AlphaPy

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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, and CatBoost.
• 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.

.. image:: https://github.com/Alpha314/AlphaPy/blob/master/images/model_pipeline.png :width: 100% :alt: AlphaPy Model Pipeline :align: center

AlphaPy Pro: Now Available!

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.

Documentation

http://alphapy.readthedocs.io/en/latest/

Installation

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

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

XGBoost

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.

LightGBM

For instructions to install LightGBM on your specific
platform, go to https://lightgbm.readthedocs.io/en/latest/Installation-Guide.html.

CatBoost

For instructions to install CatBoost on your specific platform, go to https://catboost.ai/docs/concepts/python-installation.html.

MarketFlow

.. image:: https://github.com/Alpha314/AlphaPy/blob/master/images/market_pipeline.png :width: 100% :alt: MarketFlow Model :align: center

.. image:: https://github.com/Alpha314/AlphaPy/blob/master/images/system_pipeline.png :width: 100% :alt: MarketFlow System :align: center

SportFlow

.. image:: https://github.com/Alpha314/AlphaPy/blob/master/images/sports_pipeline.png :width: 100% :alt: SportFlow :align: center

GamePT

You can find an implementation of MarketFlow here:

https://www.scottfreellc.com/gamept

Support

The official channel for support is to open an issue on Github.

http://github.com/ScottfreeLLC/AlphaPy/issues

Follow us on Twitter:

https://twitter.com/_AlphaPy_?lang=en

Donations

If you like the software, please donate:

http://alphapy.readthedocs.io/en/latest/introduction/support.html#donations

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