Revert "Develop"

.Jules/palette.md

@@ -1,3 +1,7 @@
-## 2024-05-23 - CLI UX Enhancement
-**Learning:** Even in CLI apps, visual distinction (colors, emojis) significantly reduces cognitive load when scanning logs.
-**Action:** Use ANSI colors and consistent emojis for key events (success/failure) in future CLI tools.
+## 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 and Control in CLI Tools
+**Learning:** While color and emojis improve scannability, they can be distracting or inaccessible (e.g., for color-blind users or automated parsing). Providing `--no-color` and `--quiet` flags is essential for accessibility and flexibility.
+**Action:** Always include flags to disable visual enhancements and suppress verbose output in CLI tools to respect user preferences and support automation.

.gitignore

@@ -43,3 +43,4 @@
 # Python
 __pycache__/
 *.pyc
+.pytest_cache/

README.md

@@ -4,11 +4,10 @@ A Python-based CLI tool that simulates Bitcoin trading using a 'Golden Cross' mo
 
 ## Features
 
-- **Price Simulation:** Uses Geometric Brownian Motion to simulate Bitcoin prices.
+- **Price Simulation:** Uses Geometric Brownian Motion to simulate 60 days of 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
 
@@ -21,36 +20,16 @@ pip install -r requirements.txt
 
 ## Usage
 
-Run the simulation script with default settings (60 days, $10k initial cash):
+Run the simulation script:
 
 ```bash
 python bitcoin_trading_simulation.py
 ```
 
-### Options
-
-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`: 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 30 --quiet --no-color
-```
-
 ## Tests
 
-Run the test suite using `pytest`:
+Run the test suite:
 
 ```bash
-pytest
+python test.py
 ```

bitcoin_trading_simulation.py

@@ -1,9 +1,7 @@
-import argparse
 import numpy as np
 import pandas as pd
 import argparse
 
-
 class Colors:
     HEADER = '\033[95m'
     BLUE = '\033[94m'
@@ -21,18 +19,6 @@ def disable(cls):
         cls.ENDC = ''
         cls.BOLD = ''
 
-
-class Colors:
-    HEADER = '\033[95m'
-    BLUE = '\033[94m'
-    CYAN = '\033[96m'
-    GREEN = '\033[92m'
-    WARNING = '\033[93m'
-    FAIL = '\033[91m'
-    ENDC = '\033[0m'
-    BOLD = '\033[1m'
-    UNDERLINE = '\033[4m'
-
 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.
@@ -47,7 +33,6 @@ 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.
@@ -58,7 +43,6 @@ 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.
@@ -70,12 +54,11 @@ 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.
@@ -88,8 +71,6 @@ def simulate_trading(signals, initial_cash=10000, quiet=False):
 
     if not quiet:
         print(f"{Colors.HEADER}{Colors.BOLD}------ Daily Trading Ledger ------{Colors.ENDC}")
-
-    print(f"\n{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']
@@ -100,33 +81,30 @@ 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}")
+            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}")
+                print(f"{Colors.RED}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}")
-
+            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")
-    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")
+    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 in portfolio')
+    parser.add_argument('--initial-price', type=float, default=50000, help='Initial Bitcoin price')
+    parser.add_argument('--volatility', type=float, default=0.02, help='Volatility of price changes')
+    parser.add_argument('--quiet', '-q', action='store_true', help='Suppress daily portfolio logs')
+    parser.add_argument('--no-color', action='store_true', help='Disable colored output')
 
     args = parser.parse_args()
 
@@ -135,31 +113,33 @@ 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]
     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_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}")
+
     if profit >= 0:
-        print(f"{Colors.GREEN}💰 Profit/Loss: ${profit:.2f}{Colors.ENDC}")
+        print(f"Profit/Loss: {Colors.GREEN}📈 ${profit:.2f}{Colors.ENDC}")
     else:
-        print(f"{Colors.FAIL}📉 Profit/Loss: ${profit:.2f}{Colors.ENDC}")
+        print(f"Profit/Loss: {Colors.RED}📉 ${profit:.2f}{Colors.ENDC}")
+
     print(f"Buy and Hold Strategy Value: ${buy_and_hold_value:.2f}")
     print(f"{Colors.HEADER}-----------------------------------------{Colors.ENDC}")

test.py

@@ -0,0 +1,3 @@
+# Filename: tests/test_sample.py
+def test_example():
+    assert 1 + 1 == 2