FYI: fast.ai's "fastcore [adds] to Python features inspired by other languages we’ve loved, like multiple dispatch from Julia"

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On their homepage:

Python is a powerful, dynamic language. Rather than bake everything into the language, it lets the programmer customize it to make it work for them. fastcore uses this flexibility to add to Python features inspired by other languages we’ve loved, like multiple dispatch from Julia, mixins from Ruby, and currying, binding, and more from Haskell. It also adds some “missing features” and cleans up some rough edges in the Python standard library, such as simplifying parallel processing, and bringing ideas from NumPy over to Python’s list type.

There is a port to replicated FastAI in Julia (incomplete?):

I’m just thinking, will we not win people over to Julia? I suppose the publicity is good, that people, are inspired by Julia.

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In case you weren’t following the discussion on Slack, this talk may be interesting. Most of the FastAI and (Flux)ML ecosystem discussion happens on Slack and Zulip, with https://github.com/FluxML/ML-Coordination-Tracker as the jumping-off point.

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