Python virtual environments: venv vs conda vs uv — which one?
poze a month ago269 gadeen
I'm doing data science and web dev in Python. Tutorials use venv, conda, or uv. Which should I standardize on?
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1 Repons
- uv: extremely fast, manages Python versions *and* dependencies with a lockfile (uv.lock), and works with standard pyproject.toml. Great default for web and most data work in 2026. - venv + pip: built into Python and always available. Fine for simple projects, but you need extra tools for locking. - conda / mamba: its strength is non-Python binary dependencies (CUDA toolkits, GDAL, some scientific C libraries). Choose it when pip wheels for your stack are painful.
Pragmatic setup: uv everywhere, and conda only for the rare environment that needs complex native packages. Since PyTorch and most ML libraries ship pip wheels with CUDA, uv covers most data science too.
Konekte pou di lòt moun si li te mache.
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