PyPy v5.8 released
I have a question and then a general vent<p>1. Does anyone know the latest update on NumPyPy? PyPy for me is just not a usable proposition because I heavily use Numpy (and Scipy et al). So I am forced to use slow Python + fast Numpy or slow Numpy + fast Python. Very saddening. The C-Extension is just so off the pace, NumPyPy was meant to solve that quandry.<p>And I know some smart Alec will trot out the usual &#x27;downshift into C&#x27; line that everyone (including Guido) use as the final goto solution for performance but that is simply a disgrace in 2017. Even JavaScript is fast. Why can I not choose to write Python and it be fast?? And yet Python 3 is getting slower. Don&#x27;t agree? 
Look at these benchmarks of Python heaps written in Python (not using the C based builtin heapq) <a href="https:&#x2F;&#x2F;github.com&#x2F;MikeMirzayanov&#x2F;binary-heap-benchmark" rel="nofollow">https:&#x2F;&#x2F;github.com&#x2F;MikeMirzayanov&#x2F;binary-heap-benchmark</a> Python generally is off the pace but Python 3 is about twice as slow as 2 and miles off JavaScript.<p>But PyPy is proof that Python can be fast. It makes quote&#x2F;unquote &quot;Pure Python&quot; within striking distance of Go and and when I run that test suit on PyPy, its similar to the Node.js score. Why does this matter?
Because I want to write bloody Python not C.<p>And it is so tantalisingly close - look at a blog post like: <a href="https:&#x2F;&#x2F;dnshane.wordpress.com&#x2F;2017&#x2F;02&#x2F;14&#x2F;benchmarking-python-heaps&#x2F;" rel="nofollow">https:&#x2F;&#x2F;dnshane.wordpress.com&#x2F;2017&#x2F;02&#x2F;14&#x2F;benchmarking-python...</a> The performance of the Fibonacci Heap that someone wrote in quote&#x2F;unquote &quot;Pure Python&quot;, when run in CPython can never compete with HeapQ (the C based builtin lib), but on PyPy it can. Fast code written in Python. So what are the problems holding back PyPy? I think possibly money and number of devs working on stuff. Javascript had Mozilla, Google, Microsoft and Apple in a browser war + loads of open source input.<p>But is the biggest stumbling block not Guido himself and the core Python devs? Do they just philosophically not agree with PyPy or is it just disinterest?<p>Well whatever it is, it is heart-breaking to want to write fast code in my favourite language and leverage all its power including Numpy&#x2F;Scipy etc and not be able to. And yes my use-case is perhaps quite unique, a very CPU intensive service that ideally computes and returns a real-time calculation (that includes 500k function calls) in 10-50ms.<p>But getting fast Numpy in the PyPy mix (i.e all the speed of the JIT + no worse Numpy) would be a HUGE step forward for me in PyPy adoption. What is the latest? How can I help?