pyalgotrading

Official Python Package for Algorithmic Trading APIs powered by AlgoBulls!

Features

Powered by the AlgoBulls Platform
Everything related to Algorithmic Trading Strategies!
- Free pool of Strategies are available at pyalgostrategypool!
- Create & upload strategies easily on the cloud
- Support for all 150+ Technical Indicators provided by TA-Lib
- Support for multiple candlesticks patterns - Japanese OHLC, Renko, Heikin-Ashi, Linebreak
- Support for multiple candle intervals - 1 minute, 3 minutes, 5 minutes, 10 minutes, 15 minutes, 30 minutes, 1 hour, 1 day.
- Support for Regular Orders, Bracket Orders and Cover Orders
- Support for MARKET, LIMIT, STOPLOSS-LIMIT, STOPLOSS-MARKET orders
- Support for INTRADAY and DELIVERY orders
Support for Backtesting
Support for Paper Trading
Support for Live Trading / Real Trading
Support for multiple brokers for Live Trading. Check list of supported brokers here.
Real-time Logs for Backtesting, Paper Trading, Live Trading
Multiple real-time Reports available for Backtesting, Paper Trading and Live Trading:
- Profit-&-Loss report (P&L report)
- Statistics Report
- Order History Log for each order with state transitions & timestamps
- Detailed analytics with charts
Support for calculating Slippage
Support for calculating Brokerage
Support for importing external P&L table and generating analytics on the same
Plot Candlestick charts using plotly.py

Backtesting, Paper Trading and Real Trading can be performed on the same strategy code base!

Documentation

You can find the docs here.

Jupyter Notebooks

Easily access and use complete Jupyter Notebook for NASDSAQ and NSE markets here. You can:

Easily view them on the web using nbviewer, without installing Python or Jupyter Notebooks.
Easily execute them on the web using Binder, without installing Python or Jupyter Notebooks.
Download and use them on your local machine, and installing Python & Jupyter Notebooks

Python

Python Support: Python 3.8+.
Python Requirements: See requirements.txt.
We recommend you to use the latest version of Python (v3.8+) to enjoy better performance benefits, especially for pandas.

Installation

Package can be easily installed using pip -

pip install pyalgotrading

Support / Getting Help

Bug Reporting / New Feature Request: Please create a new issue here on GitHub.
Discussion Community: Slack
Additional Support: If none of the above help, please contact pushpak@algobulls.com.

Contribution Guidelines

Here’s how we suggest you go about proposing a change to this project:

Fork this project to your account.
Create a branch for the change you intend to make.
Make your changes to your fork.
Send a pull request from your fork’s branch to our master branch.

Rewards

If you are interested in contributing to this repo, pyalgotrading or pyalgostrategypool, our official pool of FREE algorithmic trading strategies, please join our official Slack community. You would be provided with credits for unlimited trading access on the AlgoBulls platform.

Changelog

See CHANGELOG.md.

License

See LICENSE.

Metadata

Release files for pyalgotrading 2026.2.2

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Built distribution (wheel)

Table of built distributions (wheels) for pyalgotrading 2026.2.2
File	Interpreter	ABI	Platform	Reset
pyalgotrading-2026.2.2-py3-none-any.whl 43.4 kB Feb 4, 2026	Python 3	none	any	Details

Release files / pyalgotrading-2026.2.2-py3-none-any.whl

Download URL	pyalgotrading-2026.2.2-py3-none-any.whl
Size	43.4 kB
Tags	Python 3
SHA-256 checksum How to use checksums	`7f9d00e45e7ab45e9de307d4714dbe1a98e6448ed12083d2c379239a94e24bf3`
BLAKE2b-256 checksum How to use checksums	`1d263f3a72a2baf33e40c54039b70ee175407032e6db48ef9192bfe79ecdfbd7`
Upload date	Feb 4, 2026
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/5.1.1 CPython/3.11.9`