To be fair, lots of languages have been moving closer to ML recently (and new languages tend to look more ML-like than in the past). That includes the adoption of pattern matching, but also things like value objects, first-class functions, sum types, named tuples, algebraic datatypes, type inference, etc.

I don't think that's a bad thing. I do think care should be taken when incorporating features from other languages, to see how it interacts with existing features, what the best form of that feature would be, and perhaps whether some different feature could achieve a similar goal.

(For the latter point, I find it unfortunate that languages which already contain 'try/catch' have been introducing 'yield' and 'async/await' as separate features; rather than generalising to 'shift/reset' and implementing all three as libraries)

Interested in block-level scoping in Python? Please post on the python-ideas mailing list. Thanks.

No, not interested in block-level scoping in Python. Why on earth would I ask a programming language I rely on for getting important work done to introduce so massive a breaking change as changing its scoping style?

"I don't think feature X is a good fit for Python because it interacts poorly with existing Python features Y and Z" is not a tacit statement of support for changing features Y and Z. It's a statement that means exactly what it says.

Like I alluded to in my grandparent post, I use other languages that are not Python, and like their features, too. That does not necessarily mean I want all my favorite features from those pulled into Python. Nor do I want my favorite features from Python pulled into other languages.

The best analogy I can think of is a college friend once developed this sort of transitive theory of food that went, "If A tastes good with B, and B tastes good with C, then A must taste good with C." This resulted in a number of questionable concoctions, like serving cottage cheese on top of chocolate cake because they both taste good with strawberries.

Actually, the opposite. Call me an old crank but I feel like Python should stay Python and not try to (badly) tack on ideas from ML.

For my part, as I maintain some complex academic research software, I would be much more interested in continuing support for Python 2, and more comprehensive numerical, math and vector libraries for Racket.