mypyc VS benchmarks

That would be interesting! You might already be aware. But there's mypyc[0], which is an AOT compiler for Python code with type hints (that, IIRC, mypy uses to compile itself into a native extension).

Wanted to give you a head-start on the lit-review for your students I guess :)

[0] https://github.com/mypyc/mypyc

https://github.com/mypyc/mypyc

> Mypyc compiles Python modules to C extensions. It uses standard Python type hints to generate fast code. Mypyc uses mypy to perform type checking and type inference.

> Mypyc can compile anything from one module to an entire codebase. The mypy project has been using mypyc to compile mypy since 2019, giving it a 4x performance boost over regular Python.

I have not experience a 4x boost, rather between 1.5x and 2x. I guess it depends on the code.

Funny how emergence works with tools. Give a language too few tools but viral circumstances - the ecosystem diverges (Lisps, Javascript). Give it too long an iteration time but killer guarantees, you end up with committees. Python not falling into either of these traps should be understood as nothing short of magic in emergence.

I only recently discovered that python's reference typechecker, mypy, has a small side project for typed python to emit C [1], written entirely in python. Nowadays with python's rich specializer ecosystem (LLVM, CUDA, and just generally vectorized math), the value of writing a small program in anything else diminishes quickly.

Imagine reading the C++wg release notes in the same mood that you would the python release notes.

[1] https://github.com/mypyc/mypyc

> Note that the mypyc issue tracker lives in this repository! Please don't file mypyc issues in the mypy issue tracker.

See https://github.com/mypyc/mypyc/blob/master/show_me_the_code....

And mypyc https://github.com/mypyc/mypyc

More recent approaches include mypyc which is (on the tin) quite close to what you describe, and taichi that lives in between.

Have you encountered mypyc?

https://github.com/mypyc/mypyc

> Mypyc compiles Python modules to C extensions. It uses standard Python type hints to generate fast code. Mypyc uses mypy to perform type checking and type inference.

Regarding the large execution time mentioned in your article, I discovered (mypyc)[https://github.com/mypyc/mypyc] on this subreddit in a post from the black formatter team https://www.reddit.com/r/Python/comments/v2009i/im_that_person_who_got_black_compiled_with_mypyc/?utm_medium=android_app&utm_source=share

GitHub - kostya/benchmarks: Some benchmarks of different languages

In all the language comparisons I've found over the years, Python consistently comes out slightly slower, for example:

https://github.com/kostya/benchmarks

Bearing in mind these are probably not even using YJIT, which makes Ruby considerably faster in some scenarios.

Also, here is another benchmark: https://github.com/kostya/benchmarks