Metadata-Version: 2.1
Name: pystockfilter
Version: 2.1.3
Summary: Intelligent Stock Screening for Informed Investment Decisions
License: MIT
Author: SlashGordon
Author-email: slash.gordon.dev@gmail.com
Requires-Python: >=3.11,<4.0
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Requires-Dist: backtesting (>=0.3.3,<0.4.0)
Requires-Dist: beautifulsoup4 (>=4.12.3,<5.0.0)
Requires-Dist: click (>=8.1.7,<9.0.0)
Requires-Dist: joblib (>=1.4.2,<2.0.0)
Requires-Dist: pandas-ta (>=0.3.14b0,<0.4.0)
Requires-Dist: pystockdb (>=1.2.0,<2.0.0)
Requires-Dist: python-dateutil (>=2.8.2,<3.0.0)
Requires-Dist: pytickersymbols (>=1.15.0,<2.0.0)
Requires-Dist: scikit-optimize (>=0.10.2,<0.11.0)
Requires-Dist: yfinance (>=0.2.43,<0.3.0)
Description-Content-Type: text/markdown

# PyStockFilter

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PyStockFilter is a Python library that allows users to create custom stock filters using a range of fundamental and technical indicators. With support for data sources like Yahoo Finance, local data, and `pystockdb`, PyStockFilter is a versatile solution for building and backtesting technical and fundamental trading strategies.

## Features

- **Data Compatibility**: Integrates with Yahoo Finance, local data, and `pystockdb`.
- **Built-in Indicators**: Includes essential technical indicators, and supports custom indicator creation.
- **Backtesting**: Enables testing of strategies on historical data.
- **Optimization Tools**: Offers parameter optimization, including sequential and chunked data optimization.
- **Custom Strategy Support**: Extendable with your own strategies and indicators.

## Built-in Filters

### Technical Filters
PyStockFilter includes several popular technical indicators, which can be used out of the box or customized:

- **Simple Moving Average (SMA)**
- **Exponential Moving Average (EMA)**
- **Relative Strength Index (RSI)**
- **Ultimate Oscillator (UO)**
- **Moving Average Convergence Divergence (MACD)**
- **Bollinger Bands (BB)**

For custom indicators, refer to the examples in the `src/pystockfilter/strategy` directory.

## Installation

To install PyStockFilter, run:

```shell
pip install pystockfilter
```

## Quick Start Guide

For detailed examples on setting up strategies, defining parameters, and running the optimizer, please visit the [Examples Directory](https://github.com/portfolioplus/pystockfilter/tree/master/examples) in the PyStockFilter repository.

## Issue Tracker

Report issues, request features, or contribute via the GitHub Issue Tracker:

[PyStockFilter Issue Tracker](https://github.com/portfolioplus/pystockfilter/issues)


## Disclaimer

This software is for educational purposes only. Do not risk money which you are afraid to lose. USE THE SOFTWARE AT YOUR OWN RISK. THE AUTHORS AND ALL AFFILIATES ASSUME NO RESPONSIBILITY FOR YOUR TRADING RESULTS.
