pypy

I am using some numpy tools (mainly arrays) and I wanted to run the script with pypy, but i can't make it work. The error that i get is: ImportError: No module named multiarray. I checked if the multiarray.so file was in the core folder. Can someone tell me if first: is possible to do what I am trying to do and second: How can I do it? I've just posted a blog post explaining what's the status and what's the plan. In short numpy will not work with PyPy's cpyext and even if it does, it would be too slow for usage. The other answers are quite old. Here is the the completely unscientific measure

According to this post: https://groups.google.com/forum/?fromgroups#!topic/kivy-users/n7c3thksnzg , it is possible to use Eclipse as an IDE for Kivy through PyDev. However, I didn't understand the instructions. Can anyone please elaborate on how to connect Kivy with Eclipse. Note: I'm on a Windows machine. Also, is it possible to use PyPy instead of the Python Interpreter? Thanks~! Using Kivy with Pydev on Windows xp/7 Under Window/Preferences/PyDev/Interpreter-Python add a new interpreter pointing to the python executable which ships with kivy portable add kivy package folder under libraries

I was trying to implement a Miller-Rabin primality test , and was puzzled why it was taking so long (> 20 seconds) for midsize numbers (~7 digits). I eventually found the following line of code to be the source of the problem: x = a**d % n (where a , d , and n are all similar, but unequal, midsize numbers, ** is the exponentiation operator, and % is the modulo operator) I then I tried replacing it with the following: x = pow(a, d, n) and it by comparison it is almost instantaneous. For context, here is the original function: from random import randint def primalityTest(n, k): if n < 2: return

From the Google Open Source Blog : PyPy is a reimplementation of Python in Python, using advanced techniques to try to attain better performance than CPython. Many years of hard work have finally paid off. Our speed results often beat CPython, ranging from being slightly slower, to speedups of up to 2x on real application code, to speedups of up to 10x on small benchmarks. How is this possible? Which Python implementation was used to implement PyPy? CPython ? And what are the chances of a PyPyPy or PyPyPyPy beating their score? (On a related note... why would anyone try something like this?)

I've been hearing a lot about the PyPy project. They claim it is 6.3 times faster than the CPython interpreter on their site . Whenever we talk about dynamic languages like Python, speed is one of the top issues. To solve this, they say PyPy is 6.3 times faster. The second issue is parallelism, the infamous Global Interpreter Lock (GIL). For this, PyPy says it can give GIL-less Python . If PyPy can solve these great challenges, what are its weaknesses that are preventing wider adoption? That is to say, what's preventing someone like me, a typical Python developer, from switching to PyPy right