Web scraping 从Yahoo finance中获取股票代码的Python代码

我有一份超过1000家公司的名单，可以用来投资。我需要所有这些公司的股票代码id。当我试图剥离汤的输出时，当我试图循环遍历所有公司名称时，我会发现困难

请参见网站示例：

https://finance.yahoo.com/lookup?s=asml

。其想法是替换asml并将其放入

'https://finance.yahoo.com/lookup?s=“+公司

，这样我可以遍历所有公司

companies=df    
        Company name
    0   Abbott Laboratories
    1   ABBVIE
    2   Abercrombie
    3   Abiomed
    4   Accenture Plc

这就是我现在拥有的代码，其中条形代码不起作用，而所有公司的循环也不起作用

#Create a function to scrape the data
def scrape_stock_symbols():
  Companies=df
  url= 'https://finance.yahoo.com/lookup?s='+ Companies
  page= requests.get(url)

  soup = BeautifulSoup(page.text, "html.parser")
  Company_Symbol=Soup.find_all('td',attrs ={'class':'data-col0 Ta(start) Pstart(6px) Pend(15px)'})

  for i in company_symbol:
       try:
       row = i.find_all('td')
       company_symbol.append(row[0].text.strip())
    
     except Exception: 
      if company not in company_symbol:
        next(Company)

  return (company_symbol)

#Loop through every company in companies to get all of the tickers from the website
for Company in companies:
  try:
    (temp_company_symbol) = scrape_stock_symbols(company)

  except Exception: 
    if company not in companies:
        next(Company)

另一个困难是，从yahoo finance中查找的符号将检索许多公司的名称。 之后我必须清除数据。我想将AMS交易所设置为标准，因此，如果一家公司在多个交易所上市，我只对AMS股票代码感兴趣。最终目标是创建一个新的数据帧：

    Comapny name           Company_symbol
0   Abbott Laboratories    ABT
1   ABBVIE                 ABBV  
2   Abercrombie            ANF

---

这里有一个解决方案，不需要任何刮擦。它使用一个名为（免责声明：我是作者）的包，该包利用一个API端点为用户的查询返回符号。您可以这样做：

import pandas as pd
import yahooquery as yq

def get_symbol(query, preferred_exchange='AMS'):
    try:
        data = yq.search(query)
    except ValueError: # Will catch JSONDecodeError
        print(query)
    else:
        quotes = data['quotes']
        if len(quotes) == 0:
            return 'No Symbol Found'

        symbol = quotes[0]['symbol']
        for quote in quotes:
            if quote['exchange'] == preferred_exchange:
                symbol = quote['symbol']
                break
        return symbol

companies = ['Abbott Laboratories', 'ABBVIE', 'Abercrombie', 'Abiomed', 'Accenture Plc']
df = pd.DataFrame({'Company name': companies})
df['Company symbol'] = df.apply(lambda x: get_symbol(x['Company name']), axis=1)

          Company name Company symbol
0  Abbott Laboratories            ABT
1               ABBVIE           ABBV
2          Abercrombie            ANF
3              Abiomed           ABMD
4        Accenture Plc            ACN