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.example.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.

You can use the --data-provider-historical option to change where the data is retrieved. This option updates the Lean configuration file, so you don't need to use this option multiple times for the same data provider if you are not switching between them. The following table shows the available data providers and their required options in non-interactive mode:

You can use the --download-data flag as an alias for --data-provider-historical QuantConnect. This data provider automatically downloads the required data files when your backtest requests them. After it downloads a data file, it stores it in your local data directory so that in future runs, it won't have to download it again. If the file contain data for multiple days (for example, daily Equity price data files), the ApiDataProvider re-downloads the file if your local version is at least 7 days old. To adjust this setting, update the downloader-data-update-period value in your Lean configuration file.

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"

To estimate the cost of running an optimization job without actually running it, add the --estimate option to the command. You need to backtest the project at least once in order to estimate the cost of optimizing it.

To set the maximum number of concurrent backtests to run, use the --max-concurrent-backtests option.

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: