This is amazing -- we have a small mountain of Cython code, and almost everything is working out of the box!<p>Tests failing:<p>* <a href="https://github.com/explosion/spaCy" rel="nofollow">https://github.com/explosion/spaCy</a><p>Confirmed working:<p>* <a href="https://github.com/explosion/thinc" rel="nofollow">https://github.com/explosion/thinc</a><p>* <a href="https://github.com/explosion/preshed" rel="nofollow">https://github.com/explosion/preshed</a><p>* <a href="https://github.com/explosion/cymem" rel="nofollow">https://github.com/explosion/cymem</a><p>* <a href="https://github.com/explosion/murmurhash" rel="nofollow">https://github.com/explosion/murmurhash</a><p>I doubt spaCy will ever be faster on PyPy (the neural network library Thinc is currently 50% slower). It'd still be really great to get it running, so people who benefit from PyPy for other parts of their stack don't have to manage two Python environments.
This is great. Can't wait until Python 3.5 support is out of beta.<p>Just out of curiosity, I'd love to hear from others who've used PyPy for their web apps. Are there any issues to look out for? I remember that a few years ago, packages like psycopg2 were not compatible, which made the migration somewhat difficult. Would love to hear real-world experiences here.
The original title emphasises that NumPy and Pandas now are functional on PyPy.<p>The PyPy JIT cannot look inside C code, and crossing the python-c interface is slow, but give it a chance and you may be pleasantly surprised how fast your pure python code can run.
I wonder if this will run apistar: <a href="https://github.com/encode/apistar" rel="nofollow">https://github.com/encode/apistar</a> which is currently the fastest (python 3.6 generally) python web framework out there.
As I do with every PyPy release, I would like to point out that the PyPy official benchmarks for comparison against CPython[0] continue to misleadingly compare their latest and greatest with CPython 2.7.2 (released in 2011), as opposed to the modern CPython 2.7.13 or 3.5.3 versions for which they target API compatibility.<p>[0]<a href="http://speed.pypy.org" rel="nofollow">http://speed.pypy.org</a>
Is there a list of well-known c-extensions for which PyPy is known to work or for which there are well-maintained cpyext ports ?<p>Update: found it at <a href="https://bitbucket.org/pypy/compatibility/wiki/Home" rel="nofollow">https://bitbucket.org/pypy/compatibility/wiki/Home</a>
Was surprised to see Cython support on this list. Can somebody elaborate on the relationship between the two? I had always viewed them as alternatives.
Is PyPy <i>ideally</i> plug'n'play, i.e. is it supposed to be able to seamlessly replace the CPython interpreter (<i>ideally</i> in that it may not factually be completely compatible, but is it aimed to be completely compatible)?
Thanks @fijal and team for all the effort! This is awesome.<p>The last update on the Pypy+Pandas wiki[0] is from this August, and it mentions that there are still 15 outstanding failing tests. Does this release mean that 5.9 is now at 100% parity? What does the same metric look like for Pypy+Numpy, and where can that one be tracked if not 100% yet?<p>I am looking forward to migrating some pipelines over to 5.9 soon.<p>[0] <a href="https://bitbucket.org/pypy/pypy/wiki/cpyext_2_-_cython_and_pandas" rel="nofollow">https://bitbucket.org/pypy/pypy/wiki/cpyext_2_-_cython_and_p...</a>