📅 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.

🕒 Last updated: 2026-05-23 · 📊 12 fields per record · 📅 366 calendar days · 🌍 10 languages · 🗂️ 6 category slices

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

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📋 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.

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🎬 Full Demo

🚧 Coming soon: a 3-minute walkthrough showing how to schedule a daily run and pipe the records into a social-content workflow.

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⚙️ Input

Input	Type	Default	Behavior
maxItems	integer	10	Records to return. Free plan caps at 10, paid plan at 1,000,000.
dates	array	["05-24"]	Calendar dates as MM-DD. Leave empty to use today.
type	string	"selected"	One of all, selected, births, deaths, events, holidays.
language	string	"en"	Wikipedia language edition. One of 10 supported codes.

Example: editor-curated highlights for Christmas Day in English.

{
    "maxItems": 50,
    "dates": ["12-25"],
    "type": "selected",
    "language": "en"
}

Example: notable births across a week in German.

{
    "maxItems": 200,
    "dates": ["01-01", "01-02", "01-03", "01-04", "01-05", "01-06", "01-07"],
    "type": "births",
    "language": "de"
}

⚠️ Good to Know: the curated feed reflects what active Wikipedia editors choose to highlight on a given date. The same date in different language editions can surface different events and biographies, which is great for localization but worth knowing.

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📊 Output

Each record contains 12 fields. Download the dataset as CSV, Excel, JSON, or XML.

🧾 Schema

Field	Type	Example
🖼️ thumbnailUrl	string | null	"https://upload.wikimedia.org/.../Apollo11.jpg"
📅 date	string	"07-20"
🌍 language	string	"en"
🏷️ category	string	"events"
📆 year	number | null	1969
📝 text	string	"Apollo 11 lands on the Moon..."
📖 pageTitle	string	"Apollo 11"
📰 pageDescription	string	"1969 American crewed spaceflight..."
📃 pageExtract	string	"Apollo 11 was the American spaceflight..."
🔗 pageUrl	string	"https://en.wikipedia.org/wiki/Apollo_11"
📚 pages	array	All linked pages for the entry
🕒 scrapedAt	ISO 8601	"2026-05-23T00:00:00.000Z"

📦 Sample records

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✨ Why choose this Actor

	Capability
📅	Complete calendar. All 366 dates, every category, on demand.
🌍	10 language editions. Localize "on this day" content for global audiences.
🗂️	Six category slices. Selected, births, deaths, events, holidays, or everything combined.
🖼️	Image thumbnails. Ready-to-use Wikipedia Commons URLs for social and newsletter graphics.
⚡	Fast. A full day of curated content in seconds.
🔁	Always fresh. Pulls live curated content so editor updates appear immediately.
🚫	No authentication. Works against the public Wikipedia feed. No login or key needed.

📊 "On this day" is the unsung evergreen of content marketing: low effort to produce, high effort to maintain at scale. This Actor solves the maintenance side.

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📈 How it compares to alternatives

Approach	Cost	Coverage	Refresh	Categories	Setup
⭐ Wikipedia On This Day Scraper (this Actor)	$5 free credit, then pay-per-use	366 days, 10 languages	Live per run	selected, births, deaths, events, holidays, all	⚡ 2 min
Manual page scraping	Free	Full	Live	Inconsistent HTML	🐢 Hours per day
Custom feed builder	Free	Full	Custom	Build yourself	⏳ Days
Third-party "today in history" widgets	Varies	Limited	Mixed	Limited	🕒 Variable

Pick this Actor when you want clean curated records on demand without writing parsers.

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🚀 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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💼 Business use cases

📱 Newsroom Social Teams Daily "on this day" social posts with images Localized variants across 10 language editions Pre-scheduled multi-day content calendars Auto-generated newsletter sidebars	🎓 EdTech & E-learning Daily history flashcards in classroom apps Subject-aligned biography spotlights Multilingual content for language learners Trivia generators for student engagement
🎙️ Podcasts & Daily Briefings "Today in history" voice-assistant skills Episode openers with curated history hooks Per-episode show notes with linked sources Multi-language radio segment scripts	📊 Reference & Almanac Apps Pre-warmed daily-content caches for mobile apps Almanac databases with multilingual entries Calendar-app history overlays Smart speakers daily-fact briefings

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🔌 Automating Wikipedia On This Day Scraper

Control the scraper programmatically for scheduled runs and pipeline integrations:

• 🟢 Node.js. Install the apify-client NPM package.
• 🐍 Python. Use the apify-client PyPI package.
• 📚 See the Apify API documentation for full details.

The Apify Schedules feature lets you trigger this Actor on any cron interval. A daily 06:00 UTC run is the most popular pattern for newsroom and social-team workflows.

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🌟 Beyond business use cases

Daily curated history has reach well beyond commercial workflows. The same structured records support research, education, civic projects, and personal initiatives.

🎓 Research and academia Cross-cultural comparison studies of "notable" history Quantitative history projects with year-level features Multilingual NLP datasets for entity-recognition models Classroom modules on Wikipedia editorial choices	🎨 Personal and creative Daily-history journals and Notion dashboards Birthday-and-anniversary trivia for friends and family Newsletter side-projects and indie blogs Daily-art prompts based on historical events
🤝 Non-profit and civic Community-history education for libraries and museums Veteran and remembrance-day content automation Cultural-heritage social media for civic groups Multilingual outreach for diaspora communities	🧪 Experimentation Train LLMs on date-aligned history snippets Build agentic chatbots that answer "what happened on X" Prototype calendar widgets with rich history overlays A/B test social-content templates with real history items

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🤖 Ask an AI assistant about this scraper

Open a ready-to-send prompt about this ParseForge actor in the AI of your choice:

• 💬 ChatGPT
• 🧠 Claude
• 🔍 Perplexity
• 🅒 Copilot

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❓ Frequently Asked Questions

🧩 How does it work?

Pass one or more MM-DD dates, pick a category and language, click Start, and the Actor pulls the curated feed for each date and emits a clean structured record per entry.

📏 How accurate is the data?

The "On This Day" feed is curated by active Wikipedia editors and reviewed by the community. Per-entry accuracy reflects the linked Wikipedia article. For citation-grade work, follow the page URL and review the source article.

🔁 How often is the data refreshed?

The curated feed is updated continuously by Wikipedia editors. Every run of this Actor fetches live data, so editor updates appear immediately.

🌍 Which languages are supported?

Ten Wikipedia editions: English, Spanish, French, German, Italian, Portuguese, Russian, Chinese, Japanese, and Korean. Each edition is independently curated, so the same date can surface different highlights in different languages.

🗂️ What do the categories mean?

• selected: handpicked headline items for the date
• events: historical events on the date
• births and deaths: notable biographies
• holidays: observed national and religious holidays
• all: every category combined

⏰ Can I schedule regular runs?

Yes. Use Apify Schedules to run this Actor daily and pipe the output into your social-publishing or newsletter platform.

⚖️ Is this data legal to use?

Wikipedia content is published under the Creative Commons BY-SA license. Attribution to Wikipedia and the article authors is required. Verify per-record license for embedded images.

💳 Do I need a paid Apify plan to use this Actor?

No. The free Apify plan is enough for testing and small runs (10 records per run). A paid plan unlocks daily scheduling for production content workflows.

🔁 What happens if a run fails or gets interrupted?

Apify automatically retries transient errors. If a run still fails, inspect the log, fix the input, and re-run. Partial datasets from failed runs are preserved.

🖼️ Are images included?

Yes when the curated entry has a thumbnail. The thumbnailUrl field links directly to Wikimedia Commons, and you can use the image under its individual Commons license.

🆘 What if I need help?

Our support team is here to help. Contact us through the Apify platform or use the Tally form linked below.

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🔌 Integrate with any app

Wikipedia On This Day Scraper connects to any cloud service via Apify integrations:

• Make - Automate multi-step workflows
• Zapier - Connect with 5,000+ apps
• Slack - Get daily history posts in your channels
• Airbyte - Pipe history items into your warehouse
• GitHub - Trigger runs from commits and releases
• Google Drive - Export datasets straight to Sheets

You can also use webhooks to trigger downstream actions when a run finishes. Push daily history items into your CMS or alert your team in Slack with a curated morning brief.

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

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🆘 Need Help? Open our contact form to request a new scraper, propose a custom data project, or report an issue.

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⚠️ 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.