# ⚑Vimeo Profile Scraper πŸ‘€ (`scrapearchitect/vimeo-profile-scraper`) Actor πŸš€ Scrape Vimeo profiles πŸ‘€, bios πŸ“, HD images πŸ–ΌοΈ + raw JSON-LD 🧩! Bulk URLs πŸ”„, timestamps ⏰, Apify storage πŸ”’. For recruiters πŸ‘©πŸ’», analysts πŸ“Š, archivists πŸ“š. Fast ⚑, encrypted πŸ›‘οΈ! ⚑ Vimeo Profile Scraper πŸ‘€ - **URL**: https://apify.com/scrapearchitect/vimeo-profile-scraper.md - **Developed by:** [Scrape Architect](https://apify.com/scrapearchitect) (community) - **Categories:** Social media, Developer tools, Other - **Stats:** 8 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing $5.00/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 --- ## πŸš€ Vimeo Profile Scraper – Bulk Data Extraction + Rich Metadata 🌟 **Scrape Vimeo profiles at scale!** Get creator bios πŸ“, profile images πŸ–ΌοΈ, raw JSON-LD schemas 🧩, and timestamps ⏰. Perfect for talent discovery 🎬, competitor analysis πŸ”, and data pipelines πŸ“Š. --- ### 🌟 Overview Need to analyze Vimeo creators or build filmmaker databases? This actor delivers: βœ… **Full profile data**: Bios, names, profile URLs βœ… **Schema.org metadata**: Raw JSON-LD output βœ… **Bulk processing**: 100+ profiles per run βœ… **High-res images**: 640px profile pictures Ideal for casting directors πŸ‘©πŸ’Ό, film researchers πŸŽ₯, and HR teams πŸ‘”! > ⚑ Avg. runtime: 10-30 seconds per profile > πŸ›‘οΈ Auto-retries & proxy rotation built-in --- ### πŸ”₯ Key Features #### πŸ§‘πŸŽ¨ Profile Data Extraction - **Creator Bios**: Full descriptions with formatting - **Verification**: Profile URLs match Vimeo's official patterns - **Image Capture**: Direct links to profile pictures - **Schema.org Data**: Raw JSON-LD markup parsing #### πŸ› οΈ Technical Features - **Bulk Mode**: Process entire creator lists - **Timestamps**: Exact scrape times (ISO 8601) - **Data Freshness**: Always latest profile versions #### πŸš€ Advanced Capabilities - **Proxy Support**: Residential IPs for uninterrupted scraping - **Auto-Pagination**: Handles profile galleries - **Rate Limit Bypass**: Smart request throttling --- ### βš™οΈ Input Configuration ```json { "profile_urls": [ { "url": "https://vimeo.com/user46243372", "method": "GET" } ] } ```` #### πŸ“‹ Input Fields | Parameter | Type | Description |\ |-----------|------|-------------|\ | `profile_urls` | Array | Vimeo profile URLs (1-100+ items) |\ | `url` | String | Valid Vimeo profile link |\ | `method` | String | `GET` (HTTP method) | *** ### πŸ“€ Output Example ```json { "channel_url": "https://vimeo.com/user46243372", "name": "Ragini Bhasin", "description": "South Asian writer/director... feminist lens.", "profile_image": "https://i.vimeocdn.com/portrait/79167913_640x640...", "raw_json_ld": { "@type": "Person", "image": "https://i.vimeocdn.com/portrait/79167913_640x640...", "potentialAction": {"@type": "ViewAction"} }, "scraped_at": "2025-05-17T17:54:33.027022Z" } ``` #### πŸ—οΈ Key Output Fields **Core Data**\ | Field | Description |\ |-------|-------------|\ | `name` | Profile display name |\ | `description` | Full bio with HTML entities decoded |\ | `profile_image` | 640x640px portrait URL | **Technical Insights**\ | Field | Description |\ |-------|-------------|\ | `raw_json_ld` | Unmodified schema.org data |\ | `scraped_at` | UTC timestamp of extraction | *** ### πŸ†š Why This Actor? | Feature | πŸš€ This Actor | 🐌 Others |\ |---------|---------------|-----------|\ | Schema.org Integration | βœ… Raw JSON-LD | ❌ Basic Fields |\ | Image Resolution | 640px HD | 240px Low-Quality |\ | Bulk Scraping | 100+ Profiles | Single Pages |\ | Data Freshness | Realtime | Cached Versions |\ | Rate Handling | Auto-Throttling | Frequent Bans | *** ### πŸ› οΈ How It Works 1️⃣ **Add Vimeo Profile URLs** – Individuals or lists\ 2️⃣ **Run Actor** – Auto-detects profile type (user/channel)\ 3️⃣ **Get**: - πŸ“‡ Creator bios & names - πŸ–ΌοΈ High-res profile images - 🧩 Raw schema.org metadata - ⏱️ Precise scrape timestamps *** ### πŸ’‘ Use Cases 🎬 **Filmmakers** – Find collaboration partners\ πŸ‘©πŸ’» **Recruiters** – Source video talent\ πŸ“ˆ **Analysts** – Track creator trends\ πŸ“š **Archivists** – Preserve artist portfolios\ πŸ€– **AI Trainers** – Gather bios for LLMs *** ### ❓ Troubleshooting **Issue**: "Invalid profile URL" error\ **Fix**: - Use URLs from Vimeo's address bar (e.g., `vimeo.com/username`) - Avoid mobile links (`vimeo.com/m/...`) **Issue**: Missing `raw_json_ld` data\ **Fix**: - Profile must have schema.org markup - Retry with `method: GET` *** # Actor input Schema ## `profile_urls` (type: `array`): No description ## `proxy` (type: `object`): No description ## Actor input object example ```json { "profile_urls": [ { "url": "https://vimeo.com/user46243372" }, { "url": "https://vimeo.com/meatdept" } ] } ``` # 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 = { "profile_urls": [ { "url": "https://vimeo.com/user46243372" }, { "url": "https://vimeo.com/meatdept" } ] }; // Run the Actor and wait for it to finish const run = await client.actor("scrapearchitect/vimeo-profile-scraper").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 = { "profile_urls": [ { "url": "https://vimeo.com/user46243372" }, { "url": "https://vimeo.com/meatdept" }, ] } # Run the Actor and wait for it to finish run = client.actor("scrapearchitect/vimeo-profile-scraper").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 '{ "profile_urls": [ { "url": "https://vimeo.com/user46243372" }, { "url": "https://vimeo.com/meatdept" } ] }' | apify call scrapearchitect/vimeo-profile-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=scrapearchitect/vimeo-profile-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "⚑Vimeo Profile Scraper πŸ‘€", "description": "πŸš€ Scrape Vimeo profiles πŸ‘€, bios πŸ“, HD images πŸ–ΌοΈ + raw JSON-LD 🧩! Bulk URLs πŸ”„, timestamps ⏰, Apify storage πŸ”’. For recruiters πŸ‘©πŸ’», analysts πŸ“Š, archivists πŸ“š. Fast ⚑, encrypted πŸ›‘οΈ! ⚑ Vimeo Profile Scraper πŸ‘€", "version": "1.0", "x-build-id": "9hswb9au42jpHJDhh" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/scrapearchitect~vimeo-profile-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-scrapearchitect-vimeo-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/scrapearchitect~vimeo-profile-scraper/runs": { "post": { "operationId": "runs-sync-scrapearchitect-vimeo-profile-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/scrapearchitect~vimeo-profile-scraper/run-sync": { "post": { "operationId": "run-sync-scrapearchitect-vimeo-profile-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "profile_urls" ], "properties": { "profile_urls": { "title": "Vimeo Profile URLs", "type": "array", "items": { "type": "object", "properties": { "url": { "type": "string", "pattern": "^https?://vimeo\\.com/(?!\\d+$)[a-zA-Z0-9_]+|^https?://vimeo\\.com/user\\d+" } }, "required": [ "url" ] } }, "proxy": { "title": "Proxy Configuration", "required": [ "useApifyProxy", "apifyProxyGroups", "apifyProxyCountry" ], "type": "object", "properties": { "useApifyProxy": { "type": "boolean", "default": true }, "apifyProxyGroups": { "type": "array", "items": { "type": "string", "enum": [ "RESIDENTIAL", "OWN_PROXIES" ] }, "default": [ "RESIDENTIAL" ] }, "apifyProxyCountry": { "type": "string", "default": "US" } } } } }, "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 } } } } } } } } } } ```