Martin-Molinero
c57fd18b64
* Run CI on self-hosted runners Switch all GitHub Actions workflows from the GitHub-hosted ubuntu-24.04 runners to self-hosted runners. The Benchmarks workflow targets a runner with the dedicated 'benchmark' label so benchmarking only runs on that machine. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> * Guard disk cleanup to GitHub-hosted runners, mount benchmark data read-only Skip the 'Liberate disk space' step on self-hosted runners (only run it on github-hosted ones) and mount the benchmark /nas:/Data volume read-only. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> * Run workflows directly inside foundation container Self-hosted runners are not allowed to run docker, so the docker run/exec (runInContainer) pattern fails. Run every workflow directly inside a job-level container: quantconnect/lean:foundation, matching the benchmarks workflow. Drops the Liberate disk space, docker helper and Start container steps; secrets are passed via the container env. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> * Cancel in-progress runs on new branch commits Add a concurrency group keyed to workflow + ref with cancel-in-progress so pushing a new commit to a branch cancels the still-running workflow for the previous commit. Applied to all CI/test workflows; rebase-org-branches is left untouched to avoid cancelling a rebase mid-push. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> * Fix dotnet tools PATH in research workflow Inside a job-level container GitHub sets HOME=/github/home, so the global tool installs to $HOME/.dotnet/tools, not /root/.dotnet/tools. Use $HOME so dotnet-interactive is found and 'dotnet interactive jupyter install' works. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> * Make stub-generation check POSIX-sh compatible The container steps run under sh, where bash-only [[ ]] is unavailable. Rewrite the tag/stub-generation gate as a POSIX case + [ ] test so it behaves correctly on tag builds instead of silently being skipped. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> * Cap CI containers to 12 CPUs and 12g RAM Add docker options (--cpus 12 --memory 12g) to every workflow container so jobs running on high-core self-hosted hosts can't monopolize resources. Limits are per container, so concurrent jobs each get their own allotment. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> --------- Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Lean Home | Documentation | Download Zip | Docker Hub | Nuget
LEAN is an event-driven, professional-caliber algorithmic trading platform built with a passion for elegant engineering and deep quant concept modeling. Out-of-the-box alternative data and live-trading support.
QuantConnect Lean CLI is a command-line interface tool for interacting with the Lean algorithmic trading engine, which is an open-source platform for backtesting and live trading algorithms in multiple financial markets. It allows developers to manage projects, run backtests, deploy live algorithms, and perform various other tasks related to algorithmic trading directly from the terminal. The CLI simplifies the workflow by automating tasks, enabling seamless integration with cloud services, and facilitating collaboration with the QuantConnect community. It's designed for quant developers who need a powerful and flexible tool to streamline their trading strategies. Please watch the instructions videos to learn more.
Installation
pip install lean
Commands
Create a new project containing starter code
lean project-create
Run a local Jupyter Lab environment using Docker
lean research
Backtest a project locally using Docker
lean backtest
Optimize a project locally using Docker
lean optimize
Start live trading a project locally using Docker
lean live
Download the LEAN CLI Cheat Sheet for the full list of commands.
This section will cover how to install lean locally for you to use in your environment. For most users we strongly recommend the LEAN CLI which is prebuilt and runs on all platforms. Refer to the following readme files for a detailed guide regarding using your local IDE with Lean.
To install locally, download the zip file with the latest master and unzip it to your favorite location. Alternatively, install Git and clone the repo:
git clone https://github.com/QuantConnect/Lean.git
cd Lean
macOS
NOTE: Visual Studio for Mac has been discontinued, use Visual Studio Code instead
- Install Visual Studio Code for Mac
- Install the C# Dev Kit extension
- Install dotnet 9 SDK:
- To build the solution, either:
- choose Run Task > build from the Panel task dropdown, or
- from the command line run
dotnet build
- To run the solution, either:
- choose Run and Debug from the Activity Bar, then click Launch, or
- click F5, or
- from the command line run
cd Launcher/bin/Debug dotnet QuantConnect.Lean.Launcher.dll
Linux (Debian, Ubuntu)
- Install dotnet 9:
- Compile Lean Solution:
dotnet build QuantConnect.Lean.sln
- Run Lean:
cd Launcher/bin/Debug
dotnet QuantConnect.Lean.Launcher.dll
Windows
- Install Visual Studio
- Open
QuantConnect.Lean.slnin Visual Studio - Build the solution by clicking Build Menu -> Build Solution (this should trigger the NuGet package restore)
- Press
F5to run
Python Support
A full explanation of the Python installation process can be found in the Algorithm.Python project.
Local-Cloud Hybrid Development.
Seamlessly develop locally in your favorite development environment, with full autocomplete and debugging support to quickly and easily identify problems with your strategy. Please see the CLI Home for more information.
Issues and Feature Requests
Please submit bugs and feature requests as an issue to the Lean Repository. Before submitting an issue, please read the instructions to ensure it is not duplicated.
Mailing List
The mailing list for the project can be found on LEAN Forum. Please use this to ask for assistance with your installation and setup questions.
Contributors and Pull Requests
Contributions are warmly welcomed, but we ask you to read the existing code to see how it is formatted and commented on and ensure contributions match the existing style. All code submissions must include accompanying tests. Please see the contributor guidelines. All accepted pull requests will get a $50 cloud credit on QuantConnect. Once your pull request has been merged, write to us at support@quantconnect.com with a link to your PR to claim your free live trading. QC <3 Open Source.
A huge thank you to all our contributors!
Acknowledgements
The open sourcing of QuantConnect would not have been possible without the support of the Pioneers. The Pioneers formed the core 100 early adopters of QuantConnect who subscribed and allowed us to launch the project into open source.
Ryan H, Pravin B, Jimmie B, Nick C, Sam C, Mattias S, Michael H, Mark M, Madhan, Paul R, Nik M, Scott Y, BinaryExecutor.com, Tadas T, Matt B, Binumon P, Zyron, Mike O, TC, Luigi, Lester Z, Andreas H, Eugene K, Hugo P, Robert N, Christofer O, Ramesh L, Nicholas S, Jonathan E, Marc R, Raghav N, Marcus, Hakan D, Sergey M, Peter McE, Jim M, INTJCapital.com, Richard E, Dominik, John L, H. Orlandella, Stephen L, Risto K, E.Subasi, Peter W, Hui Z, Ross F, Archibald112, MooMooForex.com, Jae S, Eric S, Marco D, Jerome B, James B. Crocker, David Lypka, Edward T, Charlie Guse, Thomas D, Jordan I, Mark S, Bengt K, Marc D, Al C, Jan W, Ero C, Eranmn, Mitchell S, Helmuth V, Michael M, Jeremy P, PVS78, Ross D, Sergey K, John Grover, Fahiz Y, George L.Z., Craig E, Sean S, Brad G, Dennis H, Camila C, Egor U, David T, Cameron W, Napoleon Hernandez, Keeshen A, Daniel E, Daniel H, M.Patterson, Asen K, Virgil J, Balazs Trader, Stan L, Con L, Will D, Scott K, Barry K, Pawel D, S Ray, Richard C, Peter L, Thomas L., Wang H, Oliver Lee, Christian L..