> (namely, working with nontabular data, external APIs, deep learning, and productionization).
I agree with all of that except for productionisation. I would have agreed before dealing with issues around getting consistent versions of python + libraries to run.
The issues I see with Python are as follows:
- pip doesn't actually check to make sure your dependencies are compatible, which causes real problems with numpy et al
- conda isn't available by default, and running it on remote boxes is non-trivial (I spent a whole week figuring out how to get it running in a remote non-login shell).
- This makes it really, really difficult to actually get a standard set of libraries to depend upon, which is really important for production.
R, on the other hand, actually resolves dependencies in its package manager, and the R CMD BUILD for packages, while super annoying helps you produce (more) portable code (did you know that conda doesn't provide cross-platform yml files unless invoked specifically?).
In terms of handing it over to engineering/non data science people though, Python is much much much better.
tl;dr Python's an ace language with a terrible production story.
I agree with all of that except for productionisation. I would have agreed before dealing with issues around getting consistent versions of python + libraries to run.
The issues I see with Python are as follows:
- pip doesn't actually check to make sure your dependencies are compatible, which causes real problems with numpy et al
- conda isn't available by default, and running it on remote boxes is non-trivial (I spent a whole week figuring out how to get it running in a remote non-login shell).
- This makes it really, really difficult to actually get a standard set of libraries to depend upon, which is really important for production.
R, on the other hand, actually resolves dependencies in its package manager, and the R CMD BUILD for packages, while super annoying helps you produce (more) portable code (did you know that conda doesn't provide cross-platform yml files unless invoked specifically?).
In terms of handing it over to engineering/non data science people though, Python is much much much better.
tl;dr Python's an ace language with a terrible production story.