numpy array vs native

numpyarrayvsnative.py

import numpy as np
import inspect
import time

class timeit:
    def __init__(self, name=""):
        self.st_time = 0
        self.display_name = f'[{name}] ' if name != '' else f'[line {inspect.stack()[1].lineno}] '
 
    def __enter__(self):
        self.st_time = time.time()
        return self
 
    def __exit__(self,exc_type,exc_val,exc_tb):
        print(f"{self.display_name}time cost: {time.time() - self.st_time}")
        if exc_val:
            raise exc_val

ARRAY_SIZE = 100000
n1 = np.zeros(ARRAY_SIZE,dtype=np.int_)

with timeit():
    for i in range(10000):
        n1 += 2

print(n1)

n2 = [0 for _ in range(ARRAY_SIZE)]
with timeit():
    for i in range(100):
        for j in range(ARRAY_SIZE):
            n2[j] += 2

print(n2[:5])

'''
Output:
[line 21] time cost: 0.3201007843017578
[20000 20000 20000 ... 20000 20000 20000]
[line 28] time cost: 0.7021913528442383
[200, 200, 200, 200, 200]
'''