Wikipedia Scraper API
Scrape Wikipedia and collect data such as: article text, links, categories, and more. Maintain full control, flexibility, and scale without worrying about infrastructure, proxy servers, or getting blocked.
- Dedicated account manager
- Retrieve results in multiple formats
- No-code interface for rapid development
Just want data? Skip scraping.
Purchase a dataset
One API call. Tons of data.
Data Discovery
Detecting data structures and patterns to ensure efficient, targeted extraction of data.
Bulk Request Handling
Reduce server load and optimize data collection for high-volume scraping tasks.
Data Parsing
Efficiently converts raw HTML into structured data, easing data integration and analysis.
Data validation
Ensure data reliability and save time on manual checks and preprocessing.
Never worry about proxies and CAPTCHAs again
- Automatic IP Rotation
- CAPTCHA Solver
- User Agent Rotation
- Custom Headers
- JavaScript Rendering
- Residential Proxies
Starts from $0.001/record
- Pay as you go plan available
- Automated validation
- 24/7 human support
Easy to start. Easier to scale.
Unmatched Stability
Ensure consistent performance and minimize failures by relying on the world’s leading proxy infrastructure.
Simplified Web Scraping
Put your scraping on auto-pilot using production-ready APIs, saving resources and reducing maintenance.
Unlimited Scalability
Effortlessly scale your scraping projects to meet data demands, maintaining optimal performance.
API for Seamless Wikipedia Data Access
Comprehensive, Scalable, and Compliant Wikipedia Data Extraction
Tailored to your workflow
Get structured LinkedIn data in JSON, NDJSON, or CSV files through Webhook or API delivery.
Built-in infrastructure and unblocking
Get maximum control and flexibility without maintaining proxy and unblocking infrastructure. Easily scrape data from any geo-location while avoiding CAPTCHAs and blocks.
Battle-proven infrastructure
Bright Data’s platform powers over 20,000+ companies worldwide, offering peace of mind with 99.99% uptime, access to 72M+ real user IPs covering 195 countries.
Industry leading compliance
Our privacy practices comply with data protection laws, including the EU data protection regulatory framework, GDPR, and CCPA – respecting requests to exercise privacy rights and more.
Wikipedia Scraper API use cases
Collect explanations about different topics
Compare information from Wikipedia with other sources
Conduct research based on huge datasets
Scrape Wikipedia Commons images
Why 20,000+ Customers Choose Bright Data
100% Compliant
24/7 Global Support
Complete Data Coverage
Unmatched Data Quality
Powerful Infrastructure
Custom Solutions
Wikipedia Scraper FAQs
Why is it important to use proxies when scraping Wikipedia ?
Proxies are important for scraping Wikipedia because it allows the scraper to remain anonymous, avoid IP blocking, access geo-restricted content, and improve scraping speed.
Why is it important to have an unblocking solution when scraping Wikipedia ?
Having an unblocking solution when scraping Wikipedia is important because many websites have anti-scraping measures that block the scraper’s IP address or require CAPTCHA solving. The unblocking solution implemented within Bright Data’s web scraping solutions are designed to bypass these obstacles and continue gathering data without interruption.
What type of Wikipedia data can I scrape?
When scraping Wikipedia , you may only scrape publicly available data. Due to our commitment to privacy laws, we do not allow scraping behind log-ins.
Is it legal to scrape Wikipedia ?
Our privacy practices comply with data protection laws, including the EU data protection regulatory framework, GDPR, and CCPA – respecting requests to exercise privacy rights and more.