Web scraping is the process of automatically extracting data from websites, and Python has been the go-to language for data extraction for years, boasting a large community of developers as well as a wide range of web scraping tools to help scrapers extract almost any data from any website.

Today we will explore some of the best libraries and frameworks available for web scraping in Python and provide code examples of how to use them in different web scraping scenarios.

In this Python web scraping tutorial, you’ll learn how to:

  1. Preparing Python coding environment for web scraping
  2. Web scraping in Python using HTTP clients
  3. Parse HTML content with libraries such as BeautifulSoup, LXML, and PyQuery
  4. Handle dynamic websites using Selenium and Playwright
  5. Utilize advanced web scraping techniques with Scrapy
  6. Export the scraped data to CSV and Excel
  7. Deploy Python scrapers on the cloud
  8. Find additional learning resources for web scraping with Python
  9. Answer frequently asked questions about web scraping

But before we start with the tutorial, let's take a quick peek at this summary table. It gives an overview of all the Python web scraping libraries we'll cover in this article. This table will help you navigate the content and provide you with an easy way to remember the topics covered.

📚 Library 💡Features ⚡️Performance 👨‍💻 User-friendliness 👥 Community ⭐️ GitHub Stars 📥 Installation Command
https://apify.notion.site/Python-web-scraping-tutorial-Revamp-9e673b87097e4ab78497f0a60cb86a25 • HTTP(S) Proxy Support
• Connection Timeouts
• Chunked Requests Moderate Beginner friendly Well-established, strong community 51.3k pip install requests
https://apify.notion.site/Python-web-scraping-tutorial-Revamp-9e673b87097e4ab78497f0a60cb86a25 • Requests-compatible API
• Integrated command-line client
• Supports synchronous and asynchronous requests
Fast Intermediate New, growing community 6.8k pip install httpx
https://apify.notion.site/Python-web-scraping-tutorial-Revamp-9e673b87097e4ab78497f0a60cb86a25 • Intuitive syntax
• Efficient DOM parsing, manipulation, and rendering
• Parse nearly any HTML or XML document
Moderate/Limited scalability Beginner friendly Well-established, strong community n/a pip install beautifulsoup4
https://apify.notion.site/Python-web-scraping-tutorial-Revamp-9e673b87097e4ab78497f0a60cb86a25 • Fast XML/HTML processing
• Full feature set for XML, XPath, XSL
• Compatible with ElementTree API
Fast Intermediate Well-established, medium-sized community 2.6k pip install lxml
https://apify.notion.site/Python-web-scraping-tutorial-Revamp-9e673b87097e4ab78497f0a60cb86a25 • jQuery-like syntax for DOM manipulation
• Parses HTML documents
Moderate **Beginner-friendly (for devs with a jQuery background) Small, niche community 2.3k pip install pyquery
https://apify.notion.site/Python-web-scraping-tutorial-Revamp-9e673b87097e4ab78497f0a60cb86a25 • Automates web browsers
• Supports multiple browsers and OS
• Handles JavaScript-generated content for scraping dynamic pages
Slow/Resource-intensive Intermediate/Advanced Well-established, strong community 29.2k pip install selenium
https://apify.notion.site/Python-web-scraping-tutorial-Revamp-9e673b87097e4ab78497f0a60cb86a25 • Supports multiple browsers
• Handles JavaScript-generated content for scraping dynamic pages
• Synchronous and asynchronous APIs
Slow/Resource-intensive Intermediate/Advanced Fast-growing, strong community 61.3k pip install playwright
https://apify.notion.site/Python-web-scraping-tutorial-Revamp-9e673b87097e4ab78497f0a60cb86a25 • Fast data extraction and website crawling
• Asynchronous requests
• Scraping, processing, exporting data tools
Very Fast/ Highly scalable Advanced Well-established, strong community 50.7k pip install scrapy

Preparing Python coding environment for web scraping

Before diving into web scraping with Python, we need to make sure our development environment is ready. To set up your machine for web scraping, you need to install Python, choose an Integrated Development Environment (IDE), and understand the basics of how to install the Python libraries necessary for efficiently extracting data from the web.