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I found this very surprising so asked a Python-knowledgeable acquaintance who mentioned that this works as expected

    >>> seq = [x for x in range(1,11)]
    >>> list(filter(lambda x: x % 2 == 0, seq))
    [2, 4, 6, 8, 10]
    >>> list(filter(lambda x: x % 2 == 1, seq))
    [1, 3, 5, 7, 9]


Right. Because it's doing two different things. One is working with lists, the other is working with lazy calculations.

A common functional pattern is to do lazy calculations, so that you don't have to store every result in memory all at once. The subtext I'm getting at is that a language that has footguns that make it dangerous (for reasons of correctness, if not performance) to reuse and compose lazy calculations is a language that is fundamentally ill-suited to actual functional programming.

Which is fine! Python's already a great procedural-OO language. It's arguably the best procedural-OO language. Which is a big part of why it's taken over data science, business intelligence, and operations. Those are, incidentally, the domains where I feel just about the least need to program in a functional paradigm. And, in the domains where I do have a strong preference for FP, Python is already a poor choice for plenty of other reasons. (For example, the global interpreter lock eliminates one of the key practical benefits.) No amount of risky, scarring cosmetic surgery is going to change that.


OK I see, the very short sequence in your example was a stand-in for a potentially infinite one. I got nerd-sniped into understanding what was happening as I found the behavior surprising.


It is very surprising.

And that is sort of another layer to why I think that people trying to turn Python into a functional language should just simmer down. A core principle in functional programming is that you should be able to swap out different implementations of an abstraction without changing the correctness of the program. That's not really something that can be enforced by most functional languages, but it's at least a precedent they set in their standard libraries. But Python's standard library has a different way of doing things, and favors different approaches to abstraction. And those conventions make the Python ecosystem a hostile environment for functional programming.

Hylang is another interesting example. It's a cool language. But watching how it evolved is slightly disheartening. It sought to be a lisp for Python, but the compromises they needed to make to get the language to interact well with Python have hurt a lot of its lisp feel, and make it a kind of peculiar language to try to learn as someone with a lisp background. IIRC, Python's lack of block scoping was an elephant in the room for that project, too.




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