# ATP Ranking Scraper (`martin0925/scraper-atp-ranking`) Actor Extract ATP Tennis Rankings data for singles and doubles from the official ATP website. Get up-to-date player rankings, points, changes, and more. Customize the number of players and ranking type, export data (JSON, CSV, HTML), schedule runs, and integrate with other tools for seamless analysis. - **URL**: https://apify.com/martin0925/scraper-atp-ranking.md - **Developed by:** [Martin Janeček](https://apify.com/martin0925) (community) - **Categories:** Developer tools, Automation - **Stats:** 39 total users, 4 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing Pay per usage This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-usage ## 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 ## ATP Rankings Scraper 🎾 This actor scrapes ATP tennis rankings from the official ATP website, allowing you to parse both singles and doubles rankings with flexibility on the number of players you want to scrape. You can customize the actor's behavior by providing input parameters for the desired number of players and the ranking type (singles or doubles). ### Features πŸ”“ * Scrape ATP rankings for **singles** or **doubles** players. * Dynamically adjust the number of players to scrape (you can set a custom number of players). * Parse various details including rank, player name, nationality, age, points, points change, and more. ### Input Parameters πŸ–±οΈ This actor accepts the following input parameters: * **`number`** (optional, default: `100`): The number of players you want to scrape. For example, set `number = 200` to scrape the top 200 players. * **`url`** (optional, default: `'https://www.atptour.com/en/rankings/singles'`): The URL to scrape rankings from. The URL can be for singles or doubles rankings. If you want to scrape doubles rankings, use `'https://www.atptour.com/en/rankings/doubles'`. ### Example Input JSON: ```json { "url": "https://www.atptour.com/en/rankings/doubles", "number": 200 } ```` This example will scrape doubles rankings for the top 200 players. ### Output The scraper will return the following details for each player: - **rank**: Player's rank (integer). - **rankUpChange**: Rank change (integer). - **name**: Player's name (string). - **nationality**: Player's nationality (string). - **age**: Player's age (integer). - **points**: Player's total points (integer). - **pointsChange**: Change in points (integer). - **tournamentPlayed**: Number of tournaments played (integer). - **pointsDropping**: Points dropping from rankings (integer). - **pointsNext**: Points the player will earn next (integer). ### Example Output: ```json [ { "rank": 1, "rankUpChange": 0, "name": "Jannik Sinner", "nationality": "ita", "age": 23, "points": 10880, "pointsChange": 500, "tournamentPlayed": 16, "pointsDropping": 0, "pointsNext": 0 }, ... ] ``` ### Dependencies - **Apify SDK**: For orchestrating the actor and managing input/output. - **Crawlee**: A modern scraping library that integrates with Puppeteer for headless browser crawling. # Actor input Schema ## `url` (type: `string`): The base URL to scrape ATP rankings (can be singles or doubles). ## `number` (type: `integer`): The number of players to scrape (e.g., 100, 200, etc.). ## Actor input object example ```json { "url": "https://www.atptour.com/en/rankings/singles", "number": 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 = {}; // Run the Actor and wait for it to finish const run = await client.actor("martin0925/scraper-atp-ranking").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`πŸ’Ύ 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); }); // πŸ“š Want to learn more πŸ“–? Go to β†’ 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("martin0925/scraper-atp-ranking").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("πŸ’Ύ Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # πŸ“š Want to learn more πŸ“–? Go to β†’ https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{}' | apify call martin0925/scraper-atp-ranking --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=martin0925/scraper-atp-ranking", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "ATP Ranking Scraper", "description": "Extract ATP Tennis Rankings data for singles and doubles from the official ATP website. Get up-to-date player rankings, points, changes, and more. Customize the number of players and ranking type, export data (JSON, CSV, HTML), schedule runs, and integrate with other tools for seamless analysis.", "version": "1.0", "x-build-id": "nszW4aObU9cEmGM82" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/martin0925~scraper-atp-ranking/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-martin0925-scraper-atp-ranking", "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/martin0925~scraper-atp-ranking/runs": { "post": { "operationId": "runs-sync-martin0925-scraper-atp-ranking", "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/martin0925~scraper-atp-ranking/run-sync": { "post": { "operationId": "run-sync-martin0925-scraper-atp-ranking", "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": { "url": { "title": "URL", "type": "string", "description": "The base URL to scrape ATP rankings (can be singles or doubles).", "default": "https://www.atptour.com/en/rankings/singles" }, "number": { "title": "Number of Players", "minimum": 1, "type": "integer", "description": "The number of players to scrape (e.g., 100, 200, etc.).", "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 } } } } } } } } } } ```