How to Scrape URLs from a Website Using Python

In this tutorial, we will highlight how you can use Python to scrape URLs from a website. Knowing how to gather data from websites can be a useful skill when performing web analysis or seeking insights from online data.

Python provides powerful libraries like BeautifulSoup and requests that make web scraping more straightforward and efficient. Please follow the steps below:

Step 1: Installing Necessary Python Libraries

Python has two primary libraries used for web scraping – BeautifulSoup and Requests. To install these libraries, we should use pip, Python’s package manager:

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pip install beautifulsoup4 requests

Step 2: Importing Libraries

After successful installation, import these libraries into your Python script as shown below:

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import requests
from bs4 import BeautifulSoup

Step 3: Send an HTTP request to the URL

The first step to scraping a website is to download the page. We can download pages using the Python requests library.

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url = "Web page's url"
request = requests.get(url)

Step 4: Parse the page with BeautifulSoup

A Beautiful Soup constructor parses raw HTML text and breaks it into Python objects. The second argument ‘html.parser’ is the parser library that we want the beautiful soup to use behind the scenes.

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soup = BeautifulSoup(request.text, 'html.parser')

Step 5: Access the URLs found within a page’s

To access the URLs found within a page’s , we should use “a” tag and get the attribute “href”.

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for link in soup.find_all('a'):
  print(link.get('href'))

Here is the full Python code:

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import requests
from bs4 import BeautifulSoup
 
url = "Web Page’s url"
request = requests.get(url)
soup = BeautifulSoup(request.text, 'html.parser')
 
for link in soup.find_all('a'):
  print(link.get('href'))

Conclusion

In conclusion, Python is a great language for web scraping. By learning how to extract URLs and other information, you can start to unravel the rich tapestry of the internet’s data.

Remember that while our example is straightforward, real-world web scraping can face difficulties such as CAPTCHA, IP blocking, and navigating sites filled with JavaScript.