Python BeautifulSoup-使用来自给定URL的iframe抓取多个网页

我们有以下代码（感谢Cody和Alex Tereshenkov）：

import pandas as pd
import requests
from bs4 import BeautifulSoup

pd.set_option('display.width', 1000)
pd.set_option('display.max_columns', 50)

url = "https://www.aliexpress.com/store/feedback-score/1665279.html"
s = requests.Session()
r = s.get(url)

soup = BeautifulSoup(r.content, "html.parser")
iframe_src = soup.select_one("#detail-displayer").attrs["src"]

r = s.get(f"https:{iframe_src}")

soup = BeautifulSoup(r.content, "html.parser")
rows = []
for row in soup.select(".history-tb tr"):
    #print("\t".join([e.text for e in row.select("th, td")]))
    rows.append([e.text for e in row.select("th, td")])
#print

df = pd.DataFrame.from_records(
    rows,
    columns=['Feedback', '1 Month', '3 Months', '6 Months'],
)

# remove first row with column names
df = df.iloc[1:]
df['Shop'] = url.split('/')[-1].split('.')[0]

pivot = df.pivot(index='Shop', columns='Feedback')
pivot.columns = [' '.join(col).strip() for col in pivot.columns.values]

column_mapping = dict(
    zip(pivot.columns.tolist(), [col[:12] for col in pivot.columns.tolist()]))
# column_mapping
# {'1 Month Negative (1-2 Stars)': '1 Month Nega',
#  '1 Month Neutral (3 Stars)': '1 Month Neut',
#  '1 Month Positive (4-5 Stars)': '1 Month Posi',
#  '1 Month Positive feedback rate': '1 Month Posi',
#  '3 Months Negative (1-2 Stars)': '3 Months Neg',
#  '3 Months Neutral (3 Stars)': '3 Months Neu',
#  '3 Months Positive (4-5 Stars)': '3 Months Pos',
#  '3 Months Positive feedback rate': '3 Months Pos',
#  '6 Months Negative (1-2 Stars)': '6 Months Neg',
#  '6 Months Neutral (3 Stars)': '6 Months Neu',
#  '6 Months Positive (4-5 Stars)': '6 Months Pos',
#  '6 Months Positive feedback rate': '6 Months Pos'}
pivot.columns = [column_mapping[col] for col in pivot.columns]

pivot.to_excel('Report.xlsx')

该代码提取给定URL（位于iframe中）的“反馈历史记录”表，并将所有表数据转换为1行，就像这样：

另一方面，我们在同一个项目文件夹（“ urls.txt”）中有50个URL，如下所示：

https://www.aliexpress.com/store/feedback-score/4385007.html
https://www.aliexpress.com/store/feedback-score/1473089.html
https://www.aliexpress.com/store/feedback-score/3085095.html
https://www.aliexpress.com/store/feedback-score/2793002.html
https://www.aliexpress.com/store/feedback-score/4656043.html
https://www.aliexpress.com/store/feedback-score/4564021.html

我们只需要为文件中的所有URL提取相同的数据。

我们该怎么做呢？