Menulis loop yang lebih baik

Menulis Kode Python yang Efisien

Logan Thomas

Scientific Software Technical Trainer, Enthought

Catatan pelajaran

Beberapa loop berikut dapat dihilangkan dengan teknik dari pelajaran sebelumnya.
Contoh di pelajaran ini untuk tujuan demonstrasi.

alt=”Tanda peringatan bertuliskan Peringatan: hanya untuk tujuan demonstrasi”

Menulis loop yang lebih baik

Pahami apa yang dilakukan tiap iterasi loop
Pindahkan perhitungan sekali jalan ke luar (di atas) loop
Gunakan konversi holistik di luar (di bawah) loop
Apa pun yang dilakukan sekali harus di luar loop

Memindahkan perhitungan ke atas loop

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])

# Hitung rata-rata total sekali (di luar 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!

Memindahkan perhitungan ke atas loop

%%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)

Memindahkan perhitungan ke atas loop

%%timeit
# Hitung rata-rata total sekali (di luar 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)

Menggunakan konversi holistik

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], ...]

Menggunakan konversi holistik

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)

Ayo berlatih!

Menulis Kode Python yang Efisien