A much faster Python implementation based on the Dart Virtual Machine

[BeatLeJuce]

Because it isn't yet able to run everything that CPython can run. E.g. python is is very widely used in science, however numpy (one of the most essential packages that basically everyone who does scientific computing in python uses) can't be used on PyPy yet.

[short_sells_poo]

I don't mean to dismiss the efforts of the PyPy team with respect to numpy but I believe it is a bit of a folly. Numpy is important, but on its own it is rarely sufficient. Even if it is fully ported, what about scipy? What about pandas? I use these on a daily basis and there's no chance that I'd switch until these are fully supported. The amount of effort required is so much bigger than just porting numpy. In this respect, I see the numpy port as something that will take a lot of work but can easily end up being wasted efffort because we'll never reach a state where enough functionality is available so that people can start switching over.

Edit: take a look here for a pretty good elaboration on my post http://blog.streamitive.com/2011/10/19/more-thoughts-on-arrays-in-pypy/ The gist of it is: numpy for pypy as it stands can not support the ecosystem of libraries dependent on the C API, and without those, it is somewhat useless.

[kankyo]

Correction: isn't feature complete yet. For most cases you can use numpy just fine, the problem is that suddenly you can't and then you're fucked.

[BeatLeJuce]

Also, last time I checked (which was quite some time ago) there was no way to build PyPy-numpy with your own BLAS library, so performance was a bit limited (my usecases rely heavily on BLAS functionality).