What you need to know before doing Webscraping in Python
Land Your First Data Science Job
A proven roadmap to prepare for $75K+ entry-level data roles. Perfect for Data Scientist ready to level up their career.
Web-scraping is powerful.
It gives you the tool to extract any information on any website.
The method you use will highly depend on the website you are trying to get data from.
Before web scraping in Python, it is important to check the following:
- Website's terms of use: Make sure that the website allows web scraping and does not prohibit it in its terms of use.
- Robots.txt file: Check the website's
robots.txt
file to see if there are any restrictions on which pages can be crawled. - Request rate: Check the website's request rate limits to ensure that you do not overwhelm the server with too many requests.
- Dynamic content: Consider if the website's content is generated dynamically through JavaScript, and whether you will need to use a tool like
Selenium
to interact with the website's DOM. - Data format: Determine the format of the data you want to extract, and make sure that it is accessible through the website's HTML or API.
For example, if you want to scrape product information from an e-commerce website, you would check its terms of use to make sure it allows web scraping, check its robots.txt
file to see if there are any restrictions, and determine the format of the product data to make sure it can be easily extracted from the website's HTML.
Land Your First Data Science Job
A proven roadmap to prepare for $75K+ entry-level data roles. Perfect for Data Scientist ready to level up their career.
Related Articles
Continue your learning journey with these related topics
Master Data Science in Days, Not Months 🚀
Skip the theoretical rabbit holes. Get practical data science skills delivered in bite-sized lessons – Approach used by real data scientist. Not bookworms. 📚