Skip to content
/ Lean Public
forked from QuantConnect/Lean

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

License

Notifications You must be signed in to change notification settings

JosueNina/Lean

 
 

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

lean-header

Build Status     Regression Tests     LEAN Forum     Discord Chat

Lean Home | Documentation | Download Zip | Docker Hub | Nuget

features-header

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.

feature-list

modular-header LEAN is modular in design, with each component pluggable and customizable. It ships with models for all major plug-in points.

modular-architecture

cli-header lean-animation

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.

modular-architecture

This section will cover how to install lean locally for you to use in your environment. 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 6 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 6:
  • 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.sln in Visual Studio
  • Build the solution by clicking Build Menu -> Build Solution (this should trigger the NuGet package restore)
  • Press F5 to 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 [email protected] 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..

About

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

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • C# 94.1%
  • Python 5.7%
  • Jupyter Notebook 0.1%
  • HTML 0.1%
  • CSS 0.0%
  • Shell 0.0%