Betere lussen schrijven

Efficiënte Python-code schrijven

Logan Thomas

Scientific Software Technical Trainer, Enthought

Kanttekening bij de les

Sommige van de volgende lussen kun je schrappen met technieken uit eerdere lessen.
Voorbeelden in deze les zijn ter demonstratie.

alt=”Waarschuwingsbord met tekst Waarschuwing: alleen voor demonstratie”

Betere lussen schrijven

Begrijp wat elke iteratie doet
Verplaats eenmalige berekeningen buiten (boven) de lus
Gebruik holistische conversies buiten (onder) de lus
Alles wat je één keer doet, hoort buiten de lus

Berekeningen boven een lus verplaatsen

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])

# Bereken totale gemiddelde één keer (buiten de lus)
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!

Berekeningen boven een lus verplaatsen

%%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)

Berekeningen boven een lus verplaatsen

%%timeit
# Bereken totale gemiddelde één keer (buiten de lus)
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)

Holistische conversies gebruiken

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], ...]

Holistische conversies gebruiken

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)

Tijd om te oefenen!

Efficiënte Python-code schrijven