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I also do scientific computing all day every day with Python. I've used the built-in virtual environments using `python -m venv` for years on a project-by-proje
by acidburnNSA 5y ago
I also do scientific computing all day every day with Python. I've used the built-in virtual environments using `python -m venv` for years on a project-by-project basis and have never had too much trouble. Yes, finding the right package compiled on Windows sometimes requires a trip to Christoph Gohlke's website, but beyond that it's never been a problem.
What does conda give you that is so much better than venvs?
- 41b696ef1113 5y agoI utilize a package that only distributes source or binary through Conda. Building it is very much non-trivial, so as to not go insane, I have to use Conda. Would really rather not use Conda, but bespoke packages + the trivial ability to define a specific Python version ($WORK servers use ancient RedHat with dated Python) has forced my hand. Poetry feels better, if only because it separates out explicit vs transitive dependencies.
- dannyz 5y agoFor personal use, most of the time, not too much. However I have encountered enough binary package conflicts when using pip that is just easier to use conda (or conda-forge). On the distribution side, we are a small academic group that provides a niche, binary, scientific package that has quite a few binary dependencies (things like hdf, netcdf, etc.). We do not have the human effort to provide support for different distributions of Python, but it is very easy for us to say it will work if you use Anaconda with this environment on multiple OS's.