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by ris
2954 days ago
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> My view is that the limitations are almost purely financial Your view is wrong. Implementing highly optimized versions of different languages (which may from the layman's point of view look quite similar) is not completely comparable. Python is a much more dynamic language than javascript - huge amounts of the language are overridable object by object, even down to attribute access. Hell, even down to isinstance() behaviour. And these are all things that need e.g. deoptimization barriers added in the code fast path to check if xyz mechanism happens to have been overridden. Javascript doesn't even have operator overloading. The PyPy team have put a lot of work into building a performant python implementation (there's your "fork" for you...) having to, from what I can tell, work through a lot of these issues with a good deal of ingenuity along the way. Throwing money and/or "rockstar programmers" at projects isn't as wise as it always seems. Particularly when they don't seem to have significantly investigated the work of a team that's been working on the "fast python" problem for the last 15 years. |
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If you mean PyPy, PyPy was from the start intentionally "meta": it was never made to be simply a Python with a faster interpreter(s) and fast JIT(s) working in sync, like the modern Javascript engines work. It was intentionally a reimplementation of Python interpreter and all possible code in Python (that's where the name PyPy comes from), and then what's "optimized" is everything together: the new interpreter and the new Python implementation written in Python, all while generating a real C source. Which is then compiled as a normal C.
It's obviously too "meta" goal compared to the approaches used by fast Javascript engines, even if they also use some Javascript implementations for some library functions. When your starting goal is to "do everything in Python" you have already blocked yourself from being able to take the really best possible approach on every level of the engine. And even being meta enough, they still write:
"in code like this with a string-valued foo() function:"
"the JIT cannot optimize out intermediate copies. This code is actually quadratic in the total size of the mylist strings due to repeated string copies of ever-larger prefix segments."So yes, there's definitely a room to make a faster usable implementation compared to the current PyPy. But it is a hard work, and needs a very focused and knowable leader(s), willing to take the "harder" approaches on every level, when needed. "Harder" than "we'll do everything in Python and only then optimize the whole thing together."