>The way these type checkers get fast is usually by not supporting the crazy rich reality of realworld python code.
Nah, that's just part of the parade of excuses that comes out any time existing software solutions get smoked by a newcomer in performance, or when existing software gets more slow and bloated.
the thing is most (all) of the type checkers including e.g. mypy _do not_ support most crazy python ...
not because they don't want to or because it's to slow
but because it's not really viable without fully executing module loading in a sandbox, which might seem viable until you realize that you still need to type check `__main__` modules etc. and that its a common trend in python to do configs by loading python modules and grabbing the module locals as keys of the config or loading some things might actually idk. initialize a GPU driver :sob: So it's kinda 100% guaranteed not possible to do fully correct type checking for all project :smh:
But also python is one of the slowest popular languages (and with a large margin to any not also "one of slowest" languages). Only by moving hot code into C++/Rust is it fast, which often is good enough, but a type checker is exactly this kind of software where this approach stops working.
Python's static checking capabilities could significantly improve both tracing and compilation efficiency. The language features that currently limit type checkers are likely the same ones making efficient compilation difficult. Perhaps we'll eventually see a Python 3.40 with complete JIT compilation, functioning similarly to Julia but retaining Python's extensive ecosystem that makes it essential in certain domains.
Nah, that's just part of the parade of excuses that comes out any time existing software solutions get smoked by a newcomer in performance, or when existing software gets more slow and bloated.
Here's one of many examples:
https://m.youtube.com/watch?v=GC-0tCy4P1U&pp=0gcJCdgAo7VqN5t...