📚 Wikipedia Pageviews Scraper

🚀 Pull daily and monthly Wikipedia pageviews for any article in any language. Filter by date range, access type, and agent type. No API key, no registration, no quota negotiation.

The Wikipedia Pageviews Scraper queries the official Wikimedia REST API and returns the number of times any Wikipedia article was viewed during a date range. Each row reports the language project, article title, timestamp, access type, agent type, and view count. The endpoint covers every Wikipedia language edition, and the underlying dataset goes back to July 2015, giving you nearly a decade of continuous traffic history per article.

Wikipedia is the eighth most visited website in the world with billions of pageviews per month. Pageview trends are a leading indicator for cultural moments, search demand, breaking news, and product launches. Building your own pipeline against the Wikimedia API means handling URL encoding, paginated date ranges, and per-language hosts. This Actor handles all of that and lets you focus on the analysis.

🎯 Target Audience	💡 Primary Use Cases
SEO teams, journalists, trend researchers, market analysts, academics, dashboard builders	Search demand forecasting, cultural research, content benchmarking, trend tracking, comparative analysis

📋 What the Wikipedia Pageviews Scraper does

Five filtering workflows in a single run:

• 📚 Per-article views. Submit any Wikipedia article title and pull its full traffic history for the date range you choose.
• 🌍 Any language edition. Pick from 20+ supported language projects including English, Spanish, German, French, Japanese, Russian, and Chinese Wikipedia.
• 📅 Daily or monthly granularity. Daily rollups give you weekday seasonality. Monthly rollups give you long-term trend lines.
• 📱 Access type filter. Slice traffic by desktop, mobile web, mobile app, or all-access combined.
• 🤖 Agent type filter. Separate human (user) traffic from spiders and automated agents to clean up trend lines.

Each row in the dataset reports the project (e.g. en.wikipedia), URL-encoded article title, granularity, timestamp in YYYYMMDD00 format, access slice, agent slice, and view count. Dataset entries go back to July 2015.

💡 Why it matters: pageview data is one of the cleanest free signals for tracking real-world attention. When a celebrity dies, a film trailer drops, or a country votes, the matching Wikipedia article spikes within hours. SEO teams use the pageview series as a free proxy for search demand. Researchers cite it in studies of collective attention. Dashboard builders embed it as a public-interest gauge.

📊 Data fields

Each record includes: access, agent, article, granularity, project, scrapedAt, timestamp, views. These field names come straight from the actor's dataset schema, so what you see here is what lands in your dataset.

🚀 How to use

1. 🆓 Create a free Apify account. Sign up here and get $5 in free credit.
2. 🔍 Open the Actor. Search for "Wikipedia Pageviews" in the Apify Store.
3. ⚙️ Set your inputs. Pick articles, project, date range, granularity, and any filters.
4. ▶️ Click Start. Most runs finish in under 10 seconds.
5. 📥 Download. Export as CSV, Excel, JSON, or XML, or wire it into a Make / Zapier flow.

⏱️ Total time from sign-up to first dataset: under five minutes.

🔗 Recommended Actors

• 🅱️ Bing Search Scraper - track organic search demand alongside Wikipedia traffic.
• 🦆 DuckDuckGo Search Scraper - alternative SERP signal for the same topic.
• 📰 Substack Publication Scraper - pair Wikipedia trends with newsletter cadence.
• 🐙 GitHub Trending Repos Scraper - capture developer attention next to public attention.
• 🌐 Common Crawl Index Scraper - cross-reference web archive captures with traffic data.

💡 Pro Tip: browse the complete ParseForge collection for more pre-built scrapers and data tools.

Wikipedia is a registered trademark of the Wikimedia Foundation. This Actor is not affiliated with or endorsed by the Wikimedia Foundation. It is built on the public Wikimedia REST API and respects all published rate limits.

🆘 Need Help?

If you hit a bug, have questions about setup, or need a scraper we haven't built yet, open our contact form or write to parseforge@protonmail.com. We also take on paid custom data projects.

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