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Wikipedia API

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

Wikipedia API

Extract data from Wikipedia in bulk and in seconds

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
}
]
}

Pleasant experience being partnered with Oxylabs for the past few years. Reliable services and good customer response times - appreciate the introduction of being connected on Slack with the teams.

Oxylabs client

Trusted services and professional support

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.

24/7 support and other handy features

Guided integration

Get a quick start with detailed documentation and demo video.

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 1000 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.

Smart data extraction with API features

Custom Parser

Custom Parser

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

Web Crawler

Web Crawler

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

Scheduler

Scheduler

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

Wikipedia API pricing

Gather cost-effective Wikipedia data

Regular
Enterprise

Pay only for successful results

Gather highly-localized data

Receive scraping know-how

Don’t miss out

Free Trial

0

1 week trial

Limited to 1 user

Micro

49

$2.80 / 1K results

$49 + VAT billed monthly

Starter

99

$2.60 / 1K results

$99 + VAT billed monthly

Advanced

249

$2.40 / 1K results

$249 + VAT billed monthly

Results
5,000

17,500

38,000

104,000

Rate limit
5 requests / s

10 requests / s

15 requests / s

30 requests / s

JavaScript rendering
Country-level targeting
24/7 support
Dedicated Account Manager

We accept these payment methods:

Frequently asked questions

Is it legal to extract data from Wikipedia?

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.

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