Wikipedia Scraper

Use the Web Scraper IDE tool to retrieve publicly available data from Wikipedia.

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Generic scraping image

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)
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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

 

 

 

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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
Develop and customize your scraper

STEP 3

Choose when to get the data: In real-time or batches
Choose when to get the data

STEP 4

Choose the file format and where to send the data
Choose format and where to send the data

Want to learn more?

Talk to an expert to discuss your data collection needs and see our platform in action.

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