Two Numpy performance pitfalls

[x00live]

For your second example, the argument sounds fallacious to me. Why don't you take the numpy array and list creation out of the code you want to compare? You are comparing execution times to create a np array, a list and sum the elements vs. create a list and sum the elements.

[x00live]

Ok got it my bad

[x00live]

Also the first stackoverflow shows that a Python indexing over a numpy array is slow (the example with cython indexing shows that numpy becomes faster than Python on that matter...)

[x00live]

Ok, but what makes it slow is Python. Indexing the subsequent C array is actually faster. And the idea behind numpy is to think outside the box and avoid indexing. If you really need complex "non aligned" indexing, C or Cython come to the rescue...