Use the Web Scraper IDE tool to retrieve publicly available data from Wikipedia.
Wikipedia Scraper
Use Bright Data’s Web Scraper IDE,
or purchase a pre-collected dataset
- Collect explanations about different topics
- Compare information from Wikipedia with other sources
- Conduct research based on huge datasets
- Scrape Wikipedia Commons images
Wikipedia Scraper Overview
- platform integrates with our industry-leading proxy networks
- Utilizes proprietary site unlocking technology
- Adapts to site changes: when Wikipedia changes its site structure Web Scraper IDE will adapt
- Infinitely scalable – collect as much data as you need quickly and completely
- Fully compliant with industry best practices and privacy regulations (GDPR, CCPA)
Web Scraper IDE Features
Leave your scraping limitations behind with our hosted cloud solution
Pre-made web scraper templates
Get started quickly and adapt existing code to your specific needs
Interactive preview
Watch your code as you build it and debug errors in your code quickly
Built-in debug tools
Debug what happened in a past crawl to understand what needs fixing in the next version
Browser scripting in JavaScript
Handle your browser control and parsing codes with simple procedural JavaScript
Ready-made functions
Capture browser network calls, configure a proxy, extract data from lazy loading UI, and more!
Easy parser creation
Write your parsers in cheerio and run live previews to see what data it produced
Auto-scaling infrastructure
You don’t need to invest in the hardware or software to manage an enterprise-grade web scraper
Integration
Emulate a user in any geo-location with built-in fingerprinting, automated retries, CAPTCHA solving, and more.
Built-in debug tools
Trigger crawls on a schedule or by API, and connect our API to major storage platforms
Leverage a Wikipedia Scraper to:
- Use Wikipedia’s massive troves of data as your own business database
- Provide answers on your website to questions related to your vertical or industry directly on your website
- Power your machine training algorithms with data related to your business
- Scrape lists data for businesses in a specific vertical or people in a specific industry
How to develop a web scraper
STEP 1
Choose from ready-made code templates or start from scratch
STEP 2
Develop and customize your scraper using Bright Data’s ready-made scraping functions
STEP 3
Choose when to get the data: In real-time or batches
STEP 4
Choose the file format and where to send the data
