🎨 Palette: CLI Arguments & Accessibility Improvements

.Jules/palette.md

@@ -2,6 +2,6 @@
 **Learning:** Adding color-coded indicators (Green/Red) and emojis (💰, 📉) in CLI tools significantly reduces cognitive load when parsing financial data streams. It transforms a wall of text into a scannable narrative.
 **Action:** For data-heavy CLI applications, always implement a semantic color system and visual anchors (icons/emojis) for key events.
 
-## 2026-02-11 - Accessibility in CLI Tools
-**Learning:** Hardcoded ANSI colors exclude users with visual impairments or conflicting terminal themes. Providing a standard `--no-color` flag is a zero-cost accessibility win that respects user preference.
-**Action:** Always wrap color codes in a configurable class and expose a disable mechanism via CLI arguments.
+## 2024-05-23 - CLI Accessibility and Control
+**Learning:** While color and emojis enhance UX, they can be inaccessible (color blindness) or intrusive (automation logs). Providing `--no-color` and `--quiet` flags is essential for a robust CLI tool that respects user context and accessibility needs.
+**Action:** Always include flags to disable visual enhancements and suppress verbose output in CLI tools.

README.md

@@ -4,10 +4,11 @@ A Python-based CLI tool that simulates Bitcoin trading using a 'Golden Cross' mo
 
 ## Features
 
-- **Price Simulation:** Uses Geometric Brownian Motion to simulate 60 days of Bitcoin prices.
+- **Price Simulation:** Uses Geometric Brownian Motion to simulate Bitcoin prices.
 - **Trading Strategy:** Implements a Golden Cross strategy (Short MA > Long MA = Buy, Short MA < Long MA = Sell).
-- **Rich CLI Output:** features color-coded logs (Green for Buy/Profit, Red for Sell/Loss) and emojis for better readability.
+- **Rich CLI Output:** Features color-coded logs (Green for Buy/Profit, Red for Sell/Loss) and emojis for better readability.
 - **Performance metrics:** Compares the strategy's performance against a "Buy and Hold" approach.
+- **Customizable:** Configure simulation parameters via command-line arguments.
 
 ## Installation
 
@@ -20,33 +21,36 @@ pip install -r requirements.txt
 
 ## Usage
 
-Run the simulation script with default settings:
+Run the simulation script with default settings (60 days, $10k initial cash):
 
 ```bash
 python bitcoin_trading_simulation.py
 ```
 
 ### Options
 
-You can customize the simulation with the following arguments:
+Customize the simulation with the following arguments:
+
+```bash
+python bitcoin_trading_simulation.py --days 100 --initial-cash 5000 --initial-price 60000 --volatility 0.03
+```
 
 - `--days`: Number of days to simulate (default: 60)
 - `--initial-cash`: Initial cash amount (default: 10000)
 - `--initial-price`: Initial Bitcoin price (default: 50000)
-- `--volatility`: Volatility factor (default: 0.02)
-- `--quiet`: Suppress daily ledger output (show only final results)
-- `--no-color`: Disable colored output (for accessibility)
-
-**Example:**
+- `--volatility`: Price volatility (default: 0.02)
+- `--quiet`: Suppress daily portfolio log (only show final result)
+- `--no-color`: Disable colored output (for accessibility or logging)
 
+Example:
 ```bash
-python bitcoin_trading_simulation.py --days 100 --initial-cash 5000 --quiet
+python bitcoin_trading_simulation.py --days 30 --quiet --no-color
 ```
 
 ## Tests
 
-Run the test suite:
+Run the test suite using `pytest`:
 
 ```bash
-python -m unittest test_bitcoin_trading.py
+pytest
 ```

bitcoin_trading_simulation.py

@@ -1,9 +1,9 @@
 import argparse
-import sys
 import numpy as np
 import pandas as pd
 import argparse
 
+
 class Colors:
     HEADER = '\033[95m'
     BLUE = '\033[94m'
@@ -21,6 +21,7 @@ def disable(cls):
         cls.ENDC = ''
         cls.BOLD = ''
 
+
 def simulate_bitcoin_prices(days=60, initial_price=50000, volatility=0.02):
     """
     Simulates Bitcoin prices for a given number of days using Geometric Brownian Motion.
@@ -35,6 +36,7 @@ def simulate_bitcoin_prices(days=60, initial_price=50000, volatility=0.02):
         prices.append(prices[-1] + price_change)
     return pd.Series(prices, name='Price')
 
+
 def calculate_moving_averages(prices, short_window=7, long_window=30):
     """
     Calculates short and long moving averages for a given price series.
@@ -45,6 +47,7 @@ def calculate_moving_averages(prices, short_window=7, long_window=30):
     signals['long_mavg'] = prices.rolling(window=long_window, min_periods=1, center=False).mean()
     return signals
 
+
 def generate_trading_signals(signals):
     """
     Generates trading signals based on the Golden Cross strategy.
@@ -56,11 +59,12 @@ def generate_trading_signals(signals):
     signals.loc[signals['short_mavg'] > signals['long_mavg'], 'signal'] = 1.0
     # A Death Cross (sell signal)
     signals.loc[signals['short_mavg'] < signals['long_mavg'], 'signal'] = -1.0
-    
+
     # We create 'positions' to represent the trading action: 1 for buy, -1 for sell, 0 for hold
     signals['positions'] = signals['signal'].diff().shift(1)
     return signals
 
+
 def simulate_trading(signals, initial_cash=10000, quiet=False):
     """
     Simulates trading based on signals and prints a daily ledger.
@@ -73,6 +77,7 @@ def simulate_trading(signals, initial_cash=10000, quiet=False):
 
     if not quiet:
         print(f"{Colors.HEADER}{Colors.BOLD}------ Daily Trading Ledger ------{Colors.ENDC}")
+
     for i, row in signals.iterrows():
         if i > 0:
             portfolio.loc[i, 'cash'] = portfolio.loc[i-1, 'cash']
@@ -96,19 +101,22 @@ def simulate_trading(signals, initial_cash=10000, quiet=False):
                 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}, Cash: ${portfolio.loc[i, 'cash']:.2f}, BTC: {portfolio.loc[i, 'btc']:.4f}")
-
+            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}")
+
     return portfolio
 
+
 if __name__ == "__main__":
-    parser = argparse.ArgumentParser(description='Bitcoin Trading Simulation')
-    parser.add_argument('--days', type=int, default=60, help='Number of days to simulate')
-    parser.add_argument('--initial-cash', type=float, default=10000.0, help='Initial cash amount')
-    parser.add_argument('--initial-price', type=float, default=50000.0, help='Initial Bitcoin price')
-    parser.add_argument('--volatility', type=float, default=0.02, help='Volatility factor')
-    parser.add_argument('--quiet', action='store_true', help='Suppress daily ledger output')
-    parser.add_argument('--no-color', action='store_true', help='Disable colored output')
+    parser = argparse.ArgumentParser(description="Bitcoin Trading Simulation")
+    parser.add_argument("--days", type=int, default=60, help="Number of days to simulate")
+    parser.add_argument("--initial-cash", type=float, default=10000, help="Initial cash amount")
+    parser.add_argument("--initial-price", type=float, default=50000, help="Initial Bitcoin price")
+    parser.add_argument("--volatility", type=float, default=0.02, help="Price volatility")
+    parser.add_argument("--quiet", action="store_true", help="Suppress daily portfolio log")
+    parser.add_argument("--no-color", action="store_true", help="Disable colored output")
 
     args = parser.parse_args()
 
@@ -117,24 +125,25 @@ def simulate_trading(signals, initial_cash=10000, quiet=False):
 
     # Simulate prices
     prices = simulate_bitcoin_prices(days=args.days, initial_price=args.initial_price, volatility=args.volatility)
-    
+
     # Calculate moving averages
     signals = calculate_moving_averages(prices)
-    
+
     # Generate trading signals
     signals = generate_trading_signals(signals)
-    
+
     # Simulate trading
     portfolio = simulate_trading(signals, initial_cash=args.initial_cash, quiet=args.quiet)
-    
+
     # Final portfolio performance
     final_value = portfolio['total_value'].iloc[-1]
-    profit = final_value - args.initial_cash
-
+    initial_cash = args.initial_cash
+    profit = final_value - initial_cash
+
     # Compare with buy and hold strategy
     buy_and_hold_btc = args.initial_cash / prices.iloc[0]
     buy_and_hold_value = buy_and_hold_btc * prices.iloc[-1]
-    
+
     print(f"\n{Colors.HEADER}{Colors.BOLD}------ Final Portfolio Performance ------{Colors.ENDC}")
     print(f"Initial Cash: ${args.initial_cash:.2f}")
     print(f"Final Portfolio Value: ${final_value:.2f}")

test_bitcoin_trading.py

@@ -1,101 +1,74 @@
-import unittest
-import sys
-import io
+import pytest
 import pandas as pd
-import subprocess
-from bitcoin_trading_simulation import Colors, simulate_trading, simulate_bitcoin_prices
-
-class TestBitcoinTradingSimulation(unittest.TestCase):
-
-    def setUp(self):
-        # Reset Colors to default before each test to prevent side effects
-        Colors.HEADER = '\033[95m'
-        Colors.BLUE = '\033[94m'
-        Colors.GREEN = '\033[92m'
-        Colors.RED = '\033[91m'
-        Colors.ENDC = '\033[0m'
-        Colors.BOLD = '\033[1m'
-
-    def test_simulate_bitcoin_prices(self):
-        prices = simulate_bitcoin_prices(days=10, initial_price=100)
-        self.assertEqual(len(prices), 10)
-        self.assertEqual(prices.iloc[0], 100)
-
-    def test_colors_disable(self):
-        Colors.disable()
-        self.assertEqual(Colors.HEADER, '')
-        self.assertEqual(Colors.GREEN, '')
-        self.assertEqual(Colors.RED, '')
-
-    def test_quiet_mode_function(self):
-        # Create dummy signals
-        prices = pd.Series([100, 101, 102], name='Price')
-        signals = pd.DataFrame(index=prices.index)
-        signals['price'] = prices
-        signals['positions'] = 0.0
-
-        # Capture stdout
-        captured_output = io.StringIO()
-        sys.stdout = captured_output
-
-        simulate_trading(signals, quiet=True)
-
-        sys.stdout = sys.__stdout__
-        output = captured_output.getvalue()
-
-        # Expect no output in quiet mode (since no trades and quiet=True)
-        self.assertEqual(output, "")
-
-    def test_verbose_mode_function(self):
-        # Create dummy signals
-        prices = pd.Series([100, 101, 102], name='Price')
-        signals = pd.DataFrame(index=prices.index)
-        signals['price'] = prices
-        signals['positions'] = 0.0
-
-        # Capture stdout
-        captured_output = io.StringIO()
-        sys.stdout = captured_output
-
-        simulate_trading(signals, quiet=False)
-
-        sys.stdout = sys.__stdout__
-        output = captured_output.getvalue()
-
-        self.assertIn("Daily Trading Ledger", output)
-
-    def test_integration_no_color(self):
-        # Run the script via subprocess to verify --no-color
-        result = subprocess.run(
-            [sys.executable, 'bitcoin_trading_simulation.py', '--days', '5', '--no-color'],
-            capture_output=True,
-            text=True
-        )
-        # Check that ANSI codes are NOT present
-        self.assertNotIn('\033[', result.stdout)
-        # Check that the output is still meaningful
-        self.assertIn('Final Portfolio Performance', result.stdout)
-
-    def test_integration_quiet(self):
-        # Run the script via subprocess to verify --quiet
-        result = subprocess.run(
-            [sys.executable, 'bitcoin_trading_simulation.py', '--days', '5', '--quiet'],
-            capture_output=True,
-            text=True
-        )
-        # Check that Daily Ledger is NOT present
-        self.assertNotIn('Daily Trading Ledger', result.stdout)
-        # Check that Final Performance IS present
-        self.assertIn('Final Portfolio Performance', result.stdout)
-
-    def test_integration_args(self):
-        # Verify custom arguments work
-        result = subprocess.run(
-            [sys.executable, 'bitcoin_trading_simulation.py', '--days', '5', '--initial-cash', '500'],
-            capture_output=True,
-            text=True
-        )
-        self.assertIn('Initial Cash: $500.00', result.stdout)
-
-if __name__ == '__main__':
-    unittest.main()
+from bitcoin_trading_simulation import (
+    simulate_trading, Colors, calculate_moving_averages,
+    generate_trading_signals, simulate_bitcoin_prices
+)
+
+
+@pytest.fixture
+def reset_colors():
+    # Save original colors
+    original_colors = {
+        'HEADER': Colors.HEADER,
+        'BLUE': Colors.BLUE,
+        'GREEN': Colors.GREEN,
+        'RED': Colors.RED,
+        'ENDC': Colors.ENDC,
+        'BOLD': Colors.BOLD,
+    }
+    yield
+    # Restore colors
+    Colors.HEADER = original_colors['HEADER']
+    Colors.BLUE = original_colors['BLUE']
+    Colors.GREEN = original_colors['GREEN']
+    Colors.RED = original_colors['RED']
+    Colors.ENDC = original_colors['ENDC']
+    Colors.BOLD = original_colors['BOLD']
+
+
+def test_simulate_trading_quiet_mode(capsys):
+    """Test that quiet mode suppresses output."""
+    signals = pd.DataFrame(index=range(5))
+    signals['price'] = [100.0, 101.0, 102.0, 103.0, 104.0]
+    signals['positions'] = [0.0] * 5
+
+    simulate_trading(signals, initial_cash=1000, quiet=True)
+
+    captured = capsys.readouterr()
+    assert captured.out == ""
+
+
+def test_simulate_trading_verbose_mode(capsys):
+    """Test that verbose mode prints daily ledger."""
+    signals = pd.DataFrame(index=range(2))
+    signals['price'] = [100.0, 101.0]
+    signals['positions'] = [0.0, 0.0]
+
+    simulate_trading(signals, initial_cash=1000, quiet=False)
+
+    captured = capsys.readouterr()
+    assert "Daily Trading Ledger" in captured.out
+    assert "Portfolio Value" in captured.out
+
+
+def test_colors_disable(reset_colors):
+    """Test that Colors.disable() clears color codes."""
+    assert Colors.HEADER != ""
+    Colors.disable()
+    assert Colors.HEADER == ""
+    assert Colors.GREEN == ""
+    assert Colors.RED == ""
+
+
+def test_simulation_integration():
+    """Test full simulation pipeline with small parameters."""
+    prices = simulate_bitcoin_prices(days=10, initial_price=100)
+    signals = calculate_moving_averages(prices, short_window=2, long_window=5)
+    signals = generate_trading_signals(signals)
+    portfolio = simulate_trading(signals, quiet=True)
+
+    assert len(portfolio) == 10
+    assert 'total_value' in portfolio.columns
+    assert 'btc' in portfolio.columns
+    assert 'cash' in portfolio.columns