import timeit
import numpy as np
 
f = lambda x: x ** 2
vf = np.vectorize(f)
 
def test_array(x, n):
    t = timeit.timeit(
        'np.array([f(xi) for xi in x])',
        'from __main__ import np, x, f', number=n)
    print('array: ' + str(t))
 
def test_fromiter(x, n):
    t = timeit.timeit(
        'np.fromiter((f(xi) for xi in x), x.dtype, count=len(x))',
        'from __main__ import np, x, f', number=n)
    print('fromiter: ' + str(t))
 
def test_vectorized(x, n):
    t = timeit.timeit(
        'vf(x)',
        'from __main__ import x, vf', number=n)
    print('vectorized: ' + str(t))
 
def test_direct(x, n):
    t = timeit.timeit(
        'f(x)',
        'from __main__ import x, f', number=n)
    print('direct: ' + str(t))
 
x = np.arange(1000)
n = 1000
test_array(x, n)
test_fromiter(x, n)
test_vectorized(x, n)
test_direct(x, n)

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