.gitignore for Linux + Python
.gitignore for Python development on Linux servers or workstations.
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LinuxPython
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80 patterns · 1021 B
# Generated by DevZone Tools — https://devzone.tools/tools/gitignore-generator # Templates: Linux, Python # 2026-04-20 # ---- Linux ---- # Linux *~ .fuse_hidden* .directory .Trash-* .nfs* # ---- Python ---- # Python __pycache__/ *.py[cod] *$py.class *.so .Python build/ develop-eggs/ dist/ downloads/ eggs/ .eggs/ lib/ lib64/ parts/ sdist/ var/ wheels/ share/python-wheels/ *.egg-info/ .installed.cfg *.egg MANIFEST *.manifest *.spec pip-log.txt pip-delete-this-directory.txt .tox/ .nox/ .coverage .coverage.* .cache nosetests.xml coverage.xml *.cover *.py,cover .hypothesis/ .pytest_cache/ cover/ *.mo *.pot *.log local_settings.py db.sqlite3 db.sqlite3-journal instance/ .webassets-cache .scrapy docs/_build/ .pybuilder/ target/ .ipynb_checkpoints profile_default/ ipython_config.py .pdm.toml __pypackages__/ celerybeat-schedule celerybeat.pid *.sage.py .env .venv env/ venv/ ENV/ env.bak/ venv.bak/ .spyderproject.db .spyproject .ropeproject /site .mypy_cache/ .dmypy.json dmypy.json .pyre/ .pytype/ cython_debug/
Why use Linux + Python together?
Python development on Linux servers is common for backend, data science, and ML workflows. Linux editor backup files (*~, created by many Linux editors) can accumulate quickly — the Linux template catches them all.
Related combinations
Frequently asked questions
- Do I need to commit .gitignore?
- Yes — .gitignore should be committed to the repository so all collaborators benefit from the same ignore rules.
- How do I add custom patterns?
- Open your .gitignore file and add the pattern on a new line. Use # for comments, * for wildcards, / to match directories, and ! to un-ignore a previously ignored path.
- How do I ignore a file that is already tracked?
- Adding a file to .gitignore does not remove it from tracking if it was previously committed. Run: git rm --cached <file> to stop tracking it without deleting the file locally.
- Why combine Linux and Python?
- Python development on Linux servers is common for backend, data science, and ML workflows. Linux editor backup files (*~, created by many Linux editors) can accumulate quickly — the Linux template catches them all.
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