AlphaPy is a machine learning framework for both speculators and
data scientists. It is written in Python mainly with the scikit-learn
and pandas libraries, as well as many other helpful
packages for feature engineering and visualization.
🚀 AlphaPy Pro is Now Available!
AlphaPy Pro - the professional edition of AlphaPy - is now publicly available! Featuring modern Python 3.12+ support, enhanced performance, and enterprise-grade capabilities.
- Repository: https://github.com/ScottfreeLLC/alphapy-pro
- Documentation: https://scottfreellc.github.io/alphapy-pro/
- Installation:
pip install alphapy-pro
Here are just some of the things you can do with AlphaPy (legacy):
- Run machine learning models using
scikit-learn,Keras,xgboost,LightGBM, andCatBoost. - Generate blended or stacked ensembles.
- Create models for analyzing the markets with MarketFlow.
- Predict sporting events with SportFlow.
- Develop trading systems and analyze portfolios using MarketFlow
and Quantopian's
pyfolio.
AlphaPy Pro is the next generation of AlphaPy with enhanced features and modern capabilities:
- Modern Python 3.12+ support with UV package management
- Enhanced MarketFlow with advanced financial ML features
- MetaLabeling Support for sophisticated financial modeling
- NLP Features for sentiment analysis and text processing
- Automated CI/CD with GitHub Actions and PyPI publishing
- Comprehensive Documentation with tutorials and examples
Quick Start with AlphaPy Pro:
pip install alphapy-pro
Links:
- GitHub Repository: https://github.com/ScottfreeLLC/alphapy-pro
- Documentation: https://scottfreellc.github.io/alphapy-pro/
- PyPI Package: https://pypi.org/project/alphapy-pro/
Note: Active development has moved to AlphaPy Pro. This repository (AlphaPy) remains available for users who rely on the original version.
You should already have pip, Python, and optionally XGBoost, LightGBM, and CatBoost installed on your system (see below). Run the following command to install AlphaPy:
pip install -U alphapy
Pyfolio is automatically installed by AlphaPy, but if you encounter the following error when trying to create a tear sheet:
AttributeError: 'numpy.int64' object has no attribute 'to_pydatetime'
Install pyfolio with this command:
pip install git+https://github.com/quantopian/pyfolio
For Mac and Windows users, XGBoost will not install automatically
with pip. For instructions to install XGBoost on your specific
platform, go to http://xgboost.readthedocs.io/en/latest/build.html.
For instructions to install LightGBM on your specific platform, go to https://lightgbm.readthedocs.io/en/latest/Installation-Guide.html.
For instructions to install CatBoost on your specific platform, go to https://catboost.ai/docs/concepts/python-installation.html.
You can find an implementation of MarketFlow here:
https://www.scottfreellc.com/gamept
The official channel for support is to open an issue on Github.
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If you like the software, please donate: