diff --git a/.Jules/palette.md b/.Jules/palette.md index 5de3a38..787ef57 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. + +## 2024-05-24 - Accessibility in CLI Tools +**Learning:** While colors and emojis improve scannability, they can be inaccessible to screen readers or users with specific terminal configurations. Providing standard flags like `--quiet` (for reducing noise) and `--no-color` (for plain text) is a critical UX pattern for CLI tools, allowing users to tailor the experience to their needs. +**Action:** Always include `--quiet` and `--no-color` flags in CLI applications to support diverse user needs and automation use cases. 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/__pycache__/bitcoin_trading_simulation.cpython-312.pyc b/__pycache__/bitcoin_trading_simulation.cpython-312.pyc new file mode 100644 index 0000000..f8671ae Binary files /dev/null and b/__pycache__/bitcoin_trading_simulation.cpython-312.pyc differ diff --git a/__pycache__/test_simulation.cpython-312-pytest-9.0.2.pyc b/__pycache__/test_simulation.cpython-312-pytest-9.0.2.pyc new file mode 100644 index 0000000..05c9eb5 Binary files /dev/null and b/__pycache__/test_simulation.cpython-312-pytest-9.0.2.pyc differ diff --git a/bitcoin_trading_simulation.py b/bitcoin_trading_simulation.py index 82df43f..991a673 100644 --- a/bitcoin_trading_simulation.py +++ b/bitcoin_trading_simulation.py @@ -1,3 +1,4 @@ +import argparse import numpy as np import pandas as pd @@ -9,6 +10,16 @@ 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 +34,7 @@ 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 +45,7 @@ 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. @@ -49,7 +62,8 @@ def generate_trading_signals(signals): 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. """ @@ -81,13 +95,28 @@ 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}, 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 (default: 60)') + parser.add_argument('--initial-cash', type=float, default=10000, help='Initial cash (default: 10000)') + parser.add_argument('--initial-price', type=float, default=50000, help='Initial Bitcoin price (default: 50000)') + parser.add_argument('--volatility', type=float, default=0.02, help='Volatility factor (default: 0.02)') + 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) @@ -96,11 +125,11 @@ def simulate_trading(signals, initial_cash=10000): 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 diff --git a/requirements.txt b/requirements.txt index 5da331c..b72ba0e 100644 --- a/requirements.txt +++ b/requirements.txt @@ -1,2 +1,4 @@ numpy pandas +pytest +flake8 diff --git a/test_simulation.py b/test_simulation.py new file mode 100644 index 0000000..ce87d73 --- /dev/null +++ b/test_simulation.py @@ -0,0 +1,33 @@ +import pandas as pd +import pytest +from bitcoin_trading_simulation import simulate_bitcoin_prices, calculate_moving_averages, generate_trading_signals + +def test_simulate_bitcoin_prices(): + days = 100 + prices = simulate_bitcoin_prices(days=days) + assert len(prices) == days + assert isinstance(prices, pd.Series) + assert prices.name == 'Price' + +def test_calculate_moving_averages(): + prices = pd.Series([100] * 50, name='Price') + signals = calculate_moving_averages(prices, short_window=5, long_window=10) + assert 'short_mavg' in signals.columns + assert 'long_mavg' in signals.columns + assert 'price' in signals.columns + +def test_generate_trading_signals(): + # Create a scenario where short crosses long + # signal: 0, 0, 1, 1 + # positions: NaN, 0, 1, 0 (shifted by 1) + + data = { + 'price': [100, 100, 100, 100], + 'short_mavg': [90, 95, 105, 110], + 'long_mavg': [100, 100, 100, 100] + } + signals = pd.DataFrame(data) + signals = generate_trading_signals(signals) + + assert 'positions' in signals.columns + assert 'signal' in signals.columns