Wikipedia Pageviews Scraper

Wikipedia Pageviews Scraper

Scrape Wikipedia pageview statistics for any article, in any language, up to a million records per run. Get daily or monthly views, split by device and agent type, straight from the official Wikimedia REST API. No API key or registration needed. Export to CSV, JSON, Excel, or XML.

The Wikimedia API is public, but querying it at scale means handling pagination, rate limits, and date formatting yourself. This Actor reads pageview metrics for a list of articles across 20 language editions, buckets the data by day or month, and returns a clean, flat row for every record. It is built for content analysts and SEO researchers who need article traffic data without writing a single line of code.

Who uses it	What they scrape Wikipedia for
SEO analysts	Find which Wikipedia articles drive the most search-referred traffic for a topic cluster.
Content marketers	Measure public interest in a subject over time to plan editorial calendars.
Academic researchers	Track the popularity of scientific concepts or historical figures across language editions.
Data journalists	Pull daily view counts for breaking-news topics to build traffic timelines.

What it does

This Actor collects Wikipedia pageview counts for specified articles and returns each metric as a single row with the date, views, article title, project, access type, and agent type.

• 📅 Daily or monthly granularity: bucket pageviews by day to spot spikes, or by month for long-term trend lines.
• 🌐 20 language editions: query en, es, de, fr, ja, ru, it, pt, zh, ar, pl, nl, tr, ko, id, vi, sv, fa, uk, and he Wikipedia projects.
• 📱 Device and agent slicing: filter traffic by desktop, mobile-app, mobile-web, or all-access, and by user, spider, automated, or all-agents.
• 📋 Batch article input: paste a list of article slugs or human-readable titles and pull their metrics in one run.

Results export to CSV, JSON, Excel, or XML, or straight from the API.

What you can do with Wikipedia data

📈 Benchmark content performance.

An SEO manager pulls monthly pageviews for 50 competitor-related Wikipedia articles to identify which topics gained the most traffic quarter over quarter.

🗺️ Map regional interest.

A market researcher runs the same article list across en, es, and pt Wikipedia editions to compare readership volumes in different language markets.

📰 Build a news timeline.

A data journalist collects daily pageviews for a breaking-event article over 90 days and exports the CSV to chart the story's rise and fall.

🤖 Filter out bot traffic.

An analyst sets the agent type to 'user' to exclude spider and automated views and get a clean read of human readership.

Why choose this scraper

	What you get
No API key	Queries the public Wikimedia REST API directly, no account or token required.
Flat output	Every record is one row: date, article, project, access, agent, and views.
Date range control	Set a start and end date, or leave them empty to default to the last 30 days.
Multi-article runs	Feed in hundreds of article titles and collect all their pageviews in a single execution.

How it compares

This Actor focuses on batch article pageview collection with device and agent filtering, while the other Wikipedia pageview scrapers on Apify offer overlapping but distinct feature sets.

Feature	ParseForge	Wikipedia Pageviews - Article Traffic Stats	Wikipedia Pageviews Scraper - Article Traffic & Top Pages
Batch multiple articles in one run	Yes	Not listed	Yes
Device type filtering (desktop, mobile)	Yes	Not listed	Not listed
Agent type filtering (user, spider, bot)	Yes	Not listed	Not listed
20 language editions	Yes	Not listed	Not listed
Daily top articles by project	Not listed	Not listed	Yes
Peak day and average views	Not listed	Yes	Not listed

Configure the run

Drive the Actor with a list of Wikipedia article titles, pick a language edition, and set a date range. Filters for access type and agent run as each record is fetched so only the slice you need lands in your dataset. The Input tab lists every parameter.

A first run with the defaults:

{
 "maxItems": 10,
 "articles": [
 "Albert_Einstein",
 "ChatGPT",
 "Taylor_Swift"
 ],
 "project": "en.wikipedia.org",
 "granularity": "daily",
 "access": "all-access",
 "agent": "all-agents"
}

A larger pull:

{
 "maxItems": 200,
 "articles": [
 "Albert_Einstein",
 "ChatGPT",
 "Taylor_Swift"
 ],
 "project": "en.wikipedia.org",
 "granularity": "daily",
 "access": "all-access",
 "agent": "all-agents"
}

Pricing

Pay-per-result: $0.011 per result collected. You pay only for the results written to your dataset.

Results collected	Approximate cost
100 results	$1.10
1,000 results	$11.00
10,000 results	$110.00

New Apify accounts start with $5 in free credit.

Free users

Free-plan runs return up to 10 results as a preview. Upgrade your Apify plan to collect up to 1,000,000 results per run.

Run it

1. Create a free Apify account with $5 in credit.
2. Open the Wikipedia Pageviews Scraper.
3. Set your inputs and any filters, then click Start.
4. Export the results as CSV, Excel, JSON, or XML from the Dataset tab.

Run it programmatically through the Apify API (run-sync-get-dataset-items) or the ApifyClient for JavaScript and Python.

Use with AI agents (MCP)

Give an AI agent live access to Wikipedia through the Model Context Protocol. Add the Actor to Claude, Cursor, or any MCP client:

$claude mcp add --transport http apify "https://mcp.apify.com?tools=parseforge/wikipedia-pageviews-scraper"

Then prompt it in plain language to run the scraper and read back the results.

Troubleshooting

Why am I getting zero results for an article?

Check that the article title matches the exact Wikipedia slug. Try copying the title directly from the URL. Also verify your date range falls within the supported window (July 2015 onward for daily data).

The run is slow with many articles.

The Actor respects Wikimedia rate limits. For large article lists, increase the run timeout or split the list across multiple runs with narrower date ranges.

I see a spike in views that looks wrong.

Check your agent type filter. If it is set to 'all-agents', the count includes bot and spider traffic. Switch to 'user' to see only human views.

My date format is rejected.

Use the YYYY-MM-DD format (e.g., 2024-01-15). The Actor validates this before calling the API.

Monthly data returns fewer rows than expected.

Monthly granularity aggregates daily views into one row per month per article. If you need day-by-day detail, switch granularity to 'daily'.

FAQ

Question	Answer
Do I need a Wikipedia API key?	No. This Actor calls the public Wikimedia REST API, which does not require authentication or an API key.
How far back can I pull pageview data?	The Wikimedia API provides daily pageviews back to July 2015 and monthly pageviews back to January 2016. Set your start and end dates accordingly.
What format should I use for article titles?	Use the Wikipedia slug (the part after /wiki/ in the URL, like 'Albert_Einstein') or the human-readable title. The Actor handles both.
Can I scrape pageviews for multiple articles at once?	Yes. Add as many article titles as you need to the input list. Each article's pageviews are fetched and returned as separate rows.
What does the access type filter do?	It splits traffic by device: desktop, mobile-app, mobile-web, or all-access combined. Use it to compare how readers reach an article.
What is the agent type filter?	It separates traffic by user agent: user (human), spider (search crawlers), automated (bots), or all-agents. Useful for filtering out non-human views.
Which Wikipedia languages are supported?	20 language editions are available, including English, Spanish, German, French, Japanese, Russian, Chinese, Arabic, and more.
How is the data exported?	You can export your results to CSV, JSON, Excel, or XML directly from the Apify dataset tab.
What happens if I leave the start and end dates empty?	The Actor defaults to the last 30 days of data, with the end date set to yesterday.
Is there a limit on how many records I can pull?	You can set the maximum records per run up to 1,000,000. The Actor stops when it hits that number or exhausts the date range.

Related actors

Browse the full ParseForge collection for more scrapers.

🆘 Need help? Email parseforge@protonmail.com with your run ID, your input, and what you expected.

⚠️ Disclaimer. This Actor is unofficial and is not affiliated with, endorsed by, or sponsored by Wikimedia Foundation, Inc. It collects only publicly available data. You are responsible for using the collected data in compliance with the source's terms of service and applicable data-protection laws, including GDPR, CCPA, and PIPL. Do not use it to collect personal data unlawfully.