7-Day Python Data Scraping Roadmap: PhD Scholar’s Guide (Beginner to Advanced)

A comprehensive guide to mastering web scraping with Python in just 7 days, designed specifically for PhD scholars and researchers. This roadmap covers everything from basic Python setup to advanced production-ready scraping techniques.

Table of Contents

1. Day 1: Python Fundamentals & Environment Setup
2. Day 2: HTTP Requests & HTML Basics
3. Day 3: Advanced BeautifulSoup & CSS Selectors
4. Day 4: Dynamic Content & Selenium
5. Day 5: APIs & Advanced Techniques
6. Day 6: Scrapy Framework
7. Day 7: Advanced Topics & Production

Day 1: Python Fundamentals & Environment Setup

Block 1: Python Installation & IDE Setup (0-10 min)

• Install Python 3.11+ and VS Code
• Links:
  • Python Official Download
  • VS Code Download
  • Python Extension for VS Code

# Verify installation
python --version

Block 2: Python Basics - Variables & Data Types (10-20 min)

# Basic data types
name = "Research Data"
numbers = [1, 2, 3, 4, 5]
data_dict = {"title": "Study", "year": 2025}
print(f"Working with {name}")

Continue reading about Day 1…

Day 2: HTTP Requests & HTML Basics

Block 1: Understanding Web Scraping Basics (0-10 min)

• Learn about web scraping ethics and best practices
• Study robots.txt and rate limiting
• Understand legal implications

Block 2: HTTP Requests with Requests Library (10-20 min)

import requests
response = requests.get("https://httpbin.org/get")
print(response.status_code)
print(response.text)

Continue reading about Day 2…

[Full content continues through Day 7…]

Additional Resources

Practice Websites

• Quotes to Scrape
• Books to Scrape
• Scrape This Site

Communities & Help

• Stack Overflow - Web Scraping
• r/webscraping
• Scrapy Community

Books & Learning Materials

• “Web Scraping with Python” by Ryan Mitchell
• “Python Web Scraping Cookbook” by Michael Heydt

Tips for Success

1. Practice Daily: Consistency is key
2. Type Code Manually: Build muscle memory
3. Debug Actively: Learn from errors
4. Start Simple: Progress gradually
5. Read Documentation: Use official sources
6. Join Communities: Learn from others
7. Build Projects: Apply your skills
8. Stay Ethical: Respect website policies

Emergency Troubleshooting Guide

Common issues and their solutions:

“Module not found” error

pip install [module-name]

SSL Certificate errors

import requests
response = requests.get(url, verify=False)

[Additional troubleshooting tips…]

Conclusion

This roadmap provides a structured approach to learning web scraping with Python. By following this guide and practicing consistently, you’ll develop the skills needed for efficient data collection in your research.

Remember: The key to success is regular practice and building real-world projects relevant to your research area.

Happy scraping! 🚀📊🔬