I find it puzzling as well. Google heavily uses python, as do a number of other web companies. Further, Ubuntu and Redhat have it as a system administration language. It's almost the default language for O'Reilly books that aren't language specific. Given all that you'd think there'd be a few more corporate contributions now that a x5 speedup has already been proven and it seems to be just a matter of polishing it up.
A bit of searching and it seems the memory problems I raised in my other comment aren't so drastic after all. Theoretically it can use less memory in many operations and the current blowouts are not as high as I thought (I was going from one benchmark a HNer, brianh, was kind enough to run for me[1]).
Just because pypy is faster than cpython on a handful of test cases doesn't make it worthy of corporate sponsorship. I would sponsor development if it made a noticeable improvement.
Not to belittle the project, but I tried a vanilla order entry implementation on my test box in nasdaq. Essentially it runs an epoll loop using a C extension to take advantage of the myricom DBL calls. RT latency was roughly 5 usec faster using cpython. As for other parts of the system (eg feed handler), the performances were comparable.
For other applications (eg compliance reporting) pypy is 2x cpython speed, but I could care less about that timing (even if it ran 1000x slower than cpython, it wouldn't matter)
TL;DR: it needs to be useful. And I just don't see the usefulness for my Python applications.
> I find it puzzling as well. Google heavily uses python, as do a number of other web companies.
Especially after Google invested engineers on Unladen Swallow, which fizzled out. I've read that Google likes to max out their servers to the point where OOM is not unlikely, so PyPy memory usage might not be worth the runtime performance gains.
More likely, google requires compatibility with its set of C extensions. At least when unladen swallow was announced, this was one of the major requirement. I would expect the problem to be similar in most large corporate environments.
I agree, it is quite bizarre. PyPy is among the most remarkable and successful projects of its kind. That it isn't funded in some way is very surprising.
Perhaps there is a business opportunity here? Python as a service, sort of like how Python runs on Google App Engine, but using PyPy. PyPy's sandboxing makes this easier actually, and the main advantage of course would be performance.
A bit of searching and it seems the memory problems I raised in my other comment aren't so drastic after all. Theoretically it can use less memory in many operations and the current blowouts are not as high as I thought (I was going from one benchmark a HNer, brianh, was kind enough to run for me[1]).
[1]http://news.ycombinator.com/item?id=3357160