• noarch v3.1.0

conda install

Worried about .pyc files and __pycache__ directories? Fear not! PyClean is here to help. Finally the single-command clean up for Python bytecode files in your favorite directories. On any platform.

pyclean .
pyclean . --dry-run --verbose
pyclean --help

PyClean can clean up leftovers, generated data and temporary files from popular Python development tools in their default locations, along with Python bytecode. The following topics are currently covered:

• Cache (general purpose folder for several tools, e.g. Python eggs, legacy Pytest)
• Coverage (coverage database, and supported file formats)
• Packaging (build files and folders)
• Pytest (build files and folders)
• Ruff (ruff cache folder)
• Jupyter (notebook checkpoints) – optional
• Mypy (mypy cache folder) – optional
• Tox (tox environments) – optional

pyclean . --debris
pyclean . --debris all
pyclean . -d jupyter -n -v

PyClean also lets you remove free-form targets using globbing. Note that this is potentially dangerous: You can delete everything anywhere in the file system, including the entire project you’re working on. For this reason, the --erase option has a few artificial constraints:

• It doesn’t do recursive deletion by itself, which means that you have to specify the directory and its contents, separately and explicitly.
• The above entails that you’re responsible for the deletion order, i.e. removal of a directory will only work if you asked to delete all files inside first.
• You’re prompted interactively to confirm deletion, unless you specify the --yes option, in addition.

pyclean . --erase tmp/**/* tmp/