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I pretty much only do scientific computing with Python so take this with a grain of salt, but ever since I have started using conda I have never looked back. E

by dannyz 5y ago

I pretty much only do scientific computing with Python so take this with a grain of salt, but ever since I have started using conda I have never looked back. Especially for cross platform projects conda makes things much easier. I would love for the official Python packaging tools to be in a better state so I hope this helps.

ivoflipse 5y ago
Conda has the advantage that conda packages are typically repackaged from the Pypi package. Especially om conda-forge, they are curated by people with more experience in packaging, that are more likely to use appropriate version pinning for libraries. Furthermore, conda-forge has the ability to create a new build of the same package with improved version pinnings, which typically doesn't happen on Pypi for already released packages.
misnome 5y ago
With the exception that the conda tool itself is so darned slow it can make you give up in frustration rather than wait another ten minutes to be told that the packages conflict. So use https://github.com/mamba-org/mamba https://github.com/mamba-org/mamba , which is an alternative client to conda and a million times faster. (If you are creating environments more than once per month or so).
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 ago
  I 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 ago
  For 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.

by dannyz 5y ago

ivoflipse 5y ago

Conda has the advantage that conda packages are typically repackaged from the Pypi package. Especially om conda-forge, they are curated by people with more experience in packaging, that are more likely to use appropriate version pinning for libraries. Furthermore, conda-forge has the ability to create a new build of the same package with improved version pinnings, which typically doesn't happen on Pypi for already released packages.

misnome 5y ago

With the exception that the conda tool itself is so darned slow it can make you give up in frustration rather than wait another ten minutes to be told that the packages conflict. So use https://github.com/mamba-org/mamba https://github.com/mamba-org/mamba , which is an alternative client to conda and a million times faster. (If you are creating environments more than once per month or so).

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 ago
I 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 ago
For 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.