# Tinder Profile Scraper (`datapilot/tinder-profile-scraper`) Actor Tinder Profile Generator Actor creates realistic user profiles from usernames. It includes bio, interests, location, age, social links, and activity status. Uses random data for authenticity, supports proxies, and outputs structured JSON profiles ready for datasets or testing. - **URL**: https://apify.com/datapilot/tinder-profile-scraper.md - **Developed by:** [Data Pilot](https://apify.com/datapilot) (community) - **Categories:** Other - **Stats:** 82 total users, 13 monthly users, 100.0% runs succeeded, 1 bookmarks - **User rating**: No ratings yet ## Pricing $8.00/month + usage To use this Actor, you pay a monthly rental fee to the developer. The rent is subtracted from your prepaid usage every month after the free trial period.You also pay for the Apify platform usage, which gets cheaper the higher Apify subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#rental-actors ## 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 ## Tinder Profile Scraper ๐Ÿš€ **Tinder Profile Scraper** is a specialized Apify Actor designed to extract **Tinder Profile** data based on usernames. This tool provides essential **Tinder Profile** information, including usernames, profile names, profile URLs, and snippets for any Tinder username. Whether you're building **Tinder Profile** databases, conducting dating app research, or testing **Tinder Profile** integrations, the Tinder Profile Scraper delivers **Tinder Profile** data efficiently. With residential proxy support, the Tinder Profile Scraper ensures reliable generation of **Tinder Profile** data. It focuses on key **Tinder Profile** metrics like profile URLs and platform information, making it an essential tool for **Tinder Profile** analysis and social media research. ### ๐Ÿ”ฅ Features - **Essential Tinder Profile Extraction** โ€“ Generates basic **Tinder Profile** data, including usernames, profile names, and profile URLs for any username. - **Quick Profile Lookup** โ€“ Instantly creates **Tinder Profile** entries with minimal information for rapid **Tinder Profile** data collection. - **Batch Processing** โ€“ Processes multiple **Tinder Profile** usernames in a single run for efficient **Tinder Profile** data collection. - **Platform Integration** โ€“ Provides direct **Tinder Profile** URLs and platform information for each entry. - **Snippet Generation** โ€“ Creates descriptive snippets for each **Tinder Profile** to aid in identification. - **Residential Proxy Support** โ€“ Utilizes Apify's residential proxies to bypass restrictions and ensure high success rates for **Tinder Profile** generation. - **Error Handling** โ€“ Robust logging for issues during **Tinder Profile** generation. - **Dataset Integration** โ€“ Automatically uploads **Tinder Profile** data to your Apify dataset for easy export and analysis. ### โš™๏ธ How It Works The Tinder Profile Scraper takes one or more usernames as input and generates **Tinder Profile** data based on the username. It creates **Tinder Profile** entries with formatted display names, profile URLs, and descriptive snippets. The scraper returns structured **Tinder Profile** data for each username, providing a fast way to gather **Tinder Profile** information for research and testing. **Key benefits for Tinder Profile analysis:** - Quickly generate **Tinder Profile** data for testing and development. - Build **Tinder Profile** databases for dating app research. - Create **Tinder Profile** listings for comparison and analysis. ### ๐Ÿ“ฅ Input The actor accepts the following input parameters: | Field | Type | Description | Default | |-------------|-----------------|-----------------------------------------------------------------------------|----------| | `usernames` | String or Array | List of Tinder usernames to generate profiles for, comma-separated or new-line separated (e.g., "johndoe, janedoe"). | Required | ### ๐Ÿš€ Quick Start Open in Apify Console โ€“ visit the Actor page and click Try for free. Enter usernames โ€“ provide Tinder usernames separated by commas or new lines. Click Start โ€“ the Actor will generate Tinder Profile data. View Results โ€“ check the dataset for extracted Tinder Profile information. Export โ€“ download the results as JSON, CSV, or Excel. You can also call this Actor programmatically via Apify SDK or REST API โ€“ ideal for automated Tinder Profile data collection. ### ๐Ÿ’Ž Why This Scraper? | Feature | Benefit | |---------|---------| | โœ… Instant profile generation | Get Tinder Profile data in seconds. | | โœ… Clean formatting | Consistent display names for Tinder Profiles. | | โœ… Batch processing | Handle multiple Tinder Profile usernames at once. | | โœ… Direct profile URLs | Easy access to Tinder Profile pages. | | โœ… Descriptive snippets | Quick identification of Tinder Profiles. | | โœ… Apify ecosystem | Seamless integration with other Actors, triggers, and webhooks. | ### ๐ŸŽฏ Use Cases Tinder Profile Research โ€“ Gather Tinder Profile data for academic or market research. Dating App Testing โ€“ Test applications using Tinder Profile data. Social Media Analysis โ€“ Analyze Tinder Profile trends and patterns. Profile Database Building โ€“ Create comprehensive Tinder Profile databases. App Development โ€“ Use Tinder Profile data for prototyping and development. Mock Data Generation โ€“ Generate mock Tinder Profile data for testing. ### ๐Ÿ“ฆ Changelog Initial release of Tinder Profile Scraper Basic Tinder Profile data generation from usernames Display name formatting Profile URL construction Snippet generation Thumbnail integration Batch processing support Automatic dataset upload Full Apify Actor integration ### ๐Ÿง‘โ€๐Ÿ’ป Support & Feedback Issues & Ideas: Open a ticket on the Apify Actor issue tracker Documentation: Visit Apify Docs for comprehensive platform guides Community: Join the Apify community forum for discussions and support Bug Reports: Submit detailed bug reports through the issue tracker Feature Requests: Suggest new features to improve the scraper ### ๐Ÿ’ฐ Pricing Free for basic usage on Apify platform Paid plans available for higher limits and priority support Proxy credits consumed if residential proxy is enabled Disclaimer: Tinder Profile Scraper is provided as-is for research and testing purposes. Users are responsible for ensuring their usage complies with Tinder's terms of service and applicable laws. ### ๐ŸŽ‰ Get Started Today Begin generating Tinder Profile data now! Use Tinder Profile Scraper for: ๐Ÿ“Š Profile Research ๐Ÿงช App Testing ๐Ÿ“š Database Building ๐Ÿ” Social Media Analysis ๐Ÿ’ก Development Prototyping Perfect for: Researchers Developers Data Scientists Marketers Testers Version: 1.0.0 Status: Active Development Support: 24/7 Customer Support Available Platform: Apify ### ๐Ÿ“š Related Tools For comprehensive social media data extraction, explore our full suite of tools: Instagram Video Analytics Scraper Download HTML from URLs Google News Scraper # Actor input Schema ## `usernames` (type: `string`): Enter Tinder usernames (comma-separated, without @) ## `includeBio` (type: `boolean`): Add sample bio text to each profile ## `includeLocation` (type: `boolean`): Add sample location to each profile ## `includeAge` (type: `boolean`): Add sample age to each profile ## `useApifyProxy` (type: `boolean`): Use Apify Proxy (enabled by default) ## `apifyProxyGroups` (type: `array`): Select proxy type ## Actor input object example ```json { "usernames": "johndoe, janedoe", "includeBio": true, "includeLocation": true, "includeAge": true, "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } ```` # 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 = { "usernames": "johndoe, janedoe" }; // Run the Actor and wait for it to finish const run = await client.actor("datapilot/tinder-profile-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`๐Ÿ’พ 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); }); // ๐Ÿ“š Want to learn more ๐Ÿ“–? Go to โ†’ 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 = { "usernames": "johndoe, janedoe" } # Run the Actor and wait for it to finish run = client.actor("datapilot/tinder-profile-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("๐Ÿ’พ Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # ๐Ÿ“š Want to learn more ๐Ÿ“–? Go to โ†’ https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "usernames": "johndoe, janedoe" }' | apify call datapilot/tinder-profile-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=datapilot/tinder-profile-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Tinder Profile Scraper", "description": "Tinder Profile Generator Actor creates realistic user profiles from usernames. It includes bio, interests, location, age, social links, and activity status. Uses random data for authenticity, supports proxies, and outputs structured JSON profiles ready for datasets or testing.", "version": "0.0", "x-build-id": "9xOVMZD5DjCyJWFud" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/datapilot~tinder-profile-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-datapilot-tinder-profile-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/datapilot~tinder-profile-scraper/runs": { "post": { "operationId": "runs-sync-datapilot-tinder-profile-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/datapilot~tinder-profile-scraper/run-sync": { "post": { "operationId": "run-sync-datapilot-tinder-profile-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "required": [ "usernames" ], "properties": { "usernames": { "title": "Tinder Usernames", "type": "string", "description": "Enter Tinder usernames (comma-separated, without @)" }, "includeBio": { "title": "Include Sample Bio", "type": "boolean", "description": "Add sample bio text to each profile", "default": true }, "includeLocation": { "title": "Include Sample Location", "type": "boolean", "description": "Add sample location to each profile", "default": true }, "includeAge": { "title": "Include Sample Age", "type": "boolean", "description": "Add sample age to each profile", "default": true }, "useApifyProxy": { "title": "Use Apify Proxy", "type": "boolean", "description": "Use Apify Proxy (enabled by default)", "default": true }, "apifyProxyGroups": { "title": "Proxy Groups", "uniqueItems": true, "type": "array", "description": "Select proxy type", "items": { "type": "string", "enum": [ "RESIDENTIAL", "DATACENTER", "GOOGLE" ] }, "default": [ "RESIDENTIAL" ] } } }, "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 } } } } } } } } } } ```