alt Hacker NewsI like Julia approach, compile everything on first launch, then reuse without speed penality, if you change a function, recompile that.
On another note, I'm working on a (big) PEP for python, and looking for maintainers and sponsors (as per python's rules). Do someone know where I could find such amazing persons? (I already have the code, works in cython,graalVM and pypy, and it's kind of a big change but I believe it will help a lot the language)
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The Julia approach is the same as BASIC (as originally designed), Lisp, Prolog, as added info.
The language forum is the place to start- you should already have a thread there gathering feedback before writing a pep?
However because of this, Julia has has persistent problems with "time to first plot", which has gotten better, but they cannot fully ameliorate due to the way it fundamentally works. So there are tradeoffs -- the performance gets better, but the interpreted REPL experience is markedly worse.
There’s an #internals-and-peps channel in the Python discord where some folks hang out.
That's basically how Python already compiles source to byte-code.
> I like Julia approach, compile everything on first launch, then reuse without speed penality, if you change a function, recompile that.
Python already compiles to bytecode (the .pyc files are a cache thereof). It's just that interpreting even the simple bytecode instructions can take dozens of clock cycles each. I imagine that a lot of this is not in the interpreter loop (which has seen quite a bit of optimization, IIRC up to the level of "predictive" gotos within a big switch statement within a loop) but just unwrapping objects and moving values to and from registers, dealing with the fact that there is basically never any cache coherency for anything etc.
Basically I'm not convinced that writing out the set of machine-code instructions needed to interpret the bytecodes would be a big win, because it takes too many instructions for simple tasks.