Installation¶

This guide covers how to install Backtrader and configure your environment for optimal performance.

Requirements¶

Python: 3.9+ (3.11+ recommended for ~15% performance boost)
Operating System: Windows / macOS / Linux
Memory: 4GB+ recommended

Core Dependencies¶

NumPy >= 1.20.0
python-dateutil

Optional Dependencies¶

Package	Purpose
matplotlib	Static chart plotting
plotly	Interactive HTML charts (recommended)
bokeh	Real-time chart updates
pandas	DataFrame data feeds
scipy	Statistical functions
ib_insync	Interactive Brokers integration
ccxt	Cryptocurrency exchange integration

Installation Methods¶

From GitHub (Recommended)¶

This is the recommended method to get the latest optimized version:

# Clone from GitHub
git clone https://github.com/cloudQuant/backtrader.git
cd backtrader

# Install dependencies
pip install -r requirements.txt

# Install backtrader in development mode
pip install -e .

From Gitee (China)¶

For users in China, use the Gitee mirror for faster download:

git clone https://gitee.com/yunjinqi/backtrader.git
cd backtrader
pip install -r requirements.txt
pip install -e .

With Visualization Support¶

# Install with all plotting backends
pip install matplotlib plotly bokeh

With Live Trading Support¶

# For Interactive Brokers
pip install ib_insync

# For cryptocurrency exchanges
pip install ccxt

Virtual Environment (Recommended)¶

Using a virtual environment prevents conflicts:

# Create virtual environment
python -m venv bt_env

# Activate (Linux/Mac)
source bt_env/bin/activate

# Activate (Windows)
bt_env\Scripts\activate

# Install backtrader
pip install -e .

Performance Optimization¶

Python 3.11+¶

Using Python 3.11+ provides approximately 15-20% speed improvement:

# Check your Python version
python --version

# If needed, install Python 3.11+
# Then run your strategy
python3.11 your_strategy.py

Cython Acceleration¶

For maximum performance, compile Cython extensions:

# Install Cython
pip install cython

# Compile extensions (if available)
python setup.py build_ext --inplace

Verification¶

Verify your installation:

import backtrader as bt
print(f"Backtrader version: {bt.__version__}")

Quick Test¶

import backtrader as bt

# Create engine
cerebro = bt.Cerebro()
cerebro.broker.setcash(100000)

print(f'Starting portfolio value: {cerebro.broker.getvalue():.2f}')
cerebro.run()
print(f'Final portfolio value: {cerebro.broker.getvalue():.2f}')
print('Installation successful!')

Run Tests¶

To verify everything works correctly:

# Run test suite
pytest ./tests -n 4 -v

Troubleshooting¶

Common Issues¶

Import Error: No module named 'backtrader'

# Ensure you're in the correct environment
pip install -e .

Matplotlib backend issues

import matplotlib
matplotlib.use('Agg')  # For headless environments

Memory errors with large datasets

cerebro = bt.Cerebro(
    exactbars=True,   # Minimize memory usage
    stdstats=False    # Disable observers
)

TA-Lib Installation¶

For TA-Lib indicator support:

macOS:

brew install ta-lib
pip install TA-Lib

Linux (Ubuntu/Debian):

sudo apt-get install ta-lib
pip install TA-Lib

Windows:

Download pre-built wheel from https://www.lfd.uci.edu/~gohlke/pythonlibs/#ta-lib

pip install TA_Lib‑0.4.24‑cp311‑cp311‑win_amd64.whl

Next Steps¶

Quickstart - Your first strategy
Core Concepts - Core concepts
Data Feeds - Loading data