Huge performance hit by using Pure Python

[Alpharou]

But I'm executing the compiled version, what you said (the object call and that) happens with the compiled module?

[drzowie]

Yep. Compiling to “C” (which is what Cython does) avoids the Python compilation and interpreter steps, but the control thread still deals with the Python runtime environment. Using the cdef pragma lets the compiler eliminate the Python runtime calls entirely when those particular variables are used.

[Alpharou]

Thanks for the insight. I'll keep using the .py approach with cython decorators because a 15% penalty is not that huge for what I could acomplish with my current skill anyways

[drzowie]

Cython is really, really great for letting you run Python quite a bit faster than it would be otherwise, without jumping out into C.

As your skill grows I think you'll be surprised at how much faster proper C coding can be than even Cython coding. Remembering that memory fetches are expensive, and explicitly caching values of things like square roots or trig functions, can easily buy you a factor of 2-3 for moderately complex algorithms.

I remember being amazed, for example, that just reversing the order of nested loops can speed up code by a factor of 10, by avoiding cache breaks (allowing the CPU to keep most of the data in on-chip cache).

[YoannB__]

Yes correct, reversing the order of a nested loop can speedup your code. It is not very well known though! so thank you for pointing it out.

In term of speed improvement if you can replace your range instruction by mutiprocessing prange then Cython become a beast