cli-python-sweep

name	cli_python_sweep
description	Perform a parameter sweep over a Python function using the ensemblesweep CLI.

CLI Python Sweep

Use this skill to evaluate a Python function across a grid of parameters using ensemblesweep py. This is the fastest way to generate parallel data for any Python function without writing extra scripts.

Prerequisites

• The Python function must be importable (i.e., in a file in the current directory or on the PYTHONPATH).
• The function should take named arguments corresponding to the variables in the sweep.

Usage

1. Perform a Dry Run (Mandatory Guardrail)

Always perform a dry run first, especially for grids with more than 2 dimensions, to verify the total number of evaluations and parameter types.

ensemblesweep py --func module_name.function_name \
                 --var "param1=start:stop:num" \
                 --var "param2=val1,val2,val3" \
                 --dry-run

Review the output to ensure the "Total evaluations" is reasonable and the sample combinations look correct.

2. Execute the Sweep

Run the actual sweep, specifying the number of workers and desired output formats.

ensemblesweep py --func module_name.function_name \
                 --var "param1=-1.0:1.0:21" \
                 --var "param2=A,B,C" \
                 --workers 4 \
                 --save-csv results.csv \
                 --quiet

Tips for Agents

• Quiet Mode: Use --quiet to suppress libEnsemble logs for cleaner terminal output.
• Save Formats:
  • Use --save-csv or --save-json for easy parsing.
  • Use --save-pandas for Parquet format (best for large datasets).
  • Use --save-numpy for raw binary data.
• Variable Syntax:
  • key=val1,val2: Discrete list.
  • key=start:stop:num: Linear range (np.linspace).
• Imports: Ensure you are in the same directory as the target module, as ensemblesweep automatically identifies the current working directory.
• Remote Execution: You can pass --globus-compute-endpoint <UUID> to execute the grid remotely. However, for complex environments/dependencies, prefer using the programmatic_sweep_api skill to handle data placement and imports correctly.