Develop

.Jules/palette.md

@@ -1,7 +1,3 @@
-## 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.
+## 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.

.github/workflows/codeql.yml

@@ -0,0 +1,101 @@
+# For most projects, this workflow file will not need changing; you simply need
+# to commit it to your repository.
+#
+# You may wish to alter this file to override the set of languages analyzed,
+# or to provide custom queries or build logic.
+#
+# ******** NOTE ********
+# We have attempted to detect the languages in your repository. Please check
+# the `language` matrix defined below to confirm you have the correct set of
+# supported CodeQL languages.
+#
+name: "CodeQL Advanced"
+
+on:
+  push:
+    branches: [ "main" ]
+  pull_request:
+    branches: [ "main" ]
+  schedule:
+    - cron: '42 16 * * 6'
+
+jobs:
+  analyze:
+    name: Analyze (${{ matrix.language }})
+    # Runner size impacts CodeQL analysis time. To learn more, please see:
+    #   - https://gh.io/recommended-hardware-resources-for-running-codeql
+    #   - https://gh.io/supported-runners-and-hardware-resources
+    #   - https://gh.io/using-larger-runners (GitHub.com only)
+    # Consider using larger runners or machines with greater resources for possible analysis time improvements.
+    runs-on: ${{ (matrix.language == 'swift' && 'macos-latest') || 'ubuntu-latest' }}
+    permissions:
+      # required for all workflows
+      security-events: write
+
+      # required to fetch internal or private CodeQL packs
+      packages: read
+
+      # only required for workflows in private repositories
+      actions: read
+      contents: read
+
+    strategy:
+      fail-fast: false
+      matrix:
+        include:
+        - language: actions
+          build-mode: none
+        - language: python
+          build-mode: none
+        # CodeQL supports the following values keywords for 'language': 'actions', 'c-cpp', 'csharp', 'go', 'java-kotlin', 'javascript-typescript', 'python', 'ruby', 'rust', 'swift'
+        # Use `c-cpp` to analyze code written in C, C++ or both
+        # Use 'java-kotlin' to analyze code written in Java, Kotlin or both
+        # Use 'javascript-typescript' to analyze code written in JavaScript, TypeScript or both
+        # To learn more about changing the languages that are analyzed or customizing the build mode for your analysis,
+        # see https://docs.github.com/en/code-security/code-scanning/creating-an-advanced-setup-for-code-scanning/customizing-your-advanced-setup-for-code-scanning.
+        # If you are analyzing a compiled language, you can modify the 'build-mode' for that language to customize how
+        # your codebase is analyzed, see https://docs.github.com/en/code-security/code-scanning/creating-an-advanced-setup-for-code-scanning/codeql-code-scanning-for-compiled-languages
+    steps:
+    - name: Checkout repository
+      uses: actions/checkout@v4
+
+    # Add any setup steps before running the `github/codeql-action/init` action.
+    # This includes steps like installing compilers or runtimes (`actions/setup-node`
+    # or others). This is typically only required for manual builds.
+    # - name: Setup runtime (example)
+    #   uses: actions/setup-example@v1
+
+    # Initializes the CodeQL tools for scanning.
+    - name: Initialize CodeQL
+      uses: github/codeql-action/init@v4
+      with:
+        languages: ${{ matrix.language }}
+        build-mode: ${{ matrix.build-mode }}
+        # If you wish to specify custom queries, you can do so here or in a config file.
+        # By default, queries listed here will override any specified in a config file.
+        # Prefix the list here with "+" to use these queries and those in the config file.
+
+        # For more details on CodeQL's query packs, refer to: https://docs.github.com/en/code-security/code-scanning/automatically-scanning-your-code-for-vulnerabilities-and-errors/configuring-code-scanning#using-queries-in-ql-packs
+        # queries: security-extended,security-and-quality
+
+    # If the analyze step fails for one of the languages you are analyzing with
+    # "We were unable to automatically build your code", modify the matrix above
+    # to set the build mode to "manual" for that language. Then modify this step
+    # to build your code.
+    # ℹ️ Command-line programs to run using the OS shell.
+    # 📚 See https://docs.github.com/en/actions/using-workflows/workflow-syntax-for-github-actions#jobsjob_idstepsrun
+    - name: Run manual build steps
+      if: matrix.build-mode == 'manual'
+      shell: bash
+      run: |
+        echo 'If you are using a "manual" build mode for one or more of the' \
+          'languages you are analyzing, replace this with the commands to build' \
+          'your code, for example:'
+        echo '  make bootstrap'
+        echo '  make release'
+        exit 1
+
+    - name: Perform CodeQL Analysis
+      uses: github/codeql-action/analyze@v4
+      with:
+        category: "/language:${{matrix.language}}"

.gitignore

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

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
 
@@ -20,16 +21,36 @@ pip install -r requirements.txt
 
 ## Usage
 
-Run the simulation script:
+Run the simulation script with default settings (60 days, $10k initial cash):
 
 ```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:
+Run the test suite using `pytest`:
 
 ```bash
-python test.py
+pytest
 ```

bitcoin_trading_simulation.py

@@ -1,7 +1,9 @@
+import argparse
 import numpy as np
 import pandas as pd
 import argparse
 
+
 class Colors:
     HEADER = '\033[95m'
     BLUE = '\033[94m'
@@ -19,6 +21,18 @@ 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.
@@ -33,6 +47,7 @@ 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.
@@ -43,6 +58,7 @@ 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.
@@ -54,11 +70,12 @@ 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.
@@ -71,6 +88,8 @@ 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']
@@ -81,30 +100,33 @@ 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.RED}Day {i}: 📉 Sell {portfolio.loc[i, 'btc']:.4f} BTC at ${row['price']:.2f}{Colors.ENDC}")
+                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}, 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, 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')
+    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()
 
@@ -113,33 +135,31 @@ 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 = initial_cash / prices.iloc[0]
+    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: ${initial_cash:.2f}")
     print(f"Final Portfolio Value: ${final_value:.2f}")
-
     if profit >= 0:
-        print(f"Profit/Loss: {Colors.GREEN}📈 ${profit:.2f}{Colors.ENDC}")
+        print(f"{Colors.GREEN}💰 Profit/Loss: ${profit:.2f}{Colors.ENDC}")
     else:
-        print(f"Profit/Loss: {Colors.RED}📉 ${profit:.2f}{Colors.ENDC}")
-
+        print(f"{Colors.FAIL}📉 Profit/Loss: ${profit:.2f}{Colors.ENDC}")
     print(f"Buy and Hold Strategy Value: ${buy_and_hold_value:.2f}")
     print(f"{Colors.HEADER}-----------------------------------------{Colors.ENDC}")

test_bitcoin.py

@@ -0,0 +1,35 @@
+import pytest
+from unittest.mock import patch
+from bitcoin import get_bitcoin_price, calculate_value
+
+# Test 1: Verify the calculation logic
+def test_calculate_value():
+    """Ensure BTC to USD conversion math is correct."""
+    price = 50000.0
+    amount = 2.5
+    expected = 125000.0
+    assert calculate_value(amount, price) == expected
+
+# Test 2: Verify handling of zero amount
+def test_calculate_value_zero():
+    assert calculate_value(0, 50000.0) == 0.0
+
+# Test 3: Mocking an API response
+@patch('bitcoin.requests.get')
+def test_get_bitcoin_price(mock_get):
+    """Simulate a successful API response from CoinDesk or similar."""
+    # Mock the JSON return value
+    mock_get.return_value.json.return_value = {
+        "bpi": {"USD": {"rate_float": 62000.50}}
+    }
+    mock_get.return_value.status_code = 200
+
+    price = get_bitcoin_price()
+    assert price == 62000.50
+
+# Test 4: Handling API failure
+@patch('bitcoin.requests.get')
+def test_get_price_api_error(mock_get):
+    mock_get.return_value.status_code = 404
+    with pytest.raises(ConnectionError):
+        get_bitcoin_price()