# SPARQL Query Runner (`datamule/sparql-query-runner`) Actor Point at ANY public SPARQL endpoint (Wikidata, DBpedia, UniProt, government & museum Linked-Open-Data) and run a query over the W3C SPARQL 1.1 Protocol. SELECT flattens to dynamic columns per binding, ASK to a boolean, CONSTRUCT/DESCRIBE to triples. One actor, any knowledge graph. Pay per binding. - **URL**: https://apify.com/datamule/sparql-query-runner.md - **Developed by:** [Datamule](https://apify.com/datamule) (community) - **Categories:** Developer tools, Business - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $0.35 / 1,000 bindings This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. 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 ## SPARQL Query Runner **Point at ANY public SPARQL endpoint, send a query, get a dataset.** One actor speaks to every knowledge graph in the Linked-Open-Data world over the W3C **SPARQL 1.1 Protocol** — no per-site scraper, no host enumeration. SPARQL is *the* query language of the semantic web. Wikidata, DBpedia, UniProt / EBI (life sciences), Bio2RDF, the EU / EEA and national-library / museum Linked-Open-Data endpoints, and thousands of government open-data triplestores all serve the identical protocol. Give this actor an endpoint URL and a SPARQL query and it turns the result straight into rows. ### What it does Sends your query to the endpoint with `Accept: application/sparql-results+json` and flattens the response. The output shape follows the **query form**: | Query form | Output | |---|---| | **SELECT** | One row per result binding. Each SELECT variable becomes a **top-level column** equal to its `.value` — the columns are literally your query's variables. A variable left **unbound** in a binding (e.g. an `OPTIONAL` that didn't match) is `null`. The full typed binding (`uri` / `literal` / `bnode`, `datatype`, `xml:lang`) is preserved losslessly in `_raw`. | | **ASK** | A single row: `{ "_queryType": "ask", "boolean": true/false }`. | | **CONSTRUCT** / **DESCRIBE** | Best-effort: the query is sent with `Accept: application/n-triples` and one row is emitted per triple (`subject` / `predicate` / `object`). If the endpoint won't return N-Triples, the source is skipped with a warning (never fabricated). | Every row carries `_endpoint`, `_queryType`, `_rowIndex` and `_raw`. ### Input | Field | Description | |---|---| | `endpoint` | A SPARQL endpoint URL, e.g. `https://query.wikidata.org/sparql`. Required unless `endpoints` is given. | | `endpoints` | Optional: run the **same** query across several endpoints (mirrors / cross-KG). Each row is tagged with its `_endpoint`. | | `query` | **Required.** The SPARQL query. SELECT / ASK are primary; CONSTRUCT / DESCRIBE best-effort. | | `method` | `GET` (default) or `POST` (for queries too long for a URL). | | `maxRecords` | Optional global cap on rows across all endpoints (one billable event per row). | | `userAgent` | Optional override. A descriptive User-Agent is sent by default — **required in practice for Wikidata**, which blocks blank / generic UAs. | | `defaultGraphUri` / `namedGraphUri` | Optional SPARQL-protocol dataset graph parameters. | | `timeoutSecs` | Optional read timeout (default 90s; endpoints enforce their own server-side caps). | | `bearer` / `extraHeaders` | Optional, for auth-gated deployments. Never required, never logged. | ### Examples **All-purpose portable query** (works on almost any endpoint): ```json { "endpoint": "https://dbpedia.org/sparql", "query": "SELECT ?s ?p ?o WHERE { ?s ?p ?o } LIMIT 5" } ```` **Wikidata — countries and their population** (dynamic columns `country`, `countryLabel`, `population`): ```json { "endpoint": "https://query.wikidata.org/sparql", "query": "SELECT ?country ?countryLabel ?population WHERE { ?country wdt:P31 wd:Q3624078 . OPTIONAL { ?country wdt:P1082 ?population } SERVICE wikibase:label { bd:serviceParam wikibase:language \"en\" } } LIMIT 50" } ``` ### Resilience An endpoint that returns a 4xx/5xx, times out, or answers with a non-SPARQL body (an HTML error / anti-bot page, a SPARQL syntax-error response) is **skipped with a warning** and the batch continues. A run where **every** endpoint is skipped **fails** so nothing broken ships. A reachable endpoint that returns **0 bindings** yields 0 rows and a clean success. ### Pricing Pay-per-event: one **binding** charge per emitted row. # Actor input Schema ## `endpoint` (type: `string`): The URL of ANY public SPARQL endpoint (W3C SPARQL 1.1 Protocol). One actor speaks to all of them — Wikidata (https://query.wikidata.org/sparql), DBpedia (https://dbpedia.org/sparql), UniProt (https://sparql.uniprot.org/sparql), Bio2RDF, EU / national-library / museum Linked-Open-Data, government open-data endpoints, and any self-hosted triplestore. Required unless you use "Endpoints" below to run across several. For an auth-gated deployment, add a Bearer token or headers below. ## `endpoints` (type: `array`): Optional: run the SAME query across multiple SPARQL endpoints (mirrors, or several knowledge graphs at once). Each output row is tagged with its \_endpoint. Use this OR the single "Endpoint" above (at least one is required). An endpoint that is unreachable, auth-gated, or returns a non-SPARQL body is skipped with a warning and the batch continues. ## `query` (type: `string`): The SPARQL query to run. SELECT and ASK are the primary forms; CONSTRUCT and DESCRIBE are best-effort (emitted as one row per triple via N-Triples). A portable query that works on almost any endpoint: SELECT ?s ?p ?o WHERE { ?s ?p ?o } LIMIT 5. The output COLUMNS of a SELECT are exactly your query's variables, so shape the result by shaping the query. ## `method` (type: `string`): How to send the query. GET (default) puts the query in the URL — fine for most queries. POST sends it as an application/x-www-form-urlencoded body — use it for queries too long for a URL. ## `maxRecords` (type: `integer`): A GLOBAL cap on the number of rows emitted across ALL endpoints (each row is one result binding / triple and one billable event). Reached mid-endpoint, the run stops deterministically. Leave empty to emit every binding the query returns — most endpoints also enforce their own server-side LIMIT, and you can add LIMIT to the query itself. ## `userAgent` (type: `string`): Optional override for the request User-Agent. A descriptive User-Agent is sent by default — REQUIRED in practice for Wikidata, which blocks blank / generic UAs with 403 / 429. Only override if a specific endpoint asks you to identify differently. ## `defaultGraphUri` (type: `string`): Optional SPARQL-protocol default-graph-uri parameter — sets the default RDF dataset the query runs against on endpoints that expose named graphs. Leave empty for the endpoint's own default. ## `namedGraphUri` (type: `array`): Optional SPARQL-protocol named-graph-uri parameter(s) — one or more named graphs to add to the dataset the query runs against. Leave empty unless the endpoint documents named graphs. ## `timeoutSecs` (type: `integer`): How long to wait for the endpoint to answer (default 90). Endpoints also enforce their own server-side query timeouts (Wikidata ~60s), so a very large query may still be cut off by the server. ## `bearer` (type: `string`): Optional bearer token for an auth-gated SPARQL endpoint (sent as Authorization: Bearer \*\*\*). NOT required for public endpoints. Never logged. ## `extraHeaders` (type: `object`): Optional extra HTTP headers as a JSON object, e.g. {"X-Api-Key": "..."} for a gateway-fronted endpoint. Not required for public endpoints. Header values are never logged. ## Actor input object example ```json { "endpoint": "https://dbpedia.org/sparql", "query": "SELECT ?s ?p ?o WHERE { ?s ?p ?o } LIMIT 5", "method": "GET", "maxRecords": 1000 } ``` # Actor output Schema ## `results` (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 = { "endpoint": "https://dbpedia.org/sparql", "query": "SELECT ?s ?p ?o WHERE { ?s ?p ?o } LIMIT 5", "maxRecords": 1000 }; // Run the Actor and wait for it to finish const run = await client.actor("datamule/sparql-query-runner").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 = { "endpoint": "https://dbpedia.org/sparql", "query": "SELECT ?s ?p ?o WHERE { ?s ?p ?o } LIMIT 5", "maxRecords": 1000, } # Run the Actor and wait for it to finish run = client.actor("datamule/sparql-query-runner").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 '{ "endpoint": "https://dbpedia.org/sparql", "query": "SELECT ?s ?p ?o WHERE { ?s ?p ?o } LIMIT 5", "maxRecords": 1000 }' | apify call datamule/sparql-query-runner --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=datamule/sparql-query-runner", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "SPARQL Query Runner", "description": "Point at ANY public SPARQL endpoint (Wikidata, DBpedia, UniProt, government & museum Linked-Open-Data) and run a query over the W3C SPARQL 1.1 Protocol. SELECT flattens to dynamic columns per binding, ASK to a boolean, CONSTRUCT/DESCRIBE to triples. One actor, any knowledge graph. Pay per binding.", "version": "0.1", "x-build-id": "idXMosBEGPSQHWz9Z" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/datamule~sparql-query-runner/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-datamule-sparql-query-runner", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/datamule~sparql-query-runner/runs": { "post": { "operationId": "runs-sync-datamule-sparql-query-runner", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/datamule~sparql-query-runner/run-sync": { "post": { "operationId": "run-sync-datamule-sparql-query-runner", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "required": [ "query" ], "properties": { "endpoint": { "title": "SPARQL endpoint URL", "type": "string", "description": "The URL of ANY public SPARQL endpoint (W3C SPARQL 1.1 Protocol). One actor speaks to all of them — Wikidata (https://query.wikidata.org/sparql), DBpedia (https://dbpedia.org/sparql), UniProt (https://sparql.uniprot.org/sparql), Bio2RDF, EU / national-library / museum Linked-Open-Data, government open-data endpoints, and any self-hosted triplestore. Required unless you use \"Endpoints\" below to run across several. For an auth-gated deployment, add a Bearer token or headers below." }, "endpoints": { "title": "Endpoints (run the same query across several)", "type": "array", "description": "Optional: run the SAME query across multiple SPARQL endpoints (mirrors, or several knowledge graphs at once). Each output row is tagged with its _endpoint. Use this OR the single \"Endpoint\" above (at least one is required). An endpoint that is unreachable, auth-gated, or returns a non-SPARQL body is skipped with a warning and the batch continues.", "items": { "type": "string" } }, "query": { "title": "SPARQL query", "type": "string", "description": "The SPARQL query to run. SELECT and ASK are the primary forms; CONSTRUCT and DESCRIBE are best-effort (emitted as one row per triple via N-Triples). A portable query that works on almost any endpoint: SELECT ?s ?p ?o WHERE { ?s ?p ?o } LIMIT 5. The output COLUMNS of a SELECT are exactly your query's variables, so shape the result by shaping the query." }, "method": { "title": "HTTP method", "enum": [ "GET", "POST" ], "type": "string", "description": "How to send the query. GET (default) puts the query in the URL — fine for most queries. POST sends it as an application/x-www-form-urlencoded body — use it for queries too long for a URL.", "default": "GET" }, "maxRecords": { "title": "Max records (global cap)", "minimum": 1, "type": "integer", "description": "A GLOBAL cap on the number of rows emitted across ALL endpoints (each row is one result binding / triple and one billable event). Reached mid-endpoint, the run stops deterministically. Leave empty to emit every binding the query returns — most endpoints also enforce their own server-side LIMIT, and you can add LIMIT to the query itself." }, "userAgent": { "title": "User-Agent override", "type": "string", "description": "Optional override for the request User-Agent. A descriptive User-Agent is sent by default — REQUIRED in practice for Wikidata, which blocks blank / generic UAs with 403 / 429. Only override if a specific endpoint asks you to identify differently." }, "defaultGraphUri": { "title": "Default graph URI", "type": "string", "description": "Optional SPARQL-protocol default-graph-uri parameter — sets the default RDF dataset the query runs against on endpoints that expose named graphs. Leave empty for the endpoint's own default." }, "namedGraphUri": { "title": "Named graph URI(s)", "type": "array", "description": "Optional SPARQL-protocol named-graph-uri parameter(s) — one or more named graphs to add to the dataset the query runs against. Leave empty unless the endpoint documents named graphs.", "items": { "type": "string" } }, "timeoutSecs": { "title": "Read timeout (seconds)", "minimum": 1, "maximum": 600, "type": "integer", "description": "How long to wait for the endpoint to answer (default 90). Endpoints also enforce their own server-side query timeouts (Wikidata ~60s), so a very large query may still be cut off by the server." }, "bearer": { "title": "Bearer token", "type": "string", "description": "Optional bearer token for an auth-gated SPARQL endpoint (sent as Authorization: Bearer ***). NOT required for public endpoints. Never logged." }, "extraHeaders": { "title": "Extra request headers", "type": "object", "description": "Optional extra HTTP headers as a JSON object, e.g. {\"X-Api-Key\": \"...\"} for a gateway-fronted endpoint. Not required for public endpoints. Header values are never logged." } } }, "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 } } } } } } } } } } ```