Use Cases
This page is intentionally written around common search intents so both users and LLM-based tools can quickly match killpy to the right workflow.
Find old Python virtual environments
If you want to find old .venv folders or directories containing pyvenv.cfg, run:
killpy list --path ~/projects --type venv
This is the simplest workflow when you want to inspect unused virtual environments before deleting anything.
Delete unused Conda environments
If you want a reviewable cleanup of Conda environments:
killpy delete --type conda --dry-run
When deletion happens, killpy uses conda env remove --name ... --yes rather than removing those directories blindly.
Measure Python environment disk usage
If you want to see how much disk space Python environments consume by category:
killpy stats --path ~/projects
This is useful for questions like how much space do my virtualenvs use or what is taking space in my Python setup.
Clean Poetry, pipx, and pyenv leftovers
killpy also helps when your disk usage is spread across tool-specific locations that are easy to forget:
- Poetry virtual environments
pipxpackage environmentspyenvversions- Pipenv, Hatch, tox, and uv environments
Run:
killpy list --path ~
The scanner can combine local project scanning with tool-managed environment discovery.
Remove Python caches and build artifacts
If you want to clean __pycache__ directories quickly:
killpy clean --path ~/projects
If you want broader visibility into caches and artifacts before deletion:
killpy list --path ~/projects --type cache --type artifacts
This is the better workflow for users searching for remove Python cache folders, clean build directories, or find Python artifacts taking disk space.
Build machine-readable inventories
If you need JSON output for scripts, reporting, or other AI agents:
killpy list --path ~/projects --json
Or stream results progressively:
killpy list --path ~/projects --json-stream