f626b6688cf076af4110887413", size = 18635109, upload-time = "2026-01-31T23:10:41.924Z" }, + { url = "https://files.pythonhosted.org/packages/6c/0c/73e8be2f1accd56df74abc1c5e18527822067dced5ec0861b5bb882c2ce0/numpy-2.4.2-cp311-cp311-win32.whl", hash = "sha256:df1b10187212b198dd45fa943d8985a3c8cf854aed4923796e0e019e113a1bda", size = 6237915, upload-time = "2026-01-31T23:10:45.26Z" }, + { url = "https://files.pythonhosted.org/packages/76/ae/e0265e0163cf127c24c3969d29f1c4c64551a1e375d95a13d32eab25d364/numpy-2.4.2-cp311-cp311-win_amd64.whl", hash = "sha256:b9c618d56a29c9cb1c4da979e9899be7578d2e0b3c24d52079c166324c9e8695", size = 12607972, upload-time = "2026-01-31T23:10:47.021Z" }, + { url = "https://files.pythonhosted.org/packages/29/a5/c43029af9b8014d6ea157f192652c50042e8911f4300f8f6ed3336bf437f/numpy-2.4.2-cp311-cp311-win_arm64.whl", hash = "sha256:47c5a6ed21d9452b10227e5e8a0e1c22979811cad7dcc19d8e3e2fb8fa03f1a3", size = 10485763, upload-time = "2026-01-31T23:10:50.087Z" }, + { url = "https://files.pythonhosted.org/packages/51/6e/6f394c9c77668153e14d4da83bcc247beb5952f6ead7699a1a2992613bea/numpy-2.4.2-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:21982668592194c609de53ba4933a7471880ccbaadcc52352694a59ecc860b3a", size = 16667963, upload-time = "2026-01-31T23:10:52.147Z" }, + { url = "https://files.pythonhosted.org/packages/1f/f8/55483431f2b2fd015ae6ed4fe62288823ce908437ed49db5a03d15151678/numpy-2.4.2-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:40397bda92382fcec844066efb11f13e1c9a3e2a8e8f318fb72ed8b6db9f60f1", size = 14693571, upload-time = "2026-01-31T23:10:54.789Z" }, + { url = "https://files.pythonhosted.org/packages/2f/20/18026832b1845cdc82248208dd929ca14c9d8f2bac391f67440707fff27c/numpy-2.4.2-cp312-cp312-macosx_14_0_arm64.whl", hash = "sha256:b3a24467af63c67829bfaa61eecf18d5432d4f11992688537be59ecd6ad32f5e", size = 5203469, upload-time = "2026-01-31T23:10:57.343Z" }, + { url = "https://files.pythonhosted.org/packages/7d/33/2eb97c8a77daaba34eaa3fa7241a14ac5f51c46a6bd5911361b644c4a1e2/numpy-2.4.2-cp312-cp312-macosx_14_0_x86_64.whl", hash = "sha256:805cc8de9fd6e7a22da5aed858e0ab16be5a4db6c873dde1d7451c541553aa27", size = 6550820, upload-time = "2026-01-31T23:10:59.429Z" }, + { url = "https://files.pythonhosted.org/packages/b1/91/b97fdfd12dc75b02c44e26c6638241cc004d4079a0321a69c62f51470c4c/numpy-2.4.2-cp312-cp312-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:6d82351358ffbcdcd7b686b90742a9b86632d6c1c051016484fa0b326a0a1548", size = 15663067, upload-time = "2026-01-31T23:11:01.291Z" }, + { url = "https://files.pythonhosted.org/packages/f5/c6/a18e59f3f0b8071cc85cbc8d80cd02d68aa9710170b2553a117203d46936/numpy-2.4.2-cp312-cp312-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:9e35d3e0144137d9fdae62912e869136164534d64a169f86438bc9561b6ad49f", size = 16619782, upload-time = "2026-01-31T23:11:03.669Z" }, + { url = "https://files.pythonhosted.org/packages/b7/83/9751502164601a79e18847309f5ceec0b1446d7b6aa12305759b72cf98b2/numpy-2.4.2-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:adb6ed2ad29b9e15321d167d152ee909ec73395901b70936f029c3bc6d7f4460", size = 17013128, upload-time = "2026-01-31T23:11:05.913Z" }, + { url = "https://files.pythonhosted.org/packages/61/c4/c4066322256ec740acc1c8923a10047818691d2f8aec254798f3dd90f5f2/numpy-2.4.2-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:8906e71fd8afcb76580404e2a950caef2685df3d2a57fe82a86ac8d33cc007ba", size = 18345324, upload-time = "2026-01-31T23:11:08.248Z" }, + { url = "https://files.pythonhosted.org/packages/ab/af/6157aa6da728fa4525a755bfad486ae7e3f76d4c1864138003eb84328497/numpy-2.4.2-cp312-cp312-win32.whl", hash = "sha256:ec055f6dae239a6299cace477b479cca2fc125c5675482daf1dd886933a1076f", size = 5960282, upload-time = "2026-01-31T23:11:10.497Z" }, + { url = "https://files.pythonhosted.org/packages/92/0f/7ceaaeaacb40567071e94dbf2c9480c0ae453d5bb4f52bea3892c39dc83c/numpy-2.4.2-cp312-cp312-win_amd64.whl", hash = "sha256:209fae046e62d0ce6435fcfe3b1a10537e858249b3d9b05829e2a05218296a85", size = 12314210, upload-time = "2026-01-31T23:11:12.176Z" }, + { url = "https://files.pythonhosted.org/packages/2f/a3/56c5c604fae6dd40fa2ed3040d005fca97e91bd320d232ac9931d77ba13c/numpy-2.4.2-cp312-cp312-win_arm64.whl", hash = "sha256:fbde1b0c6e81d56f5dccd95dd4a711d9b95df1ae4009a60887e56b27e8d903fa", size = 10220171, upload-time = "2026-01-31T23:11:14.684Z" }, + { url = "https://files.pythonhosted.org/packages/a1/22/815b9fe25d1d7ae7d492152adbc7226d3eff731dffc38fe970589fcaaa38/numpy-2.4.2-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:25f2059807faea4b077a2b6837391b5d830864b3543627f381821c646f31a63c", size = 16663696, upload-time = "2026-01-31T23:11:17.516Z" }, + { url = "https://files.pythonhosted.org/packages/09/f0/817d03a03f93ba9c6c8993de509277d84e69f9453601915e4a69554102a1/numpy-2.4.2-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:bd3a7a9f5847d2fb8c2c6d1c862fa109c31a9abeca1a3c2bd5a64572955b2979", size = 14688322, upload-time = "2026-01-31T23:11:19.883Z" }, + { url = "https://files.pythonhosted.org/packages/da/b4/f805ab79293c728b9a99438775ce51885fd4f31b76178767cfc718701a39/numpy-2.4.2-cp313-cp313-macosx_14_0_arm64.whl", hash = "sha256:8e4549f8a3c6d13d55041925e912bfd834285ef1dd64d6bc7d542583355e2e98", size = 5198157, upload-time = "2026-01-31T23:11:22.375Z" }, + { url = "https://files.pythonhosted.org/packages/74/09/826e4289844eccdcd64aac27d13b0fd3f32039915dd5b9ba01baae1f436c/numpy-2.4.2-cp313-cp313-macosx_14_0_x86_64.whl", hash = "sha256:aea4f66ff44dfddf8c2cffd66ba6538c5ec67d389285292fe428cb2c738c8aef", size = 6546330, upload-time = "2026-01-31T23:11:23.958Z" }, + { url = "https://files.pythonhosted.org/packages/19/fb/cbfdbfa3057a10aea5422c558ac57538e6acc87ec1669e666d32ac198da7/numpy-2.4.2-cp313-cp313-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:c3cd545784805de05aafe1dde61752ea49a359ccba9760c1e5d1c88a93bbf2b7", size = 15660968, upload-time = "2026-01-31T23:11:25.713Z" }, + { url = "https://files.pythonhosted.org/packages/04/dc/46066ce18d01645541f0186877377b9371b8fa8017fa8262002b4ef22612/numpy-2.4.2-cp313-cp313-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:d0d9b7c93578baafcbc5f0b83eaf17b79d345c6f36917ba0c67f45226911d499", size = 16607311, upload-time = "2026-01-31T23:11:28.117Z" }, + { url = "https://files.pythonhosted.org/packages/14/d9/4b5adfc39a43fa6bf918c6d544bc60c05236cc2f6339847fc5b35e6cb5b0/numpy-2.4.2-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:f74f0f7779cc7ae07d1810aab8ac6b1464c3eafb9e283a40da7309d5e6e48fbb", size = 17012850, upload-time = "2026-01-31T23:11:30.888Z" }, + { url = "https://files.pythonhosted.org/packages/b7/20/adb6e6adde6d0130046e6fdfb7675cc62bc2f6b7b02239a09eb58435753d/numpy-2.4.2-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:c7ac672d699bf36275c035e16b65539931347d68b70667d28984c9fb34e07fa7", size = 18334210, upload-time = "2026-01-31T23:11:33.214Z" }, + { url = "https://files.pythonhosted.org/packages/78/0e/0a73b3dff26803a8c02baa76398015ea2a5434d9b8265a7898a6028c1591/numpy-2.4.2-cp313-cp313-win32.whl", hash = "sha256:8e9afaeb0beff068b4d9cd20d322ba0ee1cecfb0b08db145e4ab4dd44a6b5110", size = 5958199, upload-time = "2026-01-31T23:11:35.385Z" }, + { url = "https://files.pythonhosted.org/packages/43/bc/6352f343522fcb2c04dbaf94cb30cca6fd32c1a750c06ad6231b4293708c/numpy-2.4.2-cp313-cp313-win_amd64.whl", hash = "sha256:7df2de1e4fba69a51c06c28f5a3de36731eb9639feb8e1cf7e4a7b0daf4cf622", size = 12310848, upload-time = "2026-01-31T23:11:38.001Z" }, + { url = "https://files.pythonhosted.org/packages/6e/8d/6da186483e308da5da1cc6918ce913dcfe14ffde98e710bfeff2a6158d4e/numpy-2.4.2-cp313-cp313-win_arm64.whl", hash = "sha256:0fece1d1f0a89c16b03442eae5c56dc0be0c7883b5d388e0c03f53019a4bfd71", size = 10221082, upload-time = "2026-01-31T23:11:40.392Z" }, + { url = "https://files.pythonhosted.org/packages/25/a1/9510aa43555b44781968935c7548a8926274f815de42ad3997e9e83680dd/numpy-2.4.2-cp313-cp313t-macosx_11_0_arm64.whl", hash = "sha256:5633c0da313330fd20c484c78cdd3f9b175b55e1a766c4a174230c6b70ad8262", size = 14815866, upload-time = "2026-01-31T23:11:42.495Z" }, + { url = "https://files.pythonhosted.org/packages/36/30/6bbb5e76631a5ae46e7923dd16ca9d3f1c93cfa8d4ed79a129814a9d8db3/numpy-2.4.2-cp313-cp313t-macosx_14_0_arm64.whl", hash = "sha256:d9f64d786b3b1dd742c946c42d15b07497ed14af1a1f3ce840cce27daa0ce913", size = 5325631, upload-time = "2026-01-31T23:11:44.7Z" }, + { url = "https://files.pythonhosted.org/packages/46/00/3a490938800c1923b567b3a15cd17896e68052e2145d8662aaf3e1ffc58f/numpy-2.4.2-cp313-cp313t-macosx_14_0_x86_64.whl", hash = "sha256:b21041e8cb6a1eb5312dd1d2f80a94d91efffb7a06b70597d44f1bd2dfc315ab", size = 6646254, upload-time = "2026-01-31T23:11:46.341Z" }, + { url = "https://files.pythonhosted.org/packages/d3/e9/fac0890149898a9b609caa5af7455a948b544746e4b8fe7c212c8edd71f8/numpy-2.4.2-cp313-cp313t-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:00ab83c56211a1d7c07c25e3217ea6695e50a3e2f255053686b081dc0b091a82", size = 15720138, upload-time = "2026-01-31T23:11:48.082Z" }, + { url = "https://files.pythonhosted.org/packages/ea/5c/08887c54e68e1e28df53709f1893ce92932cc6f01f7c3d4dc952f61ffd4e/numpy-2.4.2-cp313-cp313t-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:2fb882da679409066b4603579619341c6d6898fc83a8995199d5249f986e8e8f", size = 16655398, upload-time = "2026-01-31T23:11:50.293Z" }, + { url = "https://files.pythonhosted.org/packages/4d/89/253db0fa0e66e9129c745e4ef25631dc37d5f1314dad2b53e907b8538e6d/numpy-2.4.2-cp313-cp313t-musllinux_1_2_aarch64.whl", hash = "sha256:66cb9422236317f9d44b67b4d18f44efe6e9c7f8794ac0462978513359461554", size = 17079064, upload-time = "2026-01-31T23:11:52.927Z" }, + { url = "https://files.pythonhosted.org/packages/2a/d5/cbade46ce97c59c6c3da525e8d95b7abe8a42974a1dc5c1d489c10433e88/numpy-2.4.2-cp313-cp313t-musllinux_1_2_x86_64.whl", hash = "sha256:0f01dcf33e73d80bd8dc0f20a71303abbafa26a19e23f6b68d1aa9990af90257", size = 18379680, upload-time = "2026-01-31T23:11:55.22Z" }, + { url = "https://files.pythonhosted.org/packages/40/62/48f99ae172a4b63d981babe683685030e8a3df4f246c893ea5c6ef99f018/numpy-2.4.2-cp313-cp313t-win32.whl", hash = "sha256:52b913ec40ff7ae845687b0b34d8d93b60cb66dcee06996dd5c99f2fc9328657", size = 6082433, upload-time = "2026-01-31T23:11:58.096Z" }, + { url = "https://files.pythonhosted.org/packages/07/38/e054a61cfe48ad9f1ed0d188e78b7e26859d0b60ef21cd9de4897cdb5326/numpy-2.4.2-cp313-cp313t-win_amd64.whl", hash = "sha256:5eea80d908b2c1f91486eb95b3fb6fab187e569ec9752ab7d9333d2e66bf2d6b", size = 12451181, upload-time = "2026-01-31T23:11:59.782Z" }, + { url = "https://files.pythonhosted.org/packages/6e/a4/a05c3a6418575e185dd84d0b9680b6bb2e2dc3e4202f036b7b4e22d6e9dc/numpy-2.4.2-cp313-cp313t-win_arm64.whl", hash = "sha256:fd49860271d52127d61197bb50b64f58454e9f578cb4b2c001a6de8b1f50b0b1", size = 10290756, upload-time = "2026-01-31T23:12:02.438Z" }, + { url = "https://files.pythonhosted.org/packages/18/88/b7df6050bf18fdcfb7046286c6535cabbdd2064a3440fca3f069d319c16e/numpy-2.4.2-cp314-cp314-macosx_10_15_x86_64.whl", hash = "sha256:444be170853f1f9d528428eceb55f12918e4fda5d8805480f36a002f1415e09b", size = 16663092, upload-time = "2026-01-31T23:12:04.521Z" }, + { url = "https://files.pythonhosted.org/packages/25/7a/1fee4329abc705a469a4afe6e69b1ef7e915117747886327104a8493a955/numpy-2.4.2-cp314-cp314-macosx_11_0_arm64.whl", hash = "sha256:d1240d50adff70c2a88217698ca844723068533f3f5c5fa6ee2e3220e3bdb000", size = 14698770, upload-time = "2026-01-31T23:12:06.96Z" }, + { url = "https://files.pythonhosted.org/packages/fb/0b/f9e49ba6c923678ad5bc38181c08ac5e53b7a5754dbca8e581aa1a56b1ff/numpy-2.4.2-cp314-cp314-macosx_14_0_arm64.whl", hash = "sha256:7cdde6de52fb6664b00b056341265441192d1291c130e99183ec0d4b110ff8b1", size = 5208562, upload-time = "2026-01-31T23:12:09.632Z" }, + { url = "https://files.pythonhosted.org/packages/7d/12/d7de8f6f53f9bb76997e5e4c069eda2051e3fe134e9181671c4391677bb2/numpy-2.4.2-cp314-cp314-macosx_14_0_x86_64.whl", hash = "sha256:cda077c2e5b780200b6b3e09d0b42205a3d1c68f30c6dceb90401c13bff8fe74", size = 6543710, upload-time = "2026-01-31T23:12:11.969Z" }, + { url = "https://files.pythonhosted.org/packages/09/63/c66418c2e0268a31a4cf8a8b512685748200f8e8e8ec6c507ce14e773529/numpy-2.4.2-cp314-cp314-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:d30291931c915b2ab5717c2974bb95ee891a1cf22ebc16a8006bd59cd210d40a", size = 15677205, upload-time = "2026-01-31T23:12:14.33Z" }, + { url = "https://files.pythonhosted.org/packages/5d/6c/7f237821c9642fb2a04d2f1e88b4295677144ca93285fd76eff3bcba858d/numpy-2.4.2-cp314-cp314-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:bba37bc29d4d85761deed3954a1bc62be7cf462b9510b51d367b769a8c8df325", size = 16611738, upload-time = "2026-01-31T23:12:16.525Z" }, + { url = "https://files.pythonhosted.org/packages/c2/a7/39c4cdda9f019b609b5c473899d87abff092fc908cfe4d1ecb2fcff453b0/numpy-2.4.2-cp314-cp314-musllinux_1_2_aarch64.whl", hash = "sha256:b2f0073ed0868db1dcd86e052d37279eef185b9c8db5bf61f30f46adac63c909", size = 17028888, upload-time = "2026-01-31T23:12:19.306Z" }, + { url = "https://files.pythonhosted.org/packages/da/b3/e84bb64bdfea967cc10950d71090ec2d84b49bc691df0025dddb7c26e8e3/numpy-2.4.2-cp314-cp314-musllinux_1_2_x86_64.whl", hash = "sha256:7f54844851cdb630ceb623dcec4db3240d1ac13d4990532446761baede94996a", size = 18339556, upload-time = "2026-01-31T23:12:21.816Z" }, + { url = "https://files.pythonhosted.org/packages/88/f5/954a291bc1192a27081706862ac62bb5920fbecfbaa302f64682aa90beed/numpy-2.4.2-cp314-cp314-win32.whl", hash = "sha256:12e26134a0331d8dbd9351620f037ec470b7c75929cb8a1537f6bfe411152a1a", size = 6006899, upload-time = "2026-01-31T23:12:24.14Z" }, + { url = "https://files.pythonhosted.org/packages/05/cb/eff72a91b2efdd1bc98b3b8759f6a1654aa87612fc86e3d87d6fe4f948c4/numpy-2.4.2-cp314-cp314-win_amd64.whl", hash = "sha256:068cdb2d0d644cdb45670810894f6a0600797a69c05f1ac478e8d31670b8ee75", size = 12443072, upload-time = "2026-01-31T23:12:26.33Z" }, + { url = "https://files.pythonhosted.org/packages/37/75/62726948db36a56428fce4ba80a115716dc4fad6a3a4352487f8bb950966/numpy-2.4.2-cp314-cp314-win_arm64.whl", hash = "sha256:6ed0be1ee58eef41231a5c943d7d1375f093142702d5723ca2eb07db9b934b05", size = 10494886, upload-time = "2026-01-31T23:12:28.488Z" }, + { url = "https://files.pythonhosted.org/packages/36/2f/ee93744f1e0661dc267e4b21940870cabfae187c092e1433b77b09b50ac4/numpy-2.4.2-cp314-cp314t-macosx_11_0_arm64.whl", hash = "sha256:98f16a80e917003a12c0580f97b5f875853ebc33e2eaa4bccfc8201ac6869308", size = 14818567, upload-time = "2026-01-31T23:12:30.709Z" }, + { url = "https://files.pythonhosted.org/packages/a7/24/6535212add7d76ff938d8bdc654f53f88d35cddedf807a599e180dcb8e66/numpy-2.4.2-cp314-cp314t-macosx_14_0_arm64.whl", hash = "sha256:20abd069b9cda45874498b245c8015b18ace6de8546bf50dfa8cea1696ed06ef", size = 5328372, upload-time = "2026-01-31T23:12:32.962Z" }, + { url = "https://files.pythonhosted.org/packages/5e/9d/c48f0a035725f925634bf6b8994253b43f2047f6778a54147d7e213bc5a7/numpy-2.4.2-cp314-cp314t-macosx_14_0_x86_64.whl", hash = "sha256:e98c97502435b53741540a5717a6749ac2ada901056c7db951d33e11c885cc7d", size = 6649306, upload-time = "2026-01-31T23:12:34.797Z" }, + { url = "https://files.pythonhosted.org/packages/81/05/7c73a9574cd4a53a25907bad38b59ac83919c0ddc8234ec157f344d57d9a/numpy-2.4.2-cp314-cp314t-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:da6cad4e82cb893db4b69105c604d805e0c3ce11501a55b5e9f9083b47d2ffe8", size = 15722394, upload-time = "2026-01-31T23:12:36.565Z" }, + { url = "https://files.pythonhosted.org/packages/35/fa/4de10089f21fc7d18442c4a767ab156b25c2a6eaf187c0db6d9ecdaeb43f/numpy-2.4.2-cp314-cp314t-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:9e4424677ce4b47fe73c8b5556d876571f7c6945d264201180db2dc34f676ab5", size = 16653343, upload-time = "2026-01-31T23:12:39.188Z" }, + { url = "https://files.pythonhosted.org/packages/b8/f9/d33e4ffc857f3763a57aa85650f2e82486832d7492280ac21ba9efda80da/numpy-2.4.2-cp314-cp314t-musllinux_1_2_aarch64.whl", hash = "sha256:2b8f157c8a6f20eb657e240f8985cc135598b2b46985c5bccbde7616dc9c6b1e", size = 17078045, upload-time = "2026-01-31T23:12:42.041Z" }, + { url = "https://files.pythonhosted.org/packages/c8/b8/54bdb43b6225badbea6389fa038c4ef868c44f5890f95dd530a218706da3/numpy-2.4.2-cp314-cp314t-musllinux_1_2_x86_64.whl", hash = "sha256:5daf6f3914a733336dab21a05cdec343144600e964d2fcdabaac0c0269874b2a", size = 18380024, upload-time = "2026-01-31T23:12:44.331Z" }, + { url = "https://files.pythonhosted.org/packages/a5/55/6e1a61ded7af8df04016d81b5b02daa59f2ea9252ee0397cb9f631efe9e5/numpy-2.4.2-cp314-cp314t-win32.whl", hash = "sha256:8c50dd1fc8826f5b26a5ee4d77ca55d88a895f4e4819c7ecc2a9f5905047a443", size = 6153937, upload-time = "2026-01-31T23:12:47.229Z" }, + { url = "https://files.pythonhosted.org/packages/45/aa/fa6118d1ed6d776b0983f3ceac9b1a5558e80df9365b1c3aa6d42bf9eee4/numpy-2.4.2-cp314-cp314t-win_amd64.whl", hash = "sha256:fcf92bee92742edd401ba41135185866f7026c502617f422eb432cfeca4fe236", size = 12631844, upload-time = "2026-01-31T23:12:48.997Z" }, + { url = "https://files.pythonhosted.org/packages/32/0a/2ec5deea6dcd158f254a7b372fb09cfba5719419c8d66343bab35237b3fb/numpy-2.4.2-cp314-cp314t-win_arm64.whl", hash = "sha256:1f92f53998a17265194018d1cc321b2e96e900ca52d54c7c77837b71b9465181", size = 10565379, upload-time = "2026-01-31T23:12:51.345Z" }, + { url = "https://files.pythonhosted.org/packages/f4/f8/50e14d36d915ef64d8f8bc4a087fc8264d82c785eda6711f80ab7e620335/numpy-2.4.2-pp311-pypy311_pp73-macosx_10_15_x86_64.whl", hash = "sha256:89f7268c009bc492f506abd6f5265defa7cb3f7487dc21d357c3d290add45082", size = 16833179, upload-time = "2026-01-31T23:12:53.5Z" }, + { url = "https://files.pythonhosted.org/packages/17/17/809b5cad63812058a8189e91a1e2d55a5a18fd04611dbad244e8aeae465c/numpy-2.4.2-pp311-pypy311_pp73-macosx_11_0_arm64.whl", hash = "sha256:e6dee3bb76aa4009d5a912180bf5b2de012532998d094acee25d9cb8dee3e44a", size = 14889755, upload-time = "2026-01-31T23:12:55.933Z" }, + { url = "https://files.pythonhosted.org/packages/3e/ea/181b9bcf7627fc8371720316c24db888dcb9829b1c0270abf3d288b2e29b/numpy-2.4.2-pp311-pypy311_pp73-macosx_14_0_arm64.whl", hash = "sha256:cd2bd2bbed13e213d6b55dc1d035a4f91748a7d3edc9480c13898b0353708920", size = 5399500, upload-time = "2026-01-31T23:12:58.671Z" }, + { url = "https://files.pythonhosted.org/packages/33/9f/413adf3fc955541ff5536b78fcf0754680b3c6d95103230252a2c9408d23/numpy-2.4.2-pp311-pypy311_pp73-macosx_14_0_x86_64.whl", hash = "sha256:cf28c0c1d4c4bf00f509fa7eb02c58d7caf221b50b467bcb0d9bbf1584d5c821", size = 6714252, upload-time = "2026-01-31T23:13:00.518Z" }, + { url = "https://files.pythonhosted.org/packages/91/da/643aad274e29ccbdf42ecd94dafe524b81c87bcb56b83872d54827f10543/numpy-2.4.2-pp311-pypy311_pp73-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:e04ae107ac591763a47398bb45b568fc38f02dbc4aa44c063f67a131f99346cb", size = 15797142, upload-time = "2026-01-31T23:13:02.219Z" }, + { url = "https://files.pythonhosted.org/packages/66/27/965b8525e9cb5dc16481b30a1b3c21e50c7ebf6e9dbd48d0c4d0d5089c7e/numpy-2.4.2-pp311-pypy311_pp73-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:602f65afdef699cda27ec0b9224ae5dc43e328f4c24c689deaf77133dbee74d0", size = 16727979, upload-time = "2026-01-31T23:13:04.62Z" }, + { url = "https://files.pythonhosted.org/packages/de/e5/b7d20451657664b07986c2f6e3be564433f5dcaf3482d68eaecd79afaf03/numpy-2.4.2-pp311-pypy311_pp73-win_amd64.whl", hash = "sha256:be71bf1edb48ebbbf7f6337b5bfd2f895d1902f6335a5830b20141fc126ffba0", size = 12502577, upload-time = "2026-01-31T23:13:07.08Z" }, +] + +[[package]] +name = "packaging" +version = "26.0" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/65/ee/299d360cdc32edc7d2cf530f3accf79c4fca01e96ffc950d8a52213bd8e4/packaging-26.0.tar.gz", hash = "sha256:00243ae351a257117b6a241061796684b084ed1c516a08c48a3f7e147a9d80b4", size = 143416, upload-time = "2026-01-21T20:50:39.064Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/b7/b9/c538f279a4e237a006a2c98387d081e9eb060d203d8ed34467cc0f0b9b53/packaging-26.0-py3-none-any.whl", hash = "sha256:b36f1fef9334a5588b4166f8bcd26a14e521f2b55e6b9de3aaa80d3ff7a37529", size = 74366, upload-time = "2026-01-21T20:50:37.788Z" }, +] + +[[package]] +name = "pandas" +version = "2.3.3" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "numpy" }, + { name = "python-dateutil" }, + { name = "pytz" }, + { name = "tzdata" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/33/01/d40b85317f86cf08d853a4f495195c73815fdf205eef3993821720274518/pandas-2.3.3.tar.gz", hash = "sha256:e05e1af93b977f7eafa636d043f9f94c7ee3ac81af99c13508215942e64c993b", size = 4495223, upload-time = "2025-09-29T23:34:51.853Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/c1/fa/7ac648108144a095b4fb6aa3de1954689f7af60a14cf25583f4960ecb878/pandas-2.3.3-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:602b8615ebcc4a0c1751e71840428ddebeb142ec02c786e8ad6b1ce3c8dec523", size = 11578790, upload-time = "2025-09-29T23:18:30.065Z" }, + { url = "https://files.pythonhosted.org/packages/9b/35/74442388c6cf008882d4d4bdfc4109be87e9b8b7ccd097ad1e7f006e2e95/pandas-2.3.3-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:8fe25fc7b623b0ef6b5009149627e34d2a4657e880948ec3c840e9402e5c1b45", size = 10833831, upload-time = "2025-09-29T23:38:56.071Z" }, + { url = "https://files.pythonhosted.org/packages/fe/e4/de154cbfeee13383ad58d23017da99390b91d73f8c11856f2095e813201b/pandas-2.3.3-cp311-cp311-manylinux_2_24_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:b468d3dad6ff947df92dcb32ede5b7bd41a9b3cceef0a30ed925f6d01fb8fa66", size = 12199267, upload-time = "2025-09-29T23:18:41.627Z" }, + { url = "https://files.pythonhosted.org/packages/bf/c9/63f8d545568d9ab91476b1818b4741f521646cbdd151c6efebf40d6de6f7/pandas-2.3.3-cp311-cp311-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:b98560e98cb334799c0b07ca7967ac361a47326e9b4e5a7dfb5ab2b1c9d35a1b", size = 12789281, upload-time = "2025-09-29T23:18:56.834Z" }, + { url = "https://files.pythonhosted.org/packages/f2/00/a5ac8c7a0e67fd1a6059e40aa08fa1c52cc00709077d2300e210c3ce0322/pandas-2.3.3-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:1d37b5848ba49824e5c30bedb9c830ab9b7751fd049bc7914533e01c65f79791", size = 13240453, upload-time = "2025-09-29T23:19:09.247Z" }, + { url = "https://files.pythonhosted.org/packages/27/4d/5c23a5bc7bd209231618dd9e606ce076272c9bc4f12023a70e03a86b4067/pandas-2.3.3-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:db4301b2d1f926ae677a751eb2bd0e8c5f5319c9cb3f88b0becbbb0b07b34151", size = 13890361, upload-time = "2025-09-29T23:19:25.342Z" }, + { url = "https://files.pythonhosted.org/packages/8e/59/712db1d7040520de7a4965df15b774348980e6df45c129b8c64d0dbe74ef/pandas-2.3.3-cp311-cp311-win_amd64.whl", hash = "sha256:f086f6fe114e19d92014a1966f43a3e62285109afe874f067f5abbdcbb10e59c", size = 11348702, upload-time = "2025-09-29T23:19:38.296Z" }, + { url = "https://files.pythonhosted.org/packages/9c/fb/231d89e8637c808b997d172b18e9d4a4bc7bf31296196c260526055d1ea0/pandas-2.3.3-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:6d21f6d74eb1725c2efaa71a2bfc661a0689579b58e9c0ca58a739ff0b002b53", size = 11597846, upload-time = "2025-09-29T23:19:48.856Z" }, + { url = "https://files.pythonhosted.org/packages/5c/bd/bf8064d9cfa214294356c2d6702b716d3cf3bb24be59287a6a21e24cae6b/pandas-2.3.3-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:3fd2f887589c7aa868e02632612ba39acb0b8948faf5cc58f0850e165bd46f35", size = 10729618, upload-time = "2025-09-29T23:39:08.659Z" }, + { url = "https://files.pythonhosted.org/packages/57/56/cf2dbe1a3f5271370669475ead12ce77c61726ffd19a35546e31aa8edf4e/pandas-2.3.3-cp312-cp312-manylinux_2_24_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:ecaf1e12bdc03c86ad4a7ea848d66c685cb6851d807a26aa245ca3d2017a1908", size = 11737212, upload-time = "2025-09-29T23:19:59.765Z" }, + { url = "https://files.pythonhosted.org/packages/e5/63/cd7d615331b328e287d8233ba9fdf191a9c2d11b6af0c7a59cfcec23de68/pandas-2.3.3-cp312-cp312-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:b3d11d2fda7eb164ef27ffc14b4fcab16a80e1ce67e9f57e19ec0afaf715ba89", size = 12362693, upload-time = "2025-09-29T23:20:14.098Z" }, + { url = "https://files.pythonhosted.org/packages/a6/de/8b1895b107277d52f2b42d3a6806e69cfef0d5cf1d0ba343470b9d8e0a04/pandas-2.3.3-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:a68e15f780eddf2b07d242e17a04aa187a7ee12b40b930bfdd78070556550e98", size = 12771002, upload-time = "2025-09-29T23:20:26.76Z" }, + { url = "https://files.pythonhosted.org/packages/87/21/84072af3187a677c5893b170ba2c8fbe450a6ff911234916da889b698220/pandas-2.3.3-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:371a4ab48e950033bcf52b6527eccb564f52dc826c02afd9a1bc0ab731bba084", size = 13450971, upload-time = "2025-09-29T23:20:41.344Z" }, + { url = "https://files.pythonhosted.org/packages/86/41/585a168330ff063014880a80d744219dbf1dd7a1c706e75ab3425a987384/pandas-2.3.3-cp312-cp312-win_amd64.whl", hash = "sha256:a16dcec078a01eeef8ee61bf64074b4e524a2a3f4b3be9326420cabe59c4778b", size = 10992722, upload-time = "2025-09-29T23:20:54.139Z" }, + { url = "https://files.pythonhosted.org/packages/cd/4b/18b035ee18f97c1040d94debd8f2e737000ad70ccc8f5513f4eefad75f4b/pandas-2.3.3-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:56851a737e3470de7fa88e6131f41281ed440d29a9268dcbf0002da5ac366713", size = 11544671, upload-time = "2025-09-29T23:21:05.024Z" }, + { url = "https://files.pythonhosted.org/packages/31/94/72fac03573102779920099bcac1c3b05975c2cb5f01eac609faf34bed1ca/pandas-2.3.3-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:bdcd9d1167f4885211e401b3036c0c8d9e274eee67ea8d0758a256d60704cfe8", size = 10680807, upload-time = "2025-09-29T23:21:15.979Z" }, + { url = "https://files.pythonhosted.org/packages/16/87/9472cf4a487d848476865321de18cc8c920b8cab98453ab79dbbc98db63a/pandas-2.3.3-cp313-cp313-manylinux_2_24_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:e32e7cc9af0f1cc15548288a51a3b681cc2a219faa838e995f7dc53dbab1062d", size = 11709872, upload-time = "2025-09-29T23:21:27.165Z" }, + { url = "https://files.pythonhosted.org/packages/15/07/284f757f63f8a8d69ed4472bfd85122bd086e637bf4ed09de572d575a693/pandas-2.3.3-cp313-cp313-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:318d77e0e42a628c04dc56bcef4b40de67918f7041c2b061af1da41dcff670ac", size = 12306371, upload-time = "2025-09-29T23:21:40.532Z" }, + { url = "https://files.pythonhosted.org/packages/33/81/a3afc88fca4aa925804a27d2676d22dcd2031c2ebe08aabd0ae55b9ff282/pandas-2.3.3-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:4e0a175408804d566144e170d0476b15d78458795bb18f1304fb94160cabf40c", size = 12765333, upload-time = "2025-09-29T23:21:55.77Z" }, + { url = "https://files.pythonhosted.org/packages/8d/0f/b4d4ae743a83742f1153464cf1a8ecfafc3ac59722a0b5c8602310cb7158/pandas-2.3.3-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:93c2d9ab0fc11822b5eece72ec9587e172f63cff87c00b062f6e37448ced4493", size = 13418120, upload-time = "2025-09-29T23:22:10.109Z" }, + { url = "https://files.pythonhosted.org/packages/4f/c7/e54682c96a895d0c808453269e0b5928a07a127a15704fedb643e9b0a4c8/pandas-2.3.3-cp313-cp313-win_amd64.whl", hash = "sha256:f8bfc0e12dc78f777f323f55c58649591b2cd0c43534e8355c51d3fede5f4dee", size = 10993991, upload-time = "2025-09-29T23:25:04.889Z" }, + { url = "https://files.pythonhosted.org/packages/f9/ca/3f8d4f49740799189e1395812f3bf23b5e8fc7c190827d55a610da72ce55/pandas-2.3.3-cp313-cp313t-macosx_10_13_x86_64.whl", hash = "sha256:75ea25f9529fdec2d2e93a42c523962261e567d250b0013b16210e1d40d7c2e5", size = 12048227, upload-time = "2025-09-29T23:22:24.343Z" }, + { url = "https://files.pythonhosted.org/packages/0e/5a/f43efec3e8c0cc92c4663ccad372dbdff72b60bdb56b2749f04aa1d07d7e/pandas-2.3.3-cp313-cp313t-macosx_11_0_arm64.whl", hash = "sha256:74ecdf1d301e812db96a465a525952f4dde225fdb6d8e5a521d47e1f42041e21", size = 11411056, upload-time = "2025-09-29T23:22:37.762Z" }, + { url = "https://files.pythonhosted.org/packages/46/b1/85331edfc591208c9d1a63a06baa67b21d332e63b7a591a5ba42a10bb507/pandas-2.3.3-cp313-cp313t-manylinux_2_24_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:6435cb949cb34ec11cc9860246ccb2fdc9ecd742c12d3304989017d53f039a78", size = 11645189, upload-time = "2025-09-29T23:22:51.688Z" }, + { url = "https://files.pythonhosted.org/packages/44/23/78d645adc35d94d1ac4f2a3c4112ab6f5b8999f4898b8cdf01252f8df4a9/pandas-2.3.3-cp313-cp313t-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:900f47d8f20860de523a1ac881c4c36d65efcb2eb850e6948140fa781736e110", size = 12121912, upload-time = "2025-09-29T23:23:05.042Z" }, + { url = "https://files.pythonhosted.org/packages/53/da/d10013df5e6aaef6b425aa0c32e1fc1f3e431e4bcabd420517dceadce354/pandas-2.3.3-cp313-cp313t-musllinux_1_2_aarch64.whl", hash = "sha256:a45c765238e2ed7d7c608fc5bc4a6f88b642f2f01e70c0c23d2224dd21829d86", size = 12712160, upload-time = "2025-09-29T23:23:28.57Z" }, + { url = "https://files.pythonhosted.org/packages/bd/17/e756653095a083d8a37cbd816cb87148debcfcd920129b25f99dd8d04271/pandas-2.3.3-cp313-cp313t-musllinux_1_2_x86_64.whl", hash = "sha256:c4fc4c21971a1a9f4bdb4c73978c7f7256caa3e62b323f70d6cb80db583350bc", size = 13199233, upload-time = "2025-09-29T23:24:24.876Z" }, + { url = "https://files.pythonhosted.org/packages/04/fd/74903979833db8390b73b3a8a7d30d146d710bd32703724dd9083950386f/pandas-2.3.3-cp314-cp314-macosx_10_13_x86_64.whl", hash = "sha256:ee15f284898e7b246df8087fc82b87b01686f98ee67d85a17b7ab44143a3a9a0", size = 11540635, upload-time = "2025-09-29T23:25:52.486Z" }, + { url = "https://files.pythonhosted.org/packages/21/00/266d6b357ad5e6d3ad55093a7e8efc7dd245f5a842b584db9f30b0f0a287/pandas-2.3.3-cp314-cp314-macosx_11_0_arm64.whl", hash = "sha256:1611aedd912e1ff81ff41c745822980c49ce4a7907537be8692c8dbc31924593", size = 10759079, upload-time = "2025-09-29T23:26:33.204Z" }, + { url = "https://files.pythonhosted.org/packages/ca/05/d01ef80a7a3a12b2f8bbf16daba1e17c98a2f039cbc8e2f77a2c5a63d382/pandas-2.3.3-cp314-cp314-manylinux_2_24_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:6d2cefc361461662ac48810cb14365a365ce864afe85ef1f447ff5a1e99ea81c", size = 11814049, upload-time = "2025-09-29T23:27:15.384Z" }, + { url = "https://files.pythonhosted.org/packages/15/b2/0e62f78c0c5ba7e3d2c5945a82456f4fac76c480940f805e0b97fcbc2f65/pandas-2.3.3-cp314-cp314-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:ee67acbbf05014ea6c763beb097e03cd629961c8a632075eeb34247120abcb4b", size = 12332638, upload-time = "2025-09-29T23:27:51.625Z" }, + { url = "https://files.pythonhosted.org/packages/c5/33/dd70400631b62b9b29c3c93d2feee1d0964dc2bae2e5ad7a6c73a7f25325/pandas-2.3.3-cp314-cp314-musllinux_1_2_aarch64.whl", hash = "sha256:c46467899aaa4da076d5abc11084634e2d197e9460643dd455ac3db5856b24d6", size = 12886834, upload-time = "2025-09-29T23:28:21.289Z" }, + { url = "https://files.pythonhosted.org/packages/d3/18/b5d48f55821228d0d2692b34fd5034bb185e854bdb592e9c640f6290e012/pandas-2.3.3-cp314-cp314-musllinux_1_2_x86_64.whl", hash = "sha256:6253c72c6a1d990a410bc7de641d34053364ef8bcd3126f7e7450125887dffe3", size = 13409925, upload-time = "2025-09-29T23:28:58.261Z" }, + { url = "https://files.pythonhosted.org/packages/a6/3d/124ac75fcd0ecc09b8fdccb0246ef65e35b012030defb0e0eba2cbbbe948/pandas-2.3.3-cp314-cp314-win_amd64.whl", hash = "sha256:1b07204a219b3b7350abaae088f451860223a52cfb8a6c53358e7948735158e5", size = 11109071, upload-time = "2025-09-29T23:32:27.484Z" }, + { url = "https://files.pythonhosted.org/packages/89/9c/0e21c895c38a157e0faa1fb64587a9226d6dd46452cac4532d80c3c4a244/pandas-2.3.3-cp314-cp314t-macosx_10_13_x86_64.whl", hash = "sha256:2462b1a365b6109d275250baaae7b760fd25c726aaca0054649286bcfbb3e8ec", size = 12048504, upload-time = "2025-09-29T23:29:31.47Z" }, + { url = "https://files.pythonhosted.org/packages/d7/82/b69a1c95df796858777b68fbe6a81d37443a33319761d7c652ce77797475/pandas-2.3.3-cp314-cp314t-macosx_11_0_arm64.whl", hash = "sha256:0242fe9a49aa8b4d78a4fa03acb397a58833ef6199e9aa40a95f027bb3a1b6e7", size = 11410702, upload-time = "2025-09-29T23:29:54.591Z" }, + { url = "https://files.pythonhosted.org/packages/f9/88/702bde3ba0a94b8c73a0181e05144b10f13f29ebfc2150c3a79062a8195d/pandas-2.3.3-cp314-cp314t-manylinux_2_24_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:a21d830e78df0a515db2b3d2f5570610f5e6bd2e27749770e8bb7b524b89b450", size = 11634535, upload-time = "2025-09-29T23:30:21.003Z" }, + { url = "https://files.pythonhosted.org/packages/a4/1e/1bac1a839d12e6a82ec6cb40cda2edde64a2013a66963293696bbf31fbbb/pandas-2.3.3-cp314-cp314t-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:2e3ebdb170b5ef78f19bfb71b0dc5dc58775032361fa188e814959b74d726dd5", size = 12121582, upload-time = "2025-09-29T23:30:43.391Z" }, + { url = "https://files.pythonhosted.org/packages/44/91/483de934193e12a3b1d6ae7c8645d083ff88dec75f46e827562f1e4b4da6/pandas-2.3.3-cp314-cp314t-musllinux_1_2_aarch64.whl", hash = "sha256:d051c0e065b94b7a3cea50eb1ec32e912cd96dba41647eb24104b6c6c14c5788", size = 12699963, upload-time = "2025-09-29T23:31:10.009Z" }, + { url = "https://files.pythonhosted.org/packages/70/44/5191d2e4026f86a2a109053e194d3ba7a31a2d10a9c2348368c63ed4e85a/pandas-2.3.3-cp314-cp314t-musllinux_1_2_x86_64.whl", hash = "sha256:3869faf4bd07b3b66a9f462417d0ca3a9df29a9f6abd5d0d0dbab15dac7abe87", size = 13202175, upload-time = "2025-09-29T23:31:59.173Z" }, +] + +[[package]] +name = "pandas-stubs" +version = "3.0.0.260204" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "numpy" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/27/1d/297ff2c7ea50a768a2247621d6451abb2a07c0e9be7ca6d36ebe371658e5/pandas_stubs-3.0.0.260204.tar.gz", hash = "sha256:bf9294b76352effcffa9cb85edf0bed1339a7ec0c30b8e1ac3d66b4228f1fbc3", size = 109383, upload-time = "2026-02-04T15:17:17.247Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/7c/2f/f91e4eee21585ff548e83358332d5632ee49f6b2dcd96cb5dca4e0468951/pandas_stubs-3.0.0.260204-py3-none-any.whl", hash = "sha256:5ab9e4d55a6e2752e9720828564af40d48c4f709e6a2c69b743014a6fcb6c241", size = 168540, upload-time = "2026-02-04T15:17:15.615Z" }, +] + +[[package]] +name = "pandoc" +version = "2.4" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "plumbum" }, + { name = "ply" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/10/9a/e3186e760c57ee5f1c27ea5cea577a0ff9abfca51eefcb4d9a4cd39aff2e/pandoc-2.4.tar.gz", hash = "sha256:ecd1f8cbb7f4180c6b5db4a17a7c1a74df519995f5f186ef81ce72a9cbd0dd9a", size = 34635, upload-time = "2024-08-07T14:33:58.016Z" } + +[[package]] +name = "pandocfilters" +version = "1.5.1" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/70/6f/3dd4940bbe001c06a65f88e36bad298bc7a0de5036115639926b0c5c0458/pandocfilters-1.5.1.tar.gz", hash = "sha256:002b4a555ee4ebc03f8b66307e287fa492e4a77b4ea14d3f934328297bb4939e", size = 8454, upload-time = "2024-01-18T20:08:13.726Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/ef/af/4fbc8cab944db5d21b7e2a5b8e9211a03a79852b1157e2c102fcc61ac440/pandocfilters-1.5.1-py2.py3-none-any.whl", hash = "sha256:93be382804a9cdb0a7267585f157e5d1731bbe5545a85b268d6f5fe6232de2bc", size = 8663, upload-time = "2024-01-18T20:08:11.28Z" }, +] + +[[package]] +name = "parso" +version = "0.8.6" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/81/76/a1e769043c0c0c9fe391b702539d594731a4362334cdf4dc25d0c09761e7/parso-0.8.6.tar.gz", hash = "sha256:2b9a0332696df97d454fa67b81618fd69c35a7b90327cbe6ba5c92d2c68a7bfd", size = 401621, upload-time = "2026-02-09T15:45:24.425Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/b6/61/fae042894f4296ec49e3f193aff5d7c18440da9e48102c3315e1bc4519a7/parso-0.8.6-py2.py3-none-any.whl", hash = "sha256:2c549f800b70a5c4952197248825584cb00f033b29c692671d3bf08bf380baff", size = 106894, upload-time = "2026-02-09T15:45:21.391Z" }, +] + +[[package]] +name = "patsy" +version = "1.0.2" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "numpy" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/be/44/ed13eccdd0519eff265f44b670d46fbb0ec813e2274932dc1c0e48520f7d/patsy-1.0.2.tar.gz", hash = "sha256:cdc995455f6233e90e22de72c37fcadb344e7586fb83f06696f54d92f8ce74c0", size = 399942, upload-time = "2025-10-20T16:17:37.535Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/f1/70/ba4b949bdc0490ab78d545459acd7702b211dfccf7eb89bbc1060f52818d/patsy-1.0.2-py2.py3-none-any.whl", hash = "sha256:37bfddbc58fcf0362febb5f54f10743f8b21dd2aa73dec7e7ef59d1b02ae668a", size = 233301, upload-time = "2025-10-20T16:17:36.563Z" }, +] + +[[package]] +name = "pexpect" +version = "4.9.0" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "ptyprocess" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/42/92/cc564bf6381ff43ce1f4d06852fc19a2f11d180f23dc32d9588bee2f149d/pexpect-4.9.0.tar.gz", hash = "sha256:ee7d41123f3c9911050ea2c2dac107568dc43b2d3b0c7557a33212c398ead30f", size = 166450, upload-time = "2023-11-25T09:07:26.339Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/9e/c3/059298687310d527a58bb01f3b1965787ee3b40dce76752eda8b44e9a2c5/pexpect-4.9.0-py2.py3-none-any.whl", hash = "sha256:7236d1e080e4936be2dc3e326cec0af72acf9212a7e1d060210e70a47e253523", size = 63772, upload-time = "2023-11-25T06:56:14.81Z" }, +] + +[[package]] +name = "pillow" +version = "12.1.1" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/1f/42/5c74462b4fd957fcd7b13b04fb3205ff8349236ea74c7c375766d6c82288/pillow-12.1.1.tar.gz", hash = "sha256:9ad8fa5937ab05218e2b6a4cff30295ad35afd2f83ac592e68c0d871bb0fdbc4", size = 46980264, upload-time = "2026-02-11T04:23:07.146Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/2b/46/5da1ec4a5171ee7bf1a0efa064aba70ba3d6e0788ce3f5acd1375d23c8c0/pillow-12.1.1-cp311-cp311-macosx_10_10_x86_64.whl", hash = "sha256:e879bb6cd5c73848ef3b2b48b8af9ff08c5b71ecda8048b7dd22d8a33f60be32", size = 5304084, upload-time = "2026-02-11T04:20:27.501Z" }, + { url = "https://files.pythonhosted.org/packages/78/93/a29e9bc02d1cf557a834da780ceccd54e02421627200696fcf805ebdc3fb/pillow-12.1.1-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:365b10bb9417dd4498c0e3b128018c4a624dc11c7b97d8cc54effe3b096f4c38", size = 4657866, upload-time = "2026-02-11T04:20:29.827Z" }, + { url = "https://files.pythonhosted.org/packages/13/84/583a4558d492a179d31e4aae32eadce94b9acf49c0337c4ce0b70e0a01f2/pillow-12.1.1-cp311-cp311-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:d4ce8e329c93845720cd2014659ca67eac35f6433fd3050393d85f3ecef0dad5", size = 6232148, upload-time = "2026-02-11T04:20:31.329Z" }, + { url = "https://files.pythonhosted.org/packages/d5/e2/53c43334bbbb2d3b938978532fbda8e62bb6e0b23a26ce8592f36bcc4987/pillow-12.1.1-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:fc354a04072b765eccf2204f588a7a532c9511e8b9c7f900e1b64e3e33487090", size = 8038007, upload-time = "2026-02-11T04:20:34.225Z" }, + { url = "https://files.pythonhosted.org/packages/b8/a6/3d0e79c8a9d58150dd98e199d7c1c56861027f3829a3a60b3c2784190180/pillow-12.1.1-cp311-cp311-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:7e7976bf1910a8116b523b9f9f58bf410f3e8aa330cd9a2bb2953f9266ab49af", size = 6345418, upload-time = "2026-02-11T04:20:35.858Z" }, + { url = "https://files.pythonhosted.org/packages/a2/c8/46dfeac5825e600579157eea177be43e2f7ff4a99da9d0d0a49533509ac5/pillow-12.1.1-cp311-cp311-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:597bd9c8419bc7c6af5604e55847789b69123bbe25d65cc6ad3012b4f3c98d8b", size = 7034590, upload-time = "2026-02-11T04:20:37.91Z" }, + { url = "https://files.pythonhosted.org/packages/af/bf/e6f65d3db8a8bbfeaf9e13cc0417813f6319863a73de934f14b2229ada18/pillow-12.1.1-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:2c1fc0f2ca5f96a3c8407e41cca26a16e46b21060fe6d5b099d2cb01412222f5", size = 6458655, upload-time = "2026-02-11T04:20:39.496Z" }, + { url = "https://files.pythonhosted.org/packages/f9/c2/66091f3f34a25894ca129362e510b956ef26f8fb67a0e6417bc5744e56f1/pillow-12.1.1-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:578510d88c6229d735855e1f278aa305270438d36a05031dfaae5067cc8eb04d", size = 7159286, upload-time = "2026-02-11T04:20:41.139Z" }, + { url = "https://files.pythonhosted.org/packages/7b/5a/24bc8eb526a22f957d0cec6243146744966d40857e3d8deb68f7902ca6c1/pillow-12.1.1-cp311-cp311-win32.whl", hash = "sha256:7311c0a0dcadb89b36b7025dfd8326ecfa36964e29913074d47382706e516a7c", size = 6328663, upload-time = "2026-02-11T04:20:43.184Z" }, + { url = "https://files.pythonhosted.org/packages/31/03/bef822e4f2d8f9d7448c133d0a18185d3cce3e70472774fffefe8b0ed562/pillow-12.1.1-cp311-cp311-win_amd64.whl", hash = "sha256:fbfa2a7c10cc2623f412753cddf391c7f971c52ca40a3f65dc5039b2939e8563", size = 7031448, upload-time = "2026-02-11T04:20:44.696Z" }, + { url = "https://files.pythonhosted.org/packages/49/70/f76296f53610bd17b2e7d31728b8b7825e3ac3b5b3688b51f52eab7c0818/pillow-12.1.1-cp311-cp311-win_arm64.whl", hash = "sha256:b81b5e3511211631b3f672a595e3221252c90af017e399056d0faabb9538aa80", size = 2453651, upload-time = "2026-02-11T04:20:46.243Z" }, + { url = "https://files.pythonhosted.org/packages/07/d3/8df65da0d4df36b094351dce696f2989bec731d4f10e743b1c5f4da4d3bf/pillow-12.1.1-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:ab323b787d6e18b3d91a72fc99b1a2c28651e4358749842b8f8dfacd28ef2052", size = 5262803, upload-time = "2026-02-11T04:20:47.653Z" }, + { url = "https://files.pythonhosted.org/packages/d6/71/5026395b290ff404b836e636f51d7297e6c83beceaa87c592718747e670f/pillow-12.1.1-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:adebb5bee0f0af4909c30db0d890c773d1a92ffe83da908e2e9e720f8edf3984", size = 4657601, upload-time = "2026-02-11T04:20:49.328Z" }, + { url = "https://files.pythonhosted.org/packages/b1/2e/1001613d941c67442f745aff0f7cc66dd8df9a9c084eb497e6a543ee6f7e/pillow-12.1.1-cp312-cp312-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:bb66b7cc26f50977108790e2456b7921e773f23db5630261102233eb355a3b79", size = 6234995, upload-time = "2026-02-11T04:20:51.032Z" }, + { url = "https://files.pythonhosted.org/packages/07/26/246ab11455b2549b9233dbd44d358d033a2f780fa9007b61a913c5b2d24e/pillow-12.1.1-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:aee2810642b2898bb187ced9b349e95d2a7272930796e022efaf12e99dccd293", size = 8045012, upload-time = "2026-02-11T04:20:52.882Z" }, + { url = "https://files.pythonhosted.org/packages/b2/8b/07587069c27be7535ac1fe33874e32de118fbd34e2a73b7f83436a88368c/pillow-12.1.1-cp312-cp312-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:a0b1cd6232e2b618adcc54d9882e4e662a089d5768cd188f7c245b4c8c44a397", size = 6349638, upload-time = "2026-02-11T04:20:54.444Z" }, + { url = "https://files.pythonhosted.org/packages/ff/79/6df7b2ee763d619cda2fb4fea498e5f79d984dae304d45a8999b80d6cf5c/pillow-12.1.1-cp312-cp312-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:7aac39bcf8d4770d089588a2e1dd111cbaa42df5a94be3114222057d68336bd0", size = 7041540, upload-time = "2026-02-11T04:20:55.97Z" }, + { url = "https://files.pythonhosted.org/packages/2c/5e/2ba19e7e7236d7529f4d873bdaf317a318896bac289abebd4bb00ef247f0/pillow-12.1.1-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:ab174cd7d29a62dd139c44bf74b698039328f45cb03b4596c43473a46656b2f3", size = 6462613, upload-time = "2026-02-11T04:20:57.542Z" }, + { url = "https://files.pythonhosted.org/packages/03/03/31216ec124bb5c3dacd74ce8efff4cc7f52643653bad4825f8f08c697743/pillow-12.1.1-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:339ffdcb7cbeaa08221cd401d517d4b1fe7a9ed5d400e4a8039719238620ca35", size = 7166745, upload-time = "2026-02-11T04:20:59.196Z" }, + { url = "https://files.pythonhosted.org/packages/1f/e7/7c4552d80052337eb28653b617eafdef39adfb137c49dd7e831b8dc13bc5/pillow-12.1.1-cp312-cp312-win32.whl", hash = "sha256:5d1f9575a12bed9e9eedd9a4972834b08c97a352bd17955ccdebfeca5913fa0a", size = 6328823, upload-time = "2026-02-11T04:21:01.385Z" }, + { url = "https://files.pythonhosted.org/packages/3d/17/688626d192d7261bbbf98846fc98995726bddc2c945344b65bec3a29d731/pillow-12.1.1-cp312-cp312-win_amd64.whl", hash = "sha256:21329ec8c96c6e979cd0dfd29406c40c1d52521a90544463057d2aaa937d66a6", size = 7033367, upload-time = "2026-02-11T04:21:03.536Z" }, + { url = "https://files.pythonhosted.org/packages/ed/fe/a0ef1f73f939b0eca03ee2c108d0043a87468664770612602c63266a43c4/pillow-12.1.1-cp312-cp312-win_arm64.whl", hash = "sha256:af9a332e572978f0218686636610555ae3defd1633597be015ed50289a03c523", size = 2453811, upload-time = "2026-02-11T04:21:05.116Z" }, + { url = "https://files.pythonhosted.org/packages/d5/11/6db24d4bd7685583caeae54b7009584e38da3c3d4488ed4cd25b439de486/pillow-12.1.1-cp313-cp313-ios_13_0_arm64_iphoneos.whl", hash = "sha256:d242e8ac078781f1de88bf823d70c1a9b3c7950a44cdf4b7c012e22ccbcd8e4e", size = 4062689, upload-time = "2026-02-11T04:21:06.804Z" }, + { url = "https://files.pythonhosted.org/packages/33/c0/ce6d3b1fe190f0021203e0d9b5b99e57843e345f15f9ef22fcd43842fd21/pillow-12.1.1-cp313-cp313-ios_13_0_arm64_iphonesimulator.whl", hash = "sha256:02f84dfad02693676692746df05b89cf25597560db2857363a208e393429f5e9", size = 4138535, upload-time = "2026-02-11T04:21:08.452Z" }, + { url = "https://files.pythonhosted.org/packages/a0/c6/d5eb6a4fb32a3f9c21a8c7613ec706534ea1cf9f4b3663e99f0d83f6fca8/pillow-12.1.1-cp313-cp313-ios_13_0_x86_64_iphonesimulator.whl", hash = "sha256:e65498daf4b583091ccbb2556c7000abf0f3349fcd57ef7adc9a84a394ed29f6", size = 3601364, upload-time = "2026-02-11T04:21:10.194Z" }, + { url = "https://files.pythonhosted.org/packages/14/a1/16c4b823838ba4c9c52c0e6bbda903a3fe5a1bdbf1b8eb4fff7156f3e318/pillow-12.1.1-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:6c6db3b84c87d48d0088943bf33440e0c42370b99b1c2a7989216f7b42eede60", size = 5262561, upload-time = "2026-02-11T04:21:11.742Z" }, + { url = "https://files.pythonhosted.org/packages/bb/ad/ad9dc98ff24f485008aa5cdedaf1a219876f6f6c42a4626c08bc4e80b120/pillow-12.1.1-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:8b7e5304e34942bf62e15184219a7b5ad4ff7f3bb5cca4d984f37df1a0e1aee2", size = 4657460, upload-time = "2026-02-11T04:21:13.786Z" }, + { url = "https://files.pythonhosted.org/packages/9e/1b/f1a4ea9a895b5732152789326202a82464d5254759fbacae4deea3069334/pillow-12.1.1-cp313-cp313-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:18e5bddd742a44b7e6b1e773ab5db102bd7a94c32555ba656e76d319d19c3850", size = 6232698, upload-time = "2026-02-11T04:21:15.949Z" }, + { url = "https://files.pythonhosted.org/packages/95/f4/86f51b8745070daf21fd2e5b1fe0eb35d4db9ca26e6d58366562fb56a743/pillow-12.1.1-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:fc44ef1f3de4f45b50ccf9136999d71abb99dca7706bc75d222ed350b9fd2289", size = 8041706, upload-time = "2026-02-11T04:21:17.723Z" }, + { url = "https://files.pythonhosted.org/packages/29/9b/d6ecd956bb1266dd1045e995cce9b8d77759e740953a1c9aad9502a0461e/pillow-12.1.1-cp313-cp313-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:5a8eb7ed8d4198bccbd07058416eeec51686b498e784eda166395a23eb99138e", size = 6346621, upload-time = "2026-02-11T04:21:19.547Z" }, + { url = "https://files.pythonhosted.org/packages/71/24/538bff45bde96535d7d998c6fed1a751c75ac7c53c37c90dc2601b243893/pillow-12.1.1-cp313-cp313-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:47b94983da0c642de92ced1702c5b6c292a84bd3a8e1d1702ff923f183594717", size = 7038069, upload-time = "2026-02-11T04:21:21.378Z" }, + { url = "https://files.pythonhosted.org/packages/94/0e/58cb1a6bc48f746bc4cb3adb8cabff73e2742c92b3bf7a220b7cf69b9177/pillow-12.1.1-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:518a48c2aab7ce596d3bf79d0e275661b846e86e4d0e7dec34712c30fe07f02a", size = 6460040, upload-time = "2026-02-11T04:21:23.148Z" }, + { url = "https://files.pythonhosted.org/packages/6c/57/9045cb3ff11eeb6c1adce3b2d60d7d299d7b273a2e6c8381a524abfdc474/pillow-12.1.1-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:a550ae29b95c6dc13cf69e2c9dc5747f814c54eeb2e32d683e5e93af56caa029", size = 7164523, upload-time = "2026-02-11T04:21:25.01Z" }, + { url = "https://files.pythonhosted.org/packages/73/f2/9be9cb99f2175f0d4dbadd6616ce1bf068ee54a28277ea1bf1fbf729c250/pillow-12.1.1-cp313-cp313-win32.whl", hash = "sha256:a003d7422449f6d1e3a34e3dd4110c22148336918ddbfc6a32581cd54b2e0b2b", size = 6332552, upload-time = "2026-02-11T04:21:27.238Z" }, + { url = "https://files.pythonhosted.org/packages/3f/eb/b0834ad8b583d7d9d42b80becff092082a1c3c156bb582590fcc973f1c7c/pillow-12.1.1-cp313-cp313-win_amd64.whl", hash = "sha256:344cf1e3dab3be4b1fa08e449323d98a2a3f819ad20f4b22e77a0ede31f0faa1", size = 7040108, upload-time = "2026-02-11T04:21:29.462Z" }, + { url = "https://files.pythonhosted.org/packages/d5/7d/fc09634e2aabdd0feabaff4a32f4a7d97789223e7c2042fd805ea4b4d2c2/pillow-12.1.1-cp313-cp313-win_arm64.whl", hash = "sha256:5c0dd1636633e7e6a0afe7bf6a51a14992b7f8e60de5789018ebbdfae55b040a", size = 2453712, upload-time = "2026-02-11T04:21:31.072Z" }, + { url = "https://files.pythonhosted.org/packages/19/2a/b9d62794fc8a0dd14c1943df68347badbd5511103e0d04c035ffe5cf2255/pillow-12.1.1-cp313-cp313t-macosx_10_13_x86_64.whl", hash = "sha256:0330d233c1a0ead844fc097a7d16c0abff4c12e856c0b325f231820fee1f39da", size = 5264880, upload-time = "2026-02-11T04:21:32.865Z" }, + { url = "https://files.pythonhosted.org/packages/26/9d/e03d857d1347fa5ed9247e123fcd2a97b6220e15e9cb73ca0a8d91702c6e/pillow-12.1.1-cp313-cp313t-macosx_11_0_arm64.whl", hash = "sha256:5dae5f21afb91322f2ff791895ddd8889e5e947ff59f71b46041c8ce6db790bc", size = 4660616, upload-time = "2026-02-11T04:21:34.97Z" }, + { url = "https://files.pythonhosted.org/packages/f7/ec/8a6d22afd02570d30954e043f09c32772bfe143ba9285e2fdb11284952cd/pillow-12.1.1-cp313-cp313t-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:2e0c664be47252947d870ac0d327fea7e63985a08794758aa8af5b6cb6ec0c9c", size = 6269008, upload-time = "2026-02-11T04:21:36.623Z" }, + { url = "https://files.pythonhosted.org/packages/3d/1d/6d875422c9f28a4a361f495a5f68d9de4a66941dc2c619103ca335fa6446/pillow-12.1.1-cp313-cp313t-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:691ab2ac363b8217f7d31b3497108fb1f50faab2f75dfb03284ec2f217e87bf8", size = 8073226, upload-time = "2026-02-11T04:21:38.585Z" }, + { url = "https://files.pythonhosted.org/packages/a1/cd/134b0b6ee5eda6dc09e25e24b40fdafe11a520bc725c1d0bbaa5e00bf95b/pillow-12.1.1-cp313-cp313t-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:e9e8064fb1cc019296958595f6db671fba95209e3ceb0c4734c9baf97de04b20", size = 6380136, upload-time = "2026-02-11T04:21:40.562Z" }, + { url = "https://files.pythonhosted.org/packages/7a/a9/7628f013f18f001c1b98d8fffe3452f306a70dc6aba7d931019e0492f45e/pillow-12.1.1-cp313-cp313t-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:472a8d7ded663e6162dafdf20015c486a7009483ca671cece7a9279b512fcb13", size = 7067129, upload-time = "2026-02-11T04:21:42.521Z" }, + { url = "https://files.pythonhosted.org/packages/1e/f8/66ab30a2193b277785601e82ee2d49f68ea575d9637e5e234faaa98efa4c/pillow-12.1.1-cp313-cp313t-musllinux_1_2_aarch64.whl", hash = "sha256:89b54027a766529136a06cfebeecb3a04900397a3590fd252160b888479517bf", size = 6491807, upload-time = "2026-02-11T04:21:44.22Z" }, + { url = "https://files.pythonhosted.org/packages/da/0b/a877a6627dc8318fdb84e357c5e1a758c0941ab1ddffdafd231983788579/pillow-12.1.1-cp313-cp313t-musllinux_1_2_x86_64.whl", hash = "sha256:86172b0831b82ce4f7877f280055892b31179e1576aa00d0df3bb1bbf8c3e524", size = 7190954, upload-time = "2026-02-11T04:21:46.114Z" }, + { url = "https://files.pythonhosted.org/packages/83/43/6f732ff85743cf746b1361b91665d9f5155e1483817f693f8d57ea93147f/pillow-12.1.1-cp313-cp313t-win32.whl", hash = "sha256:44ce27545b6efcf0fdbdceb31c9a5bdea9333e664cda58a7e674bb74608b3986", size = 6336441, upload-time = "2026-02-11T04:21:48.22Z" }, + { url = "https://files.pythonhosted.org/packages/3b/44/e865ef3986611bb75bfabdf94a590016ea327833f434558801122979cd0e/pillow-12.1.1-cp313-cp313t-win_amd64.whl", hash = "sha256:a285e3eb7a5a45a2ff504e31f4a8d1b12ef62e84e5411c6804a42197c1cf586c", size = 7045383, upload-time = "2026-02-11T04:21:50.015Z" }, + { url = "https://files.pythonhosted.org/packages/a8/c6/f4fb24268d0c6908b9f04143697ea18b0379490cb74ba9e8d41b898bd005/pillow-12.1.1-cp313-cp313t-win_arm64.whl", hash = "sha256:cc7d296b5ea4d29e6570dabeaed58d31c3fea35a633a69679fb03d7664f43fb3", size = 2456104, upload-time = "2026-02-11T04:21:51.633Z" }, + { url = "https://files.pythonhosted.org/packages/03/d0/bebb3ffbf31c5a8e97241476c4cf8b9828954693ce6744b4a2326af3e16b/pillow-12.1.1-cp314-cp314-ios_13_0_arm64_iphoneos.whl", hash = "sha256:417423db963cb4be8bac3fc1204fe61610f6abeed1580a7a2cbb2fbda20f12af", size = 4062652, upload-time = "2026-02-11T04:21:53.19Z" }, + { url = "https://files.pythonhosted.org/packages/2d/c0/0e16fb0addda4851445c28f8350d8c512f09de27bbb0d6d0bbf8b6709605/pillow-12.1.1-cp314-cp314-ios_13_0_arm64_iphonesimulator.whl", hash = "sha256:b957b71c6b2387610f556a7eb0828afbe40b4a98036fc0d2acfa5a44a0c2036f", size = 4138823, upload-time = "2026-02-11T04:22:03.088Z" }, + { url = "https://files.pythonhosted.org/packages/6b/fb/6170ec655d6f6bb6630a013dd7cf7bc218423d7b5fa9071bf63dc32175ae/pillow-12.1.1-cp314-cp314-ios_13_0_x86_64_iphonesimulator.whl", hash = "sha256:097690ba1f2efdeb165a20469d59d8bb03c55fb6621eb2041a060ae8ea3e9642", size = 3601143, upload-time = "2026-02-11T04:22:04.909Z" }, + { url = "https://files.pythonhosted.org/packages/59/04/dc5c3f297510ba9a6837cbb318b87dd2b8f73eb41a43cc63767f65cb599c/pillow-12.1.1-cp314-cp314-macosx_10_15_x86_64.whl", hash = "sha256:2815a87ab27848db0321fb78c7f0b2c8649dee134b7f2b80c6a45c6831d75ccd", size = 5266254, upload-time = "2026-02-11T04:22:07.656Z" }, + { url = "https://files.pythonhosted.org/packages/05/30/5db1236b0d6313f03ebf97f5e17cda9ca060f524b2fcc875149a8360b21c/pillow-12.1.1-cp314-cp314-macosx_11_0_arm64.whl", hash = "sha256:f7ed2c6543bad5a7d5530eb9e78c53132f93dfa44a28492db88b41cdab885202", size = 4657499, upload-time = "2026-02-11T04:22:09.613Z" }, + { url = "https://files.pythonhosted.org/packages/6f/18/008d2ca0eb612e81968e8be0bbae5051efba24d52debf930126d7eaacbba/pillow-12.1.1-cp314-cp314-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:652a2c9ccfb556235b2b501a3a7cf3742148cd22e04b5625c5fe057ea3e3191f", size = 6232137, upload-time = "2026-02-11T04:22:11.434Z" }, + { url = "https://files.pythonhosted.org/packages/70/f1/f14d5b8eeb4b2cd62b9f9f847eb6605f103df89ef619ac68f92f748614ea/pillow-12.1.1-cp314-cp314-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:d6e4571eedf43af33d0fc233a382a76e849badbccdf1ac438841308652a08e1f", size = 8042721, upload-time = "2026-02-11T04:22:13.321Z" }, + { url = "https://files.pythonhosted.org/packages/5a/d6/17824509146e4babbdabf04d8171491fa9d776f7061ff6e727522df9bd03/pillow-12.1.1-cp314-cp314-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:b574c51cf7d5d62e9be37ba446224b59a2da26dc4c1bb2ecbe936a4fb1a7cb7f", size = 6347798, upload-time = "2026-02-11T04:22:15.449Z" }, + { url = "https://files.pythonhosted.org/packages/d1/ee/c85a38a9ab92037a75615aba572c85ea51e605265036e00c5b67dfafbfe2/pillow-12.1.1-cp314-cp314-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:a37691702ed687799de29a518d63d4682d9016932db66d4e90c345831b02fb4e", size = 7039315, upload-time = "2026-02-11T04:22:17.24Z" }, + { url = "https://files.pythonhosted.org/packages/ec/f3/bc8ccc6e08a148290d7523bde4d9a0d6c981db34631390dc6e6ec34cacf6/pillow-12.1.1-cp314-cp314-musllinux_1_2_aarch64.whl", hash = "sha256:f95c00d5d6700b2b890479664a06e754974848afaae5e21beb4d83c106923fd0", size = 6462360, upload-time = "2026-02-11T04:22:19.111Z" }, + { url = "https://files.pythonhosted.org/packages/f6/ab/69a42656adb1d0665ab051eec58a41f169ad295cf81ad45406963105408f/pillow-12.1.1-cp314-cp314-musllinux_1_2_x86_64.whl", hash = "sha256:559b38da23606e68681337ad74622c4dbba02254fc9cb4488a305dd5975c7eeb", size = 7165438, upload-time = "2026-02-11T04:22:21.041Z" }, + { url = "https://files.pythonhosted.org/packages/02/46/81f7aa8941873f0f01d4b55cc543b0a3d03ec2ee30d617a0448bf6bd6dec/pillow-12.1.1-cp314-cp314-win32.whl", hash = "sha256:03edcc34d688572014ff223c125a3f77fb08091e4607e7745002fc214070b35f", size = 6431503, upload-time = "2026-02-11T04:22:22.833Z" }, + { url = "https://files.pythonhosted.org/packages/40/72/4c245f7d1044b67affc7f134a09ea619d4895333d35322b775b928180044/pillow-12.1.1-cp314-cp314-win_amd64.whl", hash = "sha256:50480dcd74fa63b8e78235957d302d98d98d82ccbfac4c7e12108ba9ecbdba15", size = 7176748, upload-time = "2026-02-11T04:22:24.64Z" }, + { url = "https://files.pythonhosted.org/packages/e4/ad/8a87bdbe038c5c698736e3348af5c2194ffb872ea52f11894c95f9305435/pillow-12.1.1-cp314-cp314-win_arm64.whl", hash = "sha256:5cb1785d97b0c3d1d1a16bc1d710c4a0049daefc4935f3a8f31f827f4d3d2e7f", size = 2544314, upload-time = "2026-02-11T04:22:26.685Z" }, + { url = "https://files.pythonhosted.org/packages/6c/9d/efd18493f9de13b87ede7c47e69184b9e859e4427225ea962e32e56a49bc/pillow-12.1.1-cp314-cp314t-macosx_10_15_x86_64.whl", hash = "sha256:1f90cff8aa76835cba5769f0b3121a22bd4eb9e6884cfe338216e557a9a548b8", size = 5268612, upload-time = "2026-02-11T04:22:29.884Z" }, + { url = "https://files.pythonhosted.org/packages/f8/f1/4f42eb2b388eb2ffc660dcb7f7b556c1015c53ebd5f7f754965ef997585b/pillow-12.1.1-cp314-cp314t-macosx_11_0_arm64.whl", hash = "sha256:1f1be78ce9466a7ee64bfda57bdba0f7cc499d9794d518b854816c41bf0aa4e9", size = 4660567, upload-time = "2026-02-11T04:22:31.799Z" }, + { url = "https://files.pythonhosted.org/packages/01/54/df6ef130fa43e4b82e32624a7b821a2be1c5653a5fdad8469687a7db4e00/pillow-12.1.1-cp314-cp314t-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:42fc1f4677106188ad9a55562bbade416f8b55456f522430fadab3cef7cd4e60", size = 6269951, upload-time = "2026-02-11T04:22:33.921Z" }, + { url = "https://files.pythonhosted.org/packages/a9/48/618752d06cc44bb4aae8ce0cd4e6426871929ed7b46215638088270d9b34/pillow-12.1.1-cp314-cp314t-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:98edb152429ab62a1818039744d8fbb3ccab98a7c29fc3d5fcef158f3f1f68b7", size = 8074769, upload-time = "2026-02-11T04:22:35.877Z" }, + { url = "https://files.pythonhosted.org/packages/c3/bd/f1d71eb39a72fa088d938655afba3e00b38018d052752f435838961127d8/pillow-12.1.1-cp314-cp314t-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:d470ab1178551dd17fdba0fef463359c41aaa613cdcd7ff8373f54be629f9f8f", size = 6381358, upload-time = "2026-02-11T04:22:37.698Z" }, + { url = "https://files.pythonhosted.org/packages/64/ef/c784e20b96674ed36a5af839305f55616f8b4f8aa8eeccf8531a6e312243/pillow-12.1.1-cp314-cp314t-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:6408a7b064595afcab0a49393a413732a35788f2a5092fdc6266952ed67de586", size = 7068558, upload-time = "2026-02-11T04:22:39.597Z" }, + { url = "https://files.pythonhosted.org/packages/73/cb/8059688b74422ae61278202c4e1ad992e8a2e7375227be0a21c6b87ca8d5/pillow-12.1.1-cp314-cp314t-musllinux_1_2_aarch64.whl", hash = "sha256:5d8c41325b382c07799a3682c1c258469ea2ff97103c53717b7893862d0c98ce", size = 6493028, upload-time = "2026-02-11T04:22:42.73Z" }, + { url = "https://files.pythonhosted.org/packages/c6/da/e3c008ed7d2dd1f905b15949325934510b9d1931e5df999bb15972756818/pillow-12.1.1-cp314-cp314t-musllinux_1_2_x86_64.whl", hash = "sha256:c7697918b5be27424e9ce568193efd13d925c4481dd364e43f5dff72d33e10f8", size = 7191940, upload-time = "2026-02-11T04:22:44.543Z" }, + { url = "https://files.pythonhosted.org/packages/01/4a/9202e8d11714c1fc5951f2e1ef362f2d7fbc595e1f6717971d5dd750e969/pillow-12.1.1-cp314-cp314t-win32.whl", hash = "sha256:d2912fd8114fc5545aa3a4b5576512f64c55a03f3ebcca4c10194d593d43ea36", size = 6438736, upload-time = "2026-02-11T04:22:46.347Z" }, + { url = "https://files.pythonhosted.org/packages/f3/ca/cbce2327eb9885476b3957b2e82eb12c866a8b16ad77392864ad601022ce/pillow-12.1.1-cp314-cp314t-win_amd64.whl", hash = "sha256:4ceb838d4bd9dab43e06c363cab2eebf63846d6a4aeaea283bbdfd8f1a8ed58b", size = 7182894, upload-time = "2026-02-11T04:22:48.114Z" }, + { url = "https://files.pythonhosted.org/packages/ec/d2/de599c95ba0a973b94410477f8bf0b6f0b5e67360eb89bcb1ad365258beb/pillow-12.1.1-cp314-cp314t-win_arm64.whl", hash = "sha256:7b03048319bfc6170e93bd60728a1af51d3dd7704935feb228c4d4faab35d334", size = 2546446, upload-time = "2026-02-11T04:22:50.342Z" }, + { url = "https://files.pythonhosted.org/packages/56/11/5d43209aa4cb58e0cc80127956ff1796a68b928e6324bbf06ef4db34367b/pillow-12.1.1-pp311-pypy311_pp73-macosx_10_15_x86_64.whl", hash = "sha256:600fd103672b925fe62ed08e0d874ea34d692474df6f4bf7ebe148b30f89f39f", size = 5228606, upload-time = "2026-02-11T04:22:52.106Z" }, + { url = "https://files.pythonhosted.org/packages/5f/d5/3b005b4e4fda6698b371fa6c21b097d4707585d7db99e98d9b0b87ac612a/pillow-12.1.1-pp311-pypy311_pp73-macosx_11_0_arm64.whl", hash = "sha256:665e1b916b043cef294bc54d47bf02d87e13f769bc4bc5fa225a24b3a6c5aca9", size = 4622321, upload-time = "2026-02-11T04:22:53.827Z" }, + { url = "https://files.pythonhosted.org/packages/df/36/ed3ea2d594356fd8037e5a01f6156c74bc8d92dbb0fa60746cc96cabb6e8/pillow-12.1.1-pp311-pypy311_pp73-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:495c302af3aad1ca67420ddd5c7bd480c8867ad173528767d906428057a11f0e", size = 5247579, upload-time = "2026-02-11T04:22:56.094Z" }, + { url = "https://files.pythonhosted.org/packages/54/9a/9cc3e029683cf6d20ae5085da0dafc63148e3252c2f13328e553aaa13cfb/pillow-12.1.1-pp311-pypy311_pp73-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:8fd420ef0c52c88b5a035a0886f367748c72147b2b8f384c9d12656678dfdfa9", size = 6989094, upload-time = "2026-02-11T04:22:58.288Z" }, + { url = "https://files.pythonhosted.org/packages/00/98/fc53ab36da80b88df0967896b6c4b4cd948a0dc5aa40a754266aa3ae48b3/pillow-12.1.1-pp311-pypy311_pp73-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:f975aa7ef9684ce7e2c18a3aa8f8e2106ce1e46b94ab713d156b2898811651d3", size = 5313850, upload-time = "2026-02-11T04:23:00.554Z" }, + { url = "https://files.pythonhosted.org/packages/30/02/00fa585abfd9fe9d73e5f6e554dc36cc2b842898cbfc46d70353dae227f8/pillow-12.1.1-pp311-pypy311_pp73-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:8089c852a56c2966cf18835db62d9b34fef7ba74c726ad943928d494fa7f4735", size = 5963343, upload-time = "2026-02-11T04:23:02.934Z" }, + { url = "https://files.pythonhosted.org/packages/f2/26/c56ce33ca856e358d27fda9676c055395abddb82c35ac0f593877ed4562e/pillow-12.1.1-pp311-pypy311_pp73-win_amd64.whl", hash = "sha256:cb9bb857b2d057c6dfc72ac5f3b44836924ba15721882ef103cecb40d002d80e", size = 7029880, upload-time = "2026-02-11T04:23:04.783Z" }, +] + +[[package]] +name = "pip" +version = "26.0.1" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/48/83/0d7d4e9efe3344b8e2fe25d93be44f64b65364d3c8d7bc6dc90198d5422e/pip-26.0.1.tar.gz", hash = "sha256:c4037d8a277c89b320abe636d59f91e6d0922d08a05b60e85e53b296613346d8", size = 1812747, upload-time = "2026-02-05T02:20:18.702Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/de/f0/c81e05b613866b76d2d1066490adf1a3dbc4ee9d9c839961c3fc8a6997af/pip-26.0.1-py3-none-any.whl", hash = "sha256:bdb1b08f4274833d62c1aa29e20907365a2ceb950410df15fc9521bad440122b", size = 1787723, upload-time = "2026-02-05T02:20:16.416Z" }, +] + +[[package]] +name = "platformdirs" +version = "4.9.2" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/1b/04/fea538adf7dbbd6d186f551d595961e564a3b6715bdf276b477460858672/platformdirs-4.9.2.tar.gz", hash = "sha256:9a33809944b9db043ad67ca0db94b14bf452cc6aeaac46a88ea55b26e2e9d291", size = 28394, upload-time = "2026-02-16T03:56:10.574Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/48/31/05e764397056194206169869b50cf2fee4dbbbc71b344705b9c0d878d4d8/platformdirs-4.9.2-py3-none-any.whl", hash = "sha256:9170634f126f8efdae22fb58ae8a0eaa86f38365bc57897a6c4f781d1f5875bd", size = 21168, upload-time = "2026-02-16T03:56:08.891Z" }, +] + +[[package]] +name = "pluggy" +version = "1.6.0" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/f9/e2/3e91f31a7d2b083fe6ef3fa267035b518369d9511ffab804f839851d2779/pluggy-1.6.0.tar.gz", hash = "sha256:7dcc130b76258d33b90f61b658791dede3486c3e6bfb003ee5c9bfb396dd22f3", size = 69412, upload-time = "2025-05-15T12:30:07.975Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/54/20/4d324d65cc6d9205fabedc306948156824eb9f0ee1633355a8f7ec5c66bf/pluggy-1.6.0-py3-none-any.whl", hash = "sha256:e920276dd6813095e9377c0bc5566d94c932c33b27a3e3945d8389c374dd4746", size = 20538, upload-time = "2025-05-15T12:30:06.134Z" }, +] + +[[package]] +name = "plumbum" +version = "1.10.0" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "pywin32", marker = "platform_python_implementation != 'PyPy' and sys_platform == 'win32'" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/dc/c8/11a5f792704b70f071a3dbc329105a98e9cc8d25daaf09f733c44eb0ef8e/plumbum-1.10.0.tar.gz", hash = "sha256:f8cbf0ecec0b73ff4e349398b65112a9e3f9300e7dc019001217dcc148d5c97c", size = 320039, upload-time = "2025-10-31T05:02:48.697Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/79/ad/45312df6b63ba64ea35b8d8f5f0c577aac16e6b416eafe8e1cb34e03f9a7/plumbum-1.10.0-py3-none-any.whl", hash = "sha256:9583d737ac901c474d99d030e4d5eec4c4e6d2d7417b1cf49728cf3be34f6dc8", size = 127383, upload-time = "2025-10-31T05:02:47.002Z" }, +] + +[[package]] +name = "ply" +version = "3.11" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/e5/69/882ee5c9d017149285cab114ebeab373308ef0f874fcdac9beb90e0ac4da/ply-3.11.tar.gz", hash = "sha256:00c7c1aaa88358b9c765b6d3000c6eec0ba42abca5351b095321aef446081da3", size = 159130, upload-time = "2018-02-15T19:01:31.097Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/a3/58/35da89ee790598a0700ea49b2a66594140f44dec458c07e8e3d4979137fc/ply-3.11-py2.py3-none-any.whl", hash = "sha256:096f9b8350b65ebd2fd1346b12452efe5b9607f7482813ffca50c22722a807ce", size = 49567, upload-time = "2018-02-15T19:01:27.172Z" }, +] + +[[package]] +name = "pre-commit" +version = "4.5.1" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "cfgv" }, + { name = "identify" }, + { name = "nodeenv" }, + { name = "pyyaml" }, + { name = "virtualenv" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/40/f1/6d86a29246dfd2e9b6237f0b5823717f60cad94d47ddc26afa916d21f525/pre_commit-4.5.1.tar.gz", hash = "sha256:eb545fcff725875197837263e977ea257a402056661f09dae08e4b149b030a61", size = 198232, upload-time = "2025-12-16T21:14:33.552Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/5d/19/fd3ef348460c80af7bb4669ea7926651d1f95c23ff2df18b9d24bab4f3fa/pre_commit-4.5.1-py2.py3-none-any.whl", hash = "sha256:3b3afd891e97337708c1674210f8eba659b52a38ea5f822ff142d10786221f77", size = 226437, upload-time = "2025-12-16T21:14:32.409Z" }, +] + +[[package]] +name = "prompt-toolkit" +version = "3.0.52" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "wcwidth" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/a1/96/06e01a7b38dce6fe1db213e061a4602dd6032a8a97ef6c1a862537732421/prompt_toolkit-3.0.52.tar.gz", hash = "sha256:28cde192929c8e7321de85de1ddbe736f1375148b02f2e17edd840042b1be855", size = 434198, upload-time = "2025-08-27T15:24:02.057Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/84/03/0d3ce49e2505ae70cf43bc5bb3033955d2fc9f932163e84dc0779cc47f48/prompt_toolkit-3.0.52-py3-none-any.whl", hash = "sha256:9aac639a3bbd33284347de5ad8d68ecc044b91a762dc39b7c21095fcd6a19955", size = 391431, upload-time = "2025-08-27T15:23:59.498Z" }, +] + +[[package]] +name = "psutil" +version = "7.2.2" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/aa/c6/d1ddf4abb55e93cebc4f2ed8b5d6dbad109ecb8d63748dd2b20ab5e57ebe/psutil-7.2.2.tar.gz", hash = "sha256:0746f5f8d406af344fd547f1c8daa5f5c33dbc293bb8d6a16d80b4bb88f59372", size = 493740, upload-time = "2026-01-28T18:14:54.428Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/51/08/510cbdb69c25a96f4ae523f733cdc963ae654904e8db864c07585ef99875/psutil-7.2.2-cp313-cp313t-macosx_10_13_x86_64.whl", hash = "sha256:2edccc433cbfa046b980b0df0171cd25bcaeb3a68fe9022db0979e7aa74a826b", size = 130595, upload-time = "2026-01-28T18:14:57.293Z" }, + { url = "https://files.pythonhosted.org/packages/d6/f5/97baea3fe7a5a9af7436301f85490905379b1c6f2dd51fe3ecf24b4c5fbf/psutil-7.2.2-cp313-cp313t-macosx_11_0_arm64.whl", hash = "sha256:e78c8603dcd9a04c7364f1a3e670cea95d51ee865e4efb3556a3a63adef958ea", size = 131082, upload-time = "2026-01-28T18:14:59.732Z" }, + { url = "https://files.pythonhosted.org/packages/37/d6/246513fbf9fa174af531f28412297dd05241d97a75911ac8febefa1a53c6/psutil-7.2.2-cp313-cp313t-manylinux2010_x86_64.manylinux_2_12_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:1a571f2330c966c62aeda00dd24620425d4b0cc86881c89861fbc04549e5dc63", size = 181476, upload-time = "2026-01-28T18:15:01.884Z" }, + { url = "https://files.pythonhosted.org/packages/b8/b5/9182c9af3836cca61696dabe4fd1304e17bc56cb62f17439e1154f225dd3/psutil-7.2.2-cp313-cp313t-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:917e891983ca3c1887b4ef36447b1e0873e70c933afc831c6b6da078ba474312", size = 184062, upload-time = "2026-01-28T18:15:04.436Z" }, + { url = "https://files.pythonhosted.org/packages/16/ba/0756dca669f5a9300d0cbcbfae9a4c30e446dfc7440ffe43ded5724bfd93/psutil-7.2.2-cp313-cp313t-win_amd64.whl", hash = "sha256:ab486563df44c17f5173621c7b198955bd6b613fb87c71c161f827d3fb149a9b", size = 139893, upload-time = "2026-01-28T18:15:06.378Z" }, + { url = "https://files.pythonhosted.org/packages/1c/61/8fa0e26f33623b49949346de05ec1ddaad02ed8ba64af45f40a147dbfa97/psutil-7.2.2-cp313-cp313t-win_arm64.whl", hash = "sha256:ae0aefdd8796a7737eccea863f80f81e468a1e4cf14d926bd9b6f5f2d5f90ca9", size = 135589, upload-time = "2026-01-28T18:15:08.03Z" }, + { url = "https://files.pythonhosted.org/packages/81/69/ef179ab5ca24f32acc1dac0c247fd6a13b501fd5534dbae0e05a1c48b66d/psutil-7.2.2-cp314-cp314t-macosx_10_15_x86_64.whl", hash = "sha256:eed63d3b4d62449571547b60578c5b2c4bcccc5387148db46e0c2313dad0ee00", size = 130664, upload-time = "2026-01-28T18:15:09.469Z" }, + { url = "https://files.pythonhosted.org/packages/7b/64/665248b557a236d3fa9efc378d60d95ef56dd0a490c2cd37dafc7660d4a9/psutil-7.2.2-cp314-cp314t-macosx_11_0_arm64.whl", hash = "sha256:7b6d09433a10592ce39b13d7be5a54fbac1d1228ed29abc880fb23df7cb694c9", size = 131087, upload-time = "2026-01-28T18:15:11.724Z" }, + { url = "https://files.pythonhosted.org/packages/d5/2e/e6782744700d6759ebce3043dcfa661fb61e2fb752b91cdeae9af12c2178/psutil-7.2.2-cp314-cp314t-manylinux2010_x86_64.manylinux_2_12_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:1fa4ecf83bcdf6e6c8f4449aff98eefb5d0604bf88cb883d7da3d8d2d909546a", size = 182383, upload-time = "2026-01-28T18:15:13.445Z" }, + { url = "https://files.pythonhosted.org/packages/57/49/0a41cefd10cb7505cdc04dab3eacf24c0c2cb158a998b8c7b1d27ee2c1f5/psutil-7.2.2-cp314-cp314t-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:e452c464a02e7dc7822a05d25db4cde564444a67e58539a00f929c51eddda0cf", size = 185210, upload-time = "2026-01-28T18:15:16.002Z" }, + { url = "https://files.pythonhosted.org/packages/dd/2c/ff9bfb544f283ba5f83ba725a3c5fec6d6b10b8f27ac1dc641c473dc390d/psutil-7.2.2-cp314-cp314t-win_amd64.whl", hash = "sha256:c7663d4e37f13e884d13994247449e9f8f574bc4655d509c3b95e9ec9e2b9dc1", size = 141228, upload-time = "2026-01-28T18:15:18.385Z" }, + { url = "https://files.pythonhosted.org/packages/f2/fc/f8d9c31db14fcec13748d373e668bc3bed94d9077dbc17fb0eebc073233c/psutil-7.2.2-cp314-cp314t-win_arm64.whl", hash = "sha256:11fe5a4f613759764e79c65cf11ebdf26e33d6dd34336f8a337aa2996d71c841", size = 136284, upload-time = "2026-01-28T18:15:19.912Z" }, + { url = "https://files.pythonhosted.org/packages/e7/36/5ee6e05c9bd427237b11b3937ad82bb8ad2752d72c6969314590dd0c2f6e/psutil-7.2.2-cp36-abi3-macosx_10_9_x86_64.whl", hash = "sha256:ed0cace939114f62738d808fdcecd4c869222507e266e574799e9c0faa17d486", size = 129090, upload-time = "2026-01-28T18:15:22.168Z" }, + { url = "https://files.pythonhosted.org/packages/80/c4/f5af4c1ca8c1eeb2e92ccca14ce8effdeec651d5ab6053c589b074eda6e1/psutil-7.2.2-cp36-abi3-macosx_11_0_arm64.whl", hash = "sha256:1a7b04c10f32cc88ab39cbf606e117fd74721c831c98a27dc04578deb0c16979", size = 129859, upload-time = "2026-01-28T18:15:23.795Z" }, + { url = "https://files.pythonhosted.org/packages/b5/70/5d8df3b09e25bce090399cf48e452d25c935ab72dad19406c77f4e828045/psutil-7.2.2-cp36-abi3-manylinux2010_x86_64.manylinux_2_12_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:076a2d2f923fd4821644f5ba89f059523da90dc9014e85f8e45a5774ca5bc6f9", size = 155560, upload-time = "2026-01-28T18:15:25.976Z" }, + { url = "https://files.pythonhosted.org/packages/63/65/37648c0c158dc222aba51c089eb3bdfa238e621674dc42d48706e639204f/psutil-7.2.2-cp36-abi3-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:b0726cecd84f9474419d67252add4ac0cd9811b04d61123054b9fb6f57df6e9e", size = 156997, upload-time = "2026-01-28T18:15:27.794Z" }, + { url = "https://files.pythonhosted.org/packages/8e/13/125093eadae863ce03c6ffdbae9929430d116a246ef69866dad94da3bfbc/psutil-7.2.2-cp36-abi3-musllinux_1_2_aarch64.whl", hash = "sha256:fd04ef36b4a6d599bbdb225dd1d3f51e00105f6d48a28f006da7f9822f2606d8", size = 148972, upload-time = "2026-01-28T18:15:29.342Z" }, + { url = "https://files.pythonhosted.org/packages/04/78/0acd37ca84ce3ddffaa92ef0f571e073faa6d8ff1f0559ab1272188ea2be/psutil-7.2.2-cp36-abi3-musllinux_1_2_x86_64.whl", hash = "sha256:b58fabe35e80b264a4e3bb23e6b96f9e45a3df7fb7eed419ac0e5947c61e47cc", size = 148266, upload-time = "2026-01-28T18:15:31.597Z" }, + { url = "https://files.pythonhosted.org/packages/b4/90/e2159492b5426be0c1fef7acba807a03511f97c5f86b3caeda6ad92351a7/psutil-7.2.2-cp37-abi3-win_amd64.whl", hash = "sha256:eb7e81434c8d223ec4a219b5fc1c47d0417b12be7ea866e24fb5ad6e84b3d988", size = 137737, upload-time = "2026-01-28T18:15:33.849Z" }, + { url = "https://files.pythonhosted.org/packages/8c/c7/7bb2e321574b10df20cbde462a94e2b71d05f9bbda251ef27d104668306a/psutil-7.2.2-cp37-abi3-win_arm64.whl", hash = "sha256:8c233660f575a5a89e6d4cb65d9f938126312bca76d8fe087b947b3a1aaac9ee", size = 134617, upload-time = "2026-01-28T18:15:36.514Z" }, +] + +[[package]] +name = "ptyprocess" +version = "0.7.0" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/20/e5/16ff212c1e452235a90aeb09066144d0c5a6a8c0834397e03f5224495c4e/ptyprocess-0.7.0.tar.gz", hash = "sha256:5c5d0a3b48ceee0b48485e0c26037c0acd7d29765ca3fbb5cb3831d347423220", size = 70762, upload-time = "2020-12-28T15:15:30.155Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/22/a6/858897256d0deac81a172289110f31629fc4cee19b6f01283303e18c8db3/ptyprocess-0.7.0-py2.py3-none-any.whl", hash = "sha256:4b41f3967fce3af57cc7e94b888626c18bf37a083e3651ca8feeb66d492fef35", size = 13993, upload-time = "2020-12-28T15:15:28.35Z" }, +] + +[[package]] +name = "pure-eval" +version = "0.2.3" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/cd/05/0a34433a064256a578f1783a10da6df098ceaa4a57bbeaa96a6c0352786b/pure_eval-0.2.3.tar.gz", hash = "sha256:5f4e983f40564c576c7c8635ae88db5956bb2229d7e9237d03b3c0b0190eaf42", size = 19752, upload-time = "2024-07-21T12:58:21.801Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/8e/37/efad0257dc6e593a18957422533ff0f87ede7c9c6ea010a2177d738fb82f/pure_eval-0.2.3-py3-none-any.whl", hash = "sha256:1db8e35b67b3d218d818ae653e27f06c3aa420901fa7b081ca98cbedc874e0d0", size = 11842, upload-time = "2024-07-21T12:58:20.04Z" }, +] + +[[package]] +name = "pybtex" +version = "0.25.1" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "latexcodec" }, + { name = "pyyaml" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/5f/bc/c2be05ca72f8c103670e983df8be26d1e288bc6556f487fa8cccaa27779f/pybtex-0.25.1.tar.gz", hash = "sha256:9eaf90267c7e83e225af89fea65c370afbf65f458220d3946a9e3049e1eca491", size = 406157, upload-time = "2025-06-26T13:27:41.903Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/25/68/ceb5d6679baa326261f5d3e5113d9cfed6efef2810afd9f18bffb8ed312b/pybtex-0.25.1-py2.py3-none-any.whl", hash = "sha256:9053b0d619409a0a83f38abad5d9921de5f7b3ede00742beafcd9f10ad0d8c5c", size = 127437, upload-time = "2025-06-26T13:27:43.585Z" }, +] + +[[package]] +name = "pybtex-docutils" +version = "1.0.3" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "docutils" }, + { name = "pybtex" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/7e/84/796ea94d26188a853660f81bded39f8de4cfe595130aef0dea1088705a11/pybtex-docutils-1.0.3.tar.gz", hash = "sha256:3a7ebdf92b593e00e8c1c538aa9a20bca5d92d84231124715acc964d51d93c6b", size = 18348, upload-time = "2023-08-22T18:47:54.833Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/11/b1/ce1f4596211efb5410e178a803f08e59b20bedb66837dcf41e21c54f9ec1/pybtex_docutils-1.0.3-py3-none-any.whl", hash = "sha256:8fd290d2ae48e32fcb54d86b0efb8d573198653c7e2447d5bec5847095f430b9", size = 6385, upload-time = "2023-08-22T06:43:20.513Z" }, +] + +[[package]] +name = "pyclustree" +version = "0.5.0" +source = { editable = "." } +dependencies = [ + { name = "anndata" }, + { name = "matplotlib" }, + { name = "matplotlib-sankey" }, + { name = "networkx" }, + { name = "numpy" }, + { name = "pandas" }, + { name = "seaborn" }, + { name = "session-info" }, +] + +[package.optional-dependencies] +dev = [ + { name = "build" }, + { name = "coverage" }, + { name = "docutils" }, + { name = "flit" }, + { name = "furo" }, + { name = "ipykernel" }, + { name = "ipython" }, + { name = "ipywidgets" }, + { name = "myst-parser" }, + { name = "nbsphinx" }, + { name = "pandas" }, + { name = "pandas-stubs" }, + { name = "pandoc" }, + { name = "pre-commit" }, + { name = "pytest" }, + { name = "python-igraph" }, + { name = "scanpy", version = "1.11.5", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.12'" }, + { name = "scanpy", version = "1.12", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.12'" }, + { name = "setuptools" }, + { name = "sphinx", version = "9.0.4", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.12'" }, + { name = "sphinx", version = "9.1.0", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.12'" }, + { name = "sphinx-autoapi" }, + { name = "sphinx-autodoc-typehints", version = "3.6.1", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.12'" }, + { name = "sphinx-autodoc-typehints", version = "3.6.3", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.12'" }, + { name = "sphinx-book-theme" }, + { name = "sphinx-copybutton" }, + { name = "sphinx-design" }, + { name = "sphinx-rtd-theme" }, + { name = "sphinx-tabs" }, + { name = "sphinxcontrib-bibtex" }, + { name = "sphinxext-opengraph" }, + { name = "twine" }, + { name = "types-networkx" }, +] +sklearn = [ + { name = "scikit-learn" }, +] + +[package.metadata] +requires-dist = [ + { name = "anndata" }, + { name = "build", marker = "extra == 'dev'", specifier = ">=1.4.0" }, + { name = "coverage", marker = "extra == 'dev'" }, + { name = "docutils", marker = "extra == 'dev'", specifier = ">=0.8,!=0.18.*,!=0.19.*" }, + { name = "flit", marker = "extra == 'dev'" }, + { name = "furo", marker = "extra == 'dev'" }, + { name = "ipykernel", marker = "extra == 'dev'" }, + { name = "ipython", marker = "extra == 'dev'" }, + { name = "ipywidgets", marker = "extra == 'dev'" }, + { name = "matplotlib" }, + { name = "matplotlib-sankey", specifier = ">=0.3.2" }, + { name = "myst-parser", marker = "extra == 'dev'" }, + { name = "nbsphinx", marker = "extra == 'dev'" }, + { name = "networkx" }, + { name = "numpy" }, + { name = "pandas" }, + { name = "pandas", marker = "extra == 'dev'" }, + { name = "pandas-stubs", marker = "extra == 'dev'" }, + { name = "pandoc", marker = "extra == 'dev'" }, + { name = "pre-commit", marker = "extra == 'dev'" }, + { name = "pytest", marker = "extra == 'dev'" }, + { name = "python-igraph", marker = "extra == 'dev'" }, + { name = "scanpy", marker = "extra == 'dev'" }, + { name = "scikit-learn", marker = "extra == 'sklearn'" }, + { name = "seaborn" }, + { name = "session-info" }, + { name = "setuptools", marker = "extra == 'dev'" }, + { name = "sphinx", marker = "extra == 'dev'", specifier = ">=4" }, + { name = "sphinx-autoapi", marker = "extra == 'dev'" }, + { name = "sphinx-autodoc-typehints", marker = "extra == 'dev'" }, + { name = "sphinx-book-theme", marker = "extra == 'dev'", specifier = ">=1" }, + { name = "sphinx-copybutton", marker = "extra == 'dev'" }, + { name = "sphinx-design", marker = "extra == 'dev'" }, + { name = "sphinx-rtd-theme", marker = "extra == 'dev'" }, + { name = "sphinx-tabs", marker = "extra == 'dev'" }, + { name = "sphinxcontrib-bibtex", marker = "extra == 'dev'", specifier = ">=1" }, + { name = "sphinxext-opengraph", marker = "extra == 'dev'" }, + { name = "twine", marker = "extra == 'dev'", specifier = ">=4.0.2" }, + { name = "types-networkx", marker = "extra == 'dev'" }, +] +provides-extras = ["dev", "sklearn"] + +[[package]] +name = "pycparser" +version = "3.0" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/1b/7d/92392ff7815c21062bea51aa7b87d45576f649f16458d78b7cf94b9ab2e6/pycparser-3.0.tar.gz", hash = "sha256:600f49d217304a5902ac3c37e1281c9fe94e4d0489de643a9504c5cdfdfc6b29", size = 103492, upload-time = "2026-01-21T14:26:51.89Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/0c/c3/44f3fbbfa403ea2a7c779186dc20772604442dde72947e7d01069cbe98e3/pycparser-3.0-py3-none-any.whl", hash = "sha256:b727414169a36b7d524c1c3e31839a521725078d7b2ff038656844266160a992", size = 48172, upload-time = "2026-01-21T14:26:50.693Z" }, +] + +[[package]] +name = "pydata-sphinx-theme" +version = "0.15.4" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "accessible-pygments" }, + { name = "babel" }, + { name = "beautifulsoup4" }, + { name = "docutils" }, + { name = "packaging" }, + { name = "pygments" }, + { name = "sphinx", version = "9.0.4", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.12'" }, + { name = "sphinx", version = "9.1.0", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.12'" }, + { name = "typing-extensions" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/67/ea/3ab478cccacc2e8ef69892c42c44ae547bae089f356c4b47caf61730958d/pydata_sphinx_theme-0.15.4.tar.gz", hash = "sha256:7762ec0ac59df3acecf49fd2f889e1b4565dbce8b88b2e29ee06fdd90645a06d", size = 2400673, upload-time = "2024-06-25T19:28:45.041Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/e7/d3/c622950d87a2ffd1654208733b5bd1c5645930014abed8f4c0d74863988b/pydata_sphinx_theme-0.15.4-py3-none-any.whl", hash = "sha256:2136ad0e9500d0949f96167e63f3e298620040aea8f9c74621959eda5d4cf8e6", size = 4640157, upload-time = "2024-06-25T19:28:42.383Z" }, +] + +[[package]] +name = "pygments" +version = "2.19.2" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/b0/77/a5b8c569bf593b0140bde72ea885a803b82086995367bf2037de0159d924/pygments-2.19.2.tar.gz", hash = "sha256:636cb2477cec7f8952536970bc533bc43743542f70392ae026374600add5b887", size = 4968631, upload-time = "2025-06-21T13:39:12.283Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/c7/21/705964c7812476f378728bdf590ca4b771ec72385c533964653c68e86bdc/pygments-2.19.2-py3-none-any.whl", hash = "sha256:86540386c03d588bb81d44bc3928634ff26449851e99741617ecb9037ee5ec0b", size = 1225217, upload-time = "2025-06-21T13:39:07.939Z" }, +] + +[[package]] +name = "pynndescent" +version = "0.6.0" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "joblib" }, + { name = "llvmlite" }, + { name = "numba" }, + { name = "scikit-learn" }, + { name = "scipy" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/4a/fb/7f58c397fb31666756457ee2ac4c0289ef2daad57f4ae4be8dec12f80b03/pynndescent-0.6.0.tar.gz", hash = "sha256:7ffde0fb5b400741e055a9f7d377e3702e02250616834231f6c209e39aac24f5", size = 2992987, upload-time = "2026-01-08T21:29:58.943Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/b2/e6/94145d714402fd5ade00b5661f2d0ab981219e07f7db9bfa16786cdb9c04/pynndescent-0.6.0-py3-none-any.whl", hash = "sha256:dc8c74844e4c7f5cbd1e0cd6909da86fdc789e6ff4997336e344779c3d5538ef", size = 73511, upload-time = "2026-01-08T21:29:57.306Z" }, +] + +[[package]] +name = "pyparsing" +version = "3.3.2" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/f3/91/9c6ee907786a473bf81c5f53cf703ba0957b23ab84c264080fb5a450416f/pyparsing-3.3.2.tar.gz", hash = "sha256:c777f4d763f140633dcb6d8a3eda953bf7a214dc4eff598413c070bcdc117cbc", size = 6851574, upload-time = "2026-01-21T03:57:59.36Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/10/bd/c038d7cc38edc1aa5bf91ab8068b63d4308c66c4c8bb3cbba7dfbc049f9c/pyparsing-3.3.2-py3-none-any.whl", hash = "sha256:850ba148bd908d7e2411587e247a1e4f0327839c40e2e5e6d05a007ecc69911d", size = 122781, upload-time = "2026-01-21T03:57:55.912Z" }, +] + +[[package]] +name = "pyproject-hooks" +version = "1.2.0" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/e7/82/28175b2414effca1cdac8dc99f76d660e7a4fb0ceefa4b4ab8f5f6742925/pyproject_hooks-1.2.0.tar.gz", hash = "sha256:1e859bd5c40fae9448642dd871adf459e5e2084186e8d2c2a79a824c970da1f8", size = 19228, upload-time = "2024-09-29T09:24:13.293Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/bd/24/12818598c362d7f300f18e74db45963dbcb85150324092410c8b49405e42/pyproject_hooks-1.2.0-py3-none-any.whl", hash = "sha256:9e5c6bfa8dcc30091c74b0cf803c81fdd29d94f01992a7707bc97babb1141913", size = 10216, upload-time = "2024-09-29T09:24:11.978Z" }, +] + +[[package]] +name = "pytest" +version = "9.0.2" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "colorama", marker = "sys_platform == 'win32'" }, + { name = "iniconfig" }, + { name = "packaging" }, + { name = "pluggy" }, + { name = "pygments" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/d1/db/7ef3487e0fb0049ddb5ce41d3a49c235bf9ad299b6a25d5780a89f19230f/pytest-9.0.2.tar.gz", hash = "sha256:75186651a92bd89611d1d9fc20f0b4345fd827c41ccd5c299a868a05d70edf11", size = 1568901, upload-time = "2025-12-06T21:30:51.014Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/3b/ab/b3226f0bd7cdcf710fbede2b3548584366da3b19b5021e74f5bde2a8fa3f/pytest-9.0.2-py3-none-any.whl", hash = "sha256:711ffd45bf766d5264d487b917733b453d917afd2b0ad65223959f59089f875b", size = 374801, upload-time = "2025-12-06T21:30:49.154Z" }, +] + +[[package]] +name = "python-dateutil" +version = "2.9.0.post0" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "six" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/66/c0/0c8b6ad9f17a802ee498c46e004a0eb49bc148f2fd230864601a86dcf6db/python-dateutil-2.9.0.post0.tar.gz", hash = "sha256:37dd54208da7e1cd875388217d5e00ebd4179249f90fb72437e91a35459a0ad3", size = 342432, upload-time = "2024-03-01T18:36:20.211Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/ec/57/56b9bcc3c9c6a792fcbaf139543cee77261f3651ca9da0c93f5c1221264b/python_dateutil-2.9.0.post0-py2.py3-none-any.whl", hash = "sha256:a8b2bc7bffae282281c8140a97d3aa9c14da0b136dfe83f850eea9a5f7470427", size = 229892, upload-time = "2024-03-01T18:36:18.57Z" }, +] + +[[package]] +name = "python-igraph" +version = "1.0.0" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "igraph" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/2b/b6/3c1476ec6bf06348ecea1d76af6c6b3a024dddbcd2de120d3a0de1eab29b/python_igraph-1.0.0.tar.gz", hash = "sha256:6da7ac4e9f6a9cf03734798bed6fb082bb9274f2ae288f6099121f0332803018", size = 9726, upload-time = "2025-10-23T12:28:36.266Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/31/5f/567fa047076d32d321bdafa248905a7186d2acee4916b046b11417af10d9/python_igraph-1.0.0-py3-none-any.whl", hash = "sha256:b0bb8d91cce2a1e0550fe45f9ec925bcd04152dfb5be3fa822b9f5f36eb3f380", size = 9157, upload-time = "2025-10-23T12:28:33.515Z" }, +] + +[[package]] +name = "pytz" +version = "2025.2" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/f8/bf/abbd3cdfb8fbc7fb3d4d38d320f2441b1e7cbe29be4f23797b4a2b5d8aac/pytz-2025.2.tar.gz", hash = "sha256:360b9e3dbb49a209c21ad61809c7fb453643e048b38924c765813546746e81c3", size = 320884, upload-time = "2025-03-25T02:25:00.538Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/81/c4/34e93fe5f5429d7570ec1fa436f1986fb1f00c3e0f43a589fe2bbcd22c3f/pytz-2025.2-py2.py3-none-any.whl", hash = "sha256:5ddf76296dd8c44c26eb8f4b6f35488f3ccbf6fbbd7adee0b7262d43f0ec2f00", size = 509225, upload-time = "2025-03-25T02:24:58.468Z" }, +] + +[[package]] +name = "pywin32" +version = "311" +source = { registry = "https://pypi.org/simple" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/7c/af/449a6a91e5d6db51420875c54f6aff7c97a86a3b13a0b4f1a5c13b988de3/pywin32-311-cp311-cp311-win32.whl", hash = "sha256:184eb5e436dea364dcd3d2316d577d625c0351bf237c4e9a5fabbcfa5a58b151", size = 8697031, upload-time = "2025-07-14T20:13:13.266Z" }, + { url = "https://files.pythonhosted.org/packages/51/8f/9bb81dd5bb77d22243d33c8397f09377056d5c687aa6d4042bea7fbf8364/pywin32-311-cp311-cp311-win_amd64.whl", hash = "sha256:3ce80b34b22b17ccbd937a6e78e7225d80c52f5ab9940fe0506a1a16f3dab503", size = 9508308, upload-time = "2025-07-14T20:13:15.147Z" }, + { url = "https://files.pythonhosted.org/packages/44/7b/9c2ab54f74a138c491aba1b1cd0795ba61f144c711daea84a88b63dc0f6c/pywin32-311-cp311-cp311-win_arm64.whl", hash = "sha256:a733f1388e1a842abb67ffa8e7aad0e70ac519e09b0f6a784e65a136ec7cefd2", size = 8703930, upload-time = "2025-07-14T20:13:16.945Z" }, + { url = "https://files.pythonhosted.org/packages/e7/ab/01ea1943d4eba0f850c3c61e78e8dd59757ff815ff3ccd0a84de5f541f42/pywin32-311-cp312-cp312-win32.whl", hash = "sha256:750ec6e621af2b948540032557b10a2d43b0cee2ae9758c54154d711cc852d31", size = 8706543, upload-time = "2025-07-14T20:13:20.765Z" }, + { url = "https://files.pythonhosted.org/packages/d1/a8/a0e8d07d4d051ec7502cd58b291ec98dcc0c3fff027caad0470b72cfcc2f/pywin32-311-cp312-cp312-win_amd64.whl", hash = "sha256:b8c095edad5c211ff31c05223658e71bf7116daa0ecf3ad85f3201ea3190d067", size = 9495040, upload-time = "2025-07-14T20:13:22.543Z" }, + { url = "https://files.pythonhosted.org/packages/ba/3a/2ae996277b4b50f17d61f0603efd8253cb2d79cc7ae159468007b586396d/pywin32-311-cp312-cp312-win_arm64.whl", hash = "sha256:e286f46a9a39c4a18b319c28f59b61de793654af2f395c102b4f819e584b5852", size = 8710102, upload-time = "2025-07-14T20:13:24.682Z" }, + { url = "https://files.pythonhosted.org/packages/a5/be/3fd5de0979fcb3994bfee0d65ed8ca9506a8a1260651b86174f6a86f52b3/pywin32-311-cp313-cp313-win32.whl", hash = "sha256:f95ba5a847cba10dd8c4d8fefa9f2a6cf283b8b88ed6178fa8a6c1ab16054d0d", size = 8705700, upload-time = "2025-07-14T20:13:26.471Z" }, + { url = "https://files.pythonhosted.org/packages/e3/28/e0a1909523c6890208295a29e05c2adb2126364e289826c0a8bc7297bd5c/pywin32-311-cp313-cp313-win_amd64.whl", hash = "sha256:718a38f7e5b058e76aee1c56ddd06908116d35147e133427e59a3983f703a20d", size = 9494700, upload-time = "2025-07-14T20:13:28.243Z" }, + { url = "https://files.pythonhosted.org/packages/04/bf/90339ac0f55726dce7d794e6d79a18a91265bdf3aa70b6b9ca52f35e022a/pywin32-311-cp313-cp313-win_arm64.whl", hash = "sha256:7b4075d959648406202d92a2310cb990fea19b535c7f4a78d3f5e10b926eeb8a", size = 8709318, upload-time = "2025-07-14T20:13:30.348Z" }, + { url = "https://files.pythonhosted.org/packages/c9/31/097f2e132c4f16d99a22bfb777e0fd88bd8e1c634304e102f313af69ace5/pywin32-311-cp314-cp314-win32.whl", hash = "sha256:b7a2c10b93f8986666d0c803ee19b5990885872a7de910fc460f9b0c2fbf92ee", size = 8840714, upload-time = "2025-07-14T20:13:32.449Z" }, + { url = "https://files.pythonhosted.org/packages/90/4b/07c77d8ba0e01349358082713400435347df8426208171ce297da32c313d/pywin32-311-cp314-cp314-win_amd64.whl", hash = "sha256:3aca44c046bd2ed8c90de9cb8427f581c479e594e99b5c0bb19b29c10fd6cb87", size = 9656800, upload-time = "2025-07-14T20:13:34.312Z" }, + { url = "https://files.pythonhosted.org/packages/c0/d2/21af5c535501a7233e734b8af901574572da66fcc254cb35d0609c9080dd/pywin32-311-cp314-cp314-win_arm64.whl", hash = "sha256:a508e2d9025764a8270f93111a970e1d0fbfc33f4153b388bb649b7eec4f9b42", size = 8932540, upload-time = "2025-07-14T20:13:36.379Z" }, +] + +[[package]] +name = "pywin32-ctypes" +version = "0.2.3" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/85/9f/01a1a99704853cb63f253eea009390c88e7131c67e66a0a02099a8c917cb/pywin32-ctypes-0.2.3.tar.gz", hash = "sha256:d162dc04946d704503b2edc4d55f3dba5c1d539ead017afa00142c38b9885755", size = 29471, upload-time = "2024-08-14T10:15:34.626Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/de/3d/8161f7711c017e01ac9f008dfddd9410dff3674334c233bde66e7ba65bbf/pywin32_ctypes-0.2.3-py3-none-any.whl", hash = "sha256:8a1513379d709975552d202d942d9837758905c8d01eb82b8bcc30918929e7b8", size = 30756, upload-time = "2024-08-14T10:15:33.187Z" }, +] + +[[package]] +name = "pyyaml" +version = "6.0.3" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/05/8e/961c0007c59b8dd7729d542c61a4d537767a59645b82a0b521206e1e25c2/pyyaml-6.0.3.tar.gz", hash = "sha256:d76623373421df22fb4cf8817020cbb7ef15c725b9d5e45f17e189bfc384190f", size = 130960, upload-time = "2025-09-25T21:33:16.546Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/6d/16/a95b6757765b7b031c9374925bb718d55e0a9ba8a1b6a12d25962ea44347/pyyaml-6.0.3-cp311-cp311-macosx_10_13_x86_64.whl", hash = "sha256:44edc647873928551a01e7a563d7452ccdebee747728c1080d881d68af7b997e", size = 185826, upload-time = "2025-09-25T21:31:58.655Z" }, + { url = "https://files.pythonhosted.org/packages/16/19/13de8e4377ed53079ee996e1ab0a9c33ec2faf808a4647b7b4c0d46dd239/pyyaml-6.0.3-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:652cb6edd41e718550aad172851962662ff2681490a8a711af6a4d288dd96824", size = 175577, upload-time = "2025-09-25T21:32:00.088Z" }, + { url = "https://files.pythonhosted.org/packages/0c/62/d2eb46264d4b157dae1275b573017abec435397aa59cbcdab6fc978a8af4/pyyaml-6.0.3-cp311-cp311-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:10892704fc220243f5305762e276552a0395f7beb4dbf9b14ec8fd43b57f126c", size = 775556, upload-time = "2025-09-25T21:32:01.31Z" }, + { url = "https://files.pythonhosted.org/packages/10/cb/16c3f2cf3266edd25aaa00d6c4350381c8b012ed6f5276675b9eba8d9ff4/pyyaml-6.0.3-cp311-cp311-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:850774a7879607d3a6f50d36d04f00ee69e7fc816450e5f7e58d7f17f1ae5c00", size = 882114, upload-time = "2025-09-25T21:32:03.376Z" }, + { url = "https://files.pythonhosted.org/packages/71/60/917329f640924b18ff085ab889a11c763e0b573da888e8404ff486657602/pyyaml-6.0.3-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:b8bb0864c5a28024fac8a632c443c87c5aa6f215c0b126c449ae1a150412f31d", size = 806638, upload-time = "2025-09-25T21:32:04.553Z" }, + { url = "https://files.pythonhosted.org/packages/dd/6f/529b0f316a9fd167281a6c3826b5583e6192dba792dd55e3203d3f8e655a/pyyaml-6.0.3-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:1d37d57ad971609cf3c53ba6a7e365e40660e3be0e5175fa9f2365a379d6095a", size = 767463, upload-time = "2025-09-25T21:32:06.152Z" }, + { url = "https://files.pythonhosted.org/packages/f2/6a/b627b4e0c1dd03718543519ffb2f1deea4a1e6d42fbab8021936a4d22589/pyyaml-6.0.3-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:37503bfbfc9d2c40b344d06b2199cf0e96e97957ab1c1b546fd4f87e53e5d3e4", size = 794986, upload-time = "2025-09-25T21:32:07.367Z" }, + { url = "https://files.pythonhosted.org/packages/45/91/47a6e1c42d9ee337c4839208f30d9f09caa9f720ec7582917b264defc875/pyyaml-6.0.3-cp311-cp311-win32.whl", hash = "sha256:8098f252adfa6c80ab48096053f512f2321f0b998f98150cea9bd23d83e1467b", size = 142543, upload-time = "2025-09-25T21:32:08.95Z" }, + { url = "https://files.pythonhosted.org/packages/da/e3/ea007450a105ae919a72393cb06f122f288ef60bba2dc64b26e2646fa315/pyyaml-6.0.3-cp311-cp311-win_amd64.whl", hash = "sha256:9f3bfb4965eb874431221a3ff3fdcddc7e74e3b07799e0e84ca4a0f867d449bf", size = 158763, upload-time = "2025-09-25T21:32:09.96Z" }, + { url = "https://files.pythonhosted.org/packages/d1/33/422b98d2195232ca1826284a76852ad5a86fe23e31b009c9886b2d0fb8b2/pyyaml-6.0.3-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:7f047e29dcae44602496db43be01ad42fc6f1cc0d8cd6c83d342306c32270196", size = 182063, upload-time = "2025-09-25T21:32:11.445Z" }, + { url = "https://files.pythonhosted.org/packages/89/a0/6cf41a19a1f2f3feab0e9c0b74134aa2ce6849093d5517a0c550fe37a648/pyyaml-6.0.3-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:fc09d0aa354569bc501d4e787133afc08552722d3ab34836a80547331bb5d4a0", size = 173973, upload-time = "2025-09-25T21:32:12.492Z" }, + { url = "https://files.pythonhosted.org/packages/ed/23/7a778b6bd0b9a8039df8b1b1d80e2e2ad78aa04171592c8a5c43a56a6af4/pyyaml-6.0.3-cp312-cp312-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:9149cad251584d5fb4981be1ecde53a1ca46c891a79788c0df828d2f166bda28", size = 775116, upload-time = "2025-09-25T21:32:13.652Z" }, + { url = "https://files.pythonhosted.org/packages/65/30/d7353c338e12baef4ecc1b09e877c1970bd3382789c159b4f89d6a70dc09/pyyaml-6.0.3-cp312-cp312-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:5fdec68f91a0c6739b380c83b951e2c72ac0197ace422360e6d5a959d8d97b2c", size = 844011, upload-time = "2025-09-25T21:32:15.21Z" }, + { url = "https://files.pythonhosted.org/packages/8b/9d/b3589d3877982d4f2329302ef98a8026e7f4443c765c46cfecc8858c6b4b/pyyaml-6.0.3-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:ba1cc08a7ccde2d2ec775841541641e4548226580ab850948cbfda66a1befcdc", size = 807870, upload-time = "2025-09-25T21:32:16.431Z" }, + { url = "https://files.pythonhosted.org/packages/05/c0/b3be26a015601b822b97d9149ff8cb5ead58c66f981e04fedf4e762f4bd4/pyyaml-6.0.3-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:8dc52c23056b9ddd46818a57b78404882310fb473d63f17b07d5c40421e47f8e", size = 761089, upload-time = "2025-09-25T21:32:17.56Z" }, + { url = "https://files.pythonhosted.org/packages/be/8e/98435a21d1d4b46590d5459a22d88128103f8da4c2d4cb8f14f2a96504e1/pyyaml-6.0.3-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:41715c910c881bc081f1e8872880d3c650acf13dfa8214bad49ed4cede7c34ea", size = 790181, upload-time = "2025-09-25T21:32:18.834Z" }, + { url = "https://files.pythonhosted.org/packages/74/93/7baea19427dcfbe1e5a372d81473250b379f04b1bd3c4c5ff825e2327202/pyyaml-6.0.3-cp312-cp312-win32.whl", hash = "sha256:96b533f0e99f6579b3d4d4995707cf36df9100d67e0c8303a0c55b27b5f99bc5", size = 137658, upload-time = "2025-09-25T21:32:20.209Z" }, + { url = "https://files.pythonhosted.org/packages/86/bf/899e81e4cce32febab4fb42bb97dcdf66bc135272882d1987881a4b519e9/pyyaml-6.0.3-cp312-cp312-win_amd64.whl", hash = "sha256:5fcd34e47f6e0b794d17de1b4ff496c00986e1c83f7ab2fb8fcfe9616ff7477b", size = 154003, upload-time = "2025-09-25T21:32:21.167Z" }, + { url = "https://files.pythonhosted.org/packages/1a/08/67bd04656199bbb51dbed1439b7f27601dfb576fb864099c7ef0c3e55531/pyyaml-6.0.3-cp312-cp312-win_arm64.whl", hash = "sha256:64386e5e707d03a7e172c0701abfb7e10f0fb753ee1d773128192742712a98fd", size = 140344, upload-time = "2025-09-25T21:32:22.617Z" }, + { url = "https://files.pythonhosted.org/packages/d1/11/0fd08f8192109f7169db964b5707a2f1e8b745d4e239b784a5a1dd80d1db/pyyaml-6.0.3-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:8da9669d359f02c0b91ccc01cac4a67f16afec0dac22c2ad09f46bee0697eba8", size = 181669, upload-time = "2025-09-25T21:32:23.673Z" }, + { url = "https://files.pythonhosted.org/packages/b1/16/95309993f1d3748cd644e02e38b75d50cbc0d9561d21f390a76242ce073f/pyyaml-6.0.3-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:2283a07e2c21a2aa78d9c4442724ec1eb15f5e42a723b99cb3d822d48f5f7ad1", size = 173252, upload-time = "2025-09-25T21:32:25.149Z" }, + { url = "https://files.pythonhosted.org/packages/50/31/b20f376d3f810b9b2371e72ef5adb33879b25edb7a6d072cb7ca0c486398/pyyaml-6.0.3-cp313-cp313-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:ee2922902c45ae8ccada2c5b501ab86c36525b883eff4255313a253a3160861c", size = 767081, upload-time = "2025-09-25T21:32:26.575Z" }, + { url = "https://files.pythonhosted.org/packages/49/1e/a55ca81e949270d5d4432fbbd19dfea5321eda7c41a849d443dc92fd1ff7/pyyaml-6.0.3-cp313-cp313-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:a33284e20b78bd4a18c8c2282d549d10bc8408a2a7ff57653c0cf0b9be0afce5", size = 841159, upload-time = "2025-09-25T21:32:27.727Z" }, + { url = "https://files.pythonhosted.org/packages/74/27/e5b8f34d02d9995b80abcef563ea1f8b56d20134d8f4e5e81733b1feceb2/pyyaml-6.0.3-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:0f29edc409a6392443abf94b9cf89ce99889a1dd5376d94316ae5145dfedd5d6", size = 801626, upload-time = "2025-09-25T21:32:28.878Z" }, + { url = "https://files.pythonhosted.org/packages/f9/11/ba845c23988798f40e52ba45f34849aa8a1f2d4af4b798588010792ebad6/pyyaml-6.0.3-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:f7057c9a337546edc7973c0d3ba84ddcdf0daa14533c2065749c9075001090e6", size = 753613, upload-time = "2025-09-25T21:32:30.178Z" }, + { url = "https://files.pythonhosted.org/packages/3d/e0/7966e1a7bfc0a45bf0a7fb6b98ea03fc9b8d84fa7f2229e9659680b69ee3/pyyaml-6.0.3-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:eda16858a3cab07b80edaf74336ece1f986ba330fdb8ee0d6c0d68fe82bc96be", size = 794115, upload-time = "2025-09-25T21:32:31.353Z" }, + { url = "https://files.pythonhosted.org/packages/de/94/980b50a6531b3019e45ddeada0626d45fa85cbe22300844a7983285bed3b/pyyaml-6.0.3-cp313-cp313-win32.whl", hash = "sha256:d0eae10f8159e8fdad514efdc92d74fd8d682c933a6dd088030f3834bc8e6b26", size = 137427, upload-time = "2025-09-25T21:32:32.58Z" }, + { url = "https://files.pythonhosted.org/packages/97/c9/39d5b874e8b28845e4ec2202b5da735d0199dbe5b8fb85f91398814a9a46/pyyaml-6.0.3-cp313-cp313-win_amd64.whl", hash = "sha256:79005a0d97d5ddabfeeea4cf676af11e647e41d81c9a7722a193022accdb6b7c", size = 154090, upload-time = "2025-09-25T21:32:33.659Z" }, + { url = "https://files.pythonhosted.org/packages/73/e8/2bdf3ca2090f68bb3d75b44da7bbc71843b19c9f2b9cb9b0f4ab7a5a4329/pyyaml-6.0.3-cp313-cp313-win_arm64.whl", hash = "sha256:5498cd1645aa724a7c71c8f378eb29ebe23da2fc0d7a08071d89469bf1d2defb", size = 140246, upload-time = "2025-09-25T21:32:34.663Z" }, + { url = "https://files.pythonhosted.org/packages/9d/8c/f4bd7f6465179953d3ac9bc44ac1a8a3e6122cf8ada906b4f96c60172d43/pyyaml-6.0.3-cp314-cp314-macosx_10_13_x86_64.whl", hash = "sha256:8d1fab6bb153a416f9aeb4b8763bc0f22a5586065f86f7664fc23339fc1c1fac", size = 181814, upload-time = "2025-09-25T21:32:35.712Z" }, + { url = "https://files.pythonhosted.org/packages/bd/9c/4d95bb87eb2063d20db7b60faa3840c1b18025517ae857371c4dd55a6b3a/pyyaml-6.0.3-cp314-cp314-macosx_11_0_arm64.whl", hash = "sha256:34d5fcd24b8445fadc33f9cf348c1047101756fd760b4dacb5c3e99755703310", size = 173809, upload-time = "2025-09-25T21:32:36.789Z" }, + { url = "https://files.pythonhosted.org/packages/92/b5/47e807c2623074914e29dabd16cbbdd4bf5e9b2db9f8090fa64411fc5382/pyyaml-6.0.3-cp314-cp314-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:501a031947e3a9025ed4405a168e6ef5ae3126c59f90ce0cd6f2bfc477be31b7", size = 766454, upload-time = "2025-09-25T21:32:37.966Z" }, + { url = "https://files.pythonhosted.org/packages/02/9e/e5e9b168be58564121efb3de6859c452fccde0ab093d8438905899a3a483/pyyaml-6.0.3-cp314-cp314-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:b3bc83488de33889877a0f2543ade9f70c67d66d9ebb4ac959502e12de895788", size = 836355, upload-time = "2025-09-25T21:32:39.178Z" }, + { url = "https://files.pythonhosted.org/packages/88/f9/16491d7ed2a919954993e48aa941b200f38040928474c9e85ea9e64222c3/pyyaml-6.0.3-cp314-cp314-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:c458b6d084f9b935061bc36216e8a69a7e293a2f1e68bf956dcd9e6cbcd143f5", size = 794175, upload-time = "2025-09-25T21:32:40.865Z" }, + { url = "https://files.pythonhosted.org/packages/dd/3f/5989debef34dc6397317802b527dbbafb2b4760878a53d4166579111411e/pyyaml-6.0.3-cp314-cp314-musllinux_1_2_aarch64.whl", hash = "sha256:7c6610def4f163542a622a73fb39f534f8c101d690126992300bf3207eab9764", size = 755228, upload-time = "2025-09-25T21:32:42.084Z" }, + { url = "https://files.pythonhosted.org/packages/d7/ce/af88a49043cd2e265be63d083fc75b27b6ed062f5f9fd6cdc223ad62f03e/pyyaml-6.0.3-cp314-cp314-musllinux_1_2_x86_64.whl", hash = "sha256:5190d403f121660ce8d1d2c1bb2ef1bd05b5f68533fc5c2ea899bd15f4399b35", size = 789194, upload-time = "2025-09-25T21:32:43.362Z" }, + { url = "https://files.pythonhosted.org/packages/23/20/bb6982b26a40bb43951265ba29d4c246ef0ff59c9fdcdf0ed04e0687de4d/pyyaml-6.0.3-cp314-cp314-win_amd64.whl", hash = "sha256:4a2e8cebe2ff6ab7d1050ecd59c25d4c8bd7e6f400f5f82b96557ac0abafd0ac", size = 156429, upload-time = "2025-09-25T21:32:57.844Z" }, + { url = "https://files.pythonhosted.org/packages/f4/f4/a4541072bb9422c8a883ab55255f918fa378ecf083f5b85e87fc2b4eda1b/pyyaml-6.0.3-cp314-cp314-win_arm64.whl", hash = "sha256:93dda82c9c22deb0a405ea4dc5f2d0cda384168e466364dec6255b293923b2f3", size = 143912, upload-time = "2025-09-25T21:32:59.247Z" }, + { url = "https://files.pythonhosted.org/packages/7c/f9/07dd09ae774e4616edf6cda684ee78f97777bdd15847253637a6f052a62f/pyyaml-6.0.3-cp314-cp314t-macosx_10_13_x86_64.whl", hash = "sha256:02893d100e99e03eda1c8fd5c441d8c60103fd175728e23e431db1b589cf5ab3", size = 189108, upload-time = "2025-09-25T21:32:44.377Z" }, + { url = "https://files.pythonhosted.org/packages/4e/78/8d08c9fb7ce09ad8c38ad533c1191cf27f7ae1effe5bb9400a46d9437fcf/pyyaml-6.0.3-cp314-cp314t-macosx_11_0_arm64.whl", hash = "sha256:c1ff362665ae507275af2853520967820d9124984e0f7466736aea23d8611fba", size = 183641, upload-time = "2025-09-25T21:32:45.407Z" }, + { url = "https://files.pythonhosted.org/packages/7b/5b/3babb19104a46945cf816d047db2788bcaf8c94527a805610b0289a01c6b/pyyaml-6.0.3-cp314-cp314t-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:6adc77889b628398debc7b65c073bcb99c4a0237b248cacaf3fe8a557563ef6c", size = 831901, upload-time = "2025-09-25T21:32:48.83Z" }, + { url = "https://files.pythonhosted.org/packages/8b/cc/dff0684d8dc44da4d22a13f35f073d558c268780ce3c6ba1b87055bb0b87/pyyaml-6.0.3-cp314-cp314t-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:a80cb027f6b349846a3bf6d73b5e95e782175e52f22108cfa17876aaeff93702", size = 861132, upload-time = "2025-09-25T21:32:50.149Z" }, + { url = "https://files.pythonhosted.org/packages/b1/5e/f77dc6b9036943e285ba76b49e118d9ea929885becb0a29ba8a7c75e29fe/pyyaml-6.0.3-cp314-cp314t-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:00c4bdeba853cc34e7dd471f16b4114f4162dc03e6b7afcc2128711f0eca823c", size = 839261, upload-time = "2025-09-25T21:32:51.808Z" }, + { url = "https://files.pythonhosted.org/packages/ce/88/a9db1376aa2a228197c58b37302f284b5617f56a5d959fd1763fb1675ce6/pyyaml-6.0.3-cp314-cp314t-musllinux_1_2_aarch64.whl", hash = "sha256:66e1674c3ef6f541c35191caae2d429b967b99e02040f5ba928632d9a7f0f065", size = 805272, upload-time = "2025-09-25T21:32:52.941Z" }, + { url = "https://files.pythonhosted.org/packages/da/92/1446574745d74df0c92e6aa4a7b0b3130706a4142b2d1a5869f2eaa423c6/pyyaml-6.0.3-cp314-cp314t-musllinux_1_2_x86_64.whl", hash = "sha256:16249ee61e95f858e83976573de0f5b2893b3677ba71c9dd36b9cf8be9ac6d65", size = 829923, upload-time = "2025-09-25T21:32:54.537Z" }, + { url = "https://files.pythonhosted.org/packages/f0/7a/1c7270340330e575b92f397352af856a8c06f230aa3e76f86b39d01b416a/pyyaml-6.0.3-cp314-cp314t-win_amd64.whl", hash = "sha256:4ad1906908f2f5ae4e5a8ddfce73c320c2a1429ec52eafd27138b7f1cbe341c9", size = 174062, upload-time = "2025-09-25T21:32:55.767Z" }, + { url = "https://files.pythonhosted.org/packages/f1/12/de94a39c2ef588c7e6455cfbe7343d3b2dc9d6b6b2f40c4c6565744c873d/pyyaml-6.0.3-cp314-cp314t-win_arm64.whl", hash = "sha256:ebc55a14a21cb14062aa4162f906cd962b28e2e9ea38f9b4391244cd8de4ae0b", size = 149341, upload-time = "2025-09-25T21:32:56.828Z" }, +] + +[[package]] +name = "pyzmq" +version = "27.1.0" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "cffi", marker = "implementation_name == 'pypy'" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/04/0b/3c9baedbdf613ecaa7aa07027780b8867f57b6293b6ee50de316c9f3222b/pyzmq-27.1.0.tar.gz", hash = "sha256:ac0765e3d44455adb6ddbf4417dcce460fc40a05978c08efdf2948072f6db540", size = 281750, upload-time = "2025-09-08T23:10:18.157Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/06/5d/305323ba86b284e6fcb0d842d6adaa2999035f70f8c38a9b6d21ad28c3d4/pyzmq-27.1.0-cp311-cp311-macosx_10_15_universal2.whl", hash = "sha256:226b091818d461a3bef763805e75685e478ac17e9008f49fce2d3e52b3d58b86", size = 1333328, upload-time = "2025-09-08T23:07:45.946Z" }, + { url = "https://files.pythonhosted.org/packages/bd/a0/fc7e78a23748ad5443ac3275943457e8452da67fda347e05260261108cbc/pyzmq-27.1.0-cp311-cp311-manylinux2014_i686.manylinux_2_17_i686.whl", hash = "sha256:0790a0161c281ca9723f804871b4027f2e8b5a528d357c8952d08cd1a9c15581", size = 908803, upload-time = "2025-09-08T23:07:47.551Z" }, + { url = "https://files.pythonhosted.org/packages/7e/22/37d15eb05f3bdfa4abea6f6d96eb3bb58585fbd3e4e0ded4e743bc650c97/pyzmq-27.1.0-cp311-cp311-manylinux_2_26_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:c895a6f35476b0c3a54e3eb6ccf41bf3018de937016e6e18748317f25d4e925f", size = 668836, upload-time = "2025-09-08T23:07:49.436Z" }, + { url = "https://files.pythonhosted.org/packages/b1/c4/2a6fe5111a01005fc7af3878259ce17684fabb8852815eda6225620f3c59/pyzmq-27.1.0-cp311-cp311-manylinux_2_26_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:5bbf8d3630bf96550b3be8e1fc0fea5cbdc8d5466c1192887bd94869da17a63e", size = 857038, upload-time = "2025-09-08T23:07:51.234Z" }, + { url = "https://files.pythonhosted.org/packages/cb/eb/bfdcb41d0db9cd233d6fb22dc131583774135505ada800ebf14dfb0a7c40/pyzmq-27.1.0-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:15c8bd0fe0dabf808e2d7a681398c4e5ded70a551ab47482067a572c054c8e2e", size = 1657531, upload-time = "2025-09-08T23:07:52.795Z" }, + { url = "https://files.pythonhosted.org/packages/ab/21/e3180ca269ed4a0de5c34417dfe71a8ae80421198be83ee619a8a485b0c7/pyzmq-27.1.0-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:bafcb3dd171b4ae9f19ee6380dfc71ce0390fefaf26b504c0e5f628d7c8c54f2", size = 2034786, upload-time = "2025-09-08T23:07:55.047Z" }, + { url = "https://files.pythonhosted.org/packages/3b/b1/5e21d0b517434b7f33588ff76c177c5a167858cc38ef740608898cd329f2/pyzmq-27.1.0-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:e829529fcaa09937189178115c49c504e69289abd39967cd8a4c215761373394", size = 1894220, upload-time = "2025-09-08T23:07:57.172Z" }, + { url = "https://files.pythonhosted.org/packages/03/f2/44913a6ff6941905efc24a1acf3d3cb6146b636c546c7406c38c49c403d4/pyzmq-27.1.0-cp311-cp311-win32.whl", hash = "sha256:6df079c47d5902af6db298ec92151db82ecb557af663098b92f2508c398bb54f", size = 567155, upload-time = "2025-09-08T23:07:59.05Z" }, + { url = "https://files.pythonhosted.org/packages/23/6d/d8d92a0eb270a925c9b4dd039c0b4dc10abc2fcbc48331788824ef113935/pyzmq-27.1.0-cp311-cp311-win_amd64.whl", hash = "sha256:190cbf120fbc0fc4957b56866830def56628934a9d112aec0e2507aa6a032b97", size = 633428, upload-time = "2025-09-08T23:08:00.663Z" }, + { url = "https://files.pythonhosted.org/packages/ae/14/01afebc96c5abbbd713ecfc7469cfb1bc801c819a74ed5c9fad9a48801cb/pyzmq-27.1.0-cp311-cp311-win_arm64.whl", hash = "sha256:eca6b47df11a132d1745eb3b5b5e557a7dae2c303277aa0e69c6ba91b8736e07", size = 559497, upload-time = "2025-09-08T23:08:02.15Z" }, + { url = "https://files.pythonhosted.org/packages/92/e7/038aab64a946d535901103da16b953c8c9cc9c961dadcbf3609ed6428d23/pyzmq-27.1.0-cp312-abi3-macosx_10_15_universal2.whl", hash = "sha256:452631b640340c928fa343801b0d07eb0c3789a5ffa843f6e1a9cee0ba4eb4fc", size = 1306279, upload-time = "2025-09-08T23:08:03.807Z" }, + { url = "https://files.pythonhosted.org/packages/e8/5e/c3c49fdd0f535ef45eefcc16934648e9e59dace4a37ee88fc53f6cd8e641/pyzmq-27.1.0-cp312-abi3-manylinux2014_i686.manylinux_2_17_i686.whl", hash = "sha256:1c179799b118e554b66da67d88ed66cd37a169f1f23b5d9f0a231b4e8d44a113", size = 895645, upload-time = "2025-09-08T23:08:05.301Z" }, + { url = "https://files.pythonhosted.org/packages/f8/e5/b0b2504cb4e903a74dcf1ebae157f9e20ebb6ea76095f6cfffea28c42ecd/pyzmq-27.1.0-cp312-abi3-manylinux_2_26_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:3837439b7f99e60312f0c926a6ad437b067356dc2bc2ec96eb395fd0fe804233", size = 652574, upload-time = "2025-09-08T23:08:06.828Z" }, + { url = "https://files.pythonhosted.org/packages/f8/9b/c108cdb55560eaf253f0cbdb61b29971e9fb34d9c3499b0e96e4e60ed8a5/pyzmq-27.1.0-cp312-abi3-manylinux_2_26_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:43ad9a73e3da1fab5b0e7e13402f0b2fb934ae1c876c51d0afff0e7c052eca31", size = 840995, upload-time = "2025-09-08T23:08:08.396Z" }, + { url = "https://files.pythonhosted.org/packages/c2/bb/b79798ca177b9eb0825b4c9998c6af8cd2a7f15a6a1a4272c1d1a21d382f/pyzmq-27.1.0-cp312-abi3-musllinux_1_2_aarch64.whl", hash = "sha256:0de3028d69d4cdc475bfe47a6128eb38d8bc0e8f4d69646adfbcd840facbac28", size = 1642070, upload-time = "2025-09-08T23:08:09.989Z" }, + { url = "https://files.pythonhosted.org/packages/9c/80/2df2e7977c4ede24c79ae39dcef3899bfc5f34d1ca7a5b24f182c9b7a9ca/pyzmq-27.1.0-cp312-abi3-musllinux_1_2_i686.whl", hash = "sha256:cf44a7763aea9298c0aa7dbf859f87ed7012de8bda0f3977b6fb1d96745df856", size = 2021121, upload-time = "2025-09-08T23:08:11.907Z" }, + { url = "https://files.pythonhosted.org/packages/46/bd/2d45ad24f5f5ae7e8d01525eb76786fa7557136555cac7d929880519e33a/pyzmq-27.1.0-cp312-abi3-musllinux_1_2_x86_64.whl", hash = "sha256:f30f395a9e6fbca195400ce833c731e7b64c3919aa481af4d88c3759e0cb7496", size = 1878550, upload-time = "2025-09-08T23:08:13.513Z" }, + { url = "https://files.pythonhosted.org/packages/e6/2f/104c0a3c778d7c2ab8190e9db4f62f0b6957b53c9d87db77c284b69f33ea/pyzmq-27.1.0-cp312-abi3-win32.whl", hash = "sha256:250e5436a4ba13885494412b3da5d518cd0d3a278a1ae640e113c073a5f88edd", size = 559184, upload-time = "2025-09-08T23:08:15.163Z" }, + { url = "https://files.pythonhosted.org/packages/fc/7f/a21b20d577e4100c6a41795842028235998a643b1ad406a6d4163ea8f53e/pyzmq-27.1.0-cp312-abi3-win_amd64.whl", hash = "sha256:9ce490cf1d2ca2ad84733aa1d69ce6855372cb5ce9223802450c9b2a7cba0ccf", size = 619480, upload-time = "2025-09-08T23:08:17.192Z" }, + { url = "https://files.pythonhosted.org/packages/78/c2/c012beae5f76b72f007a9e91ee9401cb88c51d0f83c6257a03e785c81cc2/pyzmq-27.1.0-cp312-abi3-win_arm64.whl", hash = "sha256:75a2f36223f0d535a0c919e23615fc85a1e23b71f40c7eb43d7b1dedb4d8f15f", size = 552993, upload-time = "2025-09-08T23:08:18.926Z" }, + { url = "https://files.pythonhosted.org/packages/60/cb/84a13459c51da6cec1b7b1dc1a47e6db6da50b77ad7fd9c145842750a011/pyzmq-27.1.0-cp313-cp313-android_24_arm64_v8a.whl", hash = "sha256:93ad4b0855a664229559e45c8d23797ceac03183c7b6f5b4428152a6b06684a5", size = 1122436, upload-time = "2025-09-08T23:08:20.801Z" }, + { url = "https://files.pythonhosted.org/packages/dc/b6/94414759a69a26c3dd674570a81813c46a078767d931a6c70ad29fc585cb/pyzmq-27.1.0-cp313-cp313-android_24_x86_64.whl", hash = "sha256:fbb4f2400bfda24f12f009cba62ad5734148569ff4949b1b6ec3b519444342e6", size = 1156301, upload-time = "2025-09-08T23:08:22.47Z" }, + { url = "https://files.pythonhosted.org/packages/a5/ad/15906493fd40c316377fd8a8f6b1f93104f97a752667763c9b9c1b71d42d/pyzmq-27.1.0-cp313-cp313t-macosx_10_15_universal2.whl", hash = "sha256:e343d067f7b151cfe4eb3bb796a7752c9d369eed007b91231e817071d2c2fec7", size = 1341197, upload-time = "2025-09-08T23:08:24.286Z" }, + { url = "https://files.pythonhosted.org/packages/14/1d/d343f3ce13db53a54cb8946594e567410b2125394dafcc0268d8dda027e0/pyzmq-27.1.0-cp313-cp313t-manylinux2014_i686.manylinux_2_17_i686.whl", hash = "sha256:08363b2011dec81c354d694bdecaef4770e0ae96b9afea70b3f47b973655cc05", size = 897275, upload-time = "2025-09-08T23:08:26.063Z" }, + { url = "https://files.pythonhosted.org/packages/69/2d/d83dd6d7ca929a2fc67d2c3005415cdf322af7751d773524809f9e585129/pyzmq-27.1.0-cp313-cp313t-manylinux_2_26_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:d54530c8c8b5b8ddb3318f481297441af102517602b569146185fa10b63f4fa9", size = 660469, upload-time = "2025-09-08T23:08:27.623Z" }, + { url = "https://files.pythonhosted.org/packages/3e/cd/9822a7af117f4bc0f1952dbe9ef8358eb50a24928efd5edf54210b850259/pyzmq-27.1.0-cp313-cp313t-manylinux_2_26_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:6f3afa12c392f0a44a2414056d730eebc33ec0926aae92b5ad5cf26ebb6cc128", size = 847961, upload-time = "2025-09-08T23:08:29.672Z" }, + { url = "https://files.pythonhosted.org/packages/9a/12/f003e824a19ed73be15542f172fd0ec4ad0b60cf37436652c93b9df7c585/pyzmq-27.1.0-cp313-cp313t-musllinux_1_2_aarch64.whl", hash = "sha256:c65047adafe573ff023b3187bb93faa583151627bc9c51fc4fb2c561ed689d39", size = 1650282, upload-time = "2025-09-08T23:08:31.349Z" }, + { url = "https://files.pythonhosted.org/packages/d5/4a/e82d788ed58e9a23995cee70dbc20c9aded3d13a92d30d57ec2291f1e8a3/pyzmq-27.1.0-cp313-cp313t-musllinux_1_2_i686.whl", hash = "sha256:90e6e9441c946a8b0a667356f7078d96411391a3b8f80980315455574177ec97", size = 2024468, upload-time = "2025-09-08T23:08:33.543Z" }, + { url = "https://files.pythonhosted.org/packages/d9/94/2da0a60841f757481e402b34bf4c8bf57fa54a5466b965de791b1e6f747d/pyzmq-27.1.0-cp313-cp313t-musllinux_1_2_x86_64.whl", hash = "sha256:add071b2d25f84e8189aaf0882d39a285b42fa3853016ebab234a5e78c7a43db", size = 1885394, upload-time = "2025-09-08T23:08:35.51Z" }, + { url = "https://files.pythonhosted.org/packages/4f/6f/55c10e2e49ad52d080dc24e37adb215e5b0d64990b57598abc2e3f01725b/pyzmq-27.1.0-cp313-cp313t-win32.whl", hash = "sha256:7ccc0700cfdf7bd487bea8d850ec38f204478681ea02a582a8da8171b7f90a1c", size = 574964, upload-time = "2025-09-08T23:08:37.178Z" }, + { url = "https://files.pythonhosted.org/packages/87/4d/2534970ba63dd7c522d8ca80fb92777f362c0f321900667c615e2067cb29/pyzmq-27.1.0-cp313-cp313t-win_amd64.whl", hash = "sha256:8085a9fba668216b9b4323be338ee5437a235fe275b9d1610e422ccc279733e2", size = 641029, upload-time = "2025-09-08T23:08:40.595Z" }, + { url = "https://files.pythonhosted.org/packages/f6/fa/f8aea7a28b0641f31d40dea42d7ef003fded31e184ef47db696bc74cd610/pyzmq-27.1.0-cp313-cp313t-win_arm64.whl", hash = "sha256:6bb54ca21bcfe361e445256c15eedf083f153811c37be87e0514934d6913061e", size = 561541, upload-time = "2025-09-08T23:08:42.668Z" }, + { url = "https://files.pythonhosted.org/packages/87/45/19efbb3000956e82d0331bafca5d9ac19ea2857722fa2caacefb6042f39d/pyzmq-27.1.0-cp314-cp314t-macosx_10_15_universal2.whl", hash = "sha256:ce980af330231615756acd5154f29813d553ea555485ae712c491cd483df6b7a", size = 1341197, upload-time = "2025-09-08T23:08:44.973Z" }, + { url = "https://files.pythonhosted.org/packages/48/43/d72ccdbf0d73d1343936296665826350cb1e825f92f2db9db3e61c2162a2/pyzmq-27.1.0-cp314-cp314t-manylinux2014_i686.manylinux_2_17_i686.whl", hash = "sha256:1779be8c549e54a1c38f805e56d2a2e5c009d26de10921d7d51cfd1c8d4632ea", size = 897175, upload-time = "2025-09-08T23:08:46.601Z" }, + { url = "https://files.pythonhosted.org/packages/2f/2e/a483f73a10b65a9ef0161e817321d39a770b2acf8bcf3004a28d90d14a94/pyzmq-27.1.0-cp314-cp314t-manylinux_2_26_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:7200bb0f03345515df50d99d3db206a0a6bee1955fbb8c453c76f5bf0e08fb96", size = 660427, upload-time = "2025-09-08T23:08:48.187Z" }, + { url = "https://files.pythonhosted.org/packages/f5/d2/5f36552c2d3e5685abe60dfa56f91169f7a2d99bbaf67c5271022ab40863/pyzmq-27.1.0-cp314-cp314t-manylinux_2_26_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:01c0e07d558b06a60773744ea6251f769cd79a41a97d11b8bf4ab8f034b0424d", size = 847929, upload-time = "2025-09-08T23:08:49.76Z" }, + { url = "https://files.pythonhosted.org/packages/c4/2a/404b331f2b7bf3198e9945f75c4c521f0c6a3a23b51f7a4a401b94a13833/pyzmq-27.1.0-cp314-cp314t-musllinux_1_2_aarch64.whl", hash = "sha256:80d834abee71f65253c91540445d37c4c561e293ba6e741b992f20a105d69146", size = 1650193, upload-time = "2025-09-08T23:08:51.7Z" }, + { url = "https://files.pythonhosted.org/packages/1c/0b/f4107e33f62a5acf60e3ded67ed33d79b4ce18de432625ce2fc5093d6388/pyzmq-27.1.0-cp314-cp314t-musllinux_1_2_i686.whl", hash = "sha256:544b4e3b7198dde4a62b8ff6685e9802a9a1ebf47e77478a5eb88eca2a82f2fd", size = 2024388, upload-time = "2025-09-08T23:08:53.393Z" }, + { url = "https://files.pythonhosted.org/packages/0d/01/add31fe76512642fd6e40e3a3bd21f4b47e242c8ba33efb6809e37076d9b/pyzmq-27.1.0-cp314-cp314t-musllinux_1_2_x86_64.whl", hash = "sha256:cedc4c68178e59a4046f97eca31b148ddcf51e88677de1ef4e78cf06c5376c9a", size = 1885316, upload-time = "2025-09-08T23:08:55.702Z" }, + { url = "https://files.pythonhosted.org/packages/c4/59/a5f38970f9bf07cee96128de79590bb354917914a9be11272cfc7ff26af0/pyzmq-27.1.0-cp314-cp314t-win32.whl", hash = "sha256:1f0b2a577fd770aa6f053211a55d1c47901f4d537389a034c690291485e5fe92", size = 587472, upload-time = "2025-09-08T23:08:58.18Z" }, + { url = "https://files.pythonhosted.org/packages/70/d8/78b1bad170f93fcf5e3536e70e8fadac55030002275c9a29e8f5719185de/pyzmq-27.1.0-cp314-cp314t-win_amd64.whl", hash = "sha256:19c9468ae0437f8074af379e986c5d3d7d7bfe033506af442e8c879732bedbe0", size = 661401, upload-time = "2025-09-08T23:08:59.802Z" }, + { url = "https://files.pythonhosted.org/packages/81/d6/4bfbb40c9a0b42fc53c7cf442f6385db70b40f74a783130c5d0a5aa62228/pyzmq-27.1.0-cp314-cp314t-win_arm64.whl", hash = "sha256:dc5dbf68a7857b59473f7df42650c621d7e8923fb03fa74a526890f4d33cc4d7", size = 575170, upload-time = "2025-09-08T23:09:01.418Z" }, + { url = "https://files.pythonhosted.org/packages/4c/c6/c4dcdecdbaa70969ee1fdced6d7b8f60cfabe64d25361f27ac4665a70620/pyzmq-27.1.0-pp311-pypy311_pp73-macosx_10_15_x86_64.whl", hash = "sha256:18770c8d3563715387139060d37859c02ce40718d1faf299abddcdcc6a649066", size = 836265, upload-time = "2025-09-08T23:09:49.376Z" }, + { url = "https://files.pythonhosted.org/packages/3e/79/f38c92eeaeb03a2ccc2ba9866f0439593bb08c5e3b714ac1d553e5c96e25/pyzmq-27.1.0-pp311-pypy311_pp73-manylinux2014_i686.manylinux_2_17_i686.whl", hash = "sha256:ac25465d42f92e990f8d8b0546b01c391ad431c3bf447683fdc40565941d0604", size = 800208, upload-time = "2025-09-08T23:09:51.073Z" }, + { url = "https://files.pythonhosted.org/packages/49/0e/3f0d0d335c6b3abb9b7b723776d0b21fa7f3a6c819a0db6097059aada160/pyzmq-27.1.0-pp311-pypy311_pp73-manylinux_2_26_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:53b40f8ae006f2734ee7608d59ed661419f087521edbfc2149c3932e9c14808c", size = 567747, upload-time = "2025-09-08T23:09:52.698Z" }, + { url = "https://files.pythonhosted.org/packages/a1/cf/f2b3784d536250ffd4be70e049f3b60981235d70c6e8ce7e3ef21e1adb25/pyzmq-27.1.0-pp311-pypy311_pp73-manylinux_2_26_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:f605d884e7c8be8fe1aa94e0a783bf3f591b84c24e4bc4f3e7564c82ac25e271", size = 747371, upload-time = "2025-09-08T23:09:54.563Z" }, + { url = "https://files.pythonhosted.org/packages/01/1b/5dbe84eefc86f48473947e2f41711aded97eecef1231f4558f1f02713c12/pyzmq-27.1.0-pp311-pypy311_pp73-win_amd64.whl", hash = "sha256:c9f7f6e13dff2e44a6afeaf2cf54cee5929ad64afaf4d40b50f93c58fc687355", size = 544862, upload-time = "2025-09-08T23:09:56.509Z" }, +] + +[[package]] +name = "readme-renderer" +version = "44.0" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "docutils" }, + { name = "nh3" }, + { name = "pygments" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/5a/a9/104ec9234c8448c4379768221ea6df01260cd6c2ce13182d4eac531c8342/readme_renderer-44.0.tar.gz", hash = "sha256:8712034eabbfa6805cacf1402b4eeb2a73028f72d1166d6f5cb7f9c047c5d1e1", size = 32056, upload-time = "2024-07-08T15:00:57.805Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/e1/67/921ec3024056483db83953ae8e48079ad62b92db7880013ca77632921dd0/readme_renderer-44.0-py3-none-any.whl", hash = "sha256:2fbca89b81a08526aadf1357a8c2ae889ec05fb03f5da67f9769c9a592166151", size = 13310, upload-time = "2024-07-08T15:00:56.577Z" }, +] + +[[package]] +name = "referencing" +version = "0.37.0" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "attrs" }, + { name = "rpds-py" }, + { name = "typing-extensions", marker = "python_full_version < '3.13'" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/22/f5/df4e9027acead3ecc63e50fe1e36aca1523e1719559c499951bb4b53188f/referencing-0.37.0.tar.gz", hash = "sha256:44aefc3142c5b842538163acb373e24cce6632bd54bdb01b21ad5863489f50d8", size = 78036, upload-time = "2025-10-13T15:30:48.871Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/2c/58/ca301544e1fa93ed4f80d724bf5b194f6e4b945841c5bfd555878eea9fcb/referencing-0.37.0-py3-none-any.whl", hash = "sha256:381329a9f99628c9069361716891d34ad94af76e461dcb0335825aecc7692231", size = 26766, upload-time = "2025-10-13T15:30:47.625Z" }, +] + +[[package]] +name = "requests" +version = "2.32.5" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "certifi" }, + { name = "charset-normalizer" }, + { name = "idna" }, + { name = "urllib3" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/c9/74/b3ff8e6c8446842c3f5c837e9c3dfcfe2018ea6ecef224c710c85ef728f4/requests-2.32.5.tar.gz", hash = "sha256:dbba0bac56e100853db0ea71b82b4dfd5fe2bf6d3754a8893c3af500cec7d7cf", size = 134517, upload-time = "2025-08-18T20:46:02.573Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/1e/db/4254e3eabe8020b458f1a747140d32277ec7a271daf1d235b70dc0b4e6e3/requests-2.32.5-py3-none-any.whl", hash = "sha256:2462f94637a34fd532264295e186976db0f5d453d1cdd31473c85a6a161affb6", size = 64738, upload-time = "2025-08-18T20:46:00.542Z" }, +] + +[[package]] +name = "requests-toolbelt" +version = "1.0.0" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "requests" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/f3/61/d7545dafb7ac2230c70d38d31cbfe4cc64f7144dc41f6e4e4b78ecd9f5bb/requests-toolbelt-1.0.0.tar.gz", hash = "sha256:7681a0a3d047012b5bdc0ee37d7f8f07ebe76ab08caeccfc3921ce23c88d5bc6", size = 206888, upload-time = "2023-05-01T04:11:33.229Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/3f/51/d4db610ef29373b879047326cbf6fa98b6c1969d6f6dc423279de2b1be2c/requests_toolbelt-1.0.0-py2.py3-none-any.whl", hash = "sha256:cccfdd665f0a24fcf4726e690f65639d272bb0637b9b92dfd91a5568ccf6bd06", size = 54481, upload-time = "2023-05-01T04:11:28.427Z" }, +] + +[[package]] +name = "rfc3986" +version = "2.0.0" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/85/40/1520d68bfa07ab5a6f065a186815fb6610c86fe957bc065754e47f7b0840/rfc3986-2.0.0.tar.gz", hash = "sha256:97aacf9dbd4bfd829baad6e6309fa6573aaf1be3f6fa735c8ab05e46cecb261c", size = 49026, upload-time = "2022-01-10T00:52:30.832Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/ff/9a/9afaade874b2fa6c752c36f1548f718b5b83af81ed9b76628329dab81c1b/rfc3986-2.0.0-py2.py3-none-any.whl", hash = "sha256:50b1502b60e289cb37883f3dfd34532b8873c7de9f49bb546641ce9cbd256ebd", size = 31326, upload-time = "2022-01-10T00:52:29.594Z" }, +] + +[[package]] +name = "rich" +version = "14.3.3" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "markdown-it-py" }, + { name = "pygments" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/b3/c6/f3b320c27991c46f43ee9d856302c70dc2d0fb2dba4842ff739d5f46b393/rich-14.3.3.tar.gz", hash = "sha256:b8daa0b9e4eef54dd8cf7c86c03713f53241884e814f4e2f5fb342fe520f639b", size = 230582, upload-time = "2026-02-19T17:23:12.474Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/14/25/b208c5683343959b670dc001595f2f3737e051da617f66c31f7c4fa93abc/rich-14.3.3-py3-none-any.whl", hash = "sha256:793431c1f8619afa7d3b52b2cdec859562b950ea0d4b6b505397612db8d5362d", size = 310458, upload-time = "2026-02-19T17:23:13.732Z" }, +] + +[[package]] +name = "roman-numerals" +version = "4.1.0" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/ae/f9/41dc953bbeb056c17d5f7a519f50fdf010bd0553be2d630bc69d1e022703/roman_numerals-4.1.0.tar.gz", hash = "sha256:1af8b147eb1405d5839e78aeb93131690495fe9da5c91856cb33ad55a7f1e5b2", size = 9077, upload-time = "2025-12-17T18:25:34.381Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/04/54/6f679c435d28e0a568d8e8a7c0a93a09010818634c3c3907fc98d8983770/roman_numerals-4.1.0-py3-none-any.whl", hash = "sha256:647ba99caddc2cc1e55a51e4360689115551bf4476d90e8162cf8c345fe233c7", size = 7676, upload-time = "2025-12-17T18:25:33.098Z" }, +] + +[[package]] +name = "rpds-py" +version = "0.30.0" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/20/af/3f2f423103f1113b36230496629986e0ef7e199d2aa8392452b484b38ced/rpds_py-0.30.0.tar.gz", hash = "sha256:dd8ff7cf90014af0c0f787eea34794ebf6415242ee1d6fa91eaba725cc441e84", size = 69469, upload-time = "2025-11-30T20:24:38.837Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/4d/6e/f964e88b3d2abee2a82c1ac8366da848fce1c6d834dc2132c3fda3970290/rpds_py-0.30.0-cp311-cp311-macosx_10_12_x86_64.whl", hash = "sha256:a2bffea6a4ca9f01b3f8e548302470306689684e61602aa3d141e34da06cf425", size = 370157, upload-time = "2025-11-30T20:21:53.789Z" }, + { url = "https://files.pythonhosted.org/packages/94/ba/24e5ebb7c1c82e74c4e4f33b2112a5573ddc703915b13a073737b59b86e0/rpds_py-0.30.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:dc4f992dfe1e2bc3ebc7444f6c7051b4bc13cd8e33e43511e8ffd13bf407010d", size = 359676, upload-time = "2025-11-30T20:21:55.475Z" }, + { url = "https://files.pythonhosted.org/packages/84/86/04dbba1b087227747d64d80c3b74df946b986c57af0a9f0c98726d4d7a3b/rpds_py-0.30.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:422c3cb9856d80b09d30d2eb255d0754b23e090034e1deb4083f8004bd0761e4", size = 389938, upload-time = "2025-11-30T20:21:57.079Z" }, + { url = "https://files.pythonhosted.org/packages/42/bb/1463f0b1722b7f45431bdd468301991d1328b16cffe0b1c2918eba2c4eee/rpds_py-0.30.0-cp311-cp311-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:07ae8a593e1c3c6b82ca3292efbe73c30b61332fd612e05abee07c79359f292f", size = 402932, upload-time = "2025-11-30T20:21:58.47Z" }, + { url = "https://files.pythonhosted.org/packages/99/ee/2520700a5c1f2d76631f948b0736cdf9b0acb25abd0ca8e889b5c62ac2e3/rpds_py-0.30.0-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:12f90dd7557b6bd57f40abe7747e81e0c0b119bef015ea7726e69fe550e394a4", size = 525830, upload-time = "2025-11-30T20:21:59.699Z" }, + { url = "https://files.pythonhosted.org/packages/e0/ad/bd0331f740f5705cc555a5e17fdf334671262160270962e69a2bdef3bf76/rpds_py-0.30.0-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:99b47d6ad9a6da00bec6aabe5a6279ecd3c06a329d4aa4771034a21e335c3a97", size = 412033, upload-time = "2025-11-30T20:22:00.991Z" }, + { url = "https://files.pythonhosted.org/packages/f8/1e/372195d326549bb51f0ba0f2ecb9874579906b97e08880e7a65c3bef1a99/rpds_py-0.30.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:33f559f3104504506a44bb666b93a33f5d33133765b0c216a5bf2f1e1503af89", size = 390828, upload-time = "2025-11-30T20:22:02.723Z" }, + { url = "https://files.pythonhosted.org/packages/ab/2b/d88bb33294e3e0c76bc8f351a3721212713629ffca1700fa94979cb3eae8/rpds_py-0.30.0-cp311-cp311-manylinux_2_31_riscv64.whl", hash = "sha256:946fe926af6e44f3697abbc305ea168c2c31d3e3ef1058cf68f379bf0335a78d", size = 404683, upload-time = "2025-11-30T20:22:04.367Z" }, + { url = "https://files.pythonhosted.org/packages/50/32/c759a8d42bcb5289c1fac697cd92f6fe01a018dd937e62ae77e0e7f15702/rpds_py-0.30.0-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:495aeca4b93d465efde585977365187149e75383ad2684f81519f504f5c13038", size = 421583, upload-time = "2025-11-30T20:22:05.814Z" }, + { url = "https://files.pythonhosted.org/packages/2b/81/e729761dbd55ddf5d84ec4ff1f47857f4374b0f19bdabfcf929164da3e24/rpds_py-0.30.0-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:d9a0ca5da0386dee0655b4ccdf46119df60e0f10da268d04fe7cc87886872ba7", size = 572496, upload-time = "2025-11-30T20:22:07.713Z" }, + { url = "https://files.pythonhosted.org/packages/14/f6/69066a924c3557c9c30baa6ec3a0aa07526305684c6f86c696b08860726c/rpds_py-0.30.0-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:8d6d1cc13664ec13c1b84241204ff3b12f9bb82464b8ad6e7a5d3486975c2eed", size = 598669, upload-time = "2025-11-30T20:22:09.312Z" }, + { url = "https://files.pythonhosted.org/packages/5f/48/905896b1eb8a05630d20333d1d8ffd162394127b74ce0b0784ae04498d32/rpds_py-0.30.0-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:3896fa1be39912cf0757753826bc8bdc8ca331a28a7c4ae46b7a21280b06bb85", size = 561011, upload-time = "2025-11-30T20:22:11.309Z" }, + { url = "https://files.pythonhosted.org/packages/22/16/cd3027c7e279d22e5eb431dd3c0fbc677bed58797fe7581e148f3f68818b/rpds_py-0.30.0-cp311-cp311-win32.whl", hash = "sha256:55f66022632205940f1827effeff17c4fa7ae1953d2b74a8581baaefb7d16f8c", size = 221406, upload-time = "2025-11-30T20:22:13.101Z" }, + { url = "https://files.pythonhosted.org/packages/fa/5b/e7b7aa136f28462b344e652ee010d4de26ee9fd16f1bfd5811f5153ccf89/rpds_py-0.30.0-cp311-cp311-win_amd64.whl", hash = "sha256:a51033ff701fca756439d641c0ad09a41d9242fa69121c7d8769604a0a629825", size = 236024, upload-time = "2025-11-30T20:22:14.853Z" }, + { url = "https://files.pythonhosted.org/packages/14/a6/364bba985e4c13658edb156640608f2c9e1d3ea3c81b27aa9d889fff0e31/rpds_py-0.30.0-cp311-cp311-win_arm64.whl", hash = "sha256:47b0ef6231c58f506ef0b74d44e330405caa8428e770fec25329ed2cb971a229", size = 229069, upload-time = "2025-11-30T20:22:16.577Z" }, + { url = "https://files.pythonhosted.org/packages/03/e7/98a2f4ac921d82f33e03f3835f5bf3a4a40aa1bfdc57975e74a97b2b4bdd/rpds_py-0.30.0-cp312-cp312-macosx_10_12_x86_64.whl", hash = "sha256:a161f20d9a43006833cd7068375a94d035714d73a172b681d8881820600abfad", size = 375086, upload-time = "2025-11-30T20:22:17.93Z" }, + { url = "https://files.pythonhosted.org/packages/4d/a1/bca7fd3d452b272e13335db8d6b0b3ecde0f90ad6f16f3328c6fb150c889/rpds_py-0.30.0-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:6abc8880d9d036ecaafe709079969f56e876fcf107f7a8e9920ba6d5a3878d05", size = 359053, upload-time = "2025-11-30T20:22:19.297Z" }, + { url = "https://files.pythonhosted.org/packages/65/1c/ae157e83a6357eceff62ba7e52113e3ec4834a84cfe07fa4b0757a7d105f/rpds_py-0.30.0-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:ca28829ae5f5d569bb62a79512c842a03a12576375d5ece7d2cadf8abe96ec28", size = 390763, upload-time = "2025-11-30T20:22:21.661Z" }, + { url = "https://files.pythonhosted.org/packages/d4/36/eb2eb8515e2ad24c0bd43c3ee9cd74c33f7ca6430755ccdb240fd3144c44/rpds_py-0.30.0-cp312-cp312-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:a1010ed9524c73b94d15919ca4d41d8780980e1765babf85f9a2f90d247153dd", size = 408951, upload-time = "2025-11-30T20:22:23.408Z" }, + { url = "https://files.pythonhosted.org/packages/d6/65/ad8dc1784a331fabbd740ef6f71ce2198c7ed0890dab595adb9ea2d775a1/rpds_py-0.30.0-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:f8d1736cfb49381ba528cd5baa46f82fdc65c06e843dab24dd70b63d09121b3f", size = 514622, upload-time = "2025-11-30T20:22:25.16Z" }, + { url = "https://files.pythonhosted.org/packages/63/8e/0cfa7ae158e15e143fe03993b5bcd743a59f541f5952e1546b1ac1b5fd45/rpds_py-0.30.0-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:d948b135c4693daff7bc2dcfc4ec57237a29bd37e60c2fabf5aff2bbacf3e2f1", size = 414492, upload-time = "2025-11-30T20:22:26.505Z" }, + { url = "https://files.pythonhosted.org/packages/60/1b/6f8f29f3f995c7ffdde46a626ddccd7c63aefc0efae881dc13b6e5d5bb16/rpds_py-0.30.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:47f236970bccb2233267d89173d3ad2703cd36a0e2a6e92d0560d333871a3d23", size = 394080, upload-time = "2025-11-30T20:22:27.934Z" }, + { url = "https://files.pythonhosted.org/packages/6d/d5/a266341051a7a3ca2f4b750a3aa4abc986378431fc2da508c5034d081b70/rpds_py-0.30.0-cp312-cp312-manylinux_2_31_riscv64.whl", hash = "sha256:2e6ecb5a5bcacf59c3f912155044479af1d0b6681280048b338b28e364aca1f6", size = 408680, upload-time = "2025-11-30T20:22:29.341Z" }, + { url = "https://files.pythonhosted.org/packages/10/3b/71b725851df9ab7a7a4e33cf36d241933da66040d195a84781f49c50490c/rpds_py-0.30.0-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:a8fa71a2e078c527c3e9dc9fc5a98c9db40bcc8a92b4e8858e36d329f8684b51", size = 423589, upload-time = "2025-11-30T20:22:31.469Z" }, + { url = "https://files.pythonhosted.org/packages/00/2b/e59e58c544dc9bd8bd8384ecdb8ea91f6727f0e37a7131baeff8d6f51661/rpds_py-0.30.0-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:73c67f2db7bc334e518d097c6d1e6fed021bbc9b7d678d6cc433478365d1d5f5", size = 573289, upload-time = "2025-11-30T20:22:32.997Z" }, + { url = "https://files.pythonhosted.org/packages/da/3e/a18e6f5b460893172a7d6a680e86d3b6bc87a54c1f0b03446a3c8c7b588f/rpds_py-0.30.0-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:5ba103fb455be00f3b1c2076c9d4264bfcb037c976167a6047ed82f23153f02e", size = 599737, upload-time = "2025-11-30T20:22:34.419Z" }, + { url = "https://files.pythonhosted.org/packages/5c/e2/714694e4b87b85a18e2c243614974413c60aa107fd815b8cbc42b873d1d7/rpds_py-0.30.0-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:7cee9c752c0364588353e627da8a7e808a66873672bcb5f52890c33fd965b394", size = 563120, upload-time = "2025-11-30T20:22:35.903Z" }, + { url = "https://files.pythonhosted.org/packages/6f/ab/d5d5e3bcedb0a77f4f613706b750e50a5a3ba1c15ccd3665ecc636c968fd/rpds_py-0.30.0-cp312-cp312-win32.whl", hash = "sha256:1ab5b83dbcf55acc8b08fc62b796ef672c457b17dbd7820a11d6c52c06839bdf", size = 223782, upload-time = "2025-11-30T20:22:37.271Z" }, + { url = "https://files.pythonhosted.org/packages/39/3b/f786af9957306fdc38a74cef405b7b93180f481fb48453a114bb6465744a/rpds_py-0.30.0-cp312-cp312-win_amd64.whl", hash = "sha256:a090322ca841abd453d43456ac34db46e8b05fd9b3b4ac0c78bcde8b089f959b", size = 240463, upload-time = "2025-11-30T20:22:39.021Z" }, + { url = "https://files.pythonhosted.org/packages/f3/d2/b91dc748126c1559042cfe41990deb92c4ee3e2b415f6b5234969ffaf0cc/rpds_py-0.30.0-cp312-cp312-win_arm64.whl", hash = "sha256:669b1805bd639dd2989b281be2cfd951c6121b65e729d9b843e9639ef1fd555e", size = 230868, upload-time = "2025-11-30T20:22:40.493Z" }, + { url = "https://files.pythonhosted.org/packages/ed/dc/d61221eb88ff410de3c49143407f6f3147acf2538c86f2ab7ce65ae7d5f9/rpds_py-0.30.0-cp313-cp313-macosx_10_12_x86_64.whl", hash = "sha256:f83424d738204d9770830d35290ff3273fbb02b41f919870479fab14b9d303b2", size = 374887, upload-time = "2025-11-30T20:22:41.812Z" }, + { url = "https://files.pythonhosted.org/packages/fd/32/55fb50ae104061dbc564ef15cc43c013dc4a9f4527a1f4d99baddf56fe5f/rpds_py-0.30.0-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:e7536cd91353c5273434b4e003cbda89034d67e7710eab8761fd918ec6c69cf8", size = 358904, upload-time = "2025-11-30T20:22:43.479Z" }, + { url = "https://files.pythonhosted.org/packages/58/70/faed8186300e3b9bdd138d0273109784eea2396c68458ed580f885dfe7ad/rpds_py-0.30.0-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:2771c6c15973347f50fece41fc447c054b7ac2ae0502388ce3b6738cd366e3d4", size = 389945, upload-time = "2025-11-30T20:22:44.819Z" }, + { url = "https://files.pythonhosted.org/packages/bd/a8/073cac3ed2c6387df38f71296d002ab43496a96b92c823e76f46b8af0543/rpds_py-0.30.0-cp313-cp313-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:0a59119fc6e3f460315fe9d08149f8102aa322299deaa5cab5b40092345c2136", size = 407783, upload-time = "2025-11-30T20:22:46.103Z" }, + { url = "https://files.pythonhosted.org/packages/77/57/5999eb8c58671f1c11eba084115e77a8899d6e694d2a18f69f0ba471ec8b/rpds_py-0.30.0-cp313-cp313-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:76fec018282b4ead0364022e3c54b60bf368b9d926877957a8624b58419169b7", size = 515021, upload-time = "2025-11-30T20:22:47.458Z" }, + { url = "https://files.pythonhosted.org/packages/e0/af/5ab4833eadc36c0a8ed2bc5c0de0493c04f6c06de223170bd0798ff98ced/rpds_py-0.30.0-cp313-cp313-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:692bef75a5525db97318e8cd061542b5a79812d711ea03dbc1f6f8dbb0c5f0d2", size = 414589, upload-time = "2025-11-30T20:22:48.872Z" }, + { url = "https://files.pythonhosted.org/packages/b7/de/f7192e12b21b9e9a68a6d0f249b4af3fdcdff8418be0767a627564afa1f1/rpds_py-0.30.0-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9027da1ce107104c50c81383cae773ef5c24d296dd11c99e2629dbd7967a20c6", size = 394025, upload-time = "2025-11-30T20:22:50.196Z" }, + { url = "https://files.pythonhosted.org/packages/91/c4/fc70cd0249496493500e7cc2de87504f5aa6509de1e88623431fec76d4b6/rpds_py-0.30.0-cp313-cp313-manylinux_2_31_riscv64.whl", hash = "sha256:9cf69cdda1f5968a30a359aba2f7f9aa648a9ce4b580d6826437f2b291cfc86e", size = 408895, upload-time = "2025-11-30T20:22:51.87Z" }, + { url = "https://files.pythonhosted.org/packages/58/95/d9275b05ab96556fefff73a385813eb66032e4c99f411d0795372d9abcea/rpds_py-0.30.0-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:a4796a717bf12b9da9d3ad002519a86063dcac8988b030e405704ef7d74d2d9d", size = 422799, upload-time = "2025-11-30T20:22:53.341Z" }, + { url = "https://files.pythonhosted.org/packages/06/c1/3088fc04b6624eb12a57eb814f0d4997a44b0d208d6cace713033ff1a6ba/rpds_py-0.30.0-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:5d4c2aa7c50ad4728a094ebd5eb46c452e9cb7edbfdb18f9e1221f597a73e1e7", size = 572731, upload-time = "2025-11-30T20:22:54.778Z" }, + { url = "https://files.pythonhosted.org/packages/d8/42/c612a833183b39774e8ac8fecae81263a68b9583ee343db33ab571a7ce55/rpds_py-0.30.0-cp313-cp313-musllinux_1_2_i686.whl", hash = "sha256:ba81a9203d07805435eb06f536d95a266c21e5b2dfbf6517748ca40c98d19e31", size = 599027, upload-time = "2025-11-30T20:22:56.212Z" }, + { url = "https://files.pythonhosted.org/packages/5f/60/525a50f45b01d70005403ae0e25f43c0384369ad24ffe46e8d9068b50086/rpds_py-0.30.0-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:945dccface01af02675628334f7cf49c2af4c1c904748efc5cf7bbdf0b579f95", size = 563020, upload-time = "2025-11-30T20:22:58.2Z" }, + { url = "https://files.pythonhosted.org/packages/0b/5d/47c4655e9bcd5ca907148535c10e7d489044243cc9941c16ed7cd53be91d/rpds_py-0.30.0-cp313-cp313-win32.whl", hash = "sha256:b40fb160a2db369a194cb27943582b38f79fc4887291417685f3ad693c5a1d5d", size = 223139, upload-time = "2025-11-30T20:23:00.209Z" }, + { url = "https://files.pythonhosted.org/packages/f2/e1/485132437d20aa4d3e1d8b3fb5a5e65aa8139f1e097080c2a8443201742c/rpds_py-0.30.0-cp313-cp313-win_amd64.whl", hash = "sha256:806f36b1b605e2d6a72716f321f20036b9489d29c51c91f4dd29a3e3afb73b15", size = 240224, upload-time = "2025-11-30T20:23:02.008Z" }, + { url = "https://files.pythonhosted.org/packages/24/95/ffd128ed1146a153d928617b0ef673960130be0009c77d8fbf0abe306713/rpds_py-0.30.0-cp313-cp313-win_arm64.whl", hash = "sha256:d96c2086587c7c30d44f31f42eae4eac89b60dabbac18c7669be3700f13c3ce1", size = 230645, upload-time = "2025-11-30T20:23:03.43Z" }, + { url = "https://files.pythonhosted.org/packages/ff/1b/b10de890a0def2a319a2626334a7f0ae388215eb60914dbac8a3bae54435/rpds_py-0.30.0-cp313-cp313t-macosx_10_12_x86_64.whl", hash = "sha256:eb0b93f2e5c2189ee831ee43f156ed34e2a89a78a66b98cadad955972548be5a", size = 364443, upload-time = "2025-11-30T20:23:04.878Z" }, + { url = "https://files.pythonhosted.org/packages/0d/bf/27e39f5971dc4f305a4fb9c672ca06f290f7c4e261c568f3dea16a410d47/rpds_py-0.30.0-cp313-cp313t-macosx_11_0_arm64.whl", hash = "sha256:922e10f31f303c7c920da8981051ff6d8c1a56207dbdf330d9047f6d30b70e5e", size = 353375, upload-time = "2025-11-30T20:23:06.342Z" }, + { url = "https://files.pythonhosted.org/packages/40/58/442ada3bba6e8e6615fc00483135c14a7538d2ffac30e2d933ccf6852232/rpds_py-0.30.0-cp313-cp313t-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:cdc62c8286ba9bf7f47befdcea13ea0e26bf294bda99758fd90535cbaf408000", size = 383850, upload-time = "2025-11-30T20:23:07.825Z" }, + { url = "https://files.pythonhosted.org/packages/14/14/f59b0127409a33c6ef6f5c1ebd5ad8e32d7861c9c7adfa9a624fc3889f6c/rpds_py-0.30.0-cp313-cp313t-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:47f9a91efc418b54fb8190a6b4aa7813a23fb79c51f4bb84e418f5476c38b8db", size = 392812, upload-time = "2025-11-30T20:23:09.228Z" }, + { url = "https://files.pythonhosted.org/packages/b3/66/e0be3e162ac299b3a22527e8913767d869e6cc75c46bd844aa43fb81ab62/rpds_py-0.30.0-cp313-cp313t-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:1f3587eb9b17f3789ad50824084fa6f81921bbf9a795826570bda82cb3ed91f2", size = 517841, upload-time = "2025-11-30T20:23:11.186Z" }, + { url = "https://files.pythonhosted.org/packages/3d/55/fa3b9cf31d0c963ecf1ba777f7cf4b2a2c976795ac430d24a1f43d25a6ba/rpds_py-0.30.0-cp313-cp313t-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:39c02563fc592411c2c61d26b6c5fe1e51eaa44a75aa2c8735ca88b0d9599daa", size = 408149, upload-time = "2025-11-30T20:23:12.864Z" }, + { url = "https://files.pythonhosted.org/packages/60/ca/780cf3b1a32b18c0f05c441958d3758f02544f1d613abf9488cd78876378/rpds_py-0.30.0-cp313-cp313t-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:51a1234d8febafdfd33a42d97da7a43f5dcb120c1060e352a3fbc0c6d36e2083", size = 383843, upload-time = "2025-11-30T20:23:14.638Z" }, + { url = "https://files.pythonhosted.org/packages/82/86/d5f2e04f2aa6247c613da0c1dd87fcd08fa17107e858193566048a1e2f0a/rpds_py-0.30.0-cp313-cp313t-manylinux_2_31_riscv64.whl", hash = "sha256:eb2c4071ab598733724c08221091e8d80e89064cd472819285a9ab0f24bcedb9", size = 396507, upload-time = "2025-11-30T20:23:16.105Z" }, + { url = "https://files.pythonhosted.org/packages/4b/9a/453255d2f769fe44e07ea9785c8347edaf867f7026872e76c1ad9f7bed92/rpds_py-0.30.0-cp313-cp313t-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:6bdfdb946967d816e6adf9a3d8201bfad269c67efe6cefd7093ef959683c8de0", size = 414949, upload-time = "2025-11-30T20:23:17.539Z" }, + { url = "https://files.pythonhosted.org/packages/a3/31/622a86cdc0c45d6df0e9ccb6becdba5074735e7033c20e401a6d9d0e2ca0/rpds_py-0.30.0-cp313-cp313t-musllinux_1_2_aarch64.whl", hash = "sha256:c77afbd5f5250bf27bf516c7c4a016813eb2d3e116139aed0096940c5982da94", size = 565790, upload-time = "2025-11-30T20:23:19.029Z" }, + { url = "https://files.pythonhosted.org/packages/1c/5d/15bbf0fb4a3f58a3b1c67855ec1efcc4ceaef4e86644665fff03e1b66d8d/rpds_py-0.30.0-cp313-cp313t-musllinux_1_2_i686.whl", hash = "sha256:61046904275472a76c8c90c9ccee9013d70a6d0f73eecefd38c1ae7c39045a08", size = 590217, upload-time = "2025-11-30T20:23:20.885Z" }, + { url = "https://files.pythonhosted.org/packages/6d/61/21b8c41f68e60c8cc3b2e25644f0e3681926020f11d06ab0b78e3c6bbff1/rpds_py-0.30.0-cp313-cp313t-musllinux_1_2_x86_64.whl", hash = "sha256:4c5f36a861bc4b7da6516dbdf302c55313afa09b81931e8280361a4f6c9a2d27", size = 555806, upload-time = "2025-11-30T20:23:22.488Z" }, + { url = "https://files.pythonhosted.org/packages/f9/39/7e067bb06c31de48de3eb200f9fc7c58982a4d3db44b07e73963e10d3be9/rpds_py-0.30.0-cp313-cp313t-win32.whl", hash = "sha256:3d4a69de7a3e50ffc214ae16d79d8fbb0922972da0356dcf4d0fdca2878559c6", size = 211341, upload-time = "2025-11-30T20:23:24.449Z" }, + { url = "https://files.pythonhosted.org/packages/0a/4d/222ef0b46443cf4cf46764d9c630f3fe4abaa7245be9417e56e9f52b8f65/rpds_py-0.30.0-cp313-cp313t-win_amd64.whl", hash = "sha256:f14fc5df50a716f7ece6a80b6c78bb35ea2ca47c499e422aa4463455dd96d56d", size = 225768, upload-time = "2025-11-30T20:23:25.908Z" }, + { url = "https://files.pythonhosted.org/packages/86/81/dad16382ebbd3d0e0328776d8fd7ca94220e4fa0798d1dc5e7da48cb3201/rpds_py-0.30.0-cp314-cp314-macosx_10_12_x86_64.whl", hash = "sha256:68f19c879420aa08f61203801423f6cd5ac5f0ac4ac82a2368a9fcd6a9a075e0", size = 362099, upload-time = "2025-11-30T20:23:27.316Z" }, + { url = "https://files.pythonhosted.org/packages/2b/60/19f7884db5d5603edf3c6bce35408f45ad3e97e10007df0e17dd57af18f8/rpds_py-0.30.0-cp314-cp314-macosx_11_0_arm64.whl", hash = "sha256:ec7c4490c672c1a0389d319b3a9cfcd098dcdc4783991553c332a15acf7249be", size = 353192, upload-time = "2025-11-30T20:23:29.151Z" }, + { url = "https://files.pythonhosted.org/packages/bf/c4/76eb0e1e72d1a9c4703c69607cec123c29028bff28ce41588792417098ac/rpds_py-0.30.0-cp314-cp314-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:f251c812357a3fed308d684a5079ddfb9d933860fc6de89f2b7ab00da481e65f", size = 384080, upload-time = "2025-11-30T20:23:30.785Z" }, + { url = "https://files.pythonhosted.org/packages/72/87/87ea665e92f3298d1b26d78814721dc39ed8d2c74b86e83348d6b48a6f31/rpds_py-0.30.0-cp314-cp314-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:ac98b175585ecf4c0348fd7b29c3864bda53b805c773cbf7bfdaffc8070c976f", size = 394841, upload-time = "2025-11-30T20:23:32.209Z" }, + { url = "https://files.pythonhosted.org/packages/77/ad/7783a89ca0587c15dcbf139b4a8364a872a25f861bdb88ed99f9b0dec985/rpds_py-0.30.0-cp314-cp314-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:3e62880792319dbeb7eb866547f2e35973289e7d5696c6e295476448f5b63c87", size = 516670, upload-time = "2025-11-30T20:23:33.742Z" }, + { url = "https://files.pythonhosted.org/packages/5b/3c/2882bdac942bd2172f3da574eab16f309ae10a3925644e969536553cb4ee/rpds_py-0.30.0-cp314-cp314-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:4e7fc54e0900ab35d041b0601431b0a0eb495f0851a0639b6ef90f7741b39a18", size = 408005, upload-time = "2025-11-30T20:23:35.253Z" }, + { url = "https://files.pythonhosted.org/packages/ce/81/9a91c0111ce1758c92516a3e44776920b579d9a7c09b2b06b642d4de3f0f/rpds_py-0.30.0-cp314-cp314-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:47e77dc9822d3ad616c3d5759ea5631a75e5809d5a28707744ef79d7a1bcfcad", size = 382112, upload-time = "2025-11-30T20:23:36.842Z" }, + { url = "https://files.pythonhosted.org/packages/cf/8e/1da49d4a107027e5fbc64daeab96a0706361a2918da10cb41769244b805d/rpds_py-0.30.0-cp314-cp314-manylinux_2_31_riscv64.whl", hash = "sha256:b4dc1a6ff022ff85ecafef7979a2c6eb423430e05f1165d6688234e62ba99a07", size = 399049, upload-time = "2025-11-30T20:23:38.343Z" }, + { url = "https://files.pythonhosted.org/packages/df/5a/7ee239b1aa48a127570ec03becbb29c9d5a9eb092febbd1699d567cae859/rpds_py-0.30.0-cp314-cp314-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:4559c972db3a360808309e06a74628b95eaccbf961c335c8fe0d590cf587456f", size = 415661, upload-time = "2025-11-30T20:23:40.263Z" }, + { url = "https://files.pythonhosted.org/packages/70/ea/caa143cf6b772f823bc7929a45da1fa83569ee49b11d18d0ada7f5ee6fd6/rpds_py-0.30.0-cp314-cp314-musllinux_1_2_aarch64.whl", hash = "sha256:0ed177ed9bded28f8deb6ab40c183cd1192aa0de40c12f38be4d59cd33cb5c65", size = 565606, upload-time = "2025-11-30T20:23:42.186Z" }, + { url = "https://files.pythonhosted.org/packages/64/91/ac20ba2d69303f961ad8cf55bf7dbdb4763f627291ba3d0d7d67333cced9/rpds_py-0.30.0-cp314-cp314-musllinux_1_2_i686.whl", hash = "sha256:ad1fa8db769b76ea911cb4e10f049d80bf518c104f15b3edb2371cc65375c46f", size = 591126, upload-time = "2025-11-30T20:23:44.086Z" }, + { url = "https://files.pythonhosted.org/packages/21/20/7ff5f3c8b00c8a95f75985128c26ba44503fb35b8e0259d812766ea966c7/rpds_py-0.30.0-cp314-cp314-musllinux_1_2_x86_64.whl", hash = "sha256:46e83c697b1f1c72b50e5ee5adb4353eef7406fb3f2043d64c33f20ad1c2fc53", size = 553371, upload-time = "2025-11-30T20:23:46.004Z" }, + { url = "https://files.pythonhosted.org/packages/72/c7/81dadd7b27c8ee391c132a6b192111ca58d866577ce2d9b0ca157552cce0/rpds_py-0.30.0-cp314-cp314-win32.whl", hash = "sha256:ee454b2a007d57363c2dfd5b6ca4a5d7e2c518938f8ed3b706e37e5d470801ed", size = 215298, upload-time = "2025-11-30T20:23:47.696Z" }, + { url = "https://files.pythonhosted.org/packages/3e/d2/1aaac33287e8cfb07aab2e6b8ac1deca62f6f65411344f1433c55e6f3eb8/rpds_py-0.30.0-cp314-cp314-win_amd64.whl", hash = "sha256:95f0802447ac2d10bcc69f6dc28fe95fdf17940367b21d34e34c737870758950", size = 228604, upload-time = "2025-11-30T20:23:49.501Z" }, + { url = "https://files.pythonhosted.org/packages/e8/95/ab005315818cc519ad074cb7784dae60d939163108bd2b394e60dc7b5461/rpds_py-0.30.0-cp314-cp314-win_arm64.whl", hash = "sha256:613aa4771c99f03346e54c3f038e4cc574ac09a3ddfb0e8878487335e96dead6", size = 222391, upload-time = "2025-11-30T20:23:50.96Z" }, + { url = "https://files.pythonhosted.org/packages/9e/68/154fe0194d83b973cdedcdcc88947a2752411165930182ae41d983dcefa6/rpds_py-0.30.0-cp314-cp314t-macosx_10_12_x86_64.whl", hash = "sha256:7e6ecfcb62edfd632e56983964e6884851786443739dbfe3582947e87274f7cb", size = 364868, upload-time = "2025-11-30T20:23:52.494Z" }, + { url = "https://files.pythonhosted.org/packages/83/69/8bbc8b07ec854d92a8b75668c24d2abcb1719ebf890f5604c61c9369a16f/rpds_py-0.30.0-cp314-cp314t-macosx_11_0_arm64.whl", hash = "sha256:a1d0bc22a7cdc173fedebb73ef81e07faef93692b8c1ad3733b67e31e1b6e1b8", size = 353747, upload-time = "2025-11-30T20:23:54.036Z" }, + { url = "https://files.pythonhosted.org/packages/ab/00/ba2e50183dbd9abcce9497fa5149c62b4ff3e22d338a30d690f9af970561/rpds_py-0.30.0-cp314-cp314t-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0d08f00679177226c4cb8c5265012eea897c8ca3b93f429e546600c971bcbae7", size = 383795, upload-time = "2025-11-30T20:23:55.556Z" }, + { url = "https://files.pythonhosted.org/packages/05/6f/86f0272b84926bcb0e4c972262f54223e8ecc556b3224d281e6598fc9268/rpds_py-0.30.0-cp314-cp314t-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:5965af57d5848192c13534f90f9dd16464f3c37aaf166cc1da1cae1fd5a34898", size = 393330, upload-time = "2025-11-30T20:23:57.033Z" }, + { url = "https://files.pythonhosted.org/packages/cb/e9/0e02bb2e6dc63d212641da45df2b0bf29699d01715913e0d0f017ee29438/rpds_py-0.30.0-cp314-cp314t-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:9a4e86e34e9ab6b667c27f3211ca48f73dba7cd3d90f8d5b11be56e5dbc3fb4e", size = 518194, upload-time = "2025-11-30T20:23:58.637Z" }, + { url = "https://files.pythonhosted.org/packages/ee/ca/be7bca14cf21513bdf9c0606aba17d1f389ea2b6987035eb4f62bd923f25/rpds_py-0.30.0-cp314-cp314t-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:e5d3e6b26f2c785d65cc25ef1e5267ccbe1b069c5c21b8cc724efee290554419", size = 408340, upload-time = "2025-11-30T20:24:00.2Z" }, + { url = "https://files.pythonhosted.org/packages/c2/c7/736e00ebf39ed81d75544c0da6ef7b0998f8201b369acf842f9a90dc8fce/rpds_py-0.30.0-cp314-cp314t-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:626a7433c34566535b6e56a1b39a7b17ba961e97ce3b80ec62e6f1312c025551", size = 383765, upload-time = "2025-11-30T20:24:01.759Z" }, + { url = "https://files.pythonhosted.org/packages/4a/3f/da50dfde9956aaf365c4adc9533b100008ed31aea635f2b8d7b627e25b49/rpds_py-0.30.0-cp314-cp314t-manylinux_2_31_riscv64.whl", hash = "sha256:acd7eb3f4471577b9b5a41baf02a978e8bdeb08b4b355273994f8b87032000a8", size = 396834, upload-time = "2025-11-30T20:24:03.687Z" }, + { url = "https://files.pythonhosted.org/packages/4e/00/34bcc2565b6020eab2623349efbdec810676ad571995911f1abdae62a3a0/rpds_py-0.30.0-cp314-cp314t-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:fe5fa731a1fa8a0a56b0977413f8cacac1768dad38d16b3a296712709476fbd5", size = 415470, upload-time = "2025-11-30T20:24:05.232Z" }, + { url = "https://files.pythonhosted.org/packages/8c/28/882e72b5b3e6f718d5453bd4d0d9cf8df36fddeb4ddbbab17869d5868616/rpds_py-0.30.0-cp314-cp314t-musllinux_1_2_aarch64.whl", hash = "sha256:74a3243a411126362712ee1524dfc90c650a503502f135d54d1b352bd01f2404", size = 565630, upload-time = "2025-11-30T20:24:06.878Z" }, + { url = "https://files.pythonhosted.org/packages/3b/97/04a65539c17692de5b85c6e293520fd01317fd878ea1995f0367d4532fb1/rpds_py-0.30.0-cp314-cp314t-musllinux_1_2_i686.whl", hash = "sha256:3e8eeb0544f2eb0d2581774be4c3410356eba189529a6b3e36bbbf9696175856", size = 591148, upload-time = "2025-11-30T20:24:08.445Z" }, + { url = "https://files.pythonhosted.org/packages/85/70/92482ccffb96f5441aab93e26c4d66489eb599efdcf96fad90c14bbfb976/rpds_py-0.30.0-cp314-cp314t-musllinux_1_2_x86_64.whl", hash = "sha256:dbd936cde57abfee19ab3213cf9c26be06d60750e60a8e4dd85d1ab12c8b1f40", size = 556030, upload-time = "2025-11-30T20:24:10.956Z" }, + { url = "https://files.pythonhosted.org/packages/20/53/7c7e784abfa500a2b6b583b147ee4bb5a2b3747a9166bab52fec4b5b5e7d/rpds_py-0.30.0-cp314-cp314t-win32.whl", hash = "sha256:dc824125c72246d924f7f796b4f63c1e9dc810c7d9e2355864b3c3a73d59ade0", size = 211570, upload-time = "2025-11-30T20:24:12.735Z" }, + { url = "https://files.pythonhosted.org/packages/d0/02/fa464cdfbe6b26e0600b62c528b72d8608f5cc49f96b8d6e38c95d60c676/rpds_py-0.30.0-cp314-cp314t-win_amd64.whl", hash = "sha256:27f4b0e92de5bfbc6f86e43959e6edd1425c33b5e69aab0984a72047f2bcf1e3", size = 226532, upload-time = "2025-11-30T20:24:14.634Z" }, + { url = "https://files.pythonhosted.org/packages/69/71/3f34339ee70521864411f8b6992e7ab13ac30d8e4e3309e07c7361767d91/rpds_py-0.30.0-pp311-pypy311_pp73-macosx_10_12_x86_64.whl", hash = "sha256:c2262bdba0ad4fc6fb5545660673925c2d2a5d9e2e0fb603aad545427be0fc58", size = 372292, upload-time = "2025-11-30T20:24:16.537Z" }, + { url = "https://files.pythonhosted.org/packages/57/09/f183df9b8f2d66720d2ef71075c59f7e1b336bec7ee4c48f0a2b06857653/rpds_py-0.30.0-pp311-pypy311_pp73-macosx_11_0_arm64.whl", hash = "sha256:ee6af14263f25eedc3bb918a3c04245106a42dfd4f5c2285ea6f997b1fc3f89a", size = 362128, upload-time = "2025-11-30T20:24:18.086Z" }, + { url = "https://files.pythonhosted.org/packages/7a/68/5c2594e937253457342e078f0cc1ded3dd7b2ad59afdbf2d354869110a02/rpds_py-0.30.0-pp311-pypy311_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:3adbb8179ce342d235c31ab8ec511e66c73faa27a47e076ccc92421add53e2bb", size = 391542, upload-time = "2025-11-30T20:24:20.092Z" }, + { url = "https://files.pythonhosted.org/packages/49/5c/31ef1afd70b4b4fbdb2800249f34c57c64beb687495b10aec0365f53dfc4/rpds_py-0.30.0-pp311-pypy311_pp73-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:250fa00e9543ac9b97ac258bd37367ff5256666122c2d0f2bc97577c60a1818c", size = 404004, upload-time = "2025-11-30T20:24:22.231Z" }, + { url = "https://files.pythonhosted.org/packages/e3/63/0cfbea38d05756f3440ce6534d51a491d26176ac045e2707adc99bb6e60a/rpds_py-0.30.0-pp311-pypy311_pp73-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:9854cf4f488b3d57b9aaeb105f06d78e5529d3145b1e4a41750167e8c213c6d3", size = 527063, upload-time = "2025-11-30T20:24:24.302Z" }, + { url = "https://files.pythonhosted.org/packages/42/e6/01e1f72a2456678b0f618fc9a1a13f882061690893c192fcad9f2926553a/rpds_py-0.30.0-pp311-pypy311_pp73-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:993914b8e560023bc0a8bf742c5f303551992dcb85e247b1e5c7f4a7d145bda5", size = 413099, upload-time = "2025-11-30T20:24:25.916Z" }, + { url = "https://files.pythonhosted.org/packages/b8/25/8df56677f209003dcbb180765520c544525e3ef21ea72279c98b9aa7c7fb/rpds_py-0.30.0-pp311-pypy311_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:58edca431fb9b29950807e301826586e5bbf24163677732429770a697ffe6738", size = 392177, upload-time = "2025-11-30T20:24:27.834Z" }, + { url = "https://files.pythonhosted.org/packages/4a/b4/0a771378c5f16f8115f796d1f437950158679bcd2a7c68cf251cfb00ed5b/rpds_py-0.30.0-pp311-pypy311_pp73-manylinux_2_31_riscv64.whl", hash = "sha256:dea5b552272a944763b34394d04577cf0f9bd013207bc32323b5a89a53cf9c2f", size = 406015, upload-time = "2025-11-30T20:24:29.457Z" }, + { url = "https://files.pythonhosted.org/packages/36/d8/456dbba0af75049dc6f63ff295a2f92766b9d521fa00de67a2bd6427d57a/rpds_py-0.30.0-pp311-pypy311_pp73-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:ba3af48635eb83d03f6c9735dfb21785303e73d22ad03d489e88adae6eab8877", size = 423736, upload-time = "2025-11-30T20:24:31.22Z" }, + { url = "https://files.pythonhosted.org/packages/13/64/b4d76f227d5c45a7e0b796c674fd81b0a6c4fbd48dc29271857d8219571c/rpds_py-0.30.0-pp311-pypy311_pp73-musllinux_1_2_aarch64.whl", hash = "sha256:dff13836529b921e22f15cb099751209a60009731a68519630a24d61f0b1b30a", size = 573981, upload-time = "2025-11-30T20:24:32.934Z" }, + { url = "https://files.pythonhosted.org/packages/20/91/092bacadeda3edf92bf743cc96a7be133e13a39cdbfd7b5082e7ab638406/rpds_py-0.30.0-pp311-pypy311_pp73-musllinux_1_2_i686.whl", hash = "sha256:1b151685b23929ab7beec71080a8889d4d6d9fa9a983d213f07121205d48e2c4", size = 599782, upload-time = "2025-11-30T20:24:35.169Z" }, + { url = "https://files.pythonhosted.org/packages/d1/b7/b95708304cd49b7b6f82fdd039f1748b66ec2b21d6a45180910802f1abf1/rpds_py-0.30.0-pp311-pypy311_pp73-musllinux_1_2_x86_64.whl", hash = "sha256:ac37f9f516c51e5753f27dfdef11a88330f04de2d564be3991384b2f3535d02e", size = 562191, upload-time = "2025-11-30T20:24:36.853Z" }, +] + +[[package]] +name = "scanpy" +version = "1.11.5" +source = { registry = "https://pypi.org/simple" } +resolution-markers = [ + "python_full_version < '3.12'", +] +dependencies = [ + { name = "anndata", marker = "python_full_version < '3.12'" }, + { name = "h5py", marker = "python_full_version < '3.12'" }, + { name = "joblib", marker = "python_full_version < '3.12'" }, + { name = "legacy-api-wrap", marker = "python_full_version < '3.12'" }, + { name = "matplotlib", marker = "python_full_version < '3.12'" }, + { name = "natsort", marker = "python_full_version < '3.12'" }, + { name = "networkx", marker = "python_full_version < '3.12'" }, + { name = "numba", marker = "python_full_version < '3.12'" }, + { name = "numpy", marker = "python_full_version < '3.12'" }, + { name = "packaging", marker = "python_full_version < '3.12'" }, + { name = "pandas", marker = "python_full_version < '3.12'" }, + { name = "patsy", marker = "python_full_version < '3.12'" }, + { name = "pynndescent", marker = "python_full_version < '3.12'" }, + { name = "scikit-learn", marker = "python_full_version < '3.12'" }, + { name = "scipy", marker = "python_full_version < '3.12'" }, + { name = "seaborn", marker = "python_full_version < '3.12'" }, + { name = "session-info2", marker = "python_full_version < '3.12'" }, + { name = "statsmodels", marker = "python_full_version < '3.12'" }, + { name = "tqdm", marker = "python_full_version < '3.12'" }, + { name = "typing-extensions", marker = "python_full_version < '3.12'" }, + { name = "umap-learn", marker = "python_full_version < '3.12'" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/d2/a8/285f1a9c995906b7e0ae3c399208fe67cfba8126dd31359dfef0908f6edc/scanpy-1.11.5.tar.gz", hash = "sha256:b2ef5476dfb1144b7dd0fae90b0198699c7988e6b27f083904150642c7ba6b89", size = 14088122, upload-time = "2025-10-21T08:24:43.999Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/32/e9/c1d43543da87cd27e8e2a74db85cf0b6c5cff2d5f04a86bd584d2fbc2bb0/scanpy-1.11.5-py3-none-any.whl", hash = "sha256:fcd383ddcf7acbf7c0ca232c25ad51b00aec9f8d2f7c8954b8c6ee0962257166", size = 2097836, upload-time = "2025-10-21T08:24:41.741Z" }, +] + +[[package]] +name = "scanpy" +version = "1.12" +source = { registry = "https://pypi.org/simple" } +resolution-markers = [ + "python_full_version >= '3.12'", +] +dependencies = [ + { name = "anndata", marker = "python_full_version >= '3.12'" }, + { name = "fast-array-utils", extra = ["accel", "sparse"], marker = "python_full_version >= '3.12'" }, + { name = "h5py", marker = "python_full_version >= '3.12'" }, + { name = "joblib", marker = "python_full_version >= '3.12'" }, + { name = "legacy-api-wrap", marker = "python_full_version >= '3.12'" }, + { name = "matplotlib", marker = "python_full_version >= '3.12'" }, + { name = "natsort", marker = "python_full_version >= '3.12'" }, + { name = "networkx", marker = "python_full_version >= '3.12'" }, + { name = "numba", marker = "python_full_version >= '3.12'" }, + { name = "numpy", marker = "python_full_version >= '3.12'" }, + { name = "packaging", marker = "python_full_version >= '3.12'" }, + { name = "pandas", marker = "python_full_version >= '3.12'" }, + { name = "patsy", marker = "python_full_version >= '3.12'" }, + { name = "pynndescent", marker = "python_full_version >= '3.12'" }, + { name = "scikit-learn", marker = "python_full_version >= '3.12'" }, + { name = "scipy", marker = "python_full_version >= '3.12'" }, + { name = "seaborn", marker = "python_full_version >= '3.12'" }, + { name = "session-info2", marker = "python_full_version >= '3.12'" }, + { name = "statsmodels", marker = "python_full_version >= '3.12'" }, + { name = "tqdm", marker = "python_full_version >= '3.12'" }, + { name = "typing-extensions", marker = "python_full_version == '3.12.*'" }, + { name = "umap-learn", marker = "python_full_version >= '3.12'" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/0e/3e/180968c66be48f9dab747330beb2056df5bb7a115a56d3700da149c48916/scanpy-1.12.tar.gz", hash = "sha256:8139840bb948ce0aa0798c9b8b88c1df4f06c27641a792f0995d39cd4dcf858a", size = 14418589, upload-time = "2026-01-23T13:25:23.414Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/44/f0/000ac705a3d5b8744c6eabfce6b413b131829542ffec05020b1e931ffed4/scanpy-1.12-py3-none-any.whl", hash = "sha256:0b89827f9ba9fea8fce5a49b311e9ce34a23f922b7d8506fa845a2dc92ef0bfe", size = 2148747, upload-time = "2026-01-23T13:25:20.84Z" }, +] + +[[package]] +name = "scikit-learn" +version = "1.8.0" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "joblib" }, + { name = "numpy" }, + { name = "scipy" }, + { name = "threadpoolctl" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/0e/d4/40988bf3b8e34feec1d0e6a051446b1f66225f8529b9309becaeef62b6c4/scikit_learn-1.8.0.tar.gz", hash = "sha256:9bccbb3b40e3de10351f8f5068e105d0f4083b1a65fa07b6634fbc401a6287fd", size = 7335585, upload-time = "2025-12-10T07:08:53.618Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/c9/92/53ea2181da8ac6bf27170191028aee7251f8f841f8d3edbfdcaf2008fde9/scikit_learn-1.8.0-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:146b4d36f800c013d267b29168813f7a03a43ecd2895d04861f1240b564421da", size = 8595835, upload-time = "2025-12-10T07:07:39.385Z" }, + { url = "https://files.pythonhosted.org/packages/01/18/d154dc1638803adf987910cdd07097d9c526663a55666a97c124d09fb96a/scikit_learn-1.8.0-cp311-cp311-macosx_12_0_arm64.whl", hash = "sha256:f984ca4b14914e6b4094c5d52a32ea16b49832c03bd17a110f004db3c223e8e1", size = 8080381, upload-time = "2025-12-10T07:07:41.93Z" }, + { url = "https://files.pythonhosted.org/packages/8a/44/226142fcb7b7101e64fdee5f49dbe6288d4c7af8abf593237b70fca080a4/scikit_learn-1.8.0-cp311-cp311-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:5e30adb87f0cc81c7690a84f7932dd66be5bac57cfe16b91cb9151683a4a2d3b", size = 8799632, upload-time = "2025-12-10T07:07:43.899Z" }, + { url = "https://files.pythonhosted.org/packages/36/4d/4a67f30778a45d542bbea5db2dbfa1e9e100bf9ba64aefe34215ba9f11f6/scikit_learn-1.8.0-cp311-cp311-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:ada8121bcb4dac28d930febc791a69f7cb1673c8495e5eee274190b73a4559c1", size = 9103788, upload-time = "2025-12-10T07:07:45.982Z" }, + { url = "https://files.pythonhosted.org/packages/89/3c/45c352094cfa60050bcbb967b1faf246b22e93cb459f2f907b600f2ceda5/scikit_learn-1.8.0-cp311-cp311-win_amd64.whl", hash = "sha256:c57b1b610bd1f40ba43970e11ce62821c2e6569e4d74023db19c6b26f246cb3b", size = 8081706, upload-time = "2025-12-10T07:07:48.111Z" }, + { url = "https://files.pythonhosted.org/packages/3d/46/5416595bb395757f754feb20c3d776553a386b661658fb21b7c814e89efe/scikit_learn-1.8.0-cp311-cp311-win_arm64.whl", hash = "sha256:2838551e011a64e3053ad7618dda9310175f7515f1742fa2d756f7c874c05961", size = 7688451, upload-time = "2025-12-10T07:07:49.873Z" }, + { url = "https://files.pythonhosted.org/packages/90/74/e6a7cc4b820e95cc38cf36cd74d5aa2b42e8ffc2d21fe5a9a9c45c1c7630/scikit_learn-1.8.0-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:5fb63362b5a7ddab88e52b6dbb47dac3fd7dafeee740dc6c8d8a446ddedade8e", size = 8548242, upload-time = "2025-12-10T07:07:51.568Z" }, + { url = "https://files.pythonhosted.org/packages/49/d8/9be608c6024d021041c7f0b3928d4749a706f4e2c3832bbede4fb4f58c95/scikit_learn-1.8.0-cp312-cp312-macosx_12_0_arm64.whl", hash = "sha256:5025ce924beccb28298246e589c691fe1b8c1c96507e6d27d12c5fadd85bfd76", size = 8079075, upload-time = "2025-12-10T07:07:53.697Z" }, + { url = "https://files.pythonhosted.org/packages/dd/47/f187b4636ff80cc63f21cd40b7b2d177134acaa10f6bb73746130ee8c2e5/scikit_learn-1.8.0-cp312-cp312-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:4496bb2cf7a43ce1a2d7524a79e40bc5da45cf598dbf9545b7e8316ccba47bb4", size = 8660492, upload-time = "2025-12-10T07:07:55.574Z" }, + { url = "https://files.pythonhosted.org/packages/97/74/b7a304feb2b49df9fafa9382d4d09061a96ee9a9449a7cbea7988dda0828/scikit_learn-1.8.0-cp312-cp312-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:a0bcfe4d0d14aec44921545fd2af2338c7471de9cb701f1da4c9d85906ab847a", size = 8931904, upload-time = "2025-12-10T07:07:57.666Z" }, + { url = "https://files.pythonhosted.org/packages/9f/c4/0ab22726a04ede56f689476b760f98f8f46607caecff993017ac1b64aa5d/scikit_learn-1.8.0-cp312-cp312-win_amd64.whl", hash = "sha256:35c007dedb2ffe38fe3ee7d201ebac4a2deccd2408e8621d53067733e3c74809", size = 8019359, upload-time = "2025-12-10T07:07:59.838Z" }, + { url = "https://files.pythonhosted.org/packages/24/90/344a67811cfd561d7335c1b96ca21455e7e472d281c3c279c4d3f2300236/scikit_learn-1.8.0-cp312-cp312-win_arm64.whl", hash = "sha256:8c497fff237d7b4e07e9ef1a640887fa4fb765647f86fbe00f969ff6280ce2bb", size = 7641898, upload-time = "2025-12-10T07:08:01.36Z" }, + { url = "https://files.pythonhosted.org/packages/03/aa/e22e0768512ce9255eba34775be2e85c2048da73da1193e841707f8f039c/scikit_learn-1.8.0-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:0d6ae97234d5d7079dc0040990a6f7aeb97cb7fa7e8945f1999a429b23569e0a", size = 8513770, upload-time = "2025-12-10T07:08:03.251Z" }, + { url = "https://files.pythonhosted.org/packages/58/37/31b83b2594105f61a381fc74ca19e8780ee923be2d496fcd8d2e1147bd99/scikit_learn-1.8.0-cp313-cp313-macosx_12_0_arm64.whl", hash = "sha256:edec98c5e7c128328124a029bceb09eda2d526997780fef8d65e9a69eead963e", size = 8044458, upload-time = "2025-12-10T07:08:05.336Z" }, + { url = "https://files.pythonhosted.org/packages/2d/5a/3f1caed8765f33eabb723596666da4ebbf43d11e96550fb18bdec42b467b/scikit_learn-1.8.0-cp313-cp313-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:74b66d8689d52ed04c271e1329f0c61635bcaf5b926db9b12d58914cdc01fe57", size = 8610341, upload-time = "2025-12-10T07:08:07.732Z" }, + { url = "https://files.pythonhosted.org/packages/38/cf/06896db3f71c75902a8e9943b444a56e727418f6b4b4a90c98c934f51ed4/scikit_learn-1.8.0-cp313-cp313-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:8fdf95767f989b0cfedb85f7ed8ca215d4be728031f56ff5a519ee1e3276dc2e", size = 8900022, upload-time = "2025-12-10T07:08:09.862Z" }, + { url = "https://files.pythonhosted.org/packages/1c/f9/9b7563caf3ec8873e17a31401858efab6b39a882daf6c1bfa88879c0aa11/scikit_learn-1.8.0-cp313-cp313-win_amd64.whl", hash = "sha256:2de443b9373b3b615aec1bb57f9baa6bb3a9bd093f1269ba95c17d870422b271", size = 7989409, upload-time = "2025-12-10T07:08:12.028Z" }, + { url = "https://files.pythonhosted.org/packages/49/bd/1f4001503650e72c4f6009ac0c4413cb17d2d601cef6f71c0453da2732fc/scikit_learn-1.8.0-cp313-cp313-win_arm64.whl", hash = "sha256:eddde82a035681427cbedded4e6eff5e57fa59216c2e3e90b10b19ab1d0a65c3", size = 7619760, upload-time = "2025-12-10T07:08:13.688Z" }, + { url = "https://files.pythonhosted.org/packages/d2/7d/a630359fc9dcc95496588c8d8e3245cc8fd81980251079bc09c70d41d951/scikit_learn-1.8.0-cp313-cp313t-macosx_10_13_x86_64.whl", hash = "sha256:7cc267b6108f0a1499a734167282c00c4ebf61328566b55ef262d48e9849c735", size = 8826045, upload-time = "2025-12-10T07:08:15.215Z" }, + { url = "https://files.pythonhosted.org/packages/cc/56/a0c86f6930cfcd1c7054a2bc417e26960bb88d32444fe7f71d5c2cfae891/scikit_learn-1.8.0-cp313-cp313t-macosx_12_0_arm64.whl", hash = "sha256:fe1c011a640a9f0791146011dfd3c7d9669785f9fed2b2a5f9e207536cf5c2fd", size = 8420324, upload-time = "2025-12-10T07:08:17.561Z" }, + { url = "https://files.pythonhosted.org/packages/46/1e/05962ea1cebc1cf3876667ecb14c283ef755bf409993c5946ade3b77e303/scikit_learn-1.8.0-cp313-cp313t-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:72358cce49465d140cc4e7792015bb1f0296a9742d5622c67e31399b75468b9e", size = 8680651, upload-time = "2025-12-10T07:08:19.952Z" }, + { url = "https://files.pythonhosted.org/packages/fe/56/a85473cd75f200c9759e3a5f0bcab2d116c92a8a02ee08ccd73b870f8bb4/scikit_learn-1.8.0-cp313-cp313t-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:80832434a6cc114f5219211eec13dcbc16c2bac0e31ef64c6d346cde3cf054cb", size = 8925045, upload-time = "2025-12-10T07:08:22.11Z" }, + { url = "https://files.pythonhosted.org/packages/cc/b7/64d8cfa896c64435ae57f4917a548d7ac7a44762ff9802f75a79b77cb633/scikit_learn-1.8.0-cp313-cp313t-win_amd64.whl", hash = "sha256:ee787491dbfe082d9c3013f01f5991658b0f38aa8177e4cd4bf434c58f551702", size = 8507994, upload-time = "2025-12-10T07:08:23.943Z" }, + { url = "https://files.pythonhosted.org/packages/5e/37/e192ea709551799379958b4c4771ec507347027bb7c942662c7fbeba31cb/scikit_learn-1.8.0-cp313-cp313t-win_arm64.whl", hash = "sha256:bf97c10a3f5a7543f9b88cbf488d33d175e9146115a451ae34568597ba33dcde", size = 7869518, upload-time = "2025-12-10T07:08:25.71Z" }, + { url = "https://files.pythonhosted.org/packages/24/05/1af2c186174cc92dcab2233f327336058c077d38f6fe2aceb08e6ab4d509/scikit_learn-1.8.0-cp314-cp314-macosx_10_15_x86_64.whl", hash = "sha256:c22a2da7a198c28dd1a6e1136f19c830beab7fdca5b3e5c8bba8394f8a5c45b3", size = 8528667, upload-time = "2025-12-10T07:08:27.541Z" }, + { url = "https://files.pythonhosted.org/packages/a8/25/01c0af38fe969473fb292bba9dc2b8f9b451f3112ff242c647fee3d0dfe7/scikit_learn-1.8.0-cp314-cp314-macosx_12_0_arm64.whl", hash = "sha256:6b595b07a03069a2b1740dc08c2299993850ea81cce4fe19b2421e0c970de6b7", size = 8066524, upload-time = "2025-12-10T07:08:29.822Z" }, + { url = "https://files.pythonhosted.org/packages/be/ce/a0623350aa0b68647333940ee46fe45086c6060ec604874e38e9ab7d8e6c/scikit_learn-1.8.0-cp314-cp314-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:29ffc74089f3d5e87dfca4c2c8450f88bdc61b0fc6ed5d267f3988f19a1309f6", size = 8657133, upload-time = "2025-12-10T07:08:31.865Z" }, + { url = "https://files.pythonhosted.org/packages/b8/cb/861b41341d6f1245e6ca80b1c1a8c4dfce43255b03df034429089ca2a2c5/scikit_learn-1.8.0-cp314-cp314-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:fb65db5d7531bccf3a4f6bec3462223bea71384e2cda41da0f10b7c292b9e7c4", size = 8923223, upload-time = "2025-12-10T07:08:34.166Z" }, + { url = "https://files.pythonhosted.org/packages/76/18/a8def8f91b18cd1ba6e05dbe02540168cb24d47e8dcf69e8d00b7da42a08/scikit_learn-1.8.0-cp314-cp314-win_amd64.whl", hash = "sha256:56079a99c20d230e873ea40753102102734c5953366972a71d5cb39a32bc40c6", size = 8096518, upload-time = "2025-12-10T07:08:36.339Z" }, + { url = "https://files.pythonhosted.org/packages/d1/77/482076a678458307f0deb44e29891d6022617b2a64c840c725495bee343f/scikit_learn-1.8.0-cp314-cp314-win_arm64.whl", hash = "sha256:3bad7565bc9cf37ce19a7c0d107742b320c1285df7aab1a6e2d28780df167242", size = 7754546, upload-time = "2025-12-10T07:08:38.128Z" }, + { url = "https://files.pythonhosted.org/packages/2d/d1/ef294ca754826daa043b2a104e59960abfab4cf653891037d19dd5b6f3cf/scikit_learn-1.8.0-cp314-cp314t-macosx_10_15_x86_64.whl", hash = "sha256:4511be56637e46c25721e83d1a9cea9614e7badc7040c4d573d75fbe257d6fd7", size = 8848305, upload-time = "2025-12-10T07:08:41.013Z" }, + { url = "https://files.pythonhosted.org/packages/5b/e2/b1f8b05138ee813b8e1a4149f2f0d289547e60851fd1bb268886915adbda/scikit_learn-1.8.0-cp314-cp314t-macosx_12_0_arm64.whl", hash = "sha256:a69525355a641bf8ef136a7fa447672fb54fe8d60cab5538d9eb7c6438543fb9", size = 8432257, upload-time = "2025-12-10T07:08:42.873Z" }, + { url = "https://files.pythonhosted.org/packages/26/11/c32b2138a85dcb0c99f6afd13a70a951bfdff8a6ab42d8160522542fb647/scikit_learn-1.8.0-cp314-cp314t-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:c2656924ec73e5939c76ac4c8b026fc203b83d8900362eb2599d8aee80e4880f", size = 8678673, upload-time = "2025-12-10T07:08:45.362Z" }, + { url = "https://files.pythonhosted.org/packages/c7/57/51f2384575bdec454f4fe4e7a919d696c9ebce914590abf3e52d47607ab8/scikit_learn-1.8.0-cp314-cp314t-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:15fc3b5d19cc2be65404786857f2e13c70c83dd4782676dd6814e3b89dc8f5b9", size = 8922467, upload-time = "2025-12-10T07:08:47.408Z" }, + { url = "https://files.pythonhosted.org/packages/35/4d/748c9e2872637a57981a04adc038dacaa16ba8ca887b23e34953f0b3f742/scikit_learn-1.8.0-cp314-cp314t-win_amd64.whl", hash = "sha256:00d6f1d66fbcf4eba6e356e1420d33cc06c70a45bb1363cd6f6a8e4ebbbdece2", size = 8774395, upload-time = "2025-12-10T07:08:49.337Z" }, + { url = "https://files.pythonhosted.org/packages/60/22/d7b2ebe4704a5e50790ba089d5c2ae308ab6bb852719e6c3bd4f04c3a363/scikit_learn-1.8.0-cp314-cp314t-win_arm64.whl", hash = "sha256:f28dd15c6bb0b66ba09728cf09fd8736c304be29409bd8445a080c1280619e8c", size = 8002647, upload-time = "2025-12-10T07:08:51.601Z" }, +] + +[[package]] +name = "scipy" +version = "1.16.3" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "numpy" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/0a/ca/d8ace4f98322d01abcd52d381134344bf7b431eba7ed8b42bdea5a3c2ac9/scipy-1.16.3.tar.gz", hash = "sha256:01e87659402762f43bd2fee13370553a17ada367d42e7487800bf2916535aecb", size = 30597883, upload-time = "2025-10-28T17:38:54.068Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/9b/5f/6f37d7439de1455ce9c5a556b8d1db0979f03a796c030bafdf08d35b7bf9/scipy-1.16.3-cp311-cp311-macosx_10_14_x86_64.whl", hash = "sha256:40be6cf99e68b6c4321e9f8782e7d5ff8265af28ef2cd56e9c9b2638fa08ad97", size = 36630881, upload-time = "2025-10-28T17:31:47.104Z" }, + { url = "https://files.pythonhosted.org/packages/7c/89/d70e9f628749b7e4db2aa4cd89735502ff3f08f7b9b27d2e799485987cd9/scipy-1.16.3-cp311-cp311-macosx_12_0_arm64.whl", hash = "sha256:8be1ca9170fcb6223cc7c27f4305d680ded114a1567c0bd2bfcbf947d1b17511", size = 28941012, upload-time = "2025-10-28T17:31:53.411Z" }, + { url = "https://files.pythonhosted.org/packages/a8/a8/0e7a9a6872a923505dbdf6bb93451edcac120363131c19013044a1e7cb0c/scipy-1.16.3-cp311-cp311-macosx_14_0_arm64.whl", hash = "sha256:bea0a62734d20d67608660f69dcda23e7f90fb4ca20974ab80b6ed40df87a005", size = 20931935, upload-time = "2025-10-28T17:31:57.361Z" }, + { url = "https://files.pythonhosted.org/packages/bd/c7/020fb72bd79ad798e4dbe53938543ecb96b3a9ac3fe274b7189e23e27353/scipy-1.16.3-cp311-cp311-macosx_14_0_x86_64.whl", hash = "sha256:2a207a6ce9c24f1951241f4693ede2d393f59c07abc159b2cb2be980820e01fb", size = 23534466, upload-time = "2025-10-28T17:32:01.875Z" }, + { url = "https://files.pythonhosted.org/packages/be/a0/668c4609ce6dbf2f948e167836ccaf897f95fb63fa231c87da7558a374cd/scipy-1.16.3-cp311-cp311-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:532fb5ad6a87e9e9cd9c959b106b73145a03f04c7d57ea3e6f6bb60b86ab0876", size = 33593618, upload-time = "2025-10-28T17:32:06.902Z" }, + { url = "https://files.pythonhosted.org/packages/ca/6e/8942461cf2636cdae083e3eb72622a7fbbfa5cf559c7d13ab250a5dbdc01/scipy-1.16.3-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:0151a0749efeaaab78711c78422d413c583b8cdd2011a3c1d6c794938ee9fdb2", size = 35899798, upload-time = "2025-10-28T17:32:12.665Z" }, + { url = "https://files.pythonhosted.org/packages/79/e8/d0f33590364cdbd67f28ce79368b373889faa4ee959588beddf6daef9abe/scipy-1.16.3-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:b7180967113560cca57418a7bc719e30366b47959dd845a93206fbed693c867e", size = 36226154, upload-time = "2025-10-28T17:32:17.961Z" }, + { url = "https://files.pythonhosted.org/packages/39/c1/1903de608c0c924a1749c590064e65810f8046e437aba6be365abc4f7557/scipy-1.16.3-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:deb3841c925eeddb6afc1e4e4a45e418d19ec7b87c5df177695224078e8ec733", size = 38878540, upload-time = "2025-10-28T17:32:23.907Z" }, + { url = "https://files.pythonhosted.org/packages/f1/d0/22ec7036ba0b0a35bccb7f25ab407382ed34af0b111475eb301c16f8a2e5/scipy-1.16.3-cp311-cp311-win_amd64.whl", hash = "sha256:53c3844d527213631e886621df5695d35e4f6a75f620dca412bcd292f6b87d78", size = 38722107, upload-time = "2025-10-28T17:32:29.921Z" }, + { url = "https://files.pythonhosted.org/packages/7b/60/8a00e5a524bb3bf8898db1650d350f50e6cffb9d7a491c561dc9826c7515/scipy-1.16.3-cp311-cp311-win_arm64.whl", hash = "sha256:9452781bd879b14b6f055b26643703551320aa8d79ae064a71df55c00286a184", size = 25506272, upload-time = "2025-10-28T17:32:34.577Z" }, + { url = "https://files.pythonhosted.org/packages/40/41/5bf55c3f386b1643812f3a5674edf74b26184378ef0f3e7c7a09a7e2ca7f/scipy-1.16.3-cp312-cp312-macosx_10_14_x86_64.whl", hash = "sha256:81fc5827606858cf71446a5e98715ba0e11f0dbc83d71c7409d05486592a45d6", size = 36659043, upload-time = "2025-10-28T17:32:40.285Z" }, + { url = "https://files.pythonhosted.org/packages/1e/0f/65582071948cfc45d43e9870bf7ca5f0e0684e165d7c9ef4e50d783073eb/scipy-1.16.3-cp312-cp312-macosx_12_0_arm64.whl", hash = "sha256:c97176013d404c7346bf57874eaac5187d969293bf40497140b0a2b2b7482e07", size = 28898986, upload-time = "2025-10-28T17:32:45.325Z" }, + { url = "https://files.pythonhosted.org/packages/96/5e/36bf3f0ac298187d1ceadde9051177d6a4fe4d507e8f59067dc9dd39e650/scipy-1.16.3-cp312-cp312-macosx_14_0_arm64.whl", hash = "sha256:2b71d93c8a9936046866acebc915e2af2e292b883ed6e2cbe5c34beb094b82d9", size = 20889814, upload-time = "2025-10-28T17:32:49.277Z" }, + { url = "https://files.pythonhosted.org/packages/80/35/178d9d0c35394d5d5211bbff7ac4f2986c5488b59506fef9e1de13ea28d3/scipy-1.16.3-cp312-cp312-macosx_14_0_x86_64.whl", hash = "sha256:3d4a07a8e785d80289dfe66b7c27d8634a773020742ec7187b85ccc4b0e7b686", size = 23565795, upload-time = "2025-10-28T17:32:53.337Z" }, + { url = "https://files.pythonhosted.org/packages/fa/46/d1146ff536d034d02f83c8afc3c4bab2eddb634624d6529a8512f3afc9da/scipy-1.16.3-cp312-cp312-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:0553371015692a898e1aa858fed67a3576c34edefa6b7ebdb4e9dde49ce5c203", size = 33349476, upload-time = "2025-10-28T17:32:58.353Z" }, + { url = "https://files.pythonhosted.org/packages/79/2e/415119c9ab3e62249e18c2b082c07aff907a273741b3f8160414b0e9193c/scipy-1.16.3-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:72d1717fd3b5e6ec747327ce9bda32d5463f472c9dce9f54499e81fbd50245a1", size = 35676692, upload-time = "2025-10-28T17:33:03.88Z" }, + { url = "https://files.pythonhosted.org/packages/27/82/df26e44da78bf8d2aeaf7566082260cfa15955a5a6e96e6a29935b64132f/scipy-1.16.3-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:1fb2472e72e24d1530debe6ae078db70fb1605350c88a3d14bc401d6306dbffe", size = 36019345, upload-time = "2025-10-28T17:33:09.773Z" }, + { url = "https://files.pythonhosted.org/packages/82/31/006cbb4b648ba379a95c87262c2855cd0d09453e500937f78b30f02fa1cd/scipy-1.16.3-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:c5192722cffe15f9329a3948c4b1db789fbb1f05c97899187dcf009b283aea70", size = 38678975, upload-time = "2025-10-28T17:33:15.809Z" }, + { url = "https://files.pythonhosted.org/packages/c2/7f/acbd28c97e990b421af7d6d6cd416358c9c293fc958b8529e0bd5d2a2a19/scipy-1.16.3-cp312-cp312-win_amd64.whl", hash = "sha256:56edc65510d1331dae01ef9b658d428e33ed48b4f77b1d51caf479a0253f96dc", size = 38555926, upload-time = "2025-10-28T17:33:21.388Z" }, + { url = "https://files.pythonhosted.org/packages/ce/69/c5c7807fd007dad4f48e0a5f2153038dc96e8725d3345b9ee31b2b7bed46/scipy-1.16.3-cp312-cp312-win_arm64.whl", hash = "sha256:a8a26c78ef223d3e30920ef759e25625a0ecdd0d60e5a8818b7513c3e5384cf2", size = 25463014, upload-time = "2025-10-28T17:33:25.975Z" }, + { url = "https://files.pythonhosted.org/packages/72/f1/57e8327ab1508272029e27eeef34f2302ffc156b69e7e233e906c2a5c379/scipy-1.16.3-cp313-cp313-macosx_10_14_x86_64.whl", hash = "sha256:d2ec56337675e61b312179a1ad124f5f570c00f920cc75e1000025451b88241c", size = 36617856, upload-time = "2025-10-28T17:33:31.375Z" }, + { url = "https://files.pythonhosted.org/packages/44/13/7e63cfba8a7452eb756306aa2fd9b37a29a323b672b964b4fdeded9a3f21/scipy-1.16.3-cp313-cp313-macosx_12_0_arm64.whl", hash = "sha256:16b8bc35a4cc24db80a0ec836a9286d0e31b2503cb2fd7ff7fb0e0374a97081d", size = 28874306, upload-time = "2025-10-28T17:33:36.516Z" }, + { url = "https://files.pythonhosted.org/packages/15/65/3a9400efd0228a176e6ec3454b1fa998fbbb5a8defa1672c3f65706987db/scipy-1.16.3-cp313-cp313-macosx_14_0_arm64.whl", hash = "sha256:5803c5fadd29de0cf27fa08ccbfe7a9e5d741bf63e4ab1085437266f12460ff9", size = 20865371, upload-time = "2025-10-28T17:33:42.094Z" }, + { url = "https://files.pythonhosted.org/packages/33/d7/eda09adf009a9fb81827194d4dd02d2e4bc752cef16737cc4ef065234031/scipy-1.16.3-cp313-cp313-macosx_14_0_x86_64.whl", hash = "sha256:b81c27fc41954319a943d43b20e07c40bdcd3ff7cf013f4fb86286faefe546c4", size = 23524877, upload-time = "2025-10-28T17:33:48.483Z" }, + { url = "https://files.pythonhosted.org/packages/7d/6b/3f911e1ebc364cb81320223a3422aab7d26c9c7973109a9cd0f27c64c6c0/scipy-1.16.3-cp313-cp313-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:0c3b4dd3d9b08dbce0f3440032c52e9e2ab9f96ade2d3943313dfe51a7056959", size = 33342103, upload-time = "2025-10-28T17:33:56.495Z" }, + { url = "https://files.pythonhosted.org/packages/21/f6/4bfb5695d8941e5c570a04d9fcd0d36bce7511b7d78e6e75c8f9791f82d0/scipy-1.16.3-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:7dc1360c06535ea6116a2220f760ae572db9f661aba2d88074fe30ec2aa1ff88", size = 35697297, upload-time = "2025-10-28T17:34:04.722Z" }, + { url = "https://files.pythonhosted.org/packages/04/e1/6496dadbc80d8d896ff72511ecfe2316b50313bfc3ebf07a3f580f08bd8c/scipy-1.16.3-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:663b8d66a8748051c3ee9c96465fb417509315b99c71550fda2591d7dd634234", size = 36021756, upload-time = "2025-10-28T17:34:13.482Z" }, + { url = "https://files.pythonhosted.org/packages/fe/bd/a8c7799e0136b987bda3e1b23d155bcb31aec68a4a472554df5f0937eef7/scipy-1.16.3-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:eab43fae33a0c39006a88096cd7b4f4ef545ea0447d250d5ac18202d40b6611d", size = 38696566, upload-time = "2025-10-28T17:34:22.384Z" }, + { url = "https://files.pythonhosted.org/packages/cd/01/1204382461fcbfeb05b6161b594f4007e78b6eba9b375382f79153172b4d/scipy-1.16.3-cp313-cp313-win_amd64.whl", hash = "sha256:062246acacbe9f8210de8e751b16fc37458213f124bef161a5a02c7a39284304", size = 38529877, upload-time = "2025-10-28T17:35:51.076Z" }, + { url = "https://files.pythonhosted.org/packages/7f/14/9d9fbcaa1260a94f4bb5b64ba9213ceb5d03cd88841fe9fd1ffd47a45b73/scipy-1.16.3-cp313-cp313-win_arm64.whl", hash = "sha256:50a3dbf286dbc7d84f176f9a1574c705f277cb6565069f88f60db9eafdbe3ee2", size = 25455366, upload-time = "2025-10-28T17:35:59.014Z" }, + { url = "https://files.pythonhosted.org/packages/e2/a3/9ec205bd49f42d45d77f1730dbad9ccf146244c1647605cf834b3a8c4f36/scipy-1.16.3-cp313-cp313t-macosx_10_14_x86_64.whl", hash = "sha256:fb4b29f4cf8cc5a8d628bc8d8e26d12d7278cd1f219f22698a378c3d67db5e4b", size = 37027931, upload-time = "2025-10-28T17:34:31.451Z" }, + { url = "https://files.pythonhosted.org/packages/25/06/ca9fd1f3a4589cbd825b1447e5db3a8ebb969c1eaf22c8579bd286f51b6d/scipy-1.16.3-cp313-cp313t-macosx_12_0_arm64.whl", hash = "sha256:8d09d72dc92742988b0e7750bddb8060b0c7079606c0d24a8cc8e9c9c11f9079", size = 29400081, upload-time = "2025-10-28T17:34:39.087Z" }, + { url = "https://files.pythonhosted.org/packages/6a/56/933e68210d92657d93fb0e381683bc0e53a965048d7358ff5fbf9e6a1b17/scipy-1.16.3-cp313-cp313t-macosx_14_0_arm64.whl", hash = "sha256:03192a35e661470197556de24e7cb1330d84b35b94ead65c46ad6f16f6b28f2a", size = 21391244, upload-time = "2025-10-28T17:34:45.234Z" }, + { url = "https://files.pythonhosted.org/packages/a8/7e/779845db03dc1418e215726329674b40576879b91814568757ff0014ad65/scipy-1.16.3-cp313-cp313t-macosx_14_0_x86_64.whl", hash = "sha256:57d01cb6f85e34f0946b33caa66e892aae072b64b034183f3d87c4025802a119", size = 23929753, upload-time = "2025-10-28T17:34:51.793Z" }, + { url = "https://files.pythonhosted.org/packages/4c/4b/f756cf8161d5365dcdef9e5f460ab226c068211030a175d2fc7f3f41ca64/scipy-1.16.3-cp313-cp313t-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:96491a6a54e995f00a28a3c3badfff58fd093bf26cd5fb34a2188c8c756a3a2c", size = 33496912, upload-time = "2025-10-28T17:34:59.8Z" }, + { url = "https://files.pythonhosted.org/packages/09/b5/222b1e49a58668f23839ca1542a6322bb095ab8d6590d4f71723869a6c2c/scipy-1.16.3-cp313-cp313t-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:cd13e354df9938598af2be05822c323e97132d5e6306b83a3b4ee6724c6e522e", size = 35802371, upload-time = "2025-10-28T17:35:08.173Z" }, + { url = "https://files.pythonhosted.org/packages/c1/8d/5964ef68bb31829bde27611f8c9deeac13764589fe74a75390242b64ca44/scipy-1.16.3-cp313-cp313t-musllinux_1_2_aarch64.whl", hash = "sha256:63d3cdacb8a824a295191a723ee5e4ea7768ca5ca5f2838532d9f2e2b3ce2135", size = 36190477, upload-time = "2025-10-28T17:35:16.7Z" }, + { url = "https://files.pythonhosted.org/packages/ab/f2/b31d75cb9b5fa4dd39a0a931ee9b33e7f6f36f23be5ef560bf72e0f92f32/scipy-1.16.3-cp313-cp313t-musllinux_1_2_x86_64.whl", hash = "sha256:e7efa2681ea410b10dde31a52b18b0154d66f2485328830e45fdf183af5aefc6", size = 38796678, upload-time = "2025-10-28T17:35:26.354Z" }, + { url = "https://files.pythonhosted.org/packages/b4/1e/b3723d8ff64ab548c38d87055483714fefe6ee20e0189b62352b5e015bb1/scipy-1.16.3-cp313-cp313t-win_amd64.whl", hash = "sha256:2d1ae2cf0c350e7705168ff2429962a89ad90c2d49d1dd300686d8b2a5af22fc", size = 38640178, upload-time = "2025-10-28T17:35:35.304Z" }, + { url = "https://files.pythonhosted.org/packages/8e/f3/d854ff38789aca9b0cc23008d607ced9de4f7ab14fa1ca4329f86b3758ca/scipy-1.16.3-cp313-cp313t-win_arm64.whl", hash = "sha256:0c623a54f7b79dd88ef56da19bc2873afec9673a48f3b85b18e4d402bdd29a5a", size = 25803246, upload-time = "2025-10-28T17:35:42.155Z" }, + { url = "https://files.pythonhosted.org/packages/99/f6/99b10fd70f2d864c1e29a28bbcaa0c6340f9d8518396542d9ea3b4aaae15/scipy-1.16.3-cp314-cp314-macosx_10_14_x86_64.whl", hash = "sha256:875555ce62743e1d54f06cdf22c1e0bc47b91130ac40fe5d783b6dfa114beeb6", size = 36606469, upload-time = "2025-10-28T17:36:08.741Z" }, + { url = "https://files.pythonhosted.org/packages/4d/74/043b54f2319f48ea940dd025779fa28ee360e6b95acb7cd188fad4391c6b/scipy-1.16.3-cp314-cp314-macosx_12_0_arm64.whl", hash = "sha256:bb61878c18a470021fb515a843dc7a76961a8daceaaaa8bad1332f1bf4b54657", size = 28872043, upload-time = "2025-10-28T17:36:16.599Z" }, + { url = "https://files.pythonhosted.org/packages/4d/e1/24b7e50cc1c4ee6ffbcb1f27fe9f4c8b40e7911675f6d2d20955f41c6348/scipy-1.16.3-cp314-cp314-macosx_14_0_arm64.whl", hash = "sha256:f2622206f5559784fa5c4b53a950c3c7c1cf3e84ca1b9c4b6c03f062f289ca26", size = 20862952, upload-time = "2025-10-28T17:36:22.966Z" }, + { url = "https://files.pythonhosted.org/packages/dd/3a/3e8c01a4d742b730df368e063787c6808597ccb38636ed821d10b39ca51b/scipy-1.16.3-cp314-cp314-macosx_14_0_x86_64.whl", hash = "sha256:7f68154688c515cdb541a31ef8eb66d8cd1050605be9dcd74199cbd22ac739bc", size = 23508512, upload-time = "2025-10-28T17:36:29.731Z" }, + { url = "https://files.pythonhosted.org/packages/1f/60/c45a12b98ad591536bfe5330cb3cfe1850d7570259303563b1721564d458/scipy-1.16.3-cp314-cp314-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:8b3c820ddb80029fe9f43d61b81d8b488d3ef8ca010d15122b152db77dc94c22", size = 33413639, upload-time = "2025-10-28T17:36:37.982Z" }, + { url = "https://files.pythonhosted.org/packages/71/bc/35957d88645476307e4839712642896689df442f3e53b0fa016ecf8a3357/scipy-1.16.3-cp314-cp314-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:d3837938ae715fc0fe3c39c0202de3a8853aff22ca66781ddc2ade7554b7e2cc", size = 35704729, upload-time = "2025-10-28T17:36:46.547Z" }, + { url = "https://files.pythonhosted.org/packages/3b/15/89105e659041b1ca11c386e9995aefacd513a78493656e57789f9d9eab61/scipy-1.16.3-cp314-cp314-musllinux_1_2_aarch64.whl", hash = "sha256:aadd23f98f9cb069b3bd64ddc900c4d277778242e961751f77a8cb5c4b946fb0", size = 36086251, upload-time = "2025-10-28T17:36:55.161Z" }, + { url = "https://files.pythonhosted.org/packages/1a/87/c0ea673ac9c6cc50b3da2196d860273bc7389aa69b64efa8493bdd25b093/scipy-1.16.3-cp314-cp314-musllinux_1_2_x86_64.whl", hash = "sha256:b7c5f1bda1354d6a19bc6af73a649f8285ca63ac6b52e64e658a5a11d4d69800", size = 38716681, upload-time = "2025-10-28T17:37:04.1Z" }, + { url = "https://files.pythonhosted.org/packages/91/06/837893227b043fb9b0d13e4bd7586982d8136cb249ffb3492930dab905b8/scipy-1.16.3-cp314-cp314-win_amd64.whl", hash = "sha256:e5d42a9472e7579e473879a1990327830493a7047506d58d73fc429b84c1d49d", size = 39358423, upload-time = "2025-10-28T17:38:20.005Z" }, + { url = "https://files.pythonhosted.org/packages/95/03/28bce0355e4d34a7c034727505a02d19548549e190bedd13a721e35380b7/scipy-1.16.3-cp314-cp314-win_arm64.whl", hash = "sha256:6020470b9d00245926f2d5bb93b119ca0340f0d564eb6fbaad843eaebf9d690f", size = 26135027, upload-time = "2025-10-28T17:38:24.966Z" }, + { url = "https://files.pythonhosted.org/packages/b2/6f/69f1e2b682efe9de8fe9f91040f0cd32f13cfccba690512ba4c582b0bc29/scipy-1.16.3-cp314-cp314t-macosx_10_14_x86_64.whl", hash = "sha256:e1d27cbcb4602680a49d787d90664fa4974063ac9d4134813332a8c53dbe667c", size = 37028379, upload-time = "2025-10-28T17:37:14.061Z" }, + { url = "https://files.pythonhosted.org/packages/7c/2d/e826f31624a5ebbab1cd93d30fd74349914753076ed0593e1d56a98c4fb4/scipy-1.16.3-cp314-cp314t-macosx_12_0_arm64.whl", hash = "sha256:9b9c9c07b6d56a35777a1b4cc8966118fb16cfd8daf6743867d17d36cfad2d40", size = 29400052, upload-time = "2025-10-28T17:37:21.709Z" }, + { url = "https://files.pythonhosted.org/packages/69/27/d24feb80155f41fd1f156bf144e7e049b4e2b9dd06261a242905e3bc7a03/scipy-1.16.3-cp314-cp314t-macosx_14_0_arm64.whl", hash = "sha256:3a4c460301fb2cffb7f88528f30b3127742cff583603aa7dc964a52c463b385d", size = 21391183, upload-time = "2025-10-28T17:37:29.559Z" }, + { url = "https://files.pythonhosted.org/packages/f8/d3/1b229e433074c5738a24277eca520a2319aac7465eea7310ea6ae0e98ae2/scipy-1.16.3-cp314-cp314t-macosx_14_0_x86_64.whl", hash = "sha256:f667a4542cc8917af1db06366d3f78a5c8e83badd56409f94d1eac8d8d9133fa", size = 23930174, upload-time = "2025-10-28T17:37:36.306Z" }, + { url = "https://files.pythonhosted.org/packages/16/9d/d9e148b0ec680c0f042581a2be79a28a7ab66c0c4946697f9e7553ead337/scipy-1.16.3-cp314-cp314t-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:f379b54b77a597aa7ee5e697df0d66903e41b9c85a6dd7946159e356319158e8", size = 33497852, upload-time = "2025-10-28T17:37:42.228Z" }, + { url = "https://files.pythonhosted.org/packages/2f/22/4e5f7561e4f98b7bea63cf3fd7934bff1e3182e9f1626b089a679914d5c8/scipy-1.16.3-cp314-cp314t-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:4aff59800a3b7f786b70bfd6ab551001cb553244988d7d6b8299cb1ea653b353", size = 35798595, upload-time = "2025-10-28T17:37:48.102Z" }, + { url = "https://files.pythonhosted.org/packages/83/42/6644d714c179429fc7196857866f219fef25238319b650bb32dde7bf7a48/scipy-1.16.3-cp314-cp314t-musllinux_1_2_aarch64.whl", hash = "sha256:da7763f55885045036fabcebd80144b757d3db06ab0861415d1c3b7c69042146", size = 36186269, upload-time = "2025-10-28T17:37:53.72Z" }, + { url = "https://files.pythonhosted.org/packages/ac/70/64b4d7ca92f9cf2e6fc6aaa2eecf80bb9b6b985043a9583f32f8177ea122/scipy-1.16.3-cp314-cp314t-musllinux_1_2_x86_64.whl", hash = "sha256:ffa6eea95283b2b8079b821dc11f50a17d0571c92b43e2b5b12764dc5f9b285d", size = 38802779, upload-time = "2025-10-28T17:37:59.393Z" }, + { url = "https://files.pythonhosted.org/packages/61/82/8d0e39f62764cce5ffd5284131e109f07cf8955aef9ab8ed4e3aa5e30539/scipy-1.16.3-cp314-cp314t-win_amd64.whl", hash = "sha256:d9f48cafc7ce94cf9b15c6bffdc443a81a27bf7075cf2dcd5c8b40f85d10c4e7", size = 39471128, upload-time = "2025-10-28T17:38:05.259Z" }, + { url = "https://files.pythonhosted.org/packages/64/47/a494741db7280eae6dc033510c319e34d42dd41b7ac0c7ead39354d1a2b5/scipy-1.16.3-cp314-cp314t-win_arm64.whl", hash = "sha256:21d9d6b197227a12dcbf9633320a4e34c6b0e51c57268df255a0942983bac562", size = 26464127, upload-time = "2025-10-28T17:38:11.34Z" }, +] + +[[package]] +name = "seaborn" +version = "0.13.2" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "matplotlib" }, + { name = "numpy" }, + { name = "pandas" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/86/59/a451d7420a77ab0b98f7affa3a1d78a313d2f7281a57afb1a34bae8ab412/seaborn-0.13.2.tar.gz", hash = "sha256:93e60a40988f4d65e9f4885df477e2fdaff6b73a9ded434c1ab356dd57eefff7", size = 1457696, upload-time = "2024-01-25T13:21:52.551Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/83/11/00d3c3dfc25ad54e731d91449895a79e4bf2384dc3ac01809010ba88f6d5/seaborn-0.13.2-py3-none-any.whl", hash = "sha256:636f8336facf092165e27924f223d3c62ca560b1f2bb5dff7ab7fad265361987", size = 294914, upload-time = "2024-01-25T13:21:49.598Z" }, +] + +[[package]] +name = "secretstorage" +version = "3.5.0" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "cryptography" }, + { name = "jeepney" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/1c/03/e834bcd866f2f8a49a85eaff47340affa3bfa391ee9912a952a1faa68c7b/secretstorage-3.5.0.tar.gz", hash = "sha256:f04b8e4689cbce351744d5537bf6b1329c6fc68f91fa666f60a380edddcd11be", size = 19884, upload-time = "2025-11-23T19:02:53.191Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/b7/46/f5af3402b579fd5e11573ce652019a67074317e18c1935cc0b4ba9b35552/secretstorage-3.5.0-py3-none-any.whl", hash = "sha256:0ce65888c0725fcb2c5bc0fdb8e5438eece02c523557ea40ce0703c266248137", size = 15554, upload-time = "2025-11-23T19:02:51.545Z" }, +] + +[[package]] +name = "session-info" +version = "1.0.1" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "stdlib-list" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/f5/dc/4a0c85aee2034be368d3ca293a563128122dde6db6e1bc9ca9ef3472c731/session_info-1.0.1.tar.gz", hash = "sha256:d71950d5a8ce7f7f7d5e86aa208c148c4e50b5440b77d5544d422b48e4f3ed41", size = 24663, upload-time = "2025-04-11T16:08:43.504Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/c5/c4/f6b7c0ec5241a2bde90c7ba1eca6ba44f8488bcedafe9072c79593015ec0/session_info-1.0.1-py3-none-any.whl", hash = "sha256:451d191e51816070b9f21a6ff3f6eb5d6015ae2738e8db63ac4e6398260a5838", size = 9119, upload-time = "2025-04-11T16:08:42.612Z" }, +] + +[[package]] +name = "session-info2" +version = "0.4" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/f7/f8/56469d9bd2cb09475cda54633660fbd2aa62f73079a1432835319f2b1a64/session_info2-0.4.tar.gz", hash = "sha256:bb01bf7c320301d6cbcfad36b85cca7befe537ffd60269be38ae9e1a956f4aa4", size = 25126, upload-time = "2026-02-07T12:05:48.182Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/44/7c/64d18f2374e19ba9bee52dee885ec81f808a1863ed0995495b83319b88bc/session_info2-0.4-py3-none-any.whl", hash = "sha256:1c06604853acd43d8cdcc9e815efbdf5534d728234e8374dea1eef29496bb1df", size = 17776, upload-time = "2026-02-07T12:05:46.878Z" }, +] + +[[package]] +name = "setuptools" +version = "82.0.0" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/82/f3/748f4d6f65d1756b9ae577f329c951cda23fb900e4de9f70900ced962085/setuptools-82.0.0.tar.gz", hash = "sha256:22e0a2d69474c6ae4feb01951cb69d515ed23728cf96d05513d36e42b62b37cb", size = 1144893, upload-time = "2026-02-08T15:08:40.206Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/e1/c6/76dc613121b793286a3f91621d7b75a2b493e0390ddca50f11993eadf192/setuptools-82.0.0-py3-none-any.whl", hash = "sha256:70b18734b607bd1da571d097d236cfcfacaf01de45717d59e6e04b96877532e0", size = 1003468, upload-time = "2026-02-08T15:08:38.723Z" }, +] + +[[package]] +name = "six" +version = "1.17.0" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/94/e7/b2c673351809dca68a0e064b6af791aa332cf192da575fd474ed7d6f16a2/six-1.17.0.tar.gz", hash = "sha256:ff70335d468e7eb6ec65b95b99d3a2836546063f63acc5171de367e834932a81", size = 34031, upload-time = "2024-12-04T17:35:28.174Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/b7/ce/149a00dd41f10bc29e5921b496af8b574d8413afcd5e30dfa0ed46c2cc5e/six-1.17.0-py2.py3-none-any.whl", hash = "sha256:4721f391ed90541fddacab5acf947aa0d3dc7d27b2e1e8eda2be8970586c3274", size = 11050, upload-time = "2024-12-04T17:35:26.475Z" }, +] + +[[package]] +name = "snowballstemmer" +version = "3.0.1" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/75/a7/9810d872919697c9d01295633f5d574fb416d47e535f258272ca1f01f447/snowballstemmer-3.0.1.tar.gz", hash = "sha256:6d5eeeec8e9f84d4d56b847692bacf79bc2c8e90c7f80ca4444ff8b6f2e52895", size = 105575, upload-time = "2025-05-09T16:34:51.843Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/c8/78/3565d011c61f5a43488987ee32b6f3f656e7f107ac2782dd57bdd7d91d9a/snowballstemmer-3.0.1-py3-none-any.whl", hash = "sha256:6cd7b3897da8d6c9ffb968a6781fa6532dce9c3618a4b127d920dab764a19064", size = 103274, upload-time = "2025-05-09T16:34:50.371Z" }, +] + +[[package]] +name = "soupsieve" +version = "2.8.3" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/7b/ae/2d9c981590ed9999a0d91755b47fc74f74de286b0f5cee14c9269041e6c4/soupsieve-2.8.3.tar.gz", hash = "sha256:3267f1eeea4251fb42728b6dfb746edc9acaffc4a45b27e19450b676586e8349", size = 118627, upload-time = "2026-01-20T04:27:02.457Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/46/2c/1462b1d0a634697ae9e55b3cecdcb64788e8b7d63f54d923fcd0bb140aed/soupsieve-2.8.3-py3-none-any.whl", hash = "sha256:ed64f2ba4eebeab06cc4962affce381647455978ffc1e36bb79a545b91f45a95", size = 37016, upload-time = "2026-01-20T04:27:01.012Z" }, +] + +[[package]] +name = "sphinx" +version = "9.0.4" +source = { registry = "https://pypi.org/simple" } +resolution-markers = [ + "python_full_version < '3.12'", +] +dependencies = [ + { name = "alabaster", marker = "python_full_version < '3.12'" }, + { name = "babel", marker = "python_full_version < '3.12'" }, + { name = "colorama", marker = "python_full_version < '3.12' and sys_platform == 'win32'" }, + { name = "docutils", marker = "python_full_version < '3.12'" }, + { name = "imagesize", marker = "python_full_version < '3.12'" }, + { name = "jinja2", marker = "python_full_version < '3.12'" }, + { name = "packaging", marker = "python_full_version < '3.12'" }, + { name = "pygments", marker = "python_full_version < '3.12'" }, + { name = "requests", marker = "python_full_version < '3.12'" }, + { name = "roman-numerals", marker = "python_full_version < '3.12'" }, + { name = "snowballstemmer", marker = "python_full_version < '3.12'" }, + { name = "sphinxcontrib-applehelp", marker = "python_full_version < '3.12'" }, + { name = "sphinxcontrib-devhelp", marker = "python_full_version < '3.12'" }, + { name = "sphinxcontrib-htmlhelp", marker = "python_full_version < '3.12'" }, + { name = "sphinxcontrib-jsmath", marker = "python_full_version < '3.12'" }, + { name = "sphinxcontrib-qthelp", marker = "python_full_version < '3.12'" }, + { name = "sphinxcontrib-serializinghtml", marker = "python_full_version < '3.12'" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/42/50/a8c6ccc36d5eacdfd7913ddccd15a9cee03ecafc5ee2bc40e1f168d85022/sphinx-9.0.4.tar.gz", hash = "sha256:594ef59d042972abbc581d8baa577404abe4e6c3b04ef61bd7fc2acbd51f3fa3", size = 8710502, upload-time = "2025-12-04T07:45:27.343Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/c6/3f/4bbd76424c393caead2e1eb89777f575dee5c8653e2d4b6afd7a564f5974/sphinx-9.0.4-py3-none-any.whl", hash = "sha256:5bebc595a5e943ea248b99c13814c1c5e10b3ece718976824ffa7959ff95fffb", size = 3917713, upload-time = "2025-12-04T07:45:24.944Z" }, +] + +[[package]] +name = "sphinx" +version = "9.1.0" +source = { registry = "https://pypi.org/simple" } +resolution-markers = [ + "python_full_version >= '3.12'", +] +dependencies = [ + { name = "alabaster", marker = "python_full_version >= '3.12'" }, + { name = "babel", marker = "python_full_version >= '3.12'" }, + { name = "colorama", marker = "python_full_version >= '3.12' and sys_platform == 'win32'" }, + { name = "docutils", marker = "python_full_version >= '3.12'" }, + { name = "imagesize", marker = "python_full_version >= '3.12'" }, + { name = "jinja2", marker = "python_full_version >= '3.12'" }, + { name = "packaging", marker = "python_full_version >= '3.12'" }, + { name = "pygments", marker = "python_full_version >= '3.12'" }, + { name = "requests", marker = "python_full_version >= '3.12'" }, + { name = "roman-numerals", marker = "python_full_version >= '3.12'" }, + { name = "snowballstemmer", marker = "python_full_version >= '3.12'" }, + { name = "sphinxcontrib-applehelp", marker = "python_full_version >= '3.12'" }, + { name = "sphinxcontrib-devhelp", marker = "python_full_version >= '3.12'" }, + { name = "sphinxcontrib-htmlhelp", marker = "python_full_version >= '3.12'" }, + { name = "sphinxcontrib-jsmath", marker = "python_full_version >= '3.12'" }, + { name = "sphinxcontrib-qthelp", marker = "python_full_version >= '3.12'" }, + { name = "sphinxcontrib-serializinghtml", marker = "python_full_version >= '3.12'" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/cd/bd/f08eb0f4eed5c83f1ba2a3bd18f7745a2b1525fad70660a1c00224ec468a/sphinx-9.1.0.tar.gz", hash = "sha256:7741722357dd75f8190766926071fed3bdc211c74dd2d7d4df5404da95930ddb", size = 8718324, upload-time = "2025-12-31T15:09:27.646Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/73/f7/b1884cb3188ab181fc81fa00c266699dab600f927a964df02ec3d5d1916a/sphinx-9.1.0-py3-none-any.whl", hash = "sha256:c84fdd4e782504495fe4f2c0b3413d6c2bf388589bb352d439b2a3bb99991978", size = 3921742, upload-time = "2025-12-31T15:09:25.561Z" }, +] + +[[package]] +name = "sphinx-autoapi" +version = "3.7.0" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "astroid", version = "3.3.11", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.12'" }, + { name = "astroid", version = "4.1.0", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.12'" }, + { name = "jinja2" }, + { name = "pyyaml" }, + { name = "sphinx", version = "9.0.4", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.12'" }, + { name = "sphinx", version = "9.1.0", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.12'" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/47/22/7ea4b660e98ffa271dbec5847b64738127955746d887f9596940279d30bf/sphinx_autoapi-3.7.0.tar.gz", hash = "sha256:5c8a934d788f00d11b8c8092536c7373592cce986820de8dd7daf6dfd79afd91", size = 58136, upload-time = "2026-02-11T05:24:29.86Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/d8/11/9825443890d3ef6b6a0db938054e7c806e9911509e0315fe984d00a090c1/sphinx_autoapi-3.7.0-py3-none-any.whl", hash = "sha256:5ea37271b50de08538cf6e33044ef4fb6e981ddb693060ec84f297005014fdfd", size = 36021, upload-time = "2026-02-11T05:24:28.657Z" }, +] + +[[package]] +name = "sphinx-autodoc-typehints" +version = "3.6.1" +source = { registry = "https://pypi.org/simple" } +resolution-markers = [ + "python_full_version < '3.12'", +] +dependencies = [ + { name = "sphinx", version = "9.0.4", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.12'" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/1d/f6/bdd93582b2aaad2cfe9eb5695a44883c8bc44572dd3c351a947acbb13789/sphinx_autodoc_typehints-3.6.1.tar.gz", hash = "sha256:fa0b686ae1b85965116c88260e5e4b82faec3687c2e94d6a10f9b36c3743e2fe", size = 37563, upload-time = "2026-01-02T15:23:46.543Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/dc/6a/c0360b115c81d449b3b73bf74b64ca773464d5c7b1b77bda87c5e874853b/sphinx_autodoc_typehints-3.6.1-py3-none-any.whl", hash = "sha256:dd818ba31d4c97f219a8c0fcacef280424f84a3589cedcb73003ad99c7da41ca", size = 20869, upload-time = "2026-01-02T15:23:45.194Z" }, +] + +[[package]] +name = "sphinx-autodoc-typehints" +version = "3.6.3" +source = { registry = "https://pypi.org/simple" } +resolution-markers = [ + "python_full_version >= '3.12'", +] +dependencies = [ + { name = "sphinx", version = "9.1.0", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.12'" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/64/5f/ebcaed1a67e623e4a7622808a8be6b0fd8344313e185f62e85a26b0ce26a/sphinx_autodoc_typehints-3.6.3.tar.gz", hash = "sha256:6c387b47d9ad5e75b157810af5bad46901f0a22708ed5e4adf466885a9c60910", size = 38288, upload-time = "2026-02-18T04:22:08.384Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/0a/bd/2b853836d152e40a27655828fdc02c5128f294ac452ad9a13424bb7f92fa/sphinx_autodoc_typehints-3.6.3-py3-none-any.whl", hash = "sha256:46ebc68fa85b320d55887a8d836a01e12e3b7744da973e70af8cedc74072aad5", size = 20882, upload-time = "2026-02-18T04:22:07.238Z" }, +] + +[[package]] +name = "sphinx-basic-ng" +version = "1.0.0b2" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "sphinx", version = "9.0.4", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.12'" }, + { name = "sphinx", version = "9.1.0", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.12'" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/98/0b/a866924ded68efec7a1759587a4e478aec7559d8165fac8b2ad1c0e774d6/sphinx_basic_ng-1.0.0b2.tar.gz", hash = "sha256:9ec55a47c90c8c002b5960c57492ec3021f5193cb26cebc2dc4ea226848651c9", size = 20736, upload-time = "2023-07-08T18:40:54.166Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/3c/dd/018ce05c532a22007ac58d4f45232514cd9d6dd0ee1dc374e309db830983/sphinx_basic_ng-1.0.0b2-py3-none-any.whl", hash = "sha256:eb09aedbabfb650607e9b4b68c9d240b90b1e1be221d6ad71d61c52e29f7932b", size = 22496, upload-time = "2023-07-08T18:40:52.659Z" }, +] + +[[package]] +name = "sphinx-book-theme" +version = "1.1.4" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "pydata-sphinx-theme" }, + { name = "sphinx", version = "9.0.4", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.12'" }, + { name = "sphinx", version = "9.1.0", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.12'" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/45/19/d002ed96bdc7738c15847c730e1e88282d738263deac705d5713b4d8fa94/sphinx_book_theme-1.1.4.tar.gz", hash = "sha256:73efe28af871d0a89bd05856d300e61edce0d5b2fbb7984e84454be0fedfe9ed", size = 439188, upload-time = "2025-02-20T16:32:32.581Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/51/9e/c41d68be04eef5b6202b468e0f90faf0c469f3a03353f2a218fd78279710/sphinx_book_theme-1.1.4-py3-none-any.whl", hash = "sha256:843b3f5c8684640f4a2d01abd298beb66452d1b2394cd9ef5be5ebd5640ea0e1", size = 433952, upload-time = "2025-02-20T16:32:31.009Z" }, +] + +[[package]] +name = "sphinx-copybutton" +version = "0.5.2" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "sphinx", version = "9.0.4", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.12'" }, + { name = "sphinx", version = "9.1.0", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.12'" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/fc/2b/a964715e7f5295f77509e59309959f4125122d648f86b4fe7d70ca1d882c/sphinx-copybutton-0.5.2.tar.gz", hash = "sha256:4cf17c82fb9646d1bc9ca92ac280813a3b605d8c421225fd9913154103ee1fbd", size = 23039, upload-time = "2023-04-14T08:10:22.998Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/9e/48/1ea60e74949eecb12cdd6ac43987f9fd331156388dcc2319b45e2ebb81bf/sphinx_copybutton-0.5.2-py3-none-any.whl", hash = "sha256:fb543fd386d917746c9a2c50360c7905b605726b9355cd26e9974857afeae06e", size = 13343, upload-time = "2023-04-14T08:10:20.844Z" }, +] + +[[package]] +name = "sphinx-design" +version = "0.7.0" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "sphinx", version = "9.0.4", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.12'" }, + { name = "sphinx", version = "9.1.0", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.12'" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/13/7b/804f311da4663a4aecc6cf7abd83443f3d4ded970826d0c958edc77d4527/sphinx_design-0.7.0.tar.gz", hash = "sha256:d2a3f5b19c24b916adb52f97c5f00efab4009ca337812001109084a740ec9b7a", size = 2203582, upload-time = "2026-01-19T13:12:53.297Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/30/cf/45dd359f6ca0c3762ce0490f681da242f0530c49c81050c035c016bfdd3a/sphinx_design-0.7.0-py3-none-any.whl", hash = "sha256:f82bf179951d58f55dca78ab3706aeafa496b741a91b1911d371441127d64282", size = 2220350, upload-time = "2026-01-19T13:12:51.077Z" }, +] + +[[package]] +name = "sphinx-rtd-theme" +version = "3.1.0" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "docutils" }, + { name = "sphinx", version = "9.0.4", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.12'" }, + { name = "sphinx", version = "9.1.0", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.12'" }, + { name = "sphinxcontrib-jquery" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/84/68/a1bfbf38c0f7bccc9b10bbf76b94606f64acb1552ae394f0b8285bfaea25/sphinx_rtd_theme-3.1.0.tar.gz", hash = "sha256:b44276f2c276e909239a4f6c955aa667aaafeb78597923b1c60babc76db78e4c", size = 7620915, upload-time = "2026-01-12T16:03:31.17Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/87/c7/b5c8015d823bfda1a346adb2c634a2101d50bb75d421eb6dcb31acd25ebc/sphinx_rtd_theme-3.1.0-py2.py3-none-any.whl", hash = "sha256:1785824ae8e6632060490f67cf3a72d404a85d2d9fc26bce3619944de5682b89", size = 7655617, upload-time = "2026-01-12T16:03:28.101Z" }, +] + +[[package]] +name = "sphinx-tabs" +version = "3.4.7" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "docutils" }, + { name = "pygments" }, + { name = "sphinx", version = "9.0.4", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.12'" }, + { name = "sphinx", version = "9.1.0", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.12'" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/6a/53/a9a91995cb365e589f413b77fc75f1c0e9b4ac61bfa8da52a779ad855cc0/sphinx-tabs-3.4.7.tar.gz", hash = "sha256:991ad4a424ff54119799ba1491701aa8130dd43509474aef45a81c42d889784d", size = 15891, upload-time = "2024-10-08T13:37:27.887Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/6b/c6/f47505b564b918a3ba60c1e99232d4942c4a7e44ecaae603e829e3d05dae/sphinx_tabs-3.4.7-py3-none-any.whl", hash = "sha256:c12d7a36fd413b369e9e9967a0a4015781b71a9c393575419834f19204bd1915", size = 9727, upload-time = "2024-10-08T13:37:26.192Z" }, +] + +[[package]] +name = "sphinxcontrib-applehelp" +version = "2.0.0" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/ba/6e/b837e84a1a704953c62ef8776d45c3e8d759876b4a84fe14eba2859106fe/sphinxcontrib_applehelp-2.0.0.tar.gz", hash = "sha256:2f29ef331735ce958efa4734873f084941970894c6090408b079c61b2e1c06d1", size = 20053, upload-time = "2024-07-29T01:09:00.465Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/5d/85/9ebeae2f76e9e77b952f4b274c27238156eae7979c5421fba91a28f4970d/sphinxcontrib_applehelp-2.0.0-py3-none-any.whl", hash = "sha256:4cd3f0ec4ac5dd9c17ec65e9ab272c9b867ea77425228e68ecf08d6b28ddbdb5", size = 119300, upload-time = "2024-07-29T01:08:58.99Z" }, +] + +[[package]] +name = "sphinxcontrib-bibtex" +version = "2.6.5" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "docutils" }, + { name = "pybtex" }, + { name = "pybtex-docutils" }, + { name = "sphinx", version = "9.0.4", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.12'" }, + { name = "sphinx", version = "9.1.0", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.12'" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/de/83/1488c9879f2fa3c2cbd6f666c7a3a42a1fa9e08462bec73281fa6c092cba/sphinxcontrib_bibtex-2.6.5.tar.gz", hash = "sha256:9b3224dd6fece9268ebd8c905dc0a83ff2f6c54148a9235fe70e9d1e9ff149c0", size = 118462, upload-time = "2025-06-27T10:40:14.061Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/9e/a0/3a612da94f828f26cabb247817393e79472c32b12c49222bf85fb6d7b6c8/sphinxcontrib_bibtex-2.6.5-py3-none-any.whl", hash = "sha256:455ea4509642ea0b28ede3721550273626f85af65af01f161bfd8e19dc1edd7d", size = 40410, upload-time = "2025-06-27T10:40:12.274Z" }, +] + +[[package]] +name = "sphinxcontrib-devhelp" +version = "2.0.0" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/f6/d2/5beee64d3e4e747f316bae86b55943f51e82bb86ecd325883ef65741e7da/sphinxcontrib_devhelp-2.0.0.tar.gz", hash = "sha256:411f5d96d445d1d73bb5d52133377b4248ec79db5c793ce7dbe59e074b4dd1ad", size = 12967, upload-time = "2024-07-29T01:09:23.417Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/35/7a/987e583882f985fe4d7323774889ec58049171828b58c2217e7f79cdf44e/sphinxcontrib_devhelp-2.0.0-py3-none-any.whl", hash = "sha256:aefb8b83854e4b0998877524d1029fd3e6879210422ee3780459e28a1f03a8a2", size = 82530, upload-time = "2024-07-29T01:09:21.945Z" }, +] + +[[package]] +name = "sphinxcontrib-htmlhelp" +version = "2.1.0" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/43/93/983afd9aa001e5201eab16b5a444ed5b9b0a7a010541e0ddfbbfd0b2470c/sphinxcontrib_htmlhelp-2.1.0.tar.gz", hash = "sha256:c9e2916ace8aad64cc13a0d233ee22317f2b9025b9cf3295249fa985cc7082e9", size = 22617, upload-time = "2024-07-29T01:09:37.889Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/0a/7b/18a8c0bcec9182c05a0b3ec2a776bba4ead82750a55ff798e8d406dae604/sphinxcontrib_htmlhelp-2.1.0-py3-none-any.whl", hash = "sha256:166759820b47002d22914d64a075ce08f4c46818e17cfc9470a9786b759b19f8", size = 98705, upload-time = "2024-07-29T01:09:36.407Z" }, +] + +[[package]] +name = "sphinxcontrib-jquery" +version = "4.1" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "sphinx", version = "9.0.4", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.12'" }, + { name = "sphinx", version = "9.1.0", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.12'" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/de/f3/aa67467e051df70a6330fe7770894b3e4f09436dea6881ae0b4f3d87cad8/sphinxcontrib-jquery-4.1.tar.gz", hash = "sha256:1620739f04e36a2c779f1a131a2dfd49b2fd07351bf1968ced074365933abc7a", size = 122331, upload-time = "2023-03-14T15:01:01.944Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/76/85/749bd22d1a68db7291c89e2ebca53f4306c3f205853cf31e9de279034c3c/sphinxcontrib_jquery-4.1-py2.py3-none-any.whl", hash = "sha256:f936030d7d0147dd026a4f2b5a57343d233f1fc7b363f68b3d4f1cb0993878ae", size = 121104, upload-time = "2023-03-14T15:01:00.356Z" }, +] + +[[package]] +name = "sphinxcontrib-jsmath" +version = "1.0.1" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/b2/e8/9ed3830aeed71f17c026a07a5097edcf44b692850ef215b161b8ad875729/sphinxcontrib-jsmath-1.0.1.tar.gz", hash = "sha256:a9925e4a4587247ed2191a22df5f6970656cb8ca2bd6284309578f2153e0c4b8", size = 5787, upload-time = "2019-01-21T16:10:16.347Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/c2/42/4c8646762ee83602e3fb3fbe774c2fac12f317deb0b5dbeeedd2d3ba4b77/sphinxcontrib_jsmath-1.0.1-py2.py3-none-any.whl", hash = "sha256:2ec2eaebfb78f3f2078e73666b1415417a116cc848b72e5172e596c871103178", size = 5071, upload-time = "2019-01-21T16:10:14.333Z" }, +] + +[[package]] +name = "sphinxcontrib-qthelp" +version = "2.0.0" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/68/bc/9104308fc285eb3e0b31b67688235db556cd5b0ef31d96f30e45f2e51cae/sphinxcontrib_qthelp-2.0.0.tar.gz", hash = "sha256:4fe7d0ac8fc171045be623aba3e2a8f613f8682731f9153bb2e40ece16b9bbab", size = 17165, upload-time = "2024-07-29T01:09:56.435Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/27/83/859ecdd180cacc13b1f7e857abf8582a64552ea7a061057a6c716e790fce/sphinxcontrib_qthelp-2.0.0-py3-none-any.whl", hash = "sha256:b18a828cdba941ccd6ee8445dbe72ffa3ef8cbe7505d8cd1fa0d42d3f2d5f3eb", size = 88743, upload-time = "2024-07-29T01:09:54.885Z" }, +] + +[[package]] +name = "sphinxcontrib-serializinghtml" +version = "2.0.0" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/3b/44/6716b257b0aa6bfd51a1b31665d1c205fb12cb5ad56de752dfa15657de2f/sphinxcontrib_serializinghtml-2.0.0.tar.gz", hash = "sha256:e9d912827f872c029017a53f0ef2180b327c3f7fd23c87229f7a8e8b70031d4d", size = 16080, upload-time = "2024-07-29T01:10:09.332Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/52/a7/d2782e4e3f77c8450f727ba74a8f12756d5ba823d81b941f1b04da9d033a/sphinxcontrib_serializinghtml-2.0.0-py3-none-any.whl", hash = "sha256:6e2cb0eef194e10c27ec0023bfeb25badbbb5868244cf5bc5bdc04e4464bf331", size = 92072, upload-time = "2024-07-29T01:10:08.203Z" }, +] + +[[package]] +name = "sphinxext-opengraph" +version = "0.13.0" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "sphinx", version = "9.0.4", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.12'" }, + { name = "sphinx", version = "9.1.0", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.12'" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/f6/c0/eb6838e3bae624ce6c8b90b245d17e84252863150e95efdb88f92c8aa3fb/sphinxext_opengraph-0.13.0.tar.gz", hash = "sha256:103335d08567ad8468faf1425f575e3b698e9621f9323949a6c8b96d9793e80b", size = 1026875, upload-time = "2025-08-29T12:20:31.066Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/bf/a4/66c1fd4f8fab88faf71cee04a945f9806ba0fef753f2cfc8be6353f64508/sphinxext_opengraph-0.13.0-py3-none-any.whl", hash = "sha256:936c07828edc9ad9a7b07908b29596dc84ed0b3ceaa77acdf51282d232d4d80e", size = 1004152, upload-time = "2025-08-29T12:20:29.072Z" }, +] + +[[package]] +name = "stack-data" +version = "0.6.3" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "asttokens" }, + { name = "executing" }, + { name = "pure-eval" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/28/e3/55dcc2cfbc3ca9c29519eb6884dd1415ecb53b0e934862d3559ddcb7e20b/stack_data-0.6.3.tar.gz", hash = "sha256:836a778de4fec4dcd1dcd89ed8abff8a221f58308462e1c4aa2a3cf30148f0b9", size = 44707, upload-time = "2023-09-30T13:58:05.479Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/f1/7b/ce1eafaf1a76852e2ec9b22edecf1daa58175c090266e9f6c64afcd81d91/stack_data-0.6.3-py3-none-any.whl", hash = "sha256:d5558e0c25a4cb0853cddad3d77da9891a08cb85dd9f9f91b9f8cd66e511e695", size = 24521, upload-time = "2023-09-30T13:58:03.53Z" }, +] + +[[package]] +name = "statsmodels" +version = "0.14.6" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "numpy" }, + { name = "packaging" }, + { name = "pandas" }, + { name = "patsy" }, + { name = "scipy" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/0d/81/e8d74b34f85285f7335d30c5e3c2d7c0346997af9f3debf9a0a9a63de184/statsmodels-0.14.6.tar.gz", hash = "sha256:4d17873d3e607d398b85126cd4ed7aad89e4e9d89fc744cdab1af3189a996c2a", size = 20689085, upload-time = "2025-12-05T23:08:39.522Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/a9/4d/df4dd089b406accfc3bb5ee53ba29bb3bdf5ae61643f86f8f604baa57656/statsmodels-0.14.6-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:6ad5c2810fc6c684254a7792bf1cbaf1606cdee2a253f8bd259c43135d87cfb4", size = 10121514, upload-time = "2025-12-05T19:28:16.521Z" }, + { url = "https://files.pythonhosted.org/packages/82/af/ec48daa7f861f993b91a0dcc791d66e1cf56510a235c5cbd2ab991a31d5c/statsmodels-0.14.6-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:341fa68a7403e10a95c7b6e41134b0da3a7b835ecff1eb266294408535a06eb6", size = 10003346, upload-time = "2025-12-05T19:28:29.568Z" }, + { url = "https://files.pythonhosted.org/packages/a9/2c/c8f7aa24cd729970728f3f98822fb45149adc216f445a9301e441f7ac760/statsmodels-0.14.6-cp311-cp311-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:bdf1dfe2a3ca56f5529118baf33a13efed2783c528f4a36409b46bbd2d9d48eb", size = 10129872, upload-time = "2025-12-05T23:09:25.724Z" }, + { url = "https://files.pythonhosted.org/packages/40/c6/9ae8e9b0721e9b6eb5f340c3a0ce8cd7cce4f66e03dd81f80d60f111987f/statsmodels-0.14.6-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:a3764ba8195c9baf0925a96da0743ff218067a269f01d155ca3558deed2658ca", size = 10381964, upload-time = "2025-12-05T23:09:41.326Z" }, + { url = "https://files.pythonhosted.org/packages/28/8c/cf3d30c8c2da78e2ad1f50ade8b7fabec3ff4cdfc56fbc02e097c4577f90/statsmodels-0.14.6-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:9e8d2e519852adb1b420e018f5ac6e6684b2b877478adf7fda2cfdb58f5acb5d", size = 10409611, upload-time = "2025-12-05T23:09:57.131Z" }, + { url = "https://files.pythonhosted.org/packages/bf/cc/018f14ecb58c6cb89de9d52695740b7d1f5a982aa9ea312483ea3c3d5f77/statsmodels-0.14.6-cp311-cp311-win_amd64.whl", hash = "sha256:2738a00fca51196f5a7d44b06970ace6b8b30289839e4808d656f8a98e35faa7", size = 9580385, upload-time = "2025-12-05T19:28:42.778Z" }, + { url = "https://files.pythonhosted.org/packages/25/ce/308e5e5da57515dd7cab3ec37ea2d5b8ff50bef1fcc8e6d31456f9fae08e/statsmodels-0.14.6-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:fe76140ae7adc5ff0e60a3f0d56f4fffef484efa803c3efebf2fcd734d72ecb5", size = 10091932, upload-time = "2025-12-05T19:28:55.446Z" }, + { url = "https://files.pythonhosted.org/packages/05/30/affbabf3c27fb501ec7b5808230c619d4d1a4525c07301074eb4bda92fa9/statsmodels-0.14.6-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:26d4f0ed3b31f3c86f83a92f5c1f5cbe63fc992cd8915daf28ca49be14463a1c", size = 9997345, upload-time = "2025-12-05T19:29:10.278Z" }, + { url = "https://files.pythonhosted.org/packages/48/f5/3a73b51e6450c31652c53a8e12e24eac64e3824be816c0c2316e7dbdcb7d/statsmodels-0.14.6-cp312-cp312-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:d8c00a42863e4f4733ac9d078bbfad816249c01451740e6f5053ecc7db6d6368", size = 10058649, upload-time = "2025-12-05T23:10:12.775Z" }, + { url = "https://files.pythonhosted.org/packages/81/68/dddd76117df2ef14c943c6bbb6618be5c9401280046f4ddfc9fb4596a1b8/statsmodels-0.14.6-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:19b58cf7474aa9e7e3b0771a66537148b2df9b5884fbf156096c0e6c1ff0469d", size = 10339446, upload-time = "2025-12-05T23:10:28.503Z" }, + { url = "https://files.pythonhosted.org/packages/56/4a/dce451c74c4050535fac1ec0c14b80706d8fc134c9da22db3c8a0ec62c33/statsmodels-0.14.6-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:81e7dcc5e9587f2567e52deaff5220b175bf2f648951549eae5fc9383b62bc37", size = 10368705, upload-time = "2025-12-05T23:10:44.339Z" }, + { url = "https://files.pythonhosted.org/packages/60/15/3daba2df40be8b8a9a027d7f54c8dedf24f0d81b96e54b52293f5f7e3418/statsmodels-0.14.6-cp312-cp312-win_amd64.whl", hash = "sha256:b5eb07acd115aa6208b4058211138393a7e6c2cf12b6f213ede10f658f6a714f", size = 9543991, upload-time = "2025-12-05T23:10:58.536Z" }, + { url = "https://files.pythonhosted.org/packages/81/59/a5aad5b0cc266f5be013db8cde563ac5d2a025e7efc0c328d83b50c72992/statsmodels-0.14.6-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:47ee7af083623d2091954fa71c7549b8443168f41b7c5dce66510274c50fd73e", size = 10072009, upload-time = "2025-12-05T23:11:14.021Z" }, + { url = "https://files.pythonhosted.org/packages/53/dd/d8cfa7922fc6dc3c56fa6c59b348ea7de829a94cd73208c6f8202dd33f17/statsmodels-0.14.6-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:aa60d82e29fcd0a736e86feb63a11d2380322d77a9369a54be8b0965a3985f71", size = 9980018, upload-time = "2025-12-05T23:11:30.907Z" }, + { url = "https://files.pythonhosted.org/packages/ee/77/0ec96803eba444efd75dba32f2ef88765ae3e8f567d276805391ec2c98c6/statsmodels-0.14.6-cp313-cp313-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:89ee7d595f5939cc20bf946faedcb5137d975f03ae080f300ebb4398f16a5bd4", size = 10060269, upload-time = "2025-12-05T23:11:46.338Z" }, + { url = "https://files.pythonhosted.org/packages/10/b9/fd41f1f6af13a1a1212a06bb377b17762feaa6d656947bf666f76300fc05/statsmodels-0.14.6-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:730f3297b26749b216a06e4327fe0be59b8d05f7d594fb6caff4287b69654589", size = 10324155, upload-time = "2025-12-05T23:12:01.805Z" }, + { url = "https://files.pythonhosted.org/packages/ee/0f/a6900e220abd2c69cd0a07e3ad26c71984be6061415a60e0f17b152ecf08/statsmodels-0.14.6-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:f1c08befa85e93acc992b72a390ddb7bd876190f1360e61d10cf43833463bc9c", size = 10349765, upload-time = "2025-12-05T23:12:18.018Z" }, + { url = "https://files.pythonhosted.org/packages/98/08/b79f0c614f38e566eebbdcff90c0bcacf3c6ba7a5bbb12183c09c29ca400/statsmodels-0.14.6-cp313-cp313-win_amd64.whl", hash = "sha256:8021271a79f35b842c02a1794465a651a9d06ec2080f76ebc3b7adce77d08233", size = 9540043, upload-time = "2025-12-05T23:12:33.887Z" }, + { url = "https://files.pythonhosted.org/packages/71/de/09540e870318e0c7b58316561d417be45eff731263b4234fdd2eee3511a8/statsmodels-0.14.6-cp314-cp314-macosx_10_15_x86_64.whl", hash = "sha256:00781869991f8f02ad3610da6627fd26ebe262210287beb59761982a8fa88cae", size = 10069403, upload-time = "2025-12-05T23:12:48.424Z" }, + { url = "https://files.pythonhosted.org/packages/ab/f0/63c1bfda75dc53cee858006e1f46bd6d6f883853bea1b97949d0087766ca/statsmodels-0.14.6-cp314-cp314-macosx_11_0_arm64.whl", hash = "sha256:73f305fbf31607b35ce919fae636ab8b80d175328ed38fdc6f354e813b86ee37", size = 9989253, upload-time = "2025-12-05T23:13:05.274Z" }, + { url = "https://files.pythonhosted.org/packages/c1/98/b0dfb4f542b2033a3341aa5f1bdd97024230a4ad3670c5b0839d54e3dcab/statsmodels-0.14.6-cp314-cp314-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:e443e7077a6e2d3faeea72f5a92c9f12c63722686eb80bb40a0f04e4a7e267ad", size = 10090802, upload-time = "2025-12-05T23:13:20.653Z" }, + { url = "https://files.pythonhosted.org/packages/34/0e/2408735aca9e764643196212f9069912100151414dd617d39ffc72d77eee/statsmodels-0.14.6-cp314-cp314-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:3414e40c073d725007a6603a18247ab7af3467e1af4a5e5a24e4c27bc26673b4", size = 10337587, upload-time = "2025-12-05T23:13:37.597Z" }, + { url = "https://files.pythonhosted.org/packages/0f/36/4d44f7035ab3c0b2b6a4c4ebb98dedf36246ccbc1b3e2f51ebcd7ac83abb/statsmodels-0.14.6-cp314-cp314-musllinux_1_2_x86_64.whl", hash = "sha256:a518d3f9889ef920116f9fa56d0338069e110f823926356946dae83bc9e33e19", size = 10363350, upload-time = "2025-12-05T23:13:53.08Z" }, + { url = "https://files.pythonhosted.org/packages/26/33/f1652d0c59fa51de18492ee2345b65372550501ad061daa38f950be390b6/statsmodels-0.14.6-cp314-cp314-win_amd64.whl", hash = "sha256:151b73e29f01fe619dbce7f66d61a356e9d1fe5e906529b78807df9189c37721", size = 9588010, upload-time = "2025-12-05T23:14:07.28Z" }, +] + +[[package]] +name = "stdlib-list" +version = "0.12.0" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/8c/25/f1540879c8815387980e56f973e54605bd924612399ace31487f7444171c/stdlib_list-0.12.0.tar.gz", hash = "sha256:517824f27ee89e591d8ae7c1dd9ff34f672eae50ee886ea31bb8816d77535675", size = 60923, upload-time = "2025-10-24T19:21:22.849Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/3b/3d/2970b27a11ae17fb2d353e7a179763a2fe6f37d6d2a9f4d40104a2f132e9/stdlib_list-0.12.0-py3-none-any.whl", hash = "sha256:df2d11e97f53812a1756fb5510393a11e3b389ebd9239dc831c7f349957f62f2", size = 87615, upload-time = "2025-10-24T19:21:20.619Z" }, +] + +[[package]] +name = "texttable" +version = "1.7.0" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/1c/dc/0aff23d6036a4d3bf4f1d8c8204c5c79c4437e25e0ae94ffe4bbb55ee3c2/texttable-1.7.0.tar.gz", hash = "sha256:2d2068fb55115807d3ac77a4ca68fa48803e84ebb0ee2340f858107a36522638", size = 12831, upload-time = "2023-10-03T09:48:12.272Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/24/99/4772b8e00a136f3e01236de33b0efda31ee7077203ba5967fcc76da94d65/texttable-1.7.0-py2.py3-none-any.whl", hash = "sha256:72227d592c82b3d7f672731ae73e4d1f88cd8e2ef5b075a7a7f01a23a3743917", size = 10768, upload-time = "2023-10-03T09:48:10.434Z" }, +] + +[[package]] +name = "threadpoolctl" +version = "3.6.0" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/b7/4d/08c89e34946fce2aec4fbb45c9016efd5f4d7f24af8e5d93296e935631d8/threadpoolctl-3.6.0.tar.gz", hash = "sha256:8ab8b4aa3491d812b623328249fab5302a68d2d71745c8a4c719a2fcaba9f44e", size = 21274, upload-time = "2025-03-13T13:49:23.031Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/32/d5/f9a850d79b0851d1d4ef6456097579a9005b31fea68726a4ae5f2d82ddd9/threadpoolctl-3.6.0-py3-none-any.whl", hash = "sha256:43a0b8fd5a2928500110039e43a5eed8480b918967083ea48dc3ab9f13c4a7fb", size = 18638, upload-time = "2025-03-13T13:49:21.846Z" }, +] + +[[package]] +name = "tinycss2" +version = "1.4.0" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "webencodings" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/7a/fd/7a5ee21fd08ff70d3d33a5781c255cbe779659bd03278feb98b19ee550f4/tinycss2-1.4.0.tar.gz", hash = "sha256:10c0972f6fc0fbee87c3edb76549357415e94548c1ae10ebccdea16fb404a9b7", size = 87085, upload-time = "2024-10-24T14:58:29.895Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/e6/34/ebdc18bae6aa14fbee1a08b63c015c72b64868ff7dae68808ab500c492e2/tinycss2-1.4.0-py3-none-any.whl", hash = "sha256:3a49cf47b7675da0b15d0c6e1df8df4ebd96e9394bb905a5775adb0d884c5289", size = 26610, upload-time = "2024-10-24T14:58:28.029Z" }, +] + +[[package]] +name = "tomli-w" +version = "1.2.0" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/19/75/241269d1da26b624c0d5e110e8149093c759b7a286138f4efd61a60e75fe/tomli_w-1.2.0.tar.gz", hash = "sha256:2dd14fac5a47c27be9cd4c976af5a12d87fb1f0b4512f81d69cce3b35ae25021", size = 7184, upload-time = "2025-01-15T12:07:24.262Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/c7/18/c86eb8e0202e32dd3df50d43d7ff9854f8e0603945ff398974c1d91ac1ef/tomli_w-1.2.0-py3-none-any.whl", hash = "sha256:188306098d013b691fcadc011abd66727d3c414c571bb01b1a174ba8c983cf90", size = 6675, upload-time = "2025-01-15T12:07:22.074Z" }, +] + +[[package]] +name = "tornado" +version = "6.5.4" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/37/1d/0a336abf618272d53f62ebe274f712e213f5a03c0b2339575430b8362ef2/tornado-6.5.4.tar.gz", hash = "sha256:a22fa9047405d03260b483980635f0b041989d8bcc9a313f8fe18b411d84b1d7", size = 513632, upload-time = "2025-12-15T19:21:03.836Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/ab/a9/e94a9d5224107d7ce3cc1fab8d5dc97f5ea351ccc6322ee4fb661da94e35/tornado-6.5.4-cp39-abi3-macosx_10_9_universal2.whl", hash = "sha256:d6241c1a16b1c9e4cc28148b1cda97dd1c6cb4fb7068ac1bedc610768dff0ba9", size = 443909, upload-time = "2025-12-15T19:20:48.382Z" }, + { url = "https://files.pythonhosted.org/packages/db/7e/f7b8d8c4453f305a51f80dbb49014257bb7d28ccb4bbb8dd328ea995ecad/tornado-6.5.4-cp39-abi3-macosx_10_9_x86_64.whl", hash = "sha256:2d50f63dda1d2cac3ae1fa23d254e16b5e38153758470e9956cbc3d813d40843", size = 442163, upload-time = "2025-12-15T19:20:49.791Z" }, + { url = "https://files.pythonhosted.org/packages/ba/b5/206f82d51e1bfa940ba366a8d2f83904b15942c45a78dd978b599870ab44/tornado-6.5.4-cp39-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:d1cf66105dc6acb5af613c054955b8137e34a03698aa53272dbda4afe252be17", size = 445746, upload-time = "2025-12-15T19:20:51.491Z" }, + { url = "https://files.pythonhosted.org/packages/8e/9d/1a3338e0bd30ada6ad4356c13a0a6c35fbc859063fa7eddb309183364ac1/tornado-6.5.4-cp39-abi3-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:50ff0a58b0dc97939d29da29cd624da010e7f804746621c78d14b80238669335", size = 445083, upload-time = "2025-12-15T19:20:52.778Z" }, + { url = "https://files.pythonhosted.org/packages/50/d4/e51d52047e7eb9a582da59f32125d17c0482d065afd5d3bc435ff2120dc5/tornado-6.5.4-cp39-abi3-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:e5fb5e04efa54cf0baabdd10061eb4148e0be137166146fff835745f59ab9f7f", size = 445315, upload-time = "2025-12-15T19:20:53.996Z" }, + { url = "https://files.pythonhosted.org/packages/27/07/2273972f69ca63dbc139694a3fc4684edec3ea3f9efabf77ed32483b875c/tornado-6.5.4-cp39-abi3-musllinux_1_2_aarch64.whl", hash = "sha256:9c86b1643b33a4cd415f8d0fe53045f913bf07b4a3ef646b735a6a86047dda84", size = 446003, upload-time = "2025-12-15T19:20:56.101Z" }, + { url = "https://files.pythonhosted.org/packages/d1/83/41c52e47502bf7260044413b6770d1a48dda2f0246f95ee1384a3cd9c44a/tornado-6.5.4-cp39-abi3-musllinux_1_2_i686.whl", hash = "sha256:6eb82872335a53dd063a4f10917b3efd28270b56a33db69009606a0312660a6f", size = 445412, upload-time = "2025-12-15T19:20:57.398Z" }, + { url = "https://files.pythonhosted.org/packages/10/c7/bc96917f06cbee182d44735d4ecde9c432e25b84f4c2086143013e7b9e52/tornado-6.5.4-cp39-abi3-musllinux_1_2_x86_64.whl", hash = "sha256:6076d5dda368c9328ff41ab5d9dd3608e695e8225d1cd0fd1e006f05da3635a8", size = 445392, upload-time = "2025-12-15T19:20:58.692Z" }, + { url = "https://files.pythonhosted.org/packages/0c/1a/d7592328d037d36f2d2462f4bc1fbb383eec9278bc786c1b111cbbd44cfa/tornado-6.5.4-cp39-abi3-win32.whl", hash = "sha256:1768110f2411d5cd281bac0a090f707223ce77fd110424361092859e089b38d1", size = 446481, upload-time = "2025-12-15T19:21:00.008Z" }, + { url = "https://files.pythonhosted.org/packages/d6/6d/c69be695a0a64fd37a97db12355a035a6d90f79067a3cf936ec2b1dc38cd/tornado-6.5.4-cp39-abi3-win_amd64.whl", hash = "sha256:fa07d31e0cd85c60713f2b995da613588aa03e1303d75705dca6af8babc18ddc", size = 446886, upload-time = "2025-12-15T19:21:01.287Z" }, + { url = "https://files.pythonhosted.org/packages/50/49/8dc3fd90902f70084bd2cd059d576ddb4f8bb44c2c7c0e33a11422acb17e/tornado-6.5.4-cp39-abi3-win_arm64.whl", hash = "sha256:053e6e16701eb6cbe641f308f4c1a9541f91b6261991160391bfc342e8a551a1", size = 445910, upload-time = "2025-12-15T19:21:02.571Z" }, +] + +[[package]] +name = "tqdm" +version = "4.67.3" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "colorama", marker = "sys_platform == 'win32'" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/09/a9/6ba95a270c6f1fbcd8dac228323f2777d886cb206987444e4bce66338dd4/tqdm-4.67.3.tar.gz", hash = "sha256:7d825f03f89244ef73f1d4ce193cb1774a8179fd96f31d7e1dcde62092b960bb", size = 169598, upload-time = "2026-02-03T17:35:53.048Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/16/e1/3079a9ff9b8e11b846c6ac5c8b5bfb7ff225eee721825310c91b3b50304f/tqdm-4.67.3-py3-none-any.whl", hash = "sha256:ee1e4c0e59148062281c49d80b25b67771a127c85fc9676d3be5f243206826bf", size = 78374, upload-time = "2026-02-03T17:35:50.982Z" }, +] + +[[package]] +name = "traitlets" +version = "5.14.3" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/eb/79/72064e6a701c2183016abbbfedaba506d81e30e232a68c9f0d6f6fcd1574/traitlets-5.14.3.tar.gz", hash = "sha256:9ed0579d3502c94b4b3732ac120375cda96f923114522847de4b3bb98b96b6b7", size = 161621, upload-time = "2024-04-19T11:11:49.746Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/00/c0/8f5d070730d7836adc9c9b6408dec68c6ced86b304a9b26a14df072a6e8c/traitlets-5.14.3-py3-none-any.whl", hash = "sha256:b74e89e397b1ed28cc831db7aea759ba6640cb3de13090ca145426688ff1ac4f", size = 85359, upload-time = "2024-04-19T11:11:46.763Z" }, +] + +[[package]] +name = "twine" +version = "6.2.0" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "id" }, + { name = "keyring", marker = "platform_machine != 'ppc64le' and platform_machine != 's390x'" }, + { name = "packaging" }, + { name = "readme-renderer" }, + { name = "requests" }, + { name = "requests-toolbelt" }, + { name = "rfc3986" }, + { name = "rich" }, + { name = "urllib3" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/e0/a8/949edebe3a82774c1ec34f637f5dd82d1cf22c25e963b7d63771083bbee5/twine-6.2.0.tar.gz", hash = "sha256:e5ed0d2fd70c9959770dce51c8f39c8945c574e18173a7b81802dab51b4b75cf", size = 172262, upload-time = "2025-09-04T15:43:17.255Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/3a/7a/882d99539b19b1490cac5d77c67338d126e4122c8276bf640e411650c830/twine-6.2.0-py3-none-any.whl", hash = "sha256:418ebf08ccda9a8caaebe414433b0ba5e25eb5e4a927667122fbe8f829f985d8", size = 42727, upload-time = "2025-09-04T15:43:15.994Z" }, +] + +[[package]] +name = "types-networkx" +version = "3.6.1.20260210" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "numpy" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/4f/d9/7ddf6afb27246998ae41f7ad19da410d83e24623b4db065b5a46888d327e/types_networkx-3.6.1.20260210.tar.gz", hash = "sha256:9864affb01ed53d6bf41c1042fbced155ac409ae02ca505e0a3fffe48901b6e1", size = 73702, upload-time = "2026-02-10T04:22:17.641Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/55/b0/1c45681a8b8d3ccf25cebaa296b06d5240518bd7a7d861cf14a15bf9dd20/types_networkx-3.6.1.20260210-py3-none-any.whl", hash = "sha256:075ccb9f2e2b370c3a9eae9636f2f38890e7c494e6323cb72a0207f104f8225e", size = 162684, upload-time = "2026-02-10T04:22:16.055Z" }, +] + +[[package]] +name = "typing-extensions" +version = "4.15.0" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/72/94/1a15dd82efb362ac84269196e94cf00f187f7ed21c242792a923cdb1c61f/typing_extensions-4.15.0.tar.gz", hash = "sha256:0cea48d173cc12fa28ecabc3b837ea3cf6f38c6d1136f85cbaaf598984861466", size = 109391, upload-time = "2025-08-25T13:49:26.313Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/18/67/36e9267722cc04a6b9f15c7f3441c2363321a3ea07da7ae0c0707beb2a9c/typing_extensions-4.15.0-py3-none-any.whl", hash = "sha256:f0fa19c6845758ab08074a0cfa8b7aecb71c999ca73d62883bc25cc018c4e548", size = 44614, upload-time = "2025-08-25T13:49:24.86Z" }, +] + +[[package]] +name = "tzdata" +version = "2025.3" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/5e/a7/c202b344c5ca7daf398f3b8a477eeb205cf3b6f32e7ec3a6bac0629ca975/tzdata-2025.3.tar.gz", hash = "sha256:de39c2ca5dc7b0344f2eba86f49d614019d29f060fc4ebc8a417896a620b56a7", size = 196772, upload-time = "2025-12-13T17:45:35.667Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/c7/b0/003792df09decd6849a5e39c28b513c06e84436a54440380862b5aeff25d/tzdata-2025.3-py2.py3-none-any.whl", hash = "sha256:06a47e5700f3081aab02b2e513160914ff0694bce9947d6b76ebd6bf57cfc5d1", size = 348521, upload-time = "2025-12-13T17:45:33.889Z" }, +] + +[[package]] +name = "umap-learn" +version = "0.5.11" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "numba" }, + { name = "numpy" }, + { name = "pynndescent" }, + { name = "scikit-learn" }, + { name = "scipy" }, + { name = "tqdm" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/94/9a/a1e4a257a9aa979dac4f6d5781dac929cbb0949959e2003ed82657d10b0f/umap_learn-0.5.11.tar.gz", hash = "sha256:31566ffd495fbf05d7ab3efcba703861c0f5e6fc6998a838d0e2becdd00e54f5", size = 96409, upload-time = "2026-01-12T20:44:47.553Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/43/d2/fcf7192dd1cd8c090b6cfd53fa223c4fb2887a17c47e06bc356d44f40dfb/umap_learn-0.5.11-py3-none-any.whl", hash = "sha256:cb17adbde9d544ba79481b3ab4d81ac222e940f3d9219307bea6044f869af3cc", size = 90890, upload-time = "2026-01-12T20:44:46.511Z" }, +] + +[[package]] +name = "urllib3" +version = "2.6.3" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/c7/24/5f1b3bdffd70275f6661c76461e25f024d5a38a46f04aaca912426a2b1d3/urllib3-2.6.3.tar.gz", hash = "sha256:1b62b6884944a57dbe321509ab94fd4d3b307075e0c2eae991ac71ee15ad38ed", size = 435556, upload-time = "2026-01-07T16:24:43.925Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/39/08/aaaad47bc4e9dc8c725e68f9d04865dbcb2052843ff09c97b08904852d84/urllib3-2.6.3-py3-none-any.whl", hash = "sha256:bf272323e553dfb2e87d9bfd225ca7b0f467b919d7bbd355436d3fd37cb0acd4", size = 131584, upload-time = "2026-01-07T16:24:42.685Z" }, +] + +[[package]] +name = "virtualenv" +version = "20.38.0" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "distlib" }, + { name = "filelock" }, + { name = "platformdirs" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/d2/03/a94d404ca09a89a7301a7008467aed525d4cdeb9186d262154dd23208709/virtualenv-20.38.0.tar.gz", hash = "sha256:94f39b1abaea5185bf7ea5a46702b56f1d0c9aa2f41a6c2b8b0af4ddc74c10a7", size = 5864558, upload-time = "2026-02-19T07:48:02.385Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/42/d7/394801755d4c8684b655d35c665aea7836ec68320304f62ab3c94395b442/virtualenv-20.38.0-py3-none-any.whl", hash = "sha256:d6e78e5889de3a4742df2d3d44e779366325a90cf356f15621fddace82431794", size = 5837778, upload-time = "2026-02-19T07:47:59.778Z" }, +] + +[[package]] +name = "wcwidth" +version = "0.6.0" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/35/a2/8e3becb46433538a38726c948d3399905a4c7cabd0df578ede5dc51f0ec2/wcwidth-0.6.0.tar.gz", hash = "sha256:cdc4e4262d6ef9a1a57e018384cbeb1208d8abbc64176027e2c2455c81313159", size = 159684, upload-time = "2026-02-06T19:19:40.919Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/68/5a/199c59e0a824a3db2b89c5d2dade7ab5f9624dbf6448dc291b46d5ec94d3/wcwidth-0.6.0-py3-none-any.whl", hash = "sha256:1a3a1e510b553315f8e146c54764f4fb6264ffad731b3d78088cdb1478ffbdad", size = 94189, upload-time = "2026-02-06T19:19:39.646Z" }, +] + +[[package]] +name = "webencodings" +version = "0.5.1" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/0b/02/ae6ceac1baeda530866a85075641cec12989bd8d31af6d5ab4a3e8c92f47/webencodings-0.5.1.tar.gz", hash = "sha256:b36a1c245f2d304965eb4e0a82848379241dc04b865afcc4aab16748587e1923", size = 9721, upload-time = "2017-04-05T20:21:34.189Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/f4/24/2a3e3df732393fed8b3ebf2ec078f05546de641fe1b667ee316ec1dcf3b7/webencodings-0.5.1-py2.py3-none-any.whl", hash = "sha256:a0af1213f3c2226497a97e2b3aa01a7e4bee4f403f95be16fc9acd2947514a78", size = 11774, upload-time = "2017-04-05T20:21:32.581Z" }, +] + +[[package]] +name = "widgetsnbextension" +version = "4.0.15" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/bd/f4/c67440c7fb409a71b7404b7aefcd7569a9c0d6bd071299bf4198ae7a5d95/widgetsnbextension-4.0.15.tar.gz", hash = "sha256:de8610639996f1567952d763a5a41af8af37f2575a41f9852a38f947eb82a3b9", size = 1097402, upload-time = "2025-11-01T21:15:55.178Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/3f/0e/fa3b193432cfc60c93b42f3be03365f5f909d2b3ea410295cf36df739e31/widgetsnbextension-4.0.15-py3-none-any.whl", hash = "sha256:8156704e4346a571d9ce73b84bee86a29906c9abfd7223b7228a28899ccf3366", size = 2196503, upload-time = "2025-11-01T21:15:53.565Z" }, +] + +[[package]] +name = "zarr" +version = "3.1.5" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "donfig" }, + { name = "google-crc32c" }, + { name = "numcodecs" }, + { name = "numpy" }, + { name = "packaging" }, + { name = "typing-extensions" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/fc/76/7fa87f57c112c7b9c82f0a730f8b6f333e792574812872e2cd45ab604199/zarr-3.1.5.tar.gz", hash = "sha256:fbe0c79675a40c996de7ca08e80a1c0a20537bd4a9f43418b6d101395c0bba2b", size = 366825, upload-time = "2025-11-21T14:06:01.492Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/44/15/bb13b4913ef95ad5448490821eee4671d0e67673342e4d4070854e5fe081/zarr-3.1.5-py3-none-any.whl", hash = "sha256:29cd905afb6235b94c09decda4258c888fcb79bb6c862ef7c0b8fe009b5c8563", size = 284067, upload-time = "2025-11-21T14:05:59.235Z" }, +] + +[[package]] +name = "zipp" +version = "3.23.0" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/e3/02/0f2892c661036d50ede074e376733dca2ae7c6eb617489437771209d4180/zipp-3.23.0.tar.gz", hash = "sha256:a07157588a12518c9d4034df3fbbee09c814741a33ff63c05fa29d26a2404166", size = 25547, upload-time = "2025-06-08T17:06:39.4Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/2e/54/647ade08bf0db230bfea292f893923872fd20be6ac6f53b2b936ba839d75/zipp-3.23.0-py3-none-any.whl", hash = "sha256:071652d6115ed432f5ce1d34c336c0adfd6a884660d1e9712a256d3d3bd4b14e", size = 10276, upload-time = "2025-06-08T17:06:38.034Z" }, +]