[Animats]

But we did see performance improvements by restricting the language in certain ways that aid in static analysis, which allowed for more performant runtime code.

Well, yes. In Python, one thread can monkey-patch the code in another thread while running. That feature is seldom used. In CPython, the data structures are optimized for that. Underneath, everything is a dict. This kills most potential optimizations, or even hard-code generation.

It's possible to deal with that efficiently. PyPy has a compiler, an interpreter, and something called the "backup interpreter", which apparently kicks in when the program being run starts doing weird stuff that requires doing everything in dynamic mode.

I proposed adding "freezing", immutable creation, to Python in 2010, as a way to make threads work without a global lock.[1] Guido didn't like it. Threads in Python still don't do much for performance.

[1] http://www.animats.com/papers/languages/pythonconcurrency.ht...

[chrisseaton]

> This kills most potential optimizations, or even hard-code generation.

It doesn’t - this has been a basically solved problem since Self and deoptimisation were invented.

[Animats]

In theory, yes. In CPython, apparently not. In PyPy, yes.[1] PyPy has to do a lot of extra work to permit some unlikely events.

[1] https://carolchen.me/blog/jits-impls/

[chrisseaton]

You’re trying to correct me by posting my own mentee’s blog post at me.