🕷️ How to Build a Web Scraper Using Python (Step-by-Step)

Have you ever wanted to collect data from a website automatically — like prices, headlines, or product details? With Python, that’s completely possible using web scraping.

In this blog, you’ll learn how to build your own web scraper from scratch using Python libraries like requests and BeautifulSoup.

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🚀 What is Web Scraping?

Web scraping is a technique used to extract data from websites. It’s widely used in:

• Price comparison tools

• Data-driven research

• News aggregators

• Job listings crawlers

• Real estate platforms

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🛠️ Tools You’ll Need

Make sure you have Python installed, then install the following libraries:

bashCopyEditpip install requests beautifulsoup4

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📄 What We'll Scrape

For this tutorial, we’ll scrape article titles from the Python.org homepage.

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🔟 Step-by-Step Guide

1. 📦 Import Required Libraries

pythonCopyEditimport requests
from bs4 import BeautifulSoup

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2. 🌐 Send an HTTP Request

We'll fetch the content of the page using requests.

pythonCopyEditURL = "https://www.python.org/"
response = requests.get(URL)

# Check if the request was successful
print("Status Code:", response.status_code)

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3. 🍜 Parse the HTML Content

We'll use BeautifulSoup to parse and navigate the HTML.

pythonCopyEditsoup = BeautifulSoup(response.text, 'html.parser')

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4. 🔍 Locate the Data

Inspect the website (right-click → Inspect Element in your browser) to find where the data is located. On python.org, upcoming events are under a <ul> with class list-recent-events.

pythonCopyEditevents = soup.find('ul', class_='list-recent-posts')
items = events.find_all('li')

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5. 📝 Extract and Print the Data

Let’s print the headlines from each post:

pythonCopyEditfor item in items:
    title = item.find('a').get_text()
    link = item.find('a')['href']
    print(f"Title: {title}")
    print(f"Link: {link}\n")

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🧾 Full Script: Web Scraper for Python.org

pythonCopyEditimport requests
from bs4 import BeautifulSoup

URL = "https://www.python.org/"
response = requests.get(URL)
soup = BeautifulSoup(response.text, 'html.parser')

events = soup.find('ul', class_='list-recent-posts')
items = events.find_all('li')

for item in items:
    title = item.find('a').get_text()
    link = item.find('a')['href']
    print(f"Title: {title}")
    print(f"Link: {link}\n")

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📌 Sample Output

yamlCopyEditTitle: Python Software Foundation Fellow Members for Q2 2024
Link: https://www.python.org/psf/fellows/q2-2024/

Title: Python 3.12.2 and 3.11.8 are now available
Link: https://www.python.org/downloads/release/python-3122/

...

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✅ Tips for Better Scraping

• Use headers to avoid getting blocked:

pythonCopyEditheaders = {'User-Agent': 'Mozilla/5.0'}
response = requests.get(URL, headers=headers)

• Respect robots.txt: Always check if a site allows scraping: https://example.com/robots.txt

• Add delays: Don’t overload websites. Use time.sleep() between requests.

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🧠 What’s Next?

• Scrape multiple pages (pagination)

• Save data to CSV or Excel

• Use Selenium for dynamic content (JavaScript-loaded)

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💬 Final Thoughts

Web scraping is one of the most useful and practical Python skills. With just a few lines of code, you can automate data collection for your next project or analysis.

Remember to scrape ethically and legally — always follow a website’s terms of service.