# Wikipedia Pageviews Scraper — Trending Articles Daily (`compute-edge/wikipedia-pageviews-scraper`) Actor Extract Wikipedia's most-viewed articles by day or month with view counts, ranks, and article URLs. Filter by project language and access type. Track trending topics and public attention across any historical date range. - **URL**: https://apify.com/compute-edge/wikipedia-pageviews-scraper.md - **Developed by:** [Compute Edge](https://apify.com/compute-edge) (community) - **Categories:** Lead generation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $3.00 / 1,000 results This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## Wikipedia Pageviews Scraper — Trending Articles by Day or Month Pull the **top-viewed Wikipedia articles** for any project (en, es, de, ja, etc.) and any device segment (all, desktop, mobile-web, mobile-app) from the official **Wikimedia Pageviews API**. Each day Wikipedia publishes the top 1,000 most-viewed articles — a powerful, real-time signal of public attention. ### What this Actor does This Actor wraps the Wikimedia REST API's `/metrics/pageviews/top/{project}/{access}/{year}/{month}/{day}` endpoint, optionally iterates over a date range, and outputs ranked article-day records ready for trend analytics, news intelligence, search demand modeling, and audience research. **Use cases:** - **News & trend intelligence**: Detect breaking events the moment they spike on Wikipedia. - **Marketing & SEO**: Identify topics with surging real-world attention to inform content calendars. - **Finance**: Wikipedia pageview spikes correlate with consumer attention shifts ahead of earnings or product launches. - **Academic research**: Build datasets for attention economics, cultural studies, or NLP topic modeling. - **AI training**: Mine high-attention article titles to expand topic coverage in RAG indexes. ### How to scrape Wikipedia pageviews 1. Pick a **Project** — `en.wikipedia` for English Wikipedia (default), `es.wikipedia`, `de.wikipedia`, `commons.wikimedia`, etc. 2. Pick an **Access Type** — `all-access`, `desktop`, `mobile-web`, `mobile-app`. 3. Set a **Start Date** and **End Date** (YYYY-MM-DD). Leave blank to default to 3 days ago (the API has a ~1-day publication lag). 4. Toggle **Exclude Meta Pages** to drop `Main_Page`, `Special:Search`, and other non-article entries. 5. Set **Max Articles Per Day** (1–1,000). 6. Run. Output is one record per article per day. ### Output fields | Field | Description | |-------|-------------| | date | Date (YYYY-MM-DD) | | rank | Daily rank (1 = most viewed) | | article | Wikipedia article title (underscored) | | articleDisplay | Human-readable title (spaces) | | views | Number of pageviews on that day | | project | Wikipedia project (e.g. en.wikipedia) | | access | Access type used (all-access, desktop, mobile-web, mobile-app) | | articleUrl | Direct article URL | ### Pricing Pay-per-result. The Wikimedia API is very generous; one HTTP request returns up to 1,000 ranked articles per day. Filtering and pagination happen client-side, so runs are fast. ### Example input ```json { "project": "en.wikipedia", "access": "all-access", "startDate": "2026-05-01", "endDate": "2026-05-07", "excludeMeta": true, "maxPerDay": 200 } ```` ### Example output (single record) ```json { "date": "2026-05-01", "rank": 5, "article": "Kentucky_Derby", "articleDisplay": "Kentucky Derby", "views": 421003, "project": "en.wikipedia", "access": "all-access", "articleUrl": "https://en.wikipedia.org/wiki/Kentucky_Derby" } ``` ### FAQ **Q: Why does today/yesterday return nothing?** Wikimedia publishes pageviews on a 1–2 day lag. Default to `daysAgo=3` if you want guaranteed data. **Q: Can I pull monthly totals?** This Actor uses the daily `top` endpoint. For monthly aggregates, use a 28–31 day range and aggregate downstream. **Q: Are bot views included?** The API filters out most automated traffic but is not perfectly clean. For research-grade exclusion, post-process against known bot lists. **Q: What's the difference between access types?** `all-access` is the union; the others slice by device class. ### Legal disclaimer This Actor uses the public Wikimedia REST API in accordance with the [Wikimedia API Terms of Use](https://wikimediafoundation.org/wiki/Terms_of_Use). Wikipedia content is released under CC BY-SA; pageview data is similarly open. Attribute Wikimedia Foundation in derivative analyses. Not affiliated with or endorsed by the Wikimedia Foundation. # Actor input Schema ## `project` (type: `string`): Wikimedia project domain. Examples: 'en.wikipedia', 'es.wikipedia', 'de.wikipedia', 'ja.wikipedia', 'en.wikisource', 'commons.wikimedia'. ## `access` (type: `string`): Device segment: 'all-access', 'desktop', 'mobile-web', or 'mobile-app'. ## `startDate` (type: `string`): Start date (YYYY-MM-DD). Leave blank to default to 3 days ago (Wikipedia publishes pageviews on a 1–2 day lag). ## `endDate` (type: `string`): End date inclusive (YYYY-MM-DD). Leave blank to use the same day as start. Max 31 days per run. ## `excludeMeta` (type: `boolean`): Exclude Main\_Page, Special:\*, and other non-article entries (recommended). ## `maxPerDay` (type: `integer`): How many top articles to keep per day (the API returns 1,000 per day). ## Actor input object example ```json { "project": "en.wikipedia", "access": "all-access", "startDate": "", "endDate": "", "excludeMeta": true, "maxPerDay": 100 } ``` # Actor output Schema ## `dataset` (type: `string`): No description # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = {}; // Run the Actor and wait for it to finish const run = await client.actor("compute-edge/wikipedia-pageviews-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = {} # Run the Actor and wait for it to finish run = client.actor("compute-edge/wikipedia-pageviews-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{}' | apify call compute-edge/wikipedia-pageviews-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=compute-edge/wikipedia-pageviews-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Wikipedia Pageviews Scraper — Trending Articles Daily", "description": "Extract Wikipedia's most-viewed articles by day or month with view counts, ranks, and article URLs. Filter by project language and access type. Track trending topics and public attention across any historical date range.", "version": "0.1", "x-build-id": "DS4axeYVGE8y1anzK" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/compute-edge~wikipedia-pageviews-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-compute-edge-wikipedia-pageviews-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/compute-edge~wikipedia-pageviews-scraper/runs": { "post": { "operationId": "runs-sync-compute-edge-wikipedia-pageviews-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/compute-edge~wikipedia-pageviews-scraper/run-sync": { "post": { "operationId": "run-sync-compute-edge-wikipedia-pageviews-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "properties": { "project": { "title": "Wikipedia Project", "type": "string", "description": "Wikimedia project domain. Examples: 'en.wikipedia', 'es.wikipedia', 'de.wikipedia', 'ja.wikipedia', 'en.wikisource', 'commons.wikimedia'.", "default": "en.wikipedia" }, "access": { "title": "Access Type", "type": "string", "description": "Device segment: 'all-access', 'desktop', 'mobile-web', or 'mobile-app'.", "default": "all-access" }, "startDate": { "title": "Start Date", "type": "string", "description": "Start date (YYYY-MM-DD). Leave blank to default to 3 days ago (Wikipedia publishes pageviews on a 1–2 day lag).", "default": "" }, "endDate": { "title": "End Date", "type": "string", "description": "End date inclusive (YYYY-MM-DD). Leave blank to use the same day as start. Max 31 days per run.", "default": "" }, "excludeMeta": { "title": "Exclude Meta Pages", "type": "boolean", "description": "Exclude Main_Page, Special:*, and other non-article entries (recommended).", "default": true }, "maxPerDay": { "title": "Max Articles Per Day", "minimum": 1, "maximum": 1000, "type": "integer", "description": "How many top articles to keep per day (the API returns 1,000 per day).", "default": 100 } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```