Use our API to collect public data from the Wikipedia website on a large scale and without interruptions. Extract up-to-date article content, its edit history, images, profile pages, and comments. From fueling content creation to monitoring your brand and conducting market research, Wikipedia data can supercharge your business.
Real-time data without IP blocking
Scalable and maintenance-free infrastructure
Pay only for successful results
*This scraper is a part of Web Scraper API
The data-gathering process is simple: form a payload with job parameters, include the Wikipedia website link you want to scrape, and send the request to our API, which will return results in HTML.
See an example of the output on the right, and explore more information in our documentation.
{
"results": [
{
"content": "\n\n
...
\n\n",
"created_at": "2023-06-28 07:56:42",
"updated_at": "2023-06-28 07:56:43",
"page": 1,
"url": "https://en.wikipedia.org/wiki/Oxylabs",
"job_id": "7079729310709324801",
"status_code": 200
}
]
}At the heart of our operations, we devote diligent effort to developing and maintaining reliable and exceptional-quality products. But we understand that challenges emerge, and for such cases, we have a professional support team always ready to assist and provide expert guidance.
Proxy management
Access a global pool of 102M+ proxies to get localized data from any site without IP blocking.
Bulk data extraction
Retrieve data from up to 5,000 URLs per batch in one go.
Multiple delivery options
Retrieve results via cloud storage bucket (AWS S3 or GCS) or our API.
Highly scalable
Easy to integrate, customize & supports a high volume of requests.
24/7 support
Receive expert assistance whenever you need it.
Independently write parsing instructions and parse any target effortlessly while using our infrastructure.
No need to maintain your own parser
Define your own parsing logic with XPath and CSS selectors
Collect ready-to-use structured data from Wikipedia
Discover all pages on Wikipedia and fetch data at scale and in real time with Web Crawler feature.
Gather only the data you need from target websites
Control the crawling scope and tailor the end result
Retrieve your results in a specified format
Automate recurring scraping and parsing jobs with the needed frequency by scheduling them with Scheduler feature.
Create multiple schedules for different jobs
Receive data automatically to your preferred cloud storage
Get notifications once each job is done
Gather cost-effective Wikipedia data
Pay only for successful results
Gather highly-localized data
Receive scraping know-how
0
1 week trial
Limited to 1 user
49
$2.00 / 1K results
$49 + VAT billed monthly
99
$1.80 / 1K results
$99 + VAT billed monthly
249
$1.65 / 1K results
$249 + VAT billed monthly
24,500
55,000
151,000
10 requests / s
10% off
Yearly plans discount
For all our plans by paying yearly. Contact sales to learn more.
We accept these payment methods:
Wikipedia provides a lot of valuable information for research and analysis. However, if you are interested in gathering public data from Wikipedia on a large scale, you will need specialized tools and technical knowledge. To start easily, we suggest checking the "How to Scrape Wikipedia" technical tutorial on our blog.
The legality of web data extraction always depends on the method and type of data being collected. Website data extraction must be conducted in compliance with relevant laws and regulations, including copyright and privacy laws, among others, to avoid any violations. Also, it must be done responsibly and ethically so that it does not affect the performance of a website and is not violating any other terms of use. To learn more about this, visit Wikimedia’s official ToS and other pages on robot policy and User-Agent policy.
As in any case that involves web scraping sites, it is highly recommended to consult a legal expert before engaging in any data extraction activities. If you are curious to learn more about this topic, check out our in-depth blog post about the legality of web scraping.