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State of the art python packaging must include support for common use cases such as conda+machine learning. It’s incredible how even Julia’s Pkg.jl supports be
by siproprio 4y ago
State of the art python packaging must include support for common use cases such as conda+machine learning.
It’s incredible how even Julia’s Pkg.jl supports better python packaging in combination with conda than the official python packaging tools.
This is very clearly a question of the culture of the core python developers (such as brett cannon) who seem to think the machine learning people with their compilers and JITs are not an important part of the community.
- klkqw 4y agoThe Twitter hero faction of the Python core "developers" (many of whom have not done much actual work for a decade) has always been pro-web and anti-C-extensions. They have been peddling the dream of speeding up Python by neglecting the scientific ecosystem for a long time without having either the expertise or a clear plan how to achieve that. All that while the primarily useful part of Python is its C extension capabilities. The web does not need Python, query/response applications are handled just fine and better by functional languages.
- siproprio 4y agoThe pypy folks and a bunch of other alternative python implementations have pooled together and are working on a soft fork of the c extension api to enable existing established projects that make heavy use of the c api to better work with the superior faster python implementations. I believe this is the way forward. Existing packages are essentially tied to cpython because that’s what the python.org website offers for download, and people will just use that by default. Once all major packages support the new c api, it will be easier to just use something other than cpython by default.