使用BeautifulSoup 4.8.2从网站抓取表格

时间:2020-07-05 19:10:59

标签: python web-scraping beautifulsoup

我正试图从网站上抓取一张桌子,但效果不佳。我正在使用Python 3.7.4和bs4 4.8.2。另外,我不精通HTML,所以请谅解某些术语。

我正在尝试使用“ id ='track_1_box'”来刮擦父类下的表类,可以看到here。我试图提取的信息是字符串“ title ='Canada'”和“ Cole”,但现在我什至无法访问该表。

这是我到目前为止尝试过的。

import requests
import numpy as np
from bs4 import BeautifulSoup
from csv import writer

#%%
url = 'https://www.mkleaderboards.com/mkw/charts/world/nonsc/12'
response = requests.get(url)

soup = BeautifulSoup(response.text, 'html.parser')

table = soup.find("table", class_='table')

但是,“ table”变量返回一个空列表。我也尝试过使用

访问父类
soup.find_all(class_ = 'panel inline_box track_box') 

返回

[<div class="panel inline_box track_box" id="track_1_box">
 </div>, <div class="panel inline_box track_box" id="track_2_box">
 </div>, <div class="panel inline_box track_box" id="track_3_box">
 </div>, <div class="panel inline_box track_box" id="track_4_box">
 </div>]

但不是四个div类的“内部”。

我做错什么了吗?或者网站上有什么阻止我刮擦桌子的东西?

1 个答案:

答案 0 :(得分:0)

数据是通过JavaScript加载的,但是您可以使用requests模块来获取数据:

import json
import requests


url = 'https://www.mkleaderboards.com/mkw/charts/world/nonsc/12'
api_url = 'https://www.mkleaderboards.com/api/charts/mkw_nonsc_world/{num}'

cup_id = int(url.split('/')[-1])

# box 1:
box1 = requests.get(api_url.format(num=cup_id*4+1)).json()
# box 2:
box2 = requests.get(api_url.format(num=cup_id*4+2)).json()
# box 3:
box3 = requests.get(api_url.format(num=cup_id*4+3)).json()
# box 4:
box4 = requests.get(api_url.format(num=cup_id*4+4)).json()

# uncomment this to print data to screen:
# print(json.dumps(box1, indent=4))
# print(json.dumps(box2, indent=4))
# print(json.dumps(box3, indent=4))
# print(json.dumps(box4, indent=4))

# print box1 to screen:
for d in box1['data']:
    print('{:<30} {:<20} {}'.format(d['name'], d['country_name'], d['score_formatted']))

打印:

Cole                           Canada               1:08.774
Kasey                          United States        1:08.881
SwareJonge                     Netherlands          1:09.036
Sosis                          United States        1:09.050
Paul M.                        United States        1:09.066
Sword                          United Kingdom       1:09.118
Gustav                         Sweden               1:09.136
Guy                            United States        1:09.143
Glaceon                        Japan                1:09.157
Liam [MKW]                     United Kingdom       1:09.171