# WikiArt Scraper - Visual Art Encyclopedia (`lulzasaur/wikiart-scraper`) Actor Scrape artworks from wikiart.org. Search by artist name or art style. Get titles, years, styles, genres, mediums, museum locations, image URLs, and tags for 250K+ artworks. - **URL**: https://apify.com/lulzasaur/wikiart-scraper.md - **Developed by:** [lulz bot](https://apify.com/lulzasaur) (community) - **Categories:** E-commerce - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $10.00 / 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 ## WikiArt Scraper Extract artwork data from [WikiArt.org](https://www.wikiart.org/), the world's largest visual art encyclopedia with 250,000+ artworks from 3,000+ artists. ### What does WikiArt Scraper do? This scraper extracts structured artwork data from WikiArt.org. Search by artist name or art style to get detailed metadata for paintings, sculptures, and other visual artworks. **For each artwork, you get:** - Title, artist name, and year - Art style (e.g., Impressionism, Cubism, Realism) - Genre (e.g., landscape, portrait, still life) - Medium and technique - Physical dimensions - Museum/gallery location - High-resolution image URL - Tags and description - Direct WikiArt URL ### How to use 1. **Add search queries** -- Enter artist names (e.g., "monet", "van gogh", "picasso") or art styles (e.g., "impressionism", "cubism") in the Search Queries field. 2. **Set max artworks** -- Choose how many artworks to scrape (default: 100). WikiArt has hundreds or thousands of works per artist. 3. **Enable full details** (optional) -- Turn on "Scrape Full Details" to get style, genre, medium, dimensions, location, tags, and description for each artwork. This is slower but provides much richer data. 4. **Run the scraper** -- Click "Start" and the scraper will resolve your queries, fetch artwork listings, and optionally enrich each with full metadata. ### Input examples #### Scrape Monet's artworks (basic) ```json { "searchQueries": ["monet"], "maxListings": 50 } ```` #### Multiple artists with full details ```json { "searchQueries": ["van gogh", "rembrandt", "vermeer"], "maxListings": 200, "scrapeDetails": true } ``` #### Search by art style ```json { "searchQueries": ["impressionism", "art nouveau"], "maxListings": 100, "scrapeDetails": true } ``` ### Output example Each artwork in the dataset looks like this: ```json { "title": "Water Lilies", "artist": "Claude Monet", "artistUrl": "https://www.wikiart.org/en/claude-monet", "year": 1906, "yearAsString": "1906", "style": "Impressionism", "genre": "flower painting", "medium": "Oil on canvas", "dimensions": "89.9 x 94.1 cm", "location": "Art Institute of Chicago, Chicago, IL, US", "imageUrl": "https://uploads0.wikiart.org/images/claude-monet/water-lilies-1906.jpg!Large.jpg", "tags": "flowers-and-plants, Water lilies", "description": null, "url": "https://www.wikiart.org/en/claude-monet/water-lilies-1906", "contentId": 212956, "searchQuery": "monet", "scrapedAt": "2026-04-25T12:00:00.000Z" } ``` ### How it works 1. **Artist resolution** -- Each search query is first checked against WikiArt's autocomplete API to find matching artists. 2. **Artwork listing** -- If an artist is found, all their artworks are fetched via WikiArt's internal API. 3. **Search fallback** -- If no artist matches, the scraper falls back to WikiArt's general search. 4. **Detail enrichment** -- When "Scrape Full Details" is enabled, each artwork's detail endpoint is queried for style, genre, medium, dimensions, location, tags, and description. ### Tips - **Basic mode is fast** -- Without details, you can scrape hundreds of artworks in seconds since the artist API returns all works at once. - **Detail mode is thorough** -- Enabling details adds ~0.3s per artwork but gives you rich metadata (style, genre, medium, location, tags). - **Artist names work best** -- The scraper resolves artist names via autocomplete, so "monet" and "claude monet" both work. - **Art styles also work** -- Searching for "impressionism" or "cubism" returns artworks from the general search index. ### Pricing This scraper uses pay-per-event pricing. You are charged $0.005 per artwork scraped. | Artworks | Cost | |----------|------| | 100 | $0.50 | | 500 | $2.50 | | 1,000 | $5.00 | | 5,000 | $25.00 | ### Integrations Connect WikiArt Scraper with other apps and services using [Apify integrations](https://apify.com/integrations). Export data to Google Sheets, Slack, Zapier, Make, GitHub, and more. Or use the [Apify API](https://docs.apify.com/api) to access your data programmatically. # Actor input Schema ## `searchQueries` (type: `array`): Artist names or art styles to search (e.g. "monet", "van gogh", "impressionism"). Each query is resolved via WikiArt's API. ## `maxListings` (type: `integer`): Maximum total number of artworks to scrape across all queries (1-10000). ## `scrapeDetails` (type: `boolean`): Fetch detailed metadata for each artwork (style, genre, medium, dimensions, location, tags, description). Slower but much richer data. ## `proxyConfiguration` (type: `object`): Optional proxy configuration for requests. ## Actor input object example ```json { "searchQueries": [ "monet" ], "maxListings": 100, "scrapeDetails": false } ``` # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "searchQueries": [ "monet" ] }; // Run the Actor and wait for it to finish const run = await client.actor("lulzasaur/wikiart-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${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 = { "searchQueries": ["monet"] } # Run the Actor and wait for it to finish run = client.actor("lulzasaur/wikiart-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 '{ "searchQueries": [ "monet" ] }' | apify call lulzasaur/wikiart-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=lulzasaur/wikiart-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "WikiArt Scraper - Visual Art Encyclopedia", "description": "Scrape artworks from wikiart.org. Search by artist name or art style. Get titles, years, styles, genres, mediums, museum locations, image URLs, and tags for 250K+ artworks.", "version": "1.0", "x-build-id": "SPs7PzfJYbCMir1Wp" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/lulzasaur~wikiart-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-lulzasaur-wikiart-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/lulzasaur~wikiart-scraper/runs": { "post": { "operationId": "runs-sync-lulzasaur-wikiart-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/lulzasaur~wikiart-scraper/run-sync": { "post": { "operationId": "run-sync-lulzasaur-wikiart-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "searchQueries": { "title": "Search Queries", "type": "array", "description": "Artist names or art styles to search (e.g. \"monet\", \"van gogh\", \"impressionism\"). Each query is resolved via WikiArt's API.", "default": [], "items": { "type": "string" } }, "maxListings": { "title": "Max Artworks", "minimum": 1, "maximum": 10000, "type": "integer", "description": "Maximum total number of artworks to scrape across all queries (1-10000).", "default": 100 }, "scrapeDetails": { "title": "Scrape Full Details", "type": "boolean", "description": "Fetch detailed metadata for each artwork (style, genre, medium, dimensions, location, tags, description). Slower but much richer data.", "default": false }, "proxyConfiguration": { "title": "Proxy Configuration", "type": "object", "description": "Optional proxy configuration for requests." } } }, "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 } } } } } } } } } } ```