📅 Wikipedia On This Day Scraper

🚀 Export curated daily history in seconds. Pull selected events, births, deaths, holidays, and editor picks for any calendar date in 10 Wikipedia language editions. No API key, no registration, no manual scraping.

The Wikipedia On This Day Scraper exports the daily curated content that powers the famous "On This Day" section on Wikipedia. For any date, you get the editor-selected events, notable births, deaths, observed holidays, and a combined "all" view. Each record carries 12 fields including category, year, thumbnail, the rendered summary text, the linked Wikipedia page title, page description, page extract, and the full page URL.

Coverage spans all 366 calendar days across 10 Wikipedia language editions (English, Spanish, French, German, Italian, Portuguese, Russian, Chinese, Japanese, Korean). This Actor turns the curated daily feed into a downloadable dataset suitable for media, education, and trivia applications.

🎯 Target Audience	💡 Primary Use Cases
Newsroom social teams, educational platforms, trivia apps, daily-content publishers, history podcasters, edu-tech vendors	"On this day" social posts, daily newsletter content, history flashcards, voice-assistant skills, classroom prompts, almanac databases

📋 What the Wikipedia On This Day Scraper does

Four content workflows in a single run:

• 📜 Selected (editor curated). The headline events Wikipedia editors handpick for each date.
• 🎂 Births. Notable people born on the date, with linked Wikipedia biographies.
• ⚰️ Deaths. Notable people who died on the date, with linked Wikipedia biographies.
• 🎉 Events and holidays. Major historical events plus observed national and religious holidays.

Set type to all to pull every slice in one call, or pass several dates at once to build a multi-day almanac.

💡 Why it matters: "on this day" content is one of the highest-engagement formats on social and email. Building it yourself means scraping inconsistent HTML or stitching multiple endpoints. This Actor returns one clean record per item, every time.

📊 Data fields

Each record includes: category, date, language, pageDescription, pageExtract, pages, pageTitle, pageUrl, scrapedAt, text, thumbnailUrl, year. 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. 📝 Sign up. Create a free account with $5 credit (takes 2 minutes).
2. 🌐 Open the Actor. Go to the Wikipedia On This Day Scraper page on the Apify Store.
3. 🎯 Set input. Pick one or more dates, choose a category and language, set maxItems.
4. 🚀 Run it. Click Start and the Actor collects the curated records.
5. 📥 Download. Grab your results in the Dataset tab as CSV, Excel, JSON, or XML.

⏱️ Total time from signup to downloaded dataset: 3-5 minutes. No coding required.

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💡 Pro Tip: browse the complete ParseForge collection for more daily-content and reference scrapers.

⚠️ Disclaimer: this Actor is an independent tool and is not affiliated with, endorsed by, or sponsored by Wikipedia or the Wikimedia Foundation. All trademarks mentioned are the property of their respective owners. Only publicly available Wikipedia content is collected.

🆘 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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