killpy
killpy finds every Python environment on your machine — .venv folders, Conda and Poetry environments, pipx packages, pyenv versions, Pipenv, Hatch, tox and uv environments, plus caches and build artifacts — shows what each one costs in disk space, and lets you delete the ones you no longer need.
uvx killpy --path ~ # instant run, no install needed

A typical development machine accumulates 10–40 GB of forgotten environments over a few years. killpy is npkill for Python: the same idea, but it understands every environment manager instead of matching folders by name.
Why killpy exists
Python tooling tends to scatter disk usage across many locations:
- local
.venvfolders inside projects - directories containing
pyvenv.cfg - Poetry-managed environments in cache directories
- Conda environments outside your repo tree
pipxpackage environmentspyenvversions- tox, Hatch, Pipenv, and uv environments
- stale caches and Python build artifacts
For many developers, these directories grow for months or years and turn into hidden disk usage. Instead of jumping between conda, Poetry cache directories, pipx, pyenv, and ad hoc shell commands, killpy gives you one scanner and one cleanup workflow that makes that usage visible, measurable, and removable.
Interfaces
killpy has two primary surfaces:
- An interactive Textual TUI launched by the top-level
killpycommand - Scriptable CLI subcommands for listing, deleting, stats, and cache cleanup
The TUI is optimized for inspection and explicit deletion. The scanner and non-interactive commands expose the broader detection model.
Important behavior notes
- The TUI currently shows environment results plus a dedicated
pipxtab. - Cache and artifact detection exists in the scanner and CLI flows, but those do not have separate TUI tables today.
killpy cleanremoves__pycache__directories recursively under the target path.- Environments managed by external tools are deleted through those tools when possible, such as
conda env removeandpipx uninstall.
Where to go next
Continue with the Quickstart for the main workflows, browse the use cases for complete, copy-pasteable recipes, or jump to the CLI reference.
If killpy saves you time or disk space, the GitHub repository is here: Tlaloc-Es/killpy.