https://github.com/xajason/bitcoin-strategy-backtester
Professional financial chart generator for cryptocurrency and stocks with technical indicators, volume analysis, and intelligent data caching.
https://github.com/xajason/bitcoin-strategy-backtester
bitcoin charting charts cli cryptocurrency data-vizualization finance financial-data matplotlib python sqlite stocks technical-analysis trading yahoo-finance
Last synced: 3 days ago
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Professional financial chart generator for cryptocurrency and stocks with technical indicators, volume analysis, and intelligent data caching.
- Host: GitHub
- URL: https://github.com/xajason/bitcoin-strategy-backtester
- Owner: XaJason
- License: mit
- Created: 2025-09-03T14:25:18.000Z (about 1 month ago)
- Default Branch: main
- Last Pushed: 2025-09-04T02:14:05.000Z (about 1 month ago)
- Last Synced: 2025-09-04T04:19:46.572Z (about 1 month ago)
- Topics: bitcoin, charting, charts, cli, cryptocurrency, data-vizualization, finance, financial-data, matplotlib, python, sqlite, stocks, technical-analysis, trading, yahoo-finance
- Language: Python
- Homepage: https://github.com/XaJason/bitcoin-strategy-backtester
- Size: 17.5 MB
- Stars: 1
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# 📈 Bitcoin Strategy Backtester
[](https://www.python.org/downloads/)
[](https://opensource.org/licenses/MIT)
[](https://github.com/psf/black)
[](https://docs.pytest.org/)
> A professional Python-based financial chart generator and data analysis tool for cryptocurrency and stock market visualization. Generate publication-ready charts with technical indicators, volume analysis, and intelligent data caching.
## 📋 Table of Contents
- [Overview](#-overview)
- [Features](#-features)
- [Installation](#-installation)
- [Quick Start](#-quick-start)
- [Usage](#-usage)
- [Chart Types & Indicators](#-chart-types--indicators)
- [Technical Architecture](#-technical-architecture)
- [Examples](#-examples)
- [Development](#-development)
- [Contributing](#-contributing)
- [License](#-license)
## 🚀 Overview
The Bitcoin Strategy Backtester is a powerful financial chart generation and data analysis tool built for traders, analysts, and developers. It provides professional-grade charting capabilities with real-time data fetching, intelligent caching, and comprehensive technical analysis features.
**What it does:**
- Generates professional financial charts for any Yahoo Finance symbol (BTC-USD, AAPL, TSLA, etc.)
- Provides multiple chart styles: candlestick, OHLC, line, and area charts
- Calculates and displays technical indicators with proper statistical validity
- Offers interactive CLI interface for rapid chart generation
- Manages data efficiently with SQLite caching and automatic expiry
**Target Users:**
- Financial analysts creating presentations and reports
- Cryptocurrency traders analyzing market trends
- Python developers building financial applications
- Researchers studying market behavior and technical analysis
## ✨ Features
### 📊 Professional Chart Generation
- **Multiple Chart Styles**: Candlestick, OHLC bars, line charts, and area charts
- **Comprehensive Timeframes**: 5D, 1M, 3M, 6M, YTD, 1Y, 5Y, and MAX (all available data)
- **Technical Indicators**: Moving averages (MA50, MA200) with proper lookback calculations
- **Volume Analysis**: Subplot and overlay volume visualization with up/down coloring
- **Scaling Options**: Linear and logarithmic price scales
### 🔄 Intelligent Data Management
- **Real-time Data**: Fetches live market data from Yahoo Finance
- **SQLite Caching**: Local database storage for improved performance
- **Cache Expiry System**: Automatic data refresh with configurable expiry (1-24 hours)
- **Gap Filling**: Smart handling of weekend and holiday data gaps
- **Data Validation**: Comprehensive OHLCV data quality checks
### 🖥️ Interactive CLI Interface
- **Command-line Interface**: Simple, powerful chart generation commands
- **Interactive Mode**: Step-by-step chart creation with guided prompts
- **Cache Management**: Built-in commands for cache status, refresh, and cleanup
- **Chart History**: Automatic saving and organization of generated charts
- **Export Options**: High-resolution PNG output for presentations
### 🏗️ Professional Architecture
- **Modular Design**: Clean separation of data, visualization, and interface layers
- **Extensible Framework**: Easy integration of new indicators and chart types
- **Memory Efficient**: Optimized data handling for large datasets
- **Error Handling**: Robust error recovery and user feedback
- **Test Coverage**: Comprehensive test suite with pytest
## 🛠 Installation
### Prerequisites
- **Python 3.11** or higher
- **pip** package manager
- **Git** for cloning the repository
### Setup Instructions
1. **Clone the repository**
```bash
git clone https://github.com/XaJason/bitcoin-strategy-backtester.git
cd bitcoin-strategy-backtester
```
2. **Create virtual environment**
```bash
# Windows
python -m venv venv
venv\Scripts\activate
# macOS/Linux
python3 -m venv venv
source venv/bin/activate
```
3. **Install dependencies**
```bash
pip install --upgrade pip
pip install -r requirements.txt
```
4. **Verify installation**
```bash
python chart_explorer.py --help
```
## 🚀 Quick Start
### Generate Your First Chart
```bash
# Bitcoin 1-year candlestick chart with moving averages
python chart_explorer.py BTC-USD --timeframe 1Y --style candlestick --indicators BOTH --volume subplot
# Apple stock 6-month chart with MA50
python chart_explorer.py AAPL --timeframe 6M --style candlestick --indicators MA50
# Tesla 5-year line chart with logarithmic scale
python chart_explorer.py TSLA --timeframe 5Y --style line --scale log
```
### Interactive Mode
```bash
python chart_explorer.py
# Follow the prompts to create custom charts
```
### Cache Management
```bash
# Check cache status
python chart_explorer.py --cache-status
# Refresh all cached data
python chart_explorer.py --cache-refresh
# View cache statistics
python chart_explorer.py --cache-info
```
## 📈 Chart Types & Indicators
### Supported Chart Styles
- **Candlestick**: Professional OHLC candlestick charts with customizable colors
- **OHLC**: Traditional open-high-low-close bar charts
- **Line**: Clean line charts using closing prices
- **Area**: Filled area charts for trend visualization
### Technical Indicators (Currently Implemented)
- **MA50**: 50-period Simple Moving Average
- **MA200**: 200-period Simple Moving Average
- **BOTH**: Display both MA50 and MA200 simultaneously
- **Proper Lookback**: Indicators calculated with sufficient historical data for statistical validity
### Volume Analysis
- **Subplot**: Volume displayed in separate chart below price data
- **Overlay**: Volume overlaid on price chart with transparency
- **Up/Down Coloring**: Green for up days, red for down days
### Supported Symbols
Any Yahoo Finance symbol including:
- **Cryptocurrencies**: BTC-USD, ETH-USD, ADA-USD, DOT-USD
- **US Stocks**: AAPL, TSLA, GOOGL, MSFT, AMZN
- **Indices**: ^GSPC (S&P 500), ^DJI (Dow Jones), ^IXIC (NASDAQ)
- **Forex**: EURUSD=X, GBPUSD=X, USDJPY=X
## 🏗️ Technical Architecture
### Core Components
```
bitcoin-strategy-backtester/
├── chart_explorer.py # Main CLI interface
├── src/
│ ├── data/
│ │ ├── database.py # SQLite OHLCV database
│ │ ├── cache_manager.py # Intelligent caching system
│ │ └── fetcher.py # Yahoo Finance data fetcher
│ ├── visualization/
│ │ ├── chart_engine.py # Core plotting engine
│ │ ├── indicators.py # Technical indicator calculations
│ │ ├── styles.py # Chart styling and themes
│ │ └── formatters.py # Axis formatting and labels
│ └── utils/
│ └── config.py # Configuration management
├── examples/ # Sample charts and demos
├── tests/ # Comprehensive test suite
└── tools/ # Database utilities
```
### Technology Stack
- **Data Processing**: pandas, numpy for efficient data manipulation
- **Visualization**: matplotlib, mplfinance for professional chart rendering
- **Data Source**: yfinance for real-time market data
- **Database**: SQLite for local data caching
- **Testing**: pytest for comprehensive test coverage
- **CLI**: argparse for command-line interface
### Performance Characteristics
- **Data Fetching**: ~1-2 seconds for real-time data
- **Chart Generation**: ~2-3 seconds for complex charts with indicators
- **Cache Hit**: <0.5 seconds for cached data retrieval
- **Memory Usage**: ~50-200MB depending on data timeframe
- **Storage**: ~1-5MB per cached symbol dataset
## 📸 Examples
### Command Examples with Outputs
```bash
# Professional Bitcoin analysis chart
python chart_explorer.py BTC-USD --timeframe 1Y --style candlestick --indicators BOTH --volume subplot
# Output: chart_BTC-USD_1Y_candlestick_[timestamp].png
# Apple stock quarterly analysis
python chart_explorer.py AAPL --timeframe 3M --style candlestick --indicators MA50 --volume overlay
# Output: chart_AAPL_3M_candlestick_[timestamp].png
# Tesla long-term trend analysis
python chart_explorer.py TSLA --timeframe 5Y --style line --scale log --indicators MA200
# Output: chart_TSLA_5Y_line_[timestamp].png
```
### Available Chart Examples
The `examples/charts/` directory contains sample outputs including:
- Multi-timeframe analysis (5D to MAX)
- Various chart styles (candlestick, line, area, OHLC)
- Technical indicator combinations
- Volume visualization options
- Linear vs logarithmic scaling examples
### Use Cases
- **Portfolio Presentations**: Generate professional charts for client meetings
- **Technical Analysis**: Analyze trends with proper moving average calculations
- **Market Research**: Compare multiple symbols across different timeframes
- **Educational Content**: Create charts for trading education and tutorials
## 🔧 Development
### Running Tests
```bash
# Run all tests
pytest
# Run with coverage
pytest --cov=src --cov-report=html
# Run specific test modules
pytest tests/test_chart_engine.py -v
```
### Code Quality
```bash
# Format code
black src/ tests/
# Check code style
flake8 src/ tests/
```
### Adding New Features
1. **New Indicators**: Add methods to `TechnicalIndicators` class in `indicators.py`
2. **Chart Styles**: Extend chart plotting methods in `chart_engine.py`
3. **Data Sources**: Implement new fetcher classes following the `YahooFetcher` pattern
## 🤝 Contributing
This project welcomes contributions! Current areas for enhancement:
### Contribution Guidelines
1. Fork the repository
2. Create a feature branch (`git checkout -b feature/new-indicator`)
3. Add tests for new functionality
4. Ensure all tests pass (`pytest`)
5. Submit a pull request
### Development Setup
```bash
# Install development dependencies
pip install -r requirements.txt
pip install black flake8 pytest-cov
# Run pre-commit checks
python -m pytest
python -m black --check src/ tests/
```
## 📄 License
This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.
---
**Built with ❤️ for the financial analysis community**
*Generate professional charts • Analyze market trends • Make data-driven decisions*