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If you don't need c or c++ dependencies it's ok. If you do, it's very very painful. To be fair, most of the DS libraries can be handled by conda, but if you nee
by disgruntledphd2 6y ago
If you don't need c or c++ dependencies it's ok. If you do, it's very very painful. To be fair, most of the DS libraries can be handled by conda, but if you need both conda and pip, then you're going to have a bad time. (Source: this is my life right now).
- codethief 6y agoOh man, this is my life right now, too. In my case, we're using tensorflow or tensorflow-gpu, depending on the host system and, unfortunately, only Conda offers tensorflow-gpu with built-in CUDA. Add to this that the tensorflow packages themselves are notoriously bad at specifying dependencies and that different versions of tensorflow(-gpu) are available on conda-forge, depending on your OS.
- disgruntledphd2 6y agoTensorflow is the worst (along with ReAgent from FB). I think it's because they have their own internal build systems, but they never play well with pip/conda et al. One of my recent breakages was installing the recsim package, which pulled in tensorflow and broke my entire app. There's actually a recsim-no-tf package on PyPi, presumably because this happens to loads of people.
- nxpnsv 6y agoI see, I miss a lot of issues as don't use any GPU stuff, mainly flask + scipy and friends.... probably this is what saves me.
- disgruntledphd2 6y agoIt's not even the GPU versions, even the CPU stuff causes issues. The core problem is that pip will happily overwrite your existing dependencies when you attempt to install a new package.