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PyPy 4.0.0 Released – A Jit with SIMD Vectorization and More

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Re: PyPy 4.0.0 Released – A Jit with SIMD Vectorization and More

#81

Post by chrisseaton »

cfontes wrote: post #50
wyldfire wrote: post #5

Kudos to the pypy team! I suspect pypy would benefit from some kind of marketing campaign. It rarely lets me down and yet lots of python devs don't know about it. The most popular package(s) that don't work with it have been numpy, scipy, etc. When I first encountered pypy, there was a numpypy and I wouldn't be surprised if that's different now. But bottom line, tons of python code out there needs more performance an…

I am a Java dev, I heard of PyPy a few years ago, I find it amazing and often tell people about it when talking about performance and other related topics. The thing is I've never found another developer that new about it, something is very wrong...

If you are a Java developer and find PyPy amazing, you should also look at Truffle and Graal http://lafo.ssw.uni-linz.ac.at/papers/2013_Onward_OneVMToRul..., http://chrisseaton.com/rubytruffle/, https://bitbucket.org/ssllab/zippy/src/700f88dc2a7d2011258ae...

Re: PyPy 4.0.0 Released – A Jit with SIMD Vectorization and More

#82

Post by kibwen »

mden wrote: post #66
saidajigumi wrote: post #63

Earlier quoted context omitted.

On the flip side of this thread, some projects have started to adopt specific tagging in their issue systems for folks looking to get started as contributors. I really like this as it's clear communication to both new contributors and to existing contributors that the issue in question is an on-ramp for the project. Here's Neovim's "entry-level" label, for example: https://github.com/neovim/neovim/issues?q=is%3Aopen+…

As another example it seems that Rust does the same: https://github.com/rust-lang/rust/issues?q=is%3Aopen+is%3Ais...

Servo inherited that policy too: https://github.com/servo/servo/issues?q=is%3Aopen+is%3Aissue...

Re: PyPy 4.0.0 Released – A Jit with SIMD Vectorization and More

#83

Post by jegutman »

wyldfire wrote: post #5

Kudos to the pypy team! I suspect pypy would benefit from some kind of marketing campaign. It rarely lets me down and yet lots of python devs don't know about it. The most popular package(s) that don't work with it have been numpy, scipy, etc. When I first encountered pypy, there was a numpypy and I wouldn't be surprised if that's different now. But bottom line, tons of python code out there needs more performance an…

Also I recently discovered that pypy supports non-ASCII characters pretty well which at least doesn't work with my version of python 2.7.6

Re: PyPy 4.0.0 Released – A Jit with SIMD Vectorization and More

#84

Post by Beltiras »

ericflo wrote: post #72
Beltiras wrote: post #40

According to data I'm getting a 20X performance increase from the rendering engine in Django. I know this is the least of the time I spend but it's significant enough to take a deeper look.

You may be surprised, I've seen a lot of Django setups where template rendering was the slowest or second-slowest part of their system behind DB queries.

Still not spending a lot of time there due to proper fragment caching.

Re: PyPy 4.0.0 Released – A Jit with SIMD Vectorization and More

#85

Post by elcct »

mixmastamyk wrote: post #73
dorfsmay wrote: post #33

Earlier quoted context omitted.

One of the rewards of participating in OSS is to make your name visible, this can then be used as creds to gain commit rights or to talk at conferences as well as proof of competence when looking for a job. Interestingly, I've had the same experience when reporting and asking how to contribute to Python 3, not by a core dev but somebody "stealing" my bug and quickly submitting a patch!

Something similar happened that left me with mixed feelings recently. I recently came up with a new feature idea for Python, and a core dev ran with it. I was very happy at first, but then he wrote a pep, implemented it, and got all the congrats. I had hoped to help, and put something on my resume, but was shut out. "Thanks for improving my pep" on a mailing list is all the credit I got (and work I was able to do on…

Sometimes person reporting an issue along with the code, doesn't get it quite right and core dev can immediately see correct solution and can't make himself to wait until original reporter makes it right... of course it doesn't happen often but it does.

Re: PyPy 4.0.0 Released – A Jit with SIMD Vectorization and More

#86

Post by ptx »

jegutman wrote: post #83
wyldfire wrote: post #5

Kudos to the pypy team! I suspect pypy would benefit from some kind of marketing campaign. It rarely lets me down and yet lots of python devs don't know about it. The most popular package(s) that don't work with it have been numpy, scipy, etc. When I first encountered pypy, there was a numpypy and I wouldn't be surprised if that's different now. But bottom line, tons of python code out there needs more performance an…

Also I recently discovered that pypy supports non-ASCII characters pretty well which at least doesn't work with my version of python 2.7.6

In what way?

Re: PyPy 4.0.0 Released – A Jit with SIMD Vectorization and More

#87

Post by [deleted] »

throwa990323249 wrote: post #75
bionsuba wrote: post #71

Earlier quoted context omitted.

The problem, which they keep mentioning over and over, is that companies who actually donate have zero interest in a python 3 version. While they are a non profit, they have to pay the bills somehow.

Chicken and egg... But if there was good Python 3 support maybe more companies would contribute.

[deleted]

Re: PyPy 4.0.0 Released – A Jit with SIMD Vectorization and More

#88

Post by vegabook »

baq wrote: post #7

python 3.4 please ;_;

"puhleeze give us Python 3...." repeated everywhere in this comment thread, yet the authors of pypy keep responding with the same line: pay some money and we'll do it. This speaks to what the real industry users of Python already know: 2.7 is where it's at, and they're prepared to pay for that, and not 3.x. Sure there'll be a bunch of people waving the 3 flag and saying "I use it" etc, but the bottom line is the bottom line: money. 2 attracts the dough.

If I were the PyPy guys I'd just announce that PyPy was now officially a fork of 2.7. This would bring all the numerical guys with them, all the corpos with big investments in 2 would fund them, and we could then let the 3.x zealots go off on their own tangent.

Anybody who likes what 3.x brings to the table should really spend a weekend learning Go, which does it all better, and faster.

I've been saying in these threads for ages that vectorization is the big win in Python (thank you PyPy), and not hobby projects like asyncio (miles better elsewhere), or (eyes rolling) type annotations.

Re: PyPy 4.0.0 Released – A Jit with SIMD Vectorization and More

#89

Post by lqdc13 »

wyldfire wrote: post #29
dr_zoidberg wrote: post #17

Earlier quoted context omitted.

I think you guys are saying the same thing. Ie, because they don't need to switch languages, and PyPy is a JIT engine for Python, these tons of Python code would benefit from if the devs were aware of PyPy .

Indeed that's what I meant and perhaps pjmlp thinks that the feature set in numpy could have been / could be implemented in pure python, now that we have PyPy.

Numpy is way faster than what you would get if you implementing things in pure Python and executed with PyPy. That's why there is numpypy in the first place.

Re: PyPy 4.0.0 Released – A Jit with SIMD Vectorization and More

#90

Post by lqdc13 »

dr_zoidberg wrote: post #17
pjmlp wrote: post #8

Earlier quoted context omitted.

> But bottom line, tons of python code out there needs more performance and has no dependency on numpy or any C extensions. What they need is nice JIT engines like PyPy and not to switch languages. If no one invested in improving implementations for modern languages and switched to something lower level all the time, we would still be using Fortran for business applications.

I think you guys are saying the same thing. Ie, because they don't need to switch languages, and PyPy is a JIT engine for Python, these tons of Python code would benefit from if the devs were aware of PyPy .

Devs are already aware of PyPy. If it was as easy as being aware, everyone would switch tomorrow. The problem is that tons of code uses C extensions created with swig or python boost and those take a lot of time to port to PyPy. Another problem is that PyPy is sometimes slower/less memory efficient than CPython when you wrote the code that is optimized for CPython. That is abusing dictionaries and very limited OO use.
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