# Parkrun Results Scraper - Athlete History & Events (`lulzasaur/parkrun-scraper`) Actor Scrape Parkrun for athlete results history, event latest results, personal bests, age grading, and run statistics. Supports all Parkrun countries. - **URL**: https://apify.com/lulzasaur/parkrun-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 ## Parkrun Results Scraper Scrape [Parkrun](https://www.parkrun.com/) for athlete results history and event results from the world's largest free weekly running events. ### Features - **Athlete History**: Full run history for any athlete by their Parkrun athlete number - **Event Results**: Latest results from any Parkrun event - **Global Coverage**: Supports all 18+ Parkrun country domains (UK, US, Australia, South Africa, etc.) - **Rich Data**: Times, positions, age grading, personal bests, year bests, summary stats ### Input | Field | Type | Description | |-------|------|-------------| | `mode` | string | `athlete-history` (default) or `event-results` | | `athleteNumbers` | string[] | Parkrun athlete IDs (for athlete mode) | | `eventNames` | string[] | Event URL slugs like `bushy` or `regents` | | `country` | string | Country domain (default: `org.uk`) | | `maxResults` | integer | Max results per athlete/event (default: 100) | | `proxyConfiguration` | object | Optional proxy settings | ### Supported Countries UK, USA, Australia, South Africa, New Zealand, Canada, Ireland, Italy, France, Poland, Sweden, Denmark, Finland, Germany, Norway, Singapore, Japan, Malaysia ### Output Example (Athlete History) ```json { "athleteNumber": "123456", "event": "Bushy Park", "date": "15/03/2025", "runNumber": 576, "position": 63, "time": "24:09", "ageGrade": "62.94%", "isPB": "No", "eventUrl": "https://www.parkrun.org.uk/bushy/results/576/" } ```` ### Use Cases - Running performance tracking and analysis - Parkrun tourism planning (finding events to visit) - Running club statistics and leaderboards - Personal fitness data export - Age-graded performance comparison ### Cost This actor uses pay-per-event pricing at $0.005 per result. # Actor input Schema ## `mode` (type: `string`): What to scrape: athlete result history or latest event results. ## `athleteNumbers` (type: `array`): Parkrun athlete numbers for 'athlete-history' mode. e.g. \["123456", "789012"] ## `eventNames` (type: `array`): Parkrun event names (URL slugs) for 'event-results' mode. e.g. \["regents", "bushy", "centralparkny"]. Find yours at parkrun.com/events ## `country` (type: `string`): Parkrun country domain. Different countries use different subdomains. ## `maxResults` (type: `integer`): Maximum number of results to scrape per athlete/event (1-1000). ## `proxyConfiguration` (type: `object`): Optional proxy configuration. ## Actor input object example ```json { "mode": "athlete-history", "athleteNumbers": [ "123456" ], "eventNames": [ "bushy" ], "country": "org.uk", "maxResults": 100 } ``` # 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 = { "athleteNumbers": [ "123456" ], "eventNames": [ "bushy" ] }; // Run the Actor and wait for it to finish const run = await client.actor("lulzasaur/parkrun-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 = { "athleteNumbers": ["123456"], "eventNames": ["bushy"], } # Run the Actor and wait for it to finish run = client.actor("lulzasaur/parkrun-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 '{ "athleteNumbers": [ "123456" ], "eventNames": [ "bushy" ] }' | apify call lulzasaur/parkrun-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=lulzasaur/parkrun-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Parkrun Results Scraper - Athlete History & Events", "description": "Scrape Parkrun for athlete results history, event latest results, personal bests, age grading, and run statistics. Supports all Parkrun countries.", "version": "1.0", "x-build-id": "xJHh48X1JNNV4zLaA" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/lulzasaur~parkrun-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-lulzasaur-parkrun-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~parkrun-scraper/runs": { "post": { "operationId": "runs-sync-lulzasaur-parkrun-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~parkrun-scraper/run-sync": { "post": { "operationId": "run-sync-lulzasaur-parkrun-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": { "mode": { "title": "Scrape Mode", "enum": [ "athlete-history", "event-results" ], "type": "string", "description": "What to scrape: athlete result history or latest event results.", "default": "athlete-history" }, "athleteNumbers": { "title": "Athlete Numbers", "type": "array", "description": "Parkrun athlete numbers for 'athlete-history' mode. e.g. [\"123456\", \"789012\"]", "items": { "type": "string" } }, "eventNames": { "title": "Event Names", "type": "array", "description": "Parkrun event names (URL slugs) for 'event-results' mode. e.g. [\"regents\", \"bushy\", \"centralparkny\"]. Find yours at parkrun.com/events", "items": { "type": "string" } }, "country": { "title": "Country Domain", "enum": [ "org.uk", "us", "com.au", "co.za", "co.nz", "ca", "ie", "it", "fr", "pl", "se", "dk", "fi", "de", "no", "sg", "jp", "my" ], "type": "string", "description": "Parkrun country domain. Different countries use different subdomains.", "default": "org.uk" }, "maxResults": { "title": "Max Results", "minimum": 1, "maximum": 1000, "type": "integer", "description": "Maximum number of results to scrape per athlete/event (1-1000).", "default": 100 }, "proxyConfiguration": { "title": "Proxy Configuration", "type": "object", "description": "Optional proxy configuration." } } }, "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 } } } } } } } } } } ```