[ghj]

If you want more examples of real world use cases, PyPy is pretty stress-tested by the competitive programming community already.

https://codeforces.com/contests has around 20-30k participants per contest, with contests happening roughly twice a week. I would say around 10% of them use python, with the vast majority choosing pypy over cpython.

I would guesstimate at least 100k lines of pypy is written per week just from these contests. This covers virtually every textbook algorithm you can think of and were automatically graded for correctness/speed/memory. Note that there's no special time multiplier for choosing a slower language, so if you're not within 2x the speed of the equivalent C++, your solution won't pass! (hence the popularity of pypy over cpython)

The sheer volume of advanced algorithms executed in pypy gives me huge amount of confidence in it. There was only one instance where I remember a contestant running into a bug with the jit, but it was fixed within a few days after being reported: https://codeforces.com/blog/entry/82329?#comment-693711 https://foss.heptapod.net/pypy/pypy/-/issues/3297.

[dragonwriter]

> If you want more examples of real world use cases, PyPy is pretty stress-tested by the competitive programming community already.

I think this is the first time I've seen someone suggest that competitive programming has much bearing on “real-world use cases”.

[saagarjha]

I guess it tells you that loops and basic containers work?

[andrewchambers]

So essentially all code right?

[saagarjha]

Right, but most code does things other than that as well.

[gabagool]

Why do competitive Python programmers use PyPy instead of CPython?

[ghj]

PyPy is easily 10x faster than CPython at numeric stuff, which is 99% of these contest problems.

For example, using CPython, if you try to make an array of a million ints, you won't get `int[1000000]` in your memory layout. Each int would actually be an object, which is huge and inefficient to reference (they are something like 24+ bytes each).

PyPy on the other hand, works as expected.

I think the more important point is that PyPy when written like C code, can actually get within 2x of the performance of C code. If it's any slower, python won't be a viable language in competitive programming at all.

(CPython is sometimes still used on other platforms like atcoder.jp, but only because they allow third party libraries like numba and numpy which can fill the same role pypy does)

[simple_phrases]

For that particular use case, how does PyPy perform in comparison to CPython's array module[1]?

[1] https://docs.python.org/3/library/array.html

[spicybright]

Why doesn't the community collectively switch over to PyPy? It seems like it's better in all reguards.

[semi-extrinsic]

Library support?

[sitkack]

The cabal that runs CPython ignores both standardization, the standard library and interop with other implementations.

PyPy shouldn't be the new default, but neither should be CPython.

[spicybright]

Don't you have to choose one or the other tho lol

[neolog]

PyPy is much faster than CPython.

[Guthur]

For some cases, and the picture often changes.

We were using pypy because it was better for our use case at one point but then later on we retested cpython and found the picture had changed.

We believe this was due to significant improvements in the regex engine for cpython over the period, but could also be due to our code base changing.

The point being it is not a given that pypy is faster.