API Reference

Runs a local optimization in a Docker container using the quantconnect/lean Docker image. The logs of the optimizer are shown in real-time and the full results of the optimizer and all executed backtests are stored in the <project>/optimizations/<timestamp> directory. You can use the --output option to change the output directory.

The given <project> argument must be either a project directory or a file containing the algorithm to optimize. If it is a project directory, the CLI looks for a main.py or Main.cs file, assuming the first file it finds to contain the algorithm to optimize.

By default, an interactive wizard is shown letting you configure the optimizer. When --optimizer-config or --strategy is given, the command runs in non-interactive mode and doesn't prompt for input.

When the --optimizer-config <config file> option is given, the specified config file is used. This option must point to a file containing a full optimizer config (the algorithm-type-name, algorithm-language and algorithm-location properties may be omitted). See the Optimizer.Launcher/config.json file in the LEAN repository for an example optimizer configuration file, which also contains documentation on all the required properties.

When --strategy is given, the optimizer configuration is read from the command-line options. This means the --strategy, --target, --target-direction, and --parameter options become required. Additionally, you can also use --constraint to specify optimization constraints.

In non-interactive mode, the parameters can be configured using the --parameter option. This option takes the following values: the name of the parameter, its minimum value, its maximum value, and its step size. You can provide this option multiple times to configure multiple parameters.

In non-interactive mode, the constraints can be configured using the --constraint option. This option takes a "statistic operator value" string as value, where the statistic must be a path to a property in a backtest's output file, like "TotalPerformance.PortfolioStatistics.SharpeRatio". This statistic can also be shortened to "SharpeRatio" or "Sharpe Ratio", in which case the command automatically converts it to the longer version. The value must be a number and the operator must be <, >, <=, >=, ==, or ==. You can provide this option multiple times to configure multiple constraints.

Example non-interactive usage:

$ lean optimize "My Project" \
    --strategy "Grid Search" \
    --target "Sharpe Ratio" \
    --target-direction "max" \
    --parameter my-first-parameter 1 10 0.5 \
    --parameter my-second-parameter 20 30 5 \
    --constraint "Drawdown < 0.5" \
    --constraint "Sharpe Ratio >= 1"

The Docker image that's used contains the same libraries as the ones available on QuantConnect. If the selected project is a C# project, it is compiled before starting the optimization.

By default, the official LEAN engine image is used. You can override this using the --image <value> option. Alternatively, you can set the default engine image for all commands using lean config set engine-image <value>. The image is pulled before running the optimizer if it doesn't exist locally yet or if you pass the --update flag.

The lean optimize command expects the following arguments:

The lean optimize command supports the following options: