Data Scraping

Data scraping, also known as data extraction, web scraping or parsing, is a method used to extract large amounts of data from websites where the data is extracted and saved to a local file in your computer or to a database in table (spreadsheet) format. The data massives are used for various reasons (i.e. market research) or simply sold to interested parties.

Basic Data Scraping Work Scheme

  1. Identify Target Website: Determine which website you’ll scrape. Ensure it contains the information you need and that this information can be accessed – some sites have anti-scraping mechanisms.

  2. Inspect Page Structure: The data on websites is usually nested in HTML tags. Use developer tools (like “Inspect Element” on Chrome) to understand the structure and how your desired data is nested.

  3. Write Code: Write code for your scraper using programming languages like Python along with libraries such as Beautiful Soup or Scrapy.

  4. Run Code & Extract Data: Execute your script to extract the required data from the target website.

  5. Store Data: Save scraped data into desirable format like CSV, JSON, XML etc., for further use or analysis.


  • Automates manual work
  • Can handle vast volumes of data
  • Profitable and scalable business in data-driven world

Potential Pitfalls:

  • Legal issues if done without permission / collected data is not public domain
  • Websites may block IP addresses they suspect are scraping their content
  • Scraped information might not always be up-to-date due to changes on source site
  • Requires serious technical background

Typical Tools Used For Scraping

  1. – User-friendly tool for non-programmers
  2. ParseHub – A powerful tool capable of handling JavaScript and AJAX pages
  3. Octoparse – Both cloud-based and installed versions available.
  4. WebHarvy– Point-and-click software for extracting specific info quickly.
  5. GoLogin – Bypassing anti-bot protection and captcha on websites and servers like Cloudflare
  6. Scrapy – An open-source framework useful for building crawling programs

Remember that while powerful, web scraping should be done responsibly respecting privacy laws/rules set by targeted websites i.e., robots.txt files etc.

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