Scrape Wikipedia data with Web Scraper 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

Scrape Wikipedia data with Web Scraper 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.

See 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
    }
  ]
}

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.

Read reviews

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

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 177M+ 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.

Smart data extraction with API features

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

Find out more

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

Find out more

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

No credit card required

Amazon: $0.50/1K results
Google: $1.00/1K results
Other: $1.15/1K results
Successful results without JS rendering

$1.35 / 1K results
Successful results with JS

10 requests / s
Rate limit

Premium proxies

AI-powered web scraping

Up to 2,000 results

Micro

Amazon: $0.50/1K results
Google: $1.00/1K results
Other: $1.15/1K results
Successful results without JS rendering

$1.35 / 1K results
Successful results with JS

From $20 to $249
Available top-up

50 requests / s Rate limit

Premium proxies

AI-powered web scraping

Up to 98,000 results

Starter

Amazon: $0.45/1K results
Google: $0.90/1K results
Other: $1.10/1K results
Successful results without JS rendering

$1.30 / 1K results
Successful results with JS

From $20 to $499
Available top-up

50 requests / s Rate limit

Premium proxies

AI-powered web scraping

Up to 220,000 results

Advanced

249

Amazon: $0.40/1K results
Google: $0.80/1K results
Other: $0.95/1K results
Successful results without JS rendering

$1.25 / 1K results
Successful results with JS

From $20 to $499
Available top-up

50 requests / s Rate limit

Premium proxies

AI-powered web scraping

Up to 622,500 results

Successful results without JS rendering

Amazon: $0.50/1K results

Google: $1.00/1K results

Other: $1.15/1K results

Amazon: $0.50/1K results

Google: $1.00/1K results

Other: $1.15/1K results

Amazon: $0.45/1K results

Google: $0.90/1K results

Other: $1.10/1K results

Amazon: $0.40/1K results

Google: $0.80/1K results

Other: $0.95/1K results

Successful results with JS

$1.35 / 1K results

$1.30 / 1K results

$1.25 / 1K results

Available top-up

From $20 to $249

From $20 to $499

Rate limit

10 requests / s

50 requests / s

Premium proxies

AI-powered web scraping

Dedicated Account Manager

10% off

Yearly plans discount

For all our plans by paying yearly. Contact sales team to learn more.

We accept these payment methods:

Frequently asked questions

How to scrape Wikipedia?

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.

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.