QuantConnect/Lean

Lean Algorithmic Trading Engine by QuantConnect (Python, C#)

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Summary Information

Updated 37 minutes ago
Added to GitGenius on December 7th, 2025
Created on November 28th, 2014
Open Issues & Pull Requests: 281 (+0)
Number of forks: 5,188
Total Stargazers: 21,330 (+0)
Total Subscribers: 491 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 5.8 days
Mean response time: 198.5 days
90th percentile: 703.1 days
Tracked items: 661

How this project is maintained

Around half of the issues opened in the past year never receive a reply. 32% of open issues come from outside the core team, a mix of external reports and the maintainers' own roadmap. Work labelled "bug" is answered fastest, typically in about 3 days, while "impact-low" waits about 30 months. 54% of tracked open issues have had no activity in three months. Only 14% of issues opened in the past year have been closed.

Charts & Analytics

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Issue Activity (beta)

Open issues: 213
New in 7 days: 9
Closed in 7 days: 4
Avg open age: 761 days
Stale 30+ days: 198
Stale 90+ days: 187

Recent activity

Opened in 7 days: 7
Closed in 7 days: 4
Comments in 7 days: 1
Events in 7 days: 5

Top labels

  • bug (859)
  • feature (416)
  • library-request (209)
  • depth (128)
  • good first issue (101)
  • indicator (82)
  • refactor (66)
  • impact-low (53)

Detailed Description

Lean is an event-driven, professional-grade algorithmic trading platform developed by QuantConnect, written primarily in C# with Python support. The engine is designed for backtesting and live trading across multiple financial markets including stocks, forex, options, and cryptocurrencies. It emphasizes elegant engineering and deep quantitative concept modeling, offering out-of-the-box support for alternative data sources and live trading capabilities.

The platform follows a modular architecture where each component is pluggable and customizable. This design allows developers to swap implementations at major integration points while the engine ships with default models for all critical plug-in points. The modularity extends to data providers, brokerages, portfolio managers, and execution models, enabling users to tailor the system to their specific requirements without modifying core functionality.

Lean includes a command-line interface tool that streamlines the workflow for quant developers. The CLI enables project management, local backtesting, algorithm optimization, and live trading deployment directly from the terminal. It supports Docker-based execution for backtesting and optimization, Jupyter Lab environments for interactive development, and seamless integration with QuantConnect's cloud services. The CLI abstracts away infrastructure complexity, allowing developers to focus on strategy development rather than deployment mechanics.

The repository supports multiple development environments. On macOS, developers can use Visual Studio Code with the C# Dev Kit extension and dotnet 9 SDK. Linux users on Debian and Ubuntu can compile and run Lean after installing dotnet 9. Windows developers have the option to use Visual Studio with the QuantConnect.Lean.sln solution file. Python algorithm development is fully supported through a dedicated Algorithm.Python project with comprehensive installation documentation.

The repository's contributor network overlaps with major open-source projects including microsoft/vscode, microsoft/typescript, and rust-lang/rust, indicating cross-pollination with the broader developer ecosystem.

The project actively encourages community contributions through a structured process. All code submissions must include accompanying tests and follow existing code formatting conventions. The repository maintains a mailing list on the LEAN Forum for installation assistance and general support questions, with a dedicated issue tracker for bug reports and feature requests.