lean 0.1.4

A CLI aimed at making it easier to run QuantConnect's LEAN engine locally and in the cloud

Lean CLI

This CLI is still in development. Bugs may still occur and breaking changes may still happen before the 1.0.0 release. Use with caution.

The Lean CLI is a CLI aimed at making it easier to run the LEAN engine locally and in the cloud.

Installation

The CLI can be installed and updated by running pip install -U lean.

After installing the CLI, simply cd into an empty directory and run lean init to set up a Lean CLI project.

Usage

A workflow with the CLI may look like this:

1. cd into the Lean CLI project.
2. Run lean create-project -l python "RSI Strategy" to create a new project with some basic code to get you started.
3. Work on your strategy in ./RSI Strategy.
4. Run a backtest with lean backtest "RSI Strategy". This runs your backtest in a Docker container containing the same packages as the ones used on QuantConnect.com, but with your own data.

Debugging backtests

To debug backtests some additional setup is needed depending on the editor and language you use.

Note: When debugging C#, after you attach to the debugger, a breakpoint will be hit for which your editor will tell you it has no code for. This is expected behavior, simply continue from that breakpoint and your algorithm will start running.

VS Code + Python

1. Install the Python extension.
2. Run the lean backtest command with the --debug ptvsd option.
3. Wait until the CLI tells you to attach to the debugger.
4. In VS Code, open the Run tab and run the configuration called "Debug Python with Lean CLI" (this configuration is created when you run lean init).

VS Code + C#

1. Install version 15.8 of the Mono Debug extension. You can do this by first installing the latest version and then clicking on the arrow button next to the Uninstall button, which will open a context menu containing the "Install Another Version" option.
2. Run the lean backtest command with the --debug mono option.
3. Wait until the CLI tells you to attach to the debugger.
4. In VS Code, open the Run tab and run the configuration called "Debug C# with Lean CLI" (this configuration is created when you run lean init).

PyCharm + Python

Note: This combination requires PyCharm Professional.

1. In PyCharm, start debugging using the "Debug with Lean CLI" run configuration (this configuration is created when you run lean init).
2. Run the lean backtest command with the --debug pycharm option.

Visual Studio + C#

1. Install the VSMonoDebugger extension.
2. In Visual Studio, go to "Extensions > Mono > Settings" and enter the following settings:
   • Remote Host IP: 127.0.0.1
   • Remote Host Port: 55555
   • Mono Debug Port: 55555
3. Run the lean backtest command with the --debug mono option.
4. Wait until the CLI tells you to attach to the debugger.
5. In Visual Studio, attach to the debugger using "Extensions > Mono > Attach to mono debugger".

Rider + C#

1. Run the lean backtest command with the --debug mono option.
2. Wait until the CLI tells you to attach to the debugger.
3. In Rider, start debugging using the "Debug with Lean CLI" run configuration (this configuration is created when you run lean init).

Development

To work on the Lean CLI, clone the repository, enter an environment containing Python 3.6+ and run pip install -r requirements.txt. This command will install the required dependencies and installs the CLI in editable mode. This means you'll be able to edit the code and immediately see the results the next time you run lean.

If you need to add dependencies, first update setup.py (if it is a production dependency) or requirements.txt (if it is a development dependency) and then re-run pip install -r requirements.txt.

The automated tests can be ran by running pytest. The filesystem and HTTP requests are mocked when running tests to make sure they run in an isolated environment.

Maintainers can publish new releases by pushing a Git tag containing the new version to GitHub. This will trigger a GitHub Actions workflow which releases the current main branch to PyPI with the value of the tag as version. Make sure the version is not prefixed with "v".