我遇到了一個小問題，希望您能提供幫助。我想通過從網頁的兩個部分抓取來創建一個 df。我似乎被困在第二部分。我的要求是獲得每個馬名和相關賠率的 df。例如。馬賠率 name1 奇數 1 name2 奇數2
我在腳本中使用了一個示例頁面，但對于任何一個頁面都是相同的：基本網址https://www.racingtv.com/racecards/tomorrow ：然后選擇任何時間以獲取另一個頁面，其中包含馬名和賠率詳細資訊等等。
import requests
import pandas as pd
from bs4 import BeautifulSoup
def main():
# base url is https://www.racingtv.com/racecards/tomorrow
# select any time to get the horse name and odds details etc.
url = 'https://www.racingtv.com/racecards/catterick-bridge/372180-watch-racing-tv-now-novices-hurdle-gbb-race?'
res = requests.get(url)
soup = BeautifulSoup(res.content, "html.parser")
strike = soup.select('div', class_='data-strike-out-group')
# this bit seems to be working
for data in soup.find_all('div',
class_='racecard__runner__column racecard__runner__name'):
for a in data.find_all('a'):
print(a.text)
# this bit sort of works but it seems to repeat the first three items of data
for odds in soup.find_all('div',
class_='racecard__runner__column racecard__runner__column--price'):
for odd1 in odds.find_all('ruk-odd'):
print(odd1.text)
# I tried this to work out how to stop getting the three duplicates but it does not work
for odds in strike.select('div',
class_='racecard__runner__column racecard__runner__column--price'):
for odd1 in odds.find_all('ruk-odd'):
print(odd1.text)
return
if __name__ == '__main__':
main()
uj5u.com熱心網友回復：
class_='data-strike-out-group'
這不是一個類，請檢查原始 html。這是 div 的一個屬性……很奇怪
很高興你發布了這個，最終可能會將此站點用于個人專案。認為您會對這段代碼感興趣：
import requests
from bs4 import BeautifulSoup
import pandas as pd
from datetime import datetime
headers = {
'accept':'*/*',
'user-agent':'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/96.0.4664.110 Safari/537.36',
}
url = 'https://www.racingtv.com/racecards/catterick-bridge/372180-watch-racing-tv-now-novices-hurdle-gbb-race?'
resp = requests.get(url,headers=headers)
print(resp)
soup = BeautifulSoup(resp.text,'html.parser')
table = soup.find('div',{'class':'page__content__section racecard'})
race_id = url.split('/')[-1].split('-')[0]
race_name = soup.find('div',class_='race__name').text.strip()
race_date = soup.find('div',class_='race__date').text.strip()
clean_date = datetime.strptime(race_date,'%d %b %Y').strftime('%Y%m%d')
race_info1 = soup.find_all('div',class_='race__subtitle')[0].text.strip()
race_info2 = soup.find_all('div',class_='race__subtitle')[1].text.strip()
final = []
for row in table.find_all('div',class_='racecard__runner--content'):
try:
num = row.find('div',class_='racecard__runner__cloth-number').text.strip()
last_days_ugly = row.find('div',class_='racecard__runner__name').find('a').find('sup').text
horse_name = row.find('div',class_='racecard__runner__name').find('a').text.strip().replace(last_days_ugly,'')
horse_link = 'http://www.racingtv.com' row.find('div',class_='racecard__runner__name').find('a')['href']
last_race_days = last_days_ugly.strip().replace('(','').replace(')','')
for people in row.find_all('div',class_='racecard__runner__person'):
if 'J:' in people.getText():
jockey = people.find('a').text.strip()
jockey_link = 'http://www.racingtv.com' people.find('a')['href']
if 'T:' in people.getText():
trainer = people.find('a').text.strip()
trainer_link = 'http://www.racingtv.com' people.find('a')['href']
form = row.find('div',class_='racecard__runner__column--form_lr').find_all('div')[0].text.strip()
equip = row.find('div',class_='racecard__runner__column--form_lr').find_all('div')[1].text.strip()
weight = row.find('div',class_='racecard__runner__column--weight_age').find_all('div')[0].text.strip()
age = row.find('div',class_='racecard__runner__column--weight_age').find_all('div')[1].text.strip()
o_r = row.find('div',class_='racecard__runner__column--or').text.strip()
odds = row.find('div',class_='racecard__runner__column--price').getText()
odds_dec = row.find('div',class_='racecard__runner__column--price').find('ruk-odd')['data-js-odds-decimal']
odds_data = row.find('div',class_='racecard__runner__column--price').find('ruk-odd')['data-js-odd-alternatives']
except AttributeError: #skip blank starting gates
continue
item = {
'race_url' : url,
'race_id': race_id,
'race_name':race_name,
'race_date':clean_date,
'race_info1':race_info1,
'race_info2':race_info2,
'num': num,
'horse_name':horse_name,
'horse_link':horse_link,
'last_race_days':last_race_days,
'jockey':jockey,
'jockey_link':jockey_link,
'trainer':trainer,
'trainer_link':trainer_link,
'form':form,
'equip':equip,
'weight':weight,
'age':age,
'o_r':o_r,
'odds':odds,
'odds_dec':odds_dec,
'odds_data':odds_data
}
final.append(item)
df = pd.DataFrame(final)
df.to_csv('racingtv.csv',index=False)
print('Saved to racingtv.csv')
uj5u.com熱心網友回復：
繼 bushcat69 提供的腳本和我隨后的問題“如何將比賽時間輸入 df”之后，我拼湊了一些代碼（從其他站點剪切和粘貼）。我想你可能會感興趣。它可能不優雅，但似乎有效。這部分：
race_data.extend(get_racecards_data(url_race, date, racetime
用于將 url 等傳遞給 bushcat69 腳本。再次感謝。
def get_meetings():
global date
global date_ext
odds_date = date_ext
url = f'https://www.racingtv.com/racecards/{date_ext}'
try:
res = requests.get(url, headers = headers)
except:
print('Date or Connection error occured! \nTry again!!')
return
soup = BeautifulSoup(res.text, 'html.parser')
meetings = soup.select('.race-selector__times__race')
course_num = len(meetings)
meetings1 = [a['href'] for a in soup.select('.race-selector__times__race')]
course_num = len(meetings1)
cnt01 = 0
if course_num == 0:
print('Provide a upcoming valid date')
return
for track in meetings1[:course_num]:
cnt01 = cnt01 1
trackref = track.split("/")[2]
print(cnt01, ": ", trackref)
need = input(f'{course_num} courses found \nHow many courses to scrape? Press \'a\' for all :\n')
if need == 'a':
n = course_num
else:
try:
n = int(need)
except:
print('Invalid input !')
return
cnt01 = 0
race_data = []
for mtm in meetings[:course_num]:
cnt01 = cnt01 1
racetime = mtm.text
href = mtm.attrs
htxt = Text(href)
url_race = htxt.partition("/")[2]
url_race = "/" url_race.rpartition("'")[0]
print(cnt01, racetime, url_race)
time.sleep(1)
race_data.extend(get_racecards_data(url_race, date, racetime))
print(f"Meeting {url_race.split('/')[2]} scraping completed")
if cnt01 == n:
break
df_race = pd.DataFrame(race_data)
df = df_race
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