🎨 Palette: Enhance quiet mode with dynamic progress bar and fully suppressed logs

.Jules/palette.md

@@ -5,3 +5,7 @@
 ## 2025-02-28 - Structured CLI Reports
 **Learning:** Dense numerical data in CLI output is hard to parse. Using ASCII box-drawing characters and alignment to create a "dashboard" or "invoice" style summary significantly improves readability and perceived quality.
 **Action:** When summarizing simulation or batch job results, always format the final report as a structured table or box rather than a list of print statements.
+
+## 2025-03-01 - Dynamic Progress Bars in Quiet Mode
+**Learning:** For long-running CLI processes that suppress verbose logging (e.g., `--quiet`), users can feel lost or assume the process has hung.
+**Action:** Implement a dynamic progress bar using `\r` and `flush=True` conditional on `sys.stdout.isatty()` to provide system status visibility without polluting standard output logs.

bitcoin_trading_simulation.py

@@ -84,7 +84,7 @@ def simulate_trading(signals, initial_cash=10000, quiet=False):
 
     if not quiet:
         print(f"\n{Colors.HEADER}{Colors.BOLD}------ Daily Trading Ledger ------{Colors.ENDC}")
-    for i, row in signals.iterrows():
+    for idx, (i, row) in enumerate(signals.iterrows()):
         if i > 0:
             portfolio.loc[i, 'cash'] = portfolio.loc[i-1, 'cash']
             portfolio.loc[i, 'btc'] = portfolio.loc[i-1, 'btc']
@@ -94,21 +94,30 @@ def simulate_trading(signals, initial_cash=10000, quiet=False):
             btc_to_buy = portfolio.loc[i, 'cash'] / row['price']
             portfolio.loc[i, 'btc'] += btc_to_buy
             portfolio.loc[i, 'cash'] -= btc_to_buy * row['price']
-            print(f"{Colors.GREEN}🟢 Day {i}: Buy {btc_to_buy:.4f} BTC at ${row['price']:.2f}{Colors.ENDC}")
+            if not quiet:
+                print(f"{Colors.GREEN}🟢 Day {i}: Buy {btc_to_buy:.4f} BTC at ${row['price']:.2f}{Colors.ENDC}")
 
         # Sell signal
         elif row['positions'] == -2.0:
             if portfolio.loc[i, 'btc'] > 0:
                 cash_received = portfolio.loc[i, 'btc'] * row['price']
                 portfolio.loc[i, 'cash'] += cash_received
-                print(f"{Colors.FAIL}🔴 Day {i}: Sell {portfolio.loc[i, 'btc']:.4f} BTC at ${row['price']:.2f}{Colors.ENDC}")
+                if not quiet:
+                    print(f"{Colors.FAIL}🔴 Day {i}: Sell {portfolio.loc[i, 'btc']:.4f} BTC at ${row['price']:.2f}{Colors.ENDC}")
                 portfolio.loc[i, 'btc'] = 0
 
         portfolio.loc[i, 'total_value'] = portfolio.loc[i, 'cash'] + portfolio.loc[i, 'btc'] * row['price']
 
         if not quiet:
             print(f"Day {i}: Portfolio Value: ${portfolio.loc[i, 'total_value']:.2f}, "
                   f"Cash: ${portfolio.loc[i, 'cash']:.2f}, BTC: {portfolio.loc[i, 'btc']:.4f}")
+        elif sys.stdout.isatty():
+            # Dynamic progress bar for quiet mode
+            progress = int((idx + 1) / len(signals) * 100)
+            print(f"\r{Colors.CYAN}Running simulation: {progress}%{Colors.ENDC}", end="", flush=True)
+
+    if quiet and sys.stdout.isatty():
+        print()
 
     return portfolio
 

main.tf

@@ -0,0 +1 @@
+terraform {}

test_isatty.py

@@ -0,0 +1,3 @@
+def test_isatty(capsys):
+    import sys
+    print("isatty:", sys.stdout.isatty())

test_progress.py

@@ -0,0 +1,12 @@
+import sys
+import pandas as pd
+from bitcoin_trading_simulation import simulate_trading, Colors
+
+# mock isatty
+sys.stdout.isatty = lambda: True
+
+signals = pd.DataFrame(index=range(10))
+signals['price'] = [100.0] * 10
+signals['positions'] = [0.0] * 10
+
+simulate_trading(signals, quiet=True)

test_quiet.py

@@ -0,0 +1,7 @@
+import sys
+from bitcoin_trading_simulation import simulate_bitcoin_prices, calculate_moving_averages, generate_trading_signals, simulate_trading
+
+prices = simulate_bitcoin_prices(days=60, initial_price=50000, volatility=0.02)
+signals = calculate_moving_averages(prices)
+signals = generate_trading_signals(signals)
+simulate_trading(signals, quiet=True)

test_quiet_buy_sell.py

@@ -0,0 +1,21 @@
+import pandas as pd
+from bitcoin_trading_simulation import simulate_trading
+
+def test_quiet_suppresses_buys_sells():
+    signals = pd.DataFrame(index=range(3))
+    signals['price'] = [100.0, 101.0, 102.0]
+    signals['positions'] = [2.0, -2.0, 0.0]
+
+    import io
+    import sys
+
+    old_stdout = sys.stdout
+    sys.stdout = io.StringIO()
+    simulate_trading(signals, initial_cash=1000, quiet=True)
+    out = sys.stdout.getvalue()
+    sys.stdout = old_stdout
+
+    assert out == ""
+
+test_quiet_suppresses_buys_sells()
+print("Passed")