Python Speed Comparison

Comparison of processing speed of basic Python functions.

Result

Basically, data size N = 10^6.

Standard Input

input() vs sys.stdin.readline()

# input()
N = int(input())
A = [int(input()) for _ in range(N)]

# sys.stdin.readline()
import sys
input = sys.stdin.readline

N = int(input())
A = [int(input()) for _ in range(N)]

	mean(ms)	std(ms)
input()	392.40	24.36
sys.stdin.readline()	37.09	1.88

Sort

sort() vs sorted()

A is a list whose elements are random integer values.

# sort()
A.sort()

# sorted()
A = sorted(A)

	mean(ms)	std(ms)
sort()	88.54	56.98
sorted()	127.03	7.51

key of sort

A is a two-dimensional array whose elements are random integer values.

# sort, lambda
A.sort(key=lambda x: x[1])

# sort, itemgetter
from operator import itemgetter
A.sort(key=itemgetter(1))

# sorted, lambda
A = sorted(A, key=lambda x: x[1])

# sorted, itemgetter
from operator import itemgetter
A = sorted(A, key=itemgetter(1))

	mean(ms)	std(ms)
sort, lambda	641.17	29.69
sort, itemgetter	521.91	4.91
sorted, lambda	688.45	35.24
sorted, itemgetter	588.17	15.32

Loop

for vs while

# for _ in range(N)
for _ in range(N):
    pass

# for i in range(N)
for i in range(N):
    i

# while i < N
i = 0
while i < N:
    i += 1

	mean(ms)	std(ms)
for _ in range(N)	20.63	0.89
for i in range(N)	25.66	0.93
while i < N	51.36	1.44

List

Initialize the list

# [None] * N
[None] * N

# [None for _ in range(N)]
[None for _ in range(N)]

	mean(ms)	std(ms)
[None] * N	5.15	0.41
[None for _ in range(N)]	41.17	2.05

Refer to in the list

# for i in range(len(A))
for i in range(len(A)):
    A[i]

# for a in A
for a in A:
    a

	mean(ms)	std(ms)
for i in range(len(A))	41.14	0.56
for a in A	11.85	1.51

Add to the list

# append()
A = []
for i in range(N):
    A.append(i)

# A[i] = i
A = [None] * N
for i in range(N):
    A[i] = i

# [i for i in range(N)]
A = [i for i in range(N)]

	mean(ms)	std(ms)
append()	103.99	2.62
A[i] = i	70.97	3.93
[i for i in range(N)]	65.83	3.20

Usage

python main.py