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| import pandas as pd | |
| import requests | |
| import isort | |
| import black | |
| import flair | |
| import time | |
| from bs4 import BeautifulSoup | |
| URL = "https://www.formula1.com/content/fom-website/en/latest/all.xml" | |
| def get_xml(url): | |
| # xpath is only for formula1 | |
| # use urllib.parse to check for formula1.com website or other news | |
| xml = pd.read_xml(url,xpath='channel/item') | |
| def check_updates(every=60): | |
| while True: | |
| time.sleep(every) | |
| latest_xml = get_xml() | |
| if ~previous_xml.equals(latest_xml): | |
| print('New articles found') | |
| new_articles_df = latest_xml[~latest_xml["guid"].isin(previous_xml["guid"])] | |
| for article in new_articles_df.iterrows(): | |
| link = row[1]["guid"] | |
| request = requests.get(link) | |
| soup = BeautifulSoup(request.content, "html.parser") | |
| # class_ below will be different for different websites | |
| s = soup.find("div", class_="col-lg-8 col-xl-7 offset-xl-1 f1-article--content") | |
| lines = s.find_all("p") | |
| text_content = pd.DataFrame(data={"text": []}) | |
| for i, line in enumerate(lines): | |
| df = pd.DataFrame(data={"text": [line.text]}) | |
| text_content = pd.concat([text_content, df], ignore_index=True) | |
| strongs = s.find_all("strong") | |
| strong_content = pd.DataFrame(data={"text": []}) | |
| for i, strong in enumerate(strongs): | |
| if i > 0: | |
| df = pd.DataFrame(data={"text": [strong.text]}) | |
| strong_content = pd.concat([strong_content, df], ignore_index=True) | |
| # df has content | |
| df = text_content[~text_content["text"].isin(strong_content["text"])].reset_index( | |
| drop=True | |
| ) | |
| return df | |
| else: | |
| print('No New article is found') | |