results.txt

python test.py
test1arr for 100000000 primes: write directly to array with new generate_n_primes_array 2.82 sec
test1iter for 100000000 primes: write to numpy data using iter interface: 3.65 sec
test1iter2 for 100000000 primes: write to numpy data using iter interface data access: 3.40 sec
test1np for 100000000 primes: use normal vector generation but copy directly to numpy on output: 4.16 sec
test2 for 100000000 primes: current vector generate_n_primes with numpy copy from vector to output list: 21.03 sec
test2a for 100000000 primes: current vector, copy to output list, create numpy array: 36.25 sec

test.py

# let the function create the array and return it
# let the function create the array and return it
def test1arr(sz = 10**8):
    import numpy_primesieve as npp
    a = npp.generate_n_primes_array(sz,1)        # will create output array and return it
    #print(a[-1])
    return a

def test1np(sz = 10**8):
    import numpy_primesieve as npp
    a = npp.generate_n_primes_numpy(sz, 1)        # will create output array and return it
    #print(a[-1])
    return a

# pass in the output array - hould have same performace as previous test
def test1iter(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_iter(sz,1, a)          # store results into array 'a' and return it
    #print(a[-1])
    return a

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

def time_them():
    import timeit
    num = 2
    sz = 10**8
    tests = {'test1arr' : "write directly to array with new generate_n_primes_array",
             'test1np'   : "use normal vector generation but copy directly to numpy on output:",
             'test1iter' : "write to numpy data using iter interface:",
             'test1iter2' : "write to numpy data using iter interface data access:",
             'test2'     : "current vector generate_n_primes with numpy copy from vector to output list:",
             'test2a'    : "current vector, copy to output list, create numpy array:"
             }
    for test in sorted(tests.keys()):
        msg = tests[test]
        call = "{}(sz={})".format(test,sz)
        setup = "from __main__ import {}".format(test)
        tm = timeit.timeit(call, setup=setup, number=num)
        print("{} for {} primes: {} {:.2f} sec".format(test,sz, msg, tm))

if __name__ == '__main__':
    time_them()