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I feel like anybody really searching for speed is using something other than Python. I don't use Python for speed, but for ease-of-use. It took me some clicks to see it's supposed to be a drop-in replacement, so that's good.
Right - but if you can get that with better performance that's good isn't it?
I don't get why people object to performance work on languages not intended for performance.
I didn't know the Pyston team had split off to form their own company! Anyone know who's involved, or if they've raised money for it?
I feel like anybody really searching for speed is using something other than Python. I don't use Python for speed, but for ease-of-use. It took me some clicks to see it's supposed to be a drop-in replacement, so that's good.
I use python because of Numpy, Scikit and Tensorflow. I don't know of any other languages with libraries as productive as these, so speeding these apps up is a big win for a lot of people. Also 20% is huge, I look forward to trying it!
Earlier quoted context omitted.
I use python because of Numpy, Scikit and Tensorflow. I don't know of any other languages with libraries as productive as these, so speeding these apps up is a big win for a lot of people. Also 20% is huge, I look forward to trying it!
The 20% speed up looked like it was for flask and Django. In their benchmarks PyTorch did not have a speed increase.
"After the project ended, some of us from the team brainstormed how we would do it differently if we were to do it again. In early 2020, enough pieces were in place for us to start a company and work on Pyston full-time." I didn't know the Pyston team had split off to form their own company! Anyone know who's involved, or if they've raised money for it?
How about PyPy?
I feel like anybody really searching for speed is using something other than Python. I don't use Python for speed, but for ease-of-use. It took me some clicks to see it's supposed to be a drop-in replacement, so that's good.
Maybe. One of my projects at work is supporting a legacy ColdFusion website that is nearly 20 years old (well, it was started 20 years ago, but has seen updates since). We'd love to move it to something faster, but it is huge and it would literally take years to rewrite it. Other things take priority so it will probably never be rewritten. I imagine there are Python projects in a similar boat.
I feel like anybody really searching for speed is using something other than Python. I don't use Python for speed, but for ease-of-use. It took me some clicks to see it's supposed to be a drop-in replacement, so that's good.
I use python because of Numpy, Scikit and Tensorflow. I don't know of any other languages with libraries as productive as these, so speeding these apps up is a big win for a lot of people. Also 20% is huge, I look forward to trying it!
That being said, those libraries are already highly optimized and all the heavy stuff running on C anyways, so making the Python itself faster won't make that much of a difference in those workflows.
Earlier quoted context omitted.
As far as I know CPython is quite welcoming. However, per the blog post, this version of Pyston is closed source. So CPython won't be interested, and many others won't be interested either.
Python is a welcoming community, but they are decidedly not welcoming of contributions that significantly increase the complexity of the CPython reference implementation. This has been discussed extensively: https://news.ycombinator.com/item?id=11125769
Pypy has done yeoman's work in improving performance while maintaining compatibility with an impressive amount of the ecosystem, and even still there are many important packages which aren't compatible with Pypy and for which Pypy-compatible analogs don't exist (or aren't supported/maintained). For example, the only Pypy-compatible Postgres drivers were unsupported last I checked.
Moreover, the Python community (or at least its leadership) seems to have very little energy around tackling these longstanding problems. Meanwhile, there are many other languages which are not only performant, but which are rapidly encroaching on Python's historically unique(ish) "easiness" (in the sense that Python is considered "easy", which is to say for people who don't have to manage build/deploy/packaging/etc or otherwise have performance issues). Further, many of these languages continue to improve at a remarkable pace, while Python is content to rest on the laurels of its scientific computing mindshare--and given the rather poor nature of the numeric computing package APIs and their somewhat low performance ceiling, I don't expect Python to be so dominant in this domain in another 5-10 years, especially as more companies need to figure out how to productionize scientific workloads.
I feel like anybody really searching for speed is using something other than Python. I don't use Python for speed, but for ease-of-use. It took me some clicks to see it's supposed to be a drop-in replacement, so that's good.
> I don't use Python for speed, but for ease-of-use. Right - but if you can get that with better performance that's good isn't it? I don't get why people object to performance work on languages not intended for performance.
Presumably because they see it as effort that could be better applied elsewhere.
I don't know that I agree, but I can understand the viewpoint.