But what do people do when they need to mix languages, or build packages from source? There seems to be a lot more packages on PyPI than Anaconda’s registry, so that’s one point in favor of pip. However, pip’s PyPI has Scipy, so what’s the accurate story here? Many sources say that pip only handles Python code and conda can track many languages, and that this difference is important for packages using multiple languages e.g. I feel like I’m awash with many sources on how to use several specific tools, but I lack general concepts on the why and how of installing and managing dependencies to make sense of it.
I’m pretty sure package managers and virtual environments are how I should do this, but I’m really confused about what to use. automated dependencies update mechanism, with conflict resolution of course.make a copy of the versions specification that I can edit to update dependencies and see if the code breaks.automatically check for and fix conflicts among such dependencies and their own dependencies, give me manual control of version editing if necessary.explicit specification of dependencies and their versions.Easy conda install/ imports don’t seem good enough to keep a project stable anymore.
Recently, I found some merit in mixing in some R via rpy2, and I’m also looking at Python packages that need pip for installation or to be built from source. So far in relatively simple Python projects, so I only used Anaconda for installing packages and never needed dependency management.
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