https://github.com/quarkfin/qf-lib

Modular Python library that provides an advanced event driven backtester and a set of high quality tools for quantitative finance. Integrated with various data vendors and brokers, supports Crypto, Stocks and Futures.
https://github.com/quarkfin/qf-lib

backtesting backtesting-frameworks backtesting-trading-strategies finance investment-analysis python quant quantitative-finance trading trading-simulator trading-strategies

Last synced: 25 days ago
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Modular Python library that provides an advanced event driven backtester and a set of high quality tools for quantitative finance. Integrated with various data vendors and brokers, supports Crypto, Stocks and Futures.

• Host: GitHub
• URL: https://github.com/quarkfin/qf-lib
• Owner: quarkfin
• License: apache-2.0
• Created: 2019-08-16T09:10:20.000Z (over 6 years ago)
• Default Branch: master
• Last Pushed: 2026-01-26T16:46:39.000Z (about 2 months ago)
• Last Synced: 2026-01-27T04:16:40.014Z (about 2 months ago)
• Topics: backtesting, backtesting-frameworks, backtesting-trading-strategies, finance, investment-analysis, python, quant, quantitative-finance, trading, trading-simulator, trading-strategies
• Language: Python
• Homepage: https://quarkfin.github.io/qf-lib-info/
• Size: 130 MB
• Stars: 848
• Watchers: 18
• Forks: 124
• Open Issues: 6
• Metadata Files:
  • Readme: README.md
  • License: LICENSE
  • Code of conduct: CODE_OF_CONDUCT.md

Awesome Lists containing this project

• awesome-quant - qf-lib - QF-Lib is a Python library that provides high quality tools for quantitative finance. (Python / Trading & Backtesting)
• awesome-systematic-trading - qf-lib - commit/quarkfin/qf-lib/master)  | Python | - Modular Python library that provides an advanced event driven backtester and a set of high quality tools for quantitative finance. Integrated with various data vendors and brokers, supports Crypto, Stocks and Futures. (Backtest + live trading / General purpose)

README

          
# QF-Lib

[![PyPI](https://img.shields.io/pypi/v/qf-lib?color=green&label=PyPI%20Latest%20Release)](https://pypi.org/project/qf-lib/)

[![Downloads](https://static.pepy.tech/personalized-badge/qf-lib?period=month&units=international_system&left_color=grey&right_color=blue&left_text=PyPI%20Downloads%20/%20month)](https://pepy.tech/project/qf-lib)

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[![Codecov](https://img.shields.io/codecov/c/gh/quarkfin/qf-lib?color=pink)](https://app.codecov.io/gh/quarkfin/qf-lib)

[![Documentation Status](https://readthedocs.org/projects/qf-lib/badge/)](https://qf-lib.readthedocs.io/)

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![PyPI - Status](https://img.shields.io/pypi/status/qf-lib?color=darkgreen)

## What is QF-lib?

**QF-Lib** is a Python library that provides high quality tools for quantitative finance. 

A large part of the project is dedicated to backtesting investment strategies. 

The Backtester uses an **event-driven architecture** and simulates events such as daily market opening 

or closing. It is designed to **test and evaluate any custom investment strategy**.

Main features include:

* Flexible data sourcing - the project supports the possibility of an easy selection of the data source. Currently provides financial data from **Bloomberg**, **Quandl**, **Haver Analytics** or **Portara**. To check if there are any additional dependencies necessary for any of these data providers please visit [the installation guide](https://qf-lib.readthedocs.io/en/latest/installation.html#installing-optional-data-providers).

* Tools to prevent look-ahead bias in the backtesting environment.

* Adapted [data containers](https://qf-lib.readthedocs.io/en/latest/reference/structure.html#containers), which extend the functionality of pandas `Series'` and `Dataframes`.

* Summary generation - all performed studies can be summarized with a practical and informative document explaining the results. [Several document templates](https://qf-lib.readthedocs.io/en/latest/reference/structure.html#analysis) are available in the project.

* Simple adjustment of existing settings and creation of new functionalities.

## Installation

You can install `qf-lib` using the pip command:

```sh

pip install qf-lib

```

 

Alternatively, to install the library from sources, you can download the project and in the qf_lib directory 

(same one where you found this file after cloning the repository) execute the following command:

```sh

python setup.py install

```

## Prerequisites

The library uses [WeasyPrint](https://weasyprint.readthedocs.io) to export documents to PDF. WeasyPrint requires additional dependencies, check the 

[platform-specific instructions for Linux, macOS and Windows installation](https://weasyprint.readthedocs.io/en/stable/install.html).

In order to facilitate the GTK3+ installation process for Windows you can use 

[following installers](https://github.com/tschoonj/GTK-for-Windows-Runtime-Environment-Installer/releases). Download and run the latest 

`gtk3-runtime-x.x.x-x-x-x-ts-win64.exe` file to install the GTK3+.

## Documentation

* Installation guide: https://qf-lib.readthedocs.io/en/latest/installation.html

* Configuration guide: https://qf-lib.readthedocs.io/en/latest/configuration.html

* API documentation: https://qf-lib.readthedocs.io/

## How to Contribute

We welcome all contributions - bug reports, fixes, documentation improvements, new features, or ideas! Here’s how you can get involved:

* Find an Issue: Check out the GitHub Issues tab. Look for labels like *documentation* or *good first issue* to get started.

* Triage Issues: Help by reproducing bugs, asking for missing details (e.g., version numbers, steps to reproduce), or clarifying discussions.

* Share Your Ideas: If you spot something missing or have an improvement in mind, open an issue or submit a pull request.

* Join the Discussion: Have questions or want to collaborate? Join our [Discord community](https://discord.gg/CfMf8zaeX9).

Code of Conduct: All participants are expected to follow our [Code of Conduct](https://github.com/quarkfin/qf-lib/blob/master/CODE_OF_CONDUCT.md).