2A.eco - Web-Scraping - pokemon#
Links: notebook
, html, python
, slides, GitHub
Il faut récupérer automatiquement des images de pokémon depuis le site pokemondb.net.
Pour cet exercice, nous vous demandons d’obtenir 1) les informations personnelles des 721 pokemons sur le site internet pokemondb.net. Les informations que nous aimerions obtenir au final pour les pokemons sont celles contenues dans 4 tableaux :
Pokédex data
Training
Breeding
Base stats
Pour exemple : Pokemon Database.
Nous aimerions que vous récupériez également les images de chacun des pokémons et que vous les enregistriez dans un dossier (indice : utilisez les modules request et shutil) pour cette question ci, il faut que vous cherchiez de vous même certains éléments, tout n’est pas présent dans le TD.
Correction#
import urllib
import bs4
import collections
import pandas as pd
# pour le site que nous utilisons, le user agent de python 3 n'est pas bien passé :
# on le change donc pour celui de Mozilla
req = urllib.request.Request('http://pokemondb.net/pokedex/national',
headers={'User-Agent': 'Mozilla/5.0'})
html = urllib.request.urlopen(req).read()
page = bs4.BeautifulSoup(html, "lxml")
# récupérer la liste des noms de pokémon
liste_pokemon =[]
for pokemon in page.findAll('span', {'class': 'infocard-lg-img'}) :
pokemon = pokemon.find('a').get('href').replace("/pokedex/",'')
liste_pokemon.append(pokemon)
Fonction pour obtenir les caractéristiques de pokemons#
def get_page(pokemon_name):
url_pokemon = 'http://pokemondb.net/pokedex/'+ pokemon_name
req = urllib.request.Request(url_pokemon, headers = {'User-Agent' : 'Mozilla/5.0'})
html = urllib.request.urlopen(req).read()
return bs4.BeautifulSoup(html, "lxml")
def get_cara_pokemon(pokemon_name):
page = get_page(pokemon_name)
data = collections.defaultdict()
# table Pokédex data, Training, Breeding, base Stats
for table in page.findAll('table', { 'class' : "vitals-table"})[0:4] :
table_body = table.find('tbody')
for rows in table_body.findChildren(['tr']) :
if len(rows) > 1 : # attention aux tr qui ne contiennent rien
column = rows.findChild('th').getText()
cells = rows.findChild('td').getText()
cells = cells.replace('\t','').replace('\n',' ')
data[column] = cells
data['name'] = pokemon_name
return dict(data)
items = []
for e, pokemon in enumerate(liste_pokemon) :
print(e, pokemon)
item = get_cara_pokemon(pokemon)
items.append(item)
if e > 20:
break
df = pd.DataFrame(items)
df.head()
0 bulbasaur
1 ivysaur
2 venusaur
3 charmander
4 charmeleon
5 charizard
6 squirtle
7 wartortle
8 blastoise
9 caterpie
10 metapod
11 butterfree
12 weedle
13 kakuna
14 beedrill
15 pidgey
16 pidgeotto
17 pidgeot
18 rattata
19 raticate
20 spearow
21 fearow
National № | name | Type | Species | Height | Weight | Abilities | Local № | EV yield | Catch rate | ... | Growth Rate | Egg Groups | Gender | Egg cycles | HP | Attack | Defense | Sp. Atk | Sp. Def | Speed | |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
0 | 001 | bulbasaur | Grass Poison | Seed Pokémon | 0.7 m (2′04″) | 6.9 kg (15.2 lbs) | 1. OvergrowChlorophyll (hidden ability) | 001 (Red/Blue/Yellow)226 (Gold/Silver/Crystal)... | 1 Special Attack | 45 (5.9% with PokéBall, full HP) | ... | Medium Slow | Grass, Monster | 87.5% male, 12.5% female | 20 (4,884–5,140 steps) | 45 | 49 | 49 | 65 | 65 | 45 |
1 | 002 | ivysaur | Grass Poison | Seed Pokémon | 1.0 m (3′03″) | 13.0 kg (28.7 lbs) | 1. OvergrowChlorophyll (hidden ability) | 002 (Red/Blue/Yellow)227 (Gold/Silver/Crystal)... | 1 Special Attack, 1 Special Defense | 45 (5.9% with PokéBall, full HP) | ... | Medium Slow | Grass, Monster | 87.5% male, 12.5% female | 20 (4,884–5,140 steps) | 60 | 62 | 63 | 80 | 80 | 60 |
2 | 003 | venusaur | Grass Poison | Seed Pokémon | 2.0 m (6′07″) | 100.0 kg (220.5 lbs) | 1. OvergrowChlorophyll (hidden ability) | 003 (Red/Blue/Yellow)228 (Gold/Silver/Crystal)... | 2 Special Attack, 1 Special Defense | 45 (5.9% with PokéBall, full HP) | ... | Medium Slow | Grass, Monster | 87.5% male, 12.5% female | 20 (4,884–5,140 steps) | 80 | 82 | 83 | 100 | 100 | 80 |
3 | 004 | charmander | Fire | Lizard Pokémon | 0.6 m (2′00″) | 8.5 kg (18.7 lbs) | 1. BlazeSolar Power (hidden ability) | 004 (Red/Blue/Yellow)229 (Gold/Silver/Crystal)... | 1 Speed | 45 (5.9% with PokéBall, full HP) | ... | Medium Slow | Dragon, Monster | 87.5% male, 12.5% female | 20 (4,884–5,140 steps) | 39 | 52 | 43 | 60 | 50 | 65 |
4 | 005 | charmeleon | Fire | Flame Pokémon | 1.1 m (3′07″) | 19.0 kg (41.9 lbs) | 1. BlazeSolar Power (hidden ability) | 005 (Red/Blue/Yellow)230 (Gold/Silver/Crystal)... | 1 Special Attack, 1 Speed | 45 (5.9% with PokéBall, full HP) | ... | Medium Slow | Dragon, Monster | 87.5% male, 12.5% female | 20 (4,884–5,140 steps) | 58 | 64 | 58 | 80 | 65 | 80 |
5 rows × 22 columns
les images de pokemon#
import shutil
import requests
for e, pokemon in enumerate(liste_pokemon) :
print(e,pokemon)
url = "https://img.pokemondb.net/artwork/{}.jpg".format(pokemon)
response = requests.get(url, stream=True)
# avec l'option stream, on ne télécharge pas l'objet de l'url
with open('{}.jpg'.format(pokemon), 'wb') as out_file:
shutil.copyfileobj(response.raw, out_file)
if e > 20:
break
0 bulbasaur
1 ivysaur
2 venusaur
3 charmander
4 charmeleon
5 charizard
6 squirtle
7 wartortle
8 blastoise
9 caterpie
10 metapod
11 butterfree
12 weedle
13 kakuna
14 beedrill
15 pidgey
16 pidgeotto
17 pidgeot
18 rattata
19 raticate
20 spearow
21 fearow
import os
names = [name for name in os.listdir('.') if '.jpg' in name]
names[:3]
['beedrill.jpg', 'blastoise.jpg', 'bulbasaur.jpg']
import matplotlib.pyplot as plt
import skimage.io as imio
fig, ax = plt.subplots(1, 3, figsize=(12,4))
for i, name in enumerate(names[:ax.shape[0]]):
img = imio.imread(name)
ax[i].imshow(img)
ax[i].get_xaxis().set_visible(False)
ax[i].get_yaxis().set_visible(False)