5 Key Considerations for Python Web Scraping Development

Learn the five essential considerations for Python web scraping, including handling robots.txt, setting request intervals, and managing anti-scraping mechanisms.

Web scraping is one of the important methods for data acquisition, but it is also a technical skill.

Today, let’s talk about five key considerations for Python web scraping development, helping you avoid pitfalls during the process.

1. Respect the Website’s robots.txt File

First, we must respect the website’s robots.txt file. This file defines which pages can be scraped and which cannot. Respecting the robots.txt file is not only an ethical requirement but also a legal one.

Example Code:

import requests

def check_robots_txt(url):
    # Get the URL of the robots.txt file
    robots_url = f"{url}/robots.txt"
    
    # Send a request to get the robots.txt file
    response = requests.get(robots_url)
    
    if response.status_code == 200:
        print("robots.txt content:")
        print(response.text)
    else:
        print(f"Unable to fetch {robots_url}'s robots.txt file")

# Test
check_robots_txt("https://www.example.com")

Output:

robots.txt content:
User-agent: *
Disallow: /admin/
Disallow: /private/