diff --git a/.Jules/palette.md b/.Jules/palette.md index 5de3a38..5f3846c 100644 --- a/.Jules/palette.md +++ b/.Jules/palette.md @@ -1,3 +1,7 @@ ## 2024-05-22 - Visual Hierarchy in CLI Output **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. + +## 2024-05-23 - Accessibility in CLI Tools +**Learning:** Command-line tools with hardcoded colors can be inaccessible or noisy in certain terminals/logs. Offering a `--no-color` and `--quiet` flag respects user preference and environment constraints. +**Action:** Always include standard `argparse` flags for verbosity and color control in CLI utilities. diff --git a/.gitignore b/.gitignore index d4fb281..907591b 100644 --- a/.gitignore +++ b/.gitignore @@ -39,3 +39,7 @@ # debug information files *.dwo + +# Python +__pycache__/ +*.pyc diff --git a/README.md b/README.md index be561ef..da86452 100644 --- a/README.md +++ b/README.md @@ -26,10 +26,25 @@ Run the simulation script: python bitcoin_trading_simulation.py ``` +### Options + +- `--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 +- `--no-color`: Disable colored output + +Example: + +```bash +python bitcoin_trading_simulation.py --days 100 --initial-cash 5000 --quiet --no-color +``` + ## Tests Run the test suite: ```bash -python test.py +pytest ``` diff --git a/bitcoin_trading_simulation.py b/bitcoin_trading_simulation.py index 82df43f..25da50c 100644 --- a/bitcoin_trading_simulation.py +++ b/bitcoin_trading_simulation.py @@ -1,6 +1,8 @@ +import argparse import numpy as np import pandas as pd + class Colors: HEADER = '\033[95m' BLUE = '\033[94m' @@ -9,6 +11,16 @@ class Colors: ENDC = '\033[0m' BOLD = '\033[1m' + @classmethod + def disable(cls): + cls.HEADER = '' + cls.BLUE = '' + cls.GREEN = '' + cls.RED = '' + 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. @@ -23,6 +35,7 @@ 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. @@ -33,6 +46,7 @@ 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. @@ -44,12 +58,13 @@ 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): + +def simulate_trading(signals, initial_cash=10000, quiet=False): """ Simulates trading based on signals and prints a daily ledger. """ @@ -59,7 +74,8 @@ def simulate_trading(signals, initial_cash=10000): portfolio['btc'] = 0.0 portfolio['total_value'] = float(initial_cash) - print(f"{Colors.HEADER}{Colors.BOLD}------ Daily Trading Ledger ------{Colors.ENDC}") + 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'] @@ -81,32 +97,49 @@ def simulate_trading(signals, initial_cash=10000): portfolio.loc[i, 'btc'] = 0 portfolio.loc[i, 'total_value'] = portfolio.loc[i, 'cash'] + portfolio.loc[i, 'btc'] * row['price'] - print(f"Day {i}: Portfolio Value: ${portfolio.loc[i, 'total_value']:.2f}, Cash: ${portfolio.loc[i, 'cash']:.2f}, BTC: {portfolio.loc[i, 'btc']:.4f}") - + 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}" + ) + 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, 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='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') + args = parser.parse_args() + + if args.no_color: + Colors.disable() + # Simulate prices - prices = simulate_bitcoin_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) - + portfolio = simulate_trading(signals, initial_cash=args.initial_cash, quiet=args.quiet) + # Final portfolio performance final_value = portfolio['total_value'].iloc[-1] - initial_cash = 10000 + initial_cash = args.initial_cash profit = final_value - initial_cash - + # Compare with buy and hold strategy buy_and_hold_btc = 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: ${initial_cash:.2f}") print(f"Final Portfolio Value: ${final_value:.2f}") diff --git a/test.py b/test.py deleted file mode 100644 index b326d87..0000000 --- a/test.py +++ /dev/null @@ -1,3 +0,0 @@ -# Filename: tests/test_sample.py -def test_example(): - assert 1 + 1 == 2 diff --git a/test_simulation.py b/test_simulation.py new file mode 100644 index 0000000..0e268fb --- /dev/null +++ b/test_simulation.py @@ -0,0 +1,42 @@ +import subprocess +import sys +import pandas as pd +from bitcoin_trading_simulation import simulate_bitcoin_prices, calculate_moving_averages, generate_trading_signals + + +def test_simulate_bitcoin_prices(): + days = 10 + prices = simulate_bitcoin_prices(days=days, initial_price=100, volatility=0.01) + assert len(prices) == days + assert isinstance(prices, pd.Series) + assert prices.iloc[0] == 100 + + +def test_calculate_moving_averages(): + prices = pd.Series([100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110]) + signals = calculate_moving_averages(prices, short_window=3, long_window=5) + assert 'short_mavg' in signals.columns + assert 'long_mavg' in signals.columns + assert not signals['short_mavg'].isnull().all() + + +def test_generate_trading_signals(): + # Create a dummy signal dataframe + data = { + 'price': [100, 110, 100, 90, 100], + 'short_mavg': [100, 110, 100, 90, 100], + 'long_mavg': [100, 100, 100, 100, 100] + } + signals = pd.DataFrame(data) + signals = generate_trading_signals(signals) + assert 'positions' in signals.columns + # Check if signals are generated (1.0 or -1.0 or 0.0) + assert signals['signal'].isin([1.0, -1.0, 0.0]).all() + + +def test_cli_execution(): + # Test running the script via subprocess to ensure it doesn't crash + result = subprocess.run([sys.executable, 'bitcoin_trading_simulation.py'], capture_output=True, text=True) + assert result.returncode == 0 + assert "Daily Trading Ledger" in result.stdout + assert "Final Portfolio Performance" in result.stdout