ci: add ruff validation for research pipeline

Author: Pigbibi

.github/workflows/ci.yml

@@ -24,6 +24,12 @@ jobs:
           if [ ! -f "$REQ_FILE" ]; then REQ_FILE="requirements.txt"; fi
           python -m pip install --upgrade pip
           python -m pip install -r "$REQ_FILE"
+          python -m pip install ruff
+
+      - name: Run ruff
+        run: |
+          set -euo pipefail
+          ruff check .
 
       - name: Run unit tests
         run: |

.ruff.toml

@@ -0,0 +1,4 @@
+target-version = "py311"
+
+[lint.per-file-ignores]
+"scripts/*.py" = ["E402"]

scripts/sweep_external_data_profiles.py

@@ -251,7 +251,7 @@ def main() -> None:
 
         scored_external = run_variant_scoring(profile_cfg)
         evaluation_start = max(scored_binance["first_scored_date"], scored_external["first_scored_date"])
-        result = evaluate_variant(profile, profile_cfg, scored_external, evaluation_start)
+        evaluate_variant(profile, profile_cfg, scored_external, evaluation_start)
         summary_rows.append(
             load_profile_row(
                 profile,

src/backtest.py

@@ -1,7 +1,7 @@
 from __future__ import annotations
 
 from dataclasses import dataclass
-from typing import Any, Optional
+from typing import Any
 
 import numpy as np
 import pandas as pd

src/pipeline.py

@@ -5,7 +5,7 @@
 
 import pandas as pd
 
-from .backtest import build_walkforward_windows, run_backtest_suite, run_walkforward_scoring
+from .backtest import run_backtest_suite, run_walkforward_scoring
 from .evaluation import evaluate_leader_selection, leader_metrics_to_frame
 from .external_data import load_optional_market_cap_metadata, merge_histories_with_external
 from .export import export_latest_ranking, export_latest_universe, export_live_pool
@@ -384,7 +384,7 @@ def build_live_pool_outputs(
 
     output_dir = config["paths"].output_dir
     export_latest_universe(panel, output_dir, latest_date)
-    ranking_snapshot = export_latest_ranking(panel, output_dir, latest_date)
+    export_latest_ranking(panel, output_dir, latest_date)
     latest_snapshot = latest_ranking_snapshot(panel, latest_date)
     live_payload = export_live_pool(
         ranking_snapshot=latest_snapshot.loc[latest_snapshot["selected_flag"] | latest_snapshot["in_universe"]],

src/portfolio.py

@@ -2,7 +2,6 @@
 
 from typing import Iterable
 
-import numpy as np
 import pandas as pd