55 lines
1.7 KiB
Python
55 lines
1.7 KiB
Python
import requests
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from bs4 import BeautifulSoup
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from urllib.parse import urlparse, urlunparse
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import pandas as pd
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headers = {'User-Agent': 'myprogram/1.0'}
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def scrape_headings(url):
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try:
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# Check if the URL has a scheme (http/https), and add one if missing
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parsed_url = urlparse(url)
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if not parsed_url.scheme:
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url = urlunparse(('http',) + parsed_url[1:])
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# Send an HTTP GET request to the specified URL
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response = requests.get(url, headers=headers)
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# Check if the request was successful
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if response.status_code == 200:
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# Parse the HTML content using BeautifulSoup
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soup = BeautifulSoup(response.text, 'html.parser')
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# Find all the heading elements (h1, h2, h3, etc.)
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headings = soup.find_all(['h1', 'h2', 'h3', 'h4', 'h5', 'h6'])
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# Extract and put to csv the result of headings
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heading_list = [heading.text for heading in headings]
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df = pd.DataFrame(heading_list)
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df.to_csv('output.csv')
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else:
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print(f"Failed to retrieve content from {url}. Status code: {response.status_code}")
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except Exception as e:
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print(f"An error occurred: {str(e)}")
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# To check if to do another search for URL
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def main_start():
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if __name__ == "__main__":
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url = input("Enter the URL: ")
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scrape_headings(url)
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# df = pd.DataFrame(scrape_headings(url))
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search_again = input("Do you want to search again? y/n:").lower()
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if search_again == 'y':
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# df.to_csv('output.csv')
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main_start()
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else:
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# df.to_csv('output.csv')
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exit()
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main_start()
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