Test timing of writing arrays in place vs using vectors for numpy primesieve bindings

results.txt

pstoll$ python test.py
test1  arrays: 6.956779105006717
test1a arrays: 6.8869501760054845
test2  native vectors: 59.97818154899869
test2a native vectors: 90.65342697499727

test.py

# let the function create the array and return it
def test1():
    sz = 10**8
    import numpy_primesieve as npp
    a = npp.generate_n_primes_array(sz,1)        # will create output array and return it
    return a

# pass in the output array - hould have same performace as previous test
def test1a():
    sz = 10**8
    import numpy_primesieve as npp
    import numpy as np
    a = np.zeros([sz],dtype=np.uint64,order='c')
    npp.generate_n_primes_array(sz,1, a)          # store results into array 'a' and return it
    return a

# just create list of primes
def test2():
    sz = 10**8
    import primesieve as ps
    a = ps.generate_n_primes(sz,1)
    return a

# create list of primes and use it to create a numpy array
def test2a():
    sz = 10**8
    import primesieve as ps
    import numpy as np
    a = np.array(ps.generate_n_primes(sz,1))
    return a

def time_them():
    import timeit
    num = 5
    print("test1  arrays:", timeit.timeit("test1()", setup="from __main__ import test1", number=num))
    print("test1a arrays:", timeit.timeit("test1a()", setup="from __main__ import test1a", number=num))
    print("test2  native vectors:",timeit.timeit("test2()", setup="from __main__ import test2", number=num))
    print("test2a native vectors:",timeit.timeit("test2a()", setup="from __main__ import test2a", number=num))
    
if __name__ == '__main__':
    time_them()