Overview
Python projects accumulate virtual environments and cache directories quickly. A single data science project with numpy, pandas, and machine learning libraries can have a virtual environment exceeding 2GB.
What Cluttered Cleans
| Artifact | Description | Typical Size |
|---|---|---|
venv/ / .venv/ | Virtual environment directories | 200MB - 3GB |
__pycache__/ | Compiled Python bytecode | 10MB - 100MB |
.pytest_cache/ | pytest result cache | 5MB - 50MB |
.mypy_cache/ | Type checking cache | 10MB - 200MB |
*.egg-info/ | Package metadata | 1MB - 10MB |
Why Virtual Environments Get Large
Python virtual environments contain:
- Complete copies of packages (not symlinks)
- Compiled C extensions (numpy, pandas)
- Multiple versions of dependencies
- Platform-specific binaries
A data science stack (numpy, pandas, scikit-learn, tensorflow) can easily exceed 2GB.
Safety Considerations
Cluttered protects your Python projects by:
- Detecting active Jupyter notebook sessions
- Checking for running Python processes
- Identifying recently modified .py files
- Respecting Poetry and Pipenv lockfiles
Package Manager Support
| Manager | Detection | Clean Support |
|---|---|---|
| pip + venv | requirements.txt | Full |
| Poetry | pyproject.toml | Full |
| Pipenv | Pipfile | Full |
| Conda | environment.yml | Partial |
Frequently Asked Questions
Will cleaning break my project?
No! Your source code and dependency specifications (requirements.txt, pyproject.toml) are never touched. Just run pip install -r requirements.txt to restore.
What about conda environments?
Cluttered detects conda environments but handles them carefully since they can be shared across projects.
Does it clean the global pip cache?
By default, Cluttered focuses on project-local artifacts. Global pip cache cleaning is available in Pro.