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    Web scraping is the process of extracting data from websites. Python, with its powerful libraries like requests and Beautiful Soup, makes web scraping straightforward and efficient. Below is a step-by-step guide to building a simple web scraper using these libraries.

    Step 1: Install Required Libraries

    First, you need to install the requests and BeautifulSoup libraries. You can do this using pip:

    pip install requests beautifulsoup4

    Step 2: Fetch HTML Content

    Use the requests library to fetch the HTML content of the webpage you want to scrape. For example, let's scrape job listings from a fake job site:

    import requests

    URL = "https://realpython.github.io/fake-jobs/"
    page = requests.get(URL)

    print(page.text) # Print the HTML content of the page

    Step 3: Parse HTML with Beautiful Soup

    Next, use BeautifulSoup to parse the HTML content and extract the data you need:

    from bs4 import BeautifulSoup

    soup = BeautifulSoup(page.content, "html.parser")

    # Find the container that holds the job listings
    results = soup.find(id="ResultsContainer")

    # Print the prettified HTML of the results
    print(results.prettify())

    Step 4: Extract Specific Data

    Now, extract specific data such as job titles, company names, and locations:

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    Includes AI-generated content
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    Web Scraping with Python: A Complete Step-by-Step Guide + Code
    Medium
    How to scrape HTML code in Python?
    In the next section, you’ll start grabbing all the HTML code from a single web page. One useful package for web scraping that you can find in Python’s standard library is urllib, which contains tools for working with URLs. In particular, the urllib.request module contains a function called urlopen() that you can use to open a URL within a program.
    realpython.com
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