So you want a system that figures out that the vast majority of function and method calls are not overridden, that these variables and fields are in practice always integers, etc.; generates some nice compiled code, and adds some interlock so that, if these assumptions do change, the code gets invalidated and replaced with new code (and maybe some data structures get patched).

I think that this kind of thing is in fact done with the high-performing Javascript engines used in major browsers. I imagine PyPy, being a JIT, is in a position to do this kind of thing. Perhaps Python is more difficult than Javascript, and/or perhaps a lot more effort has been put into the Javascript engines than into PyPy?

Python is considerably more dynamic than JavaScript. And I'm not trying to drag pypy, just saying that that's already the state of the art and there are good reasons that the authors of pypy didn't set out to do what Mojo apparently claims to have done.

> Python is considerably more dynamic than JavaScript

This is sometimes repeated but I don’t believe that is why Python is slow (nor do I think for most measures of “dynamic” it is even true). Which aspect of “dynamism” in particular are you concerned about that JavaScript lacks? The primary hindrance is keeping CPython extensions working while making Python fast. Add to that the hundreds of millions that went into V8 and other JavaScript implementation efforts.

For starters, consider that almost every operator in Python is a dynamic method call under the hood. This includes value equality and hashing, which also affects e.g. dict keys. Oh, and all built-in types can be extended and their behavior overridden.

And then there's descriptors: https://docs.python.org/3/howto/descriptor.html

Those are hardly unsolvable issues with a JIT as they are static for the vast majority of cases. Solutions have been proposed since the 90s with Self and Strongtalk[1].

Doing that, plus 100% compatibility with CPython extension API, while preserving some expectations of deterministic destruction in Python, are the challenges one would face.

[1]: http://www.strongtalk.org/

The point is that the part of mojo that is new allows you to write early bindings that can't change, immutable variables, values that are accessed without indirection, types, ownership annotations, etc, and uses all of that to do precisely what you are asking for.

If it can't do much until those extra annotations are in place, then I would imagine it's unlikely it'll ever get support from numpy, django, and the like. Uptake for mypy type annotations alone has been pretty slow.

>Uptake for mypy type annotations alone has been pretty slow.

Because they're annotations with bad checkers. They're mostly helpful as documentation.

TypeScript checking is on a whole different level.