Slow bitwise operations

Question

I am working on a Python library that performs a lot of bitwise operations on long bit strings, and I want to find a bit string type that will maximize its speed. I have tri

Answer 1

What you are trying to test - are these vector operations at all? You are simply trying to compare speeds of 1 operation and there plain python is going to win 'cos it doesn't have to setup numpy arrays or bitarrays.

How about trying out following?

x = np.array([random.randrange(2**31)]*1000) 
y = np.array([random.randrange(2**31)]*1000) 

%timeit x & y # in ipython

%timeit [ a & b for (a,b) in zip(x,y)] # even though x and y are numpy arrays, we are iterating over them - and not doing any vector operations

Interestingly, if

xxx = [random.randrange(2**31)] * 1000
yyy = [random.randrange(2**31)] * 1000 

and then

%timeit [a & b for (a,b) in zip(xxx,yyy)]

pure python lists, iterating over them is faster than iterating over numpy arrays.. a bit counter intuitive. Not sure why.

Similarly you can try for bitstrings and bitarrays

Is this what you are looking at?