如何在一个脚本中从两个网站抓取网页？

Question

我目前正在研究一个模型，需要收集的信息不仅仅是关于游戏结果 （此链接https://www.hltv.org/stats/teams/matches/4991/fnatic?startDate=2019-01-01&endDate=2019-12-31） 但是我也希望脚本在HTML源代码中打开另一个链接。。该链接在源代码中可用，它将带我进入一个页面，解释每个匹配的详细结果， （就像who want what round，https://www.hltv.org/stats/matches/mapstatsid/89458/cr4zy-vs-fnatic?startDate=2019-01-01&endDate=2019-12-31&contextIds=4991&contextTypes=team）一样，主要目标是我想知道谁赢得了比赛（从第一个链接开始）以及谁赢得了每场比赛的第一轮（在第二个链接）。这可能吗？这是我现在的剧本

import requests
r = requests.get('https://www.hltv.org/stats/teams/maps/6665/Astralis')
from bs4 import BeautifulSoup
soup = BeautifulSoup(r.text, 'html.parser')
results = soup.find_all('tr')
AstralisResults = []

for result in results[1:]:
    date = result.contents[1].text
    event = result.contents[3].text
    opponent = result.contents[7].text
    Map = result.contents[9].text
    Score = "'" + result.contents[11].text
    WinorLoss = result.contents[13].text
    AstralisResults.append((date,event,opponent,Map,Score,WinorLoss))

import pandas as pd
df5 = pd.DataFrame(AstralisResults,columns=['date','event','opponent','Map','Score','WinorLoss'])
df5.to_csv('AstralisResults.csv',index=False,encoding='utf-8')

所以我想了解以下信息：

Date | Opponent | Map | Score | Result | Round1Result |

Answer 1

看起来如果你刮得太快网站就会阻塞，所以不得不在一个时间延迟。有很多方法可以提高代码的效率，但总的来说，我认为它满足了您的要求：

from bs4 import BeautifulSoup
import requests
import pandas as pd
import time


headers={'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/76.0.3809.100 Safari/537.36'}

r = requests.get('https://www.hltv.org/stats/teams/matches/4991/fnatic?startDate=2019-01-01&endDate=2019-12-31' , headers=headers)
print (r)


soup = BeautifulSoup(r.text, 'html.parser')
results = soup.find_all('tr')
df5 = pd.DataFrame()

cnt=1
for result in results[1:]:
    print ('%s of %s' %(cnt, len(results)-1))
    date = result.contents[1].text
    event = result.contents[3].text
    opponent = result.contents[7].text
    Map = result.contents[9].text
    Score = "'" + result.contents[11].text
    WinorLoss = result.contents[13].text

    round_results = result.find('td', {'class':'time'})
    link = round_results.find('a')['href']


    r2 = requests.get('https://www.hltv.org' + link ,headers=headers)
    soup2 = BeautifulSoup(r2.text, 'html.parser')
    round_history = soup2.find('div', {'class':'standard-box round-history-con'})

    teams = round_history.find_all('img', {'class':'round-history-team'})
    teams_list = [ x['title'] for x in teams ]



    rounds_winners = {}
    n = 1
    row = round_history.find('div',{'class':'round-history-team-row'})
    for each in row.find_all('img',{'class':'round-history-outcome'}):
        if 'emptyHistory' in each['src']:
            winner = teams_list[1]
            loser = teams_list[0]
        else:
            winner = teams_list[0]
            loser = teams_list[1]

        rounds_winners['Round%02dResult' %n] = winner
        n+=1


    round_row_df = pd.DataFrame.from_dict(rounds_winners,orient='index').T

    temp_df = pd.DataFrame([[date,event,opponent,Map,Score,WinorLoss]],columns=['date','event','opponent','Map','Score','WinorLoss'])
    temp_df = temp_df.merge(round_row_df, left_index=True, right_index=True)

    df5 = df5.append(temp_df, sort=True).reset_index(drop=True)
    time.sleep(.5)
    cnt+=1

df5 = df5[['date','event','opponent','Map','Score','WinorLoss', 'Round01Result']]
df5 = df5.rename(columns={'date':'Date',
                          'event':'Event',
                          'WinorLoss':'Result',
                          'Round01Result':'Round1Result'})

df5.to_csv('AstralisResults.csv',index=False,encoding='utf-8')

输出：

print (df5.head(10).to_string())
       Date                                 Event     opponent       Map     Score Result Round1Result
0  20/07/19  Europe Minor - StarLadder Major 2019        CR4ZY     Dust2  '13 - 16      L       fnatic
1  20/07/19  Europe Minor - StarLadder Major 2019        CR4ZY     Train  '13 - 16      L       fnatic
2  19/07/19  Europe Minor - StarLadder Major 2019  mousesports   Inferno   '8 - 16      L  mousesports
3  19/07/19  Europe Minor - StarLadder Major 2019  mousesports     Dust2  '13 - 16      L       fnatic
4  17/07/19  Europe Minor - StarLadder Major 2019        North     Train   '16 - 9      W       fnatic
5  17/07/19  Europe Minor - StarLadder Major 2019        North      Nuke   '16 - 2      W       fnatic
6  17/07/19  Europe Minor - StarLadder Major 2019      Ancient    Mirage   '16 - 7      W       fnatic
7  04/07/19                  ESL One Cologne 2019     Vitality  Overpass  '17 - 19      L     Vitality
8  04/07/19                  ESL One Cologne 2019     Vitality    Mirage  '16 - 19      L       fnatic
9  03/07/19                  ESL One Cologne 2019     Astralis      Nuke   '6 - 16      L       fnatic