A comprehensive, hands-on tutorial for learning web scraping with Python. This tutorial covers everything from basic HTML parsing to advanced scraping frameworks, with practical exercises and real-world examples.
- Overview
- Prerequisites
- Installation
- Tutorial Modules
- Project Structure
- Getting Started
- Best Practices
- Contributing
- License
This tutorial is designed for students and developers who want to learn web scraping from the ground up. You'll progress through increasingly sophisticated techniques and tools:
- Basics: HTTP requests, HTML parsing with BeautifulSoup4
- Intermediate: CSS selectors, data extraction patterns
- Advanced: Dynamic content with Selenium, handling JavaScript
- Framework: Building scalable scrapers with Scrapy
- Professional: Ethics, robots.txt, rate limiting, and deployment
- Basic Python knowledge (variables, functions, loops, conditionals)
- Understanding of HTML/CSS basics
- Familiarity with command line/terminal
- Python 3.8 or higher installed
- Clone this repository:
git clone https://github.com/Jasonyou1995/web-scraping-tutorial.git
cd web-scraping-tutorial- Create a virtual environment:
python -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activate- Install dependencies:
pip install -r requirements.txtDuration: 1-2 hours | Difficulty: Beginner
Learn the fundamentals of web scraping:
- Understanding HTTP requests and responses
- Making requests with the
requestslibrary - Introduction to HTML structure
- Basic parsing with BeautifulSoup4
- Extracting text, links, and images
📂 Location: modules/01_introduction/
Duration: 2-3 hours | Difficulty: Beginner-Intermediate
Master HTML parsing techniques:
- CSS selectors and navigation
- Finding elements by attributes
- Working with tables and lists
- Data cleaning and transformation
- Handling encoding issues
📂 Location: modules/02_beautifulsoup/
Duration: 3-4 hours | Difficulty: Intermediate
Scrape JavaScript-heavy websites:
- Setting up Selenium WebDriver
- Browser automation basics
- Waiting for dynamic content
- Handling forms and authentication
- Capturing screenshots and debugging
📂 Location: modules/03_selenium/
Duration: 4-5 hours | Difficulty: Intermediate-Advanced
Build production-ready scrapers:
- Scrapy architecture and components
- Creating spiders and items
- Pipelines for data processing
- Middleware and settings
- Crawling multiple pages
- Exporting data to various formats
📂 Location: modules/04_scrapy/
Duration: 1-2 hours | Difficulty: All levels
Professional web scraping:
- Legal and ethical considerations
- Respecting robots.txt
- Rate limiting and politeness
- Error handling and retries
- Logging and monitoring
- Deployment strategies
📂 Location: modules/05_best_practices/
web-scraping-tutorial/
│
├── README.md # This file
├── requirements.txt # Python dependencies
├── .gitignore # Git ignore rules
│
├── modules/ # Tutorial modules
│ ├── 01_introduction/
│ │ ├── README.md # Module overview
│ │ ├── tutorial.md # Step-by-step guide
│ │ ├── examples/ # Code examples
│ │ ├── exercises/ # Practice exercises
│ │ └── solutions/ # Exercise solutions
│ │
│ ├── 02_beautifulsoup/
│ │ ├── README.md
│ │ ├── tutorial.md
│ │ ├── examples/
│ │ ├── exercises/
│ │ └── solutions/
│ │
│ ├── 03_selenium/
│ │ ├── README.md
│ │ ├── tutorial.md
│ │ ├── examples/
│ │ ├── exercises/
│ │ └── solutions/
│ │
│ ├── 04_scrapy/
│ │ ├── README.md
│ │ ├── tutorial.md
│ │ ├── project_template/
│ │ ├── exercises/
│ │ └── solutions/
│ │
│ └── 05_best_practices/
│ ├── README.md
│ ├── tutorial.md
│ ├── examples/
│ └── checklists/
│
├── data/ # Sample data and test pages
│ ├── sample_pages/ # Local HTML files for practice
│ ├── datasets/ # Example datasets
│ └── outputs/ # Scraped data outputs
│
├── utils/ # Utility functions and helpers
│ ├── __init__.py
│ ├── helpers.py # Common helper functions
│ ├── validators.py # URL and data validators
│ └── config.py # Configuration settings
│
└── resources/ # Additional learning resources
├── cheatsheets/ # Quick reference guides
├── troubleshooting.md # Common issues and solutions
└── references.md # External resources and links
- Start with Module 1: Begin with the introduction module to understand the basics
- Follow the tutorials: Each module has a
tutorial.mdwith step-by-step instructions - Run the examples: Execute the example scripts to see concepts in action
- Complete exercises: Practice with hands-on exercises in each module
- Check solutions: Compare your work with provided solutions
- Build projects: Apply your knowledge to real-world scraping projects
# Your first web scraper!
import requests
from bs4 import BeautifulSoup
url = "https://example.com"
response = requests.get(url)
soup = BeautifulSoup(response.content, 'html.parser')
# Extract all links
links = soup.find_all('a')
for link in links:
print(link.get('href'))- Always respect robots.txt: Check if scraping is allowed
- Rate limit your requests: Don't overwhelm servers
- Handle errors gracefully: Implement proper error handling
- Cache responses: Avoid redundant requests during development
- Use appropriate headers: Identify your scraper
- Be ethical: Respect website terms of service and privacy
Contributions are welcome! Please feel free to submit a Pull Request. For major changes:
- Fork the repository
- Create your feature branch (
git checkout -b feature/AmazingFeature) - Commit your changes (
git commit -m 'Add some AmazingFeature') - Push to the branch (
git push origin feature/AmazingFeature) - Open a Pull Request
This project is licensed under the Apache License 2.0 - see the LICENSE file for details.
- Python community for amazing libraries
- Contributors and students who helped improve this tutorial
- Open source projects that make web scraping accessible
If you have questions or run into issues:
- Check the troubleshooting guide
- Open an issue on GitHub
- Review the FAQ section
Happy Scraping! 🎉
Remember: With great scraping power comes great responsibility. Always scrape ethically and legally.