编写更优的循环

高效编写 Python 代码

Logan Thomas

Scientific Software Technical Trainer, Enthought

课程说明

下面一些循环可用前面课程的技巧消除。
本课示例仅用于演示。

alt="警告标志，文字：仅供演示使用"

编写更优的循环

理解每次循环迭代在做什么
将一次性计算放到循环外（上方）
在循环外（下方）使用整体式转换
任何只需执行一次的操作都应在循环外

将计算上移到循环之外

import numpy as np

names = ['Absol', 'Aron', 'Jynx', 'Natu', 'Onix']
attacks = np.array([130, 70, 50, 50, 45])

for pokemon,attack in zip(names, attacks):

    total_attack_avg = attacks.mean()

    if attack > total_attack_avg:
        print(
            "{}'s attack: {} > average: {}!"
            .format(pokemon, attack, total_attack_avg)
        )

Absol's attack: 130 > average: 69.0!
Aron's attack: 70 > average: 69.0!

import numpy as np

names = ['Absol', 'Aron', 'Jynx', 'Natu', 'Onix']
attacks = np.array([130, 70, 50, 50, 45])

# Calculate total average once (outside the loop)
total_attack_avg = attacks.mean()

for pokemon,attack in zip(names, attacks):

    if attack > total_attack_avg:
        print(
            "{}'s attack: {} > average: {}!"
            .format(pokemon, attack, total_attack_avg)
        )

Absol's attack: 130 > average: 69.0!
Aron's attack: 70 > average: 69.0!

将计算上移到循环之外

%%timeit
for pokemon,attack in zip(names, attacks):

    total_attack_avg = attacks.mean()

    if attack > total_attack_avg:
        print(
            "{}'s attack: {} > average: {}!"
            .format(pokemon, attack, total_attack_avg)
        )

74.9 µs ± 3.42 µs per loop (mean ± std. dev. of 7 runs, 10000 loops each)

将计算上移到循环之外

%%timeit
# Calculate total average once (outside the loop)
total_attack_avg = attacks.mean()

for pokemon,attack in zip(names, attacks):

    if attack > total_attack_avg:
        print(
            "{}'s attack: {} > average: {}!"
            .format(pokemon, attack, total_attack_avg)
        )

37.5 µs ± 281 ns per loop (mean ± std. dev. of 7 runs, 10000 loops each)

使用整体式转换

names = ['Pikachu', 'Squirtle', 'Articuno', ...]
legend_status = [False, False, True, ...]
generations = [1, 1, 1, ...]

poke_data = []
for poke_tuple in zip(names, legend_status, generations):

    poke_list = list(poke_tuple)

    poke_data.append(poke_list)

print(poke_data)

[['Pikachu', False, 1], ['Squirtle', False, 1], ['Articuno', True, 1], ...]

使用整体式转换

names = ['Pikachu', 'Squirtle', 'Articuno', ...]
legend_status = [False, False, True, ...]
generations = [1, 1, 1, ...]

poke_data_tuples = []
for poke_tuple in zip(names, legend_status, generations):
    poke_data_tuples.append(poke_tuple)

poke_data = [*map(list, poke_data_tuples)]

print(poke_data)

[['Pikachu', False, 1], ['Squirtle', False, 1], ['Articuno', True, 1], ...]

%%timeit
poke_data = []
for poke_tuple in zip(names, legend_status, generations):
    poke_list = list(poke_tuple)
    poke_data.append(poke_list)

261 µs ± 23.2 µs per loop (mean ± std. dev. of 7 runs, 1000 loops each)

%%timeit
poke_data_tuples = []
for poke_tuple in zip(names, legend_status, generations):
    poke_data_tuples.append(poke_tuple)

poke_data = [*map(list, poke_data_tuples)]

224 µs ± 1.67 µs per loop (mean ± std. dev. of 7 runs, 1000 loops each)

该练习了！

高效编写 Python 代码