What are common mistakes beginners make in Python web scraping?
Beginners often make similar mistakes that can break scrapers or get them blocked.
1. Not handling errors properly:
- Failing to catch connection errors or HTTP errors
- Not validating that elements exist before accessing them
- Use try-except blocks and check if elements are found before extracting
2. Missing User-Agent headers:
- Default Python requests look like bots
- Always set a realistic User-Agent header
- Many sites block requests without proper headers
3. Making too many requests too quickly:
- Overwhelming servers triggers rate limiting or IP bans
- Add delays between requests with
time.sleep() - Respect robots.txt and implement rate limiting
4. Not using sessions:
- Creating a new connection for every request is inefficient
- Use
requests.Session()to reuse connections and maintain cookies - Sessions handle cookies automatically for logged-in scraping
5. Parsing JavaScript-rendered content with BeautifulSoup:
- BeautifulSoup only sees initial HTML, not JavaScript-rendered content
- Use Selenium or check if data is available via API calls
- Inspect network requests to find data endpoints
6. Hardcoding selectors without fallbacks:
- Websites change frequently, breaking fragile selectors
- Use multiple selector strategies and handle missing elements gracefully
- Test selectors against multiple page samples
7. Not respecting rate limits or robots.txt:
- Ethical scraping respects site rules and limitations
- Parse robots.txt to understand crawling policies
- Implement delays and respect Crawl-delay directives
8. Storing data inefficiently:
- Writing to files in loops without buffering
- Not using proper data formats (CSV, JSON, databases)
- Use pandas or proper database connections for structured data