To be more specific: getattr, operator overloading, descriptors, heterogeneous dicts, decorators, etc.
Type checking and metaprogramming are fundamentally at odds [1]. Dynamic languages like Python have more of a focus on the latter. They later added type checking, but it comes at the "cost" of ruling out the more idiomatic metaprogramming and reflection features. In other words, static typing makes your source code bigger.
Well, optional typing to some degree lets you have the best of both worlds -- you can skip type checking of the hard parts. But optional typing doesn't let you compile your program to make it faster -- you need a fully-typed program for that.
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I'm doing something similar to mypyc with https://www.oilshell.org/ (I actually visited Dropbox and chatted with them about it back in the spring.)
The difference is that I'm compiling Oil's Python source to C++ rather than to Python-C extension modules. So it doesn't depend on the Python runtime. It's not done but it's working well so far, and it's given me a lot of appreciation for which dynamic features Python programs actually use! (both my own and others)
Also note that mypyc was used to speed up mypy, which is a type checker. A type checker is a very particular kind of program that's different than 99% of the use cases of Python. So success on speeding it up is super impressive but it's not clear it generalizes.
The same is true for Oil -- my translation work doesn't generalize to arbitrary Python programs. Lots of people have died on that hill because it's really hard. You have a hard tradeoff between the kinds of Python programs you can support and the speedup you can give them. There are 10-20 projects over the last 2 decades at various points along that spectrum. In addition to mypyc, Oil's strategy was also inspired by Shed Skin, which is an impressive but mostly dormant Python-to-C++ compiler.
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So in short I would say the problem is that nobody will be able to agree on a subset. You will have a lot of different fragments of Python geared toward particular use cases.
But Python will very often be more appealing than any of those fragments because it has a bigger ecosystem. One thing that I've appreciated more and more while designing a language is how much the network effects and inertia matter. It's why we're still using C and C++ after almost 50 years. I'm sure every day there is still a lot more C++ written than Go, Rust, Swift, and D combined, etc.
Python has a similar network effect and it will be around basically forever in its current form. Software doesn't really get rewritten or reduced -- more stuff just gets added on top.
[1] I wrote some posts about that tradeoff here: http://www.oilshell.org/blog/tags.html?tag=metaprogramming#m...
