# Youtube Scraper (`datapilot/youtube-scraper`) Actor This script scrapes YouTube search results using . It fetches the top 20 videos for a given query, extracts video and channel details (title, views, duration, publish time, thumbnails), formats the data, saves it as a JSON file - **URL**: https://apify.com/datapilot/youtube-scraper.md - **Developed by:** [Data Pilot](https://apify.com/datapilot) (community) - **Categories:** Videos, Other - **Stats:** 3 total users, 2 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing $7.00/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 ## YouTube Scraper πŸš€ **YouTube Scraper** is a robust Apify Actor designed to scrape **YouTube Scraper data** from YouTube search results. This tool provides comprehensive **YouTube Scraper information**, including video titles, view counts, durations, and channel details for any search query. Whether you're conducting SEO research, analyzing YouTube Scraper trends, or building video databases, the YouTube Scraper delivers detailed **YouTube Scraper data** efficiently. With residential proxy support, the YouTube Scraper ensures reliable and undetected scraping of **YouTube Scraper results**. It focuses on key **YouTube Scraper metrics** like view counts, upload dates, and channel information, making it an essential tool for **YouTube Scraper analysis** and content research. ### πŸ”₯ Features - **Comprehensive YouTube Scraper Extraction** – Scrapes detailed **YouTube Scraper data**, including video metadata, channel info, and engagement metrics for any search query. - **Advanced Formatting** – Provides human-readable formats for **YouTube Scraper view counts**, durations, and publication times. - **Batch Processing** – Retrieves a specified number of **YouTube Scraper results** (up to 20+) in a single run for extensive **YouTube Scraper datasets**. - **Residential Proxy Support** – Utilizes Apify's residential proxies to bypass restrictions and ensure high success rates for **YouTube Scraper scraping**. - **Metadata Enrichment** – Extracts **YouTube Scraper thumbnails**, descriptions, and channel verification status for in-depth **YouTube Scraper analysis**. - **Error Handling** – Robust logging and fallback mechanisms for failed **YouTube Scraper scrapes**. - **Dataset Integration** – Automatically uploads **YouTube Scraper data** to your Apify dataset for easy export and analysis. --- ### βš™οΈ How It Works The YouTube Scraper takes a search query as input and uses to fetch **YouTube Scraper results** from YouTube's search API. It extracts metadata for videos and channels, formats the data for readability, and returns structured **YouTube Scraper information** on success or error details on failure. This approach ensures fast, consistent results for **YouTube Scraper research** and trend analysis. **Key Processing Steps:** 1. **Query Validation** – Parse and validate search query 2. **API Querying** – Query YouTube search API via 3. **Result Extraction** – Extract video and channel data 4. **Metadata Enrichment** – Get thumbnails, descriptions, verification status 5. **Formatting** – Convert to human-readable format 6. **Data Compilation** – Aggregate results 7. **Export** – Push to dataset in JSON format **Key benefits for YouTube Scraper analysis:** - Track YouTube Scraper search result rankings and performance. - Analyze YouTube Scraper video engagement and channel metrics. - Build YouTube Scraper databases for content strategy. - Research keyword rankings on YouTube. - Analyze video performance trends. --- ### πŸ“₯ Input The scraper accepts the following input parameters: | Field | Type | Default | Description | |----------------------|---------|-------------------|-------------| | `searchQuery` | string | required | The search query to scrape YouTube Scraper results for (e.g., `"technology news"`). | | `maxResults` | integer | `20` | Maximum number of YouTube Scraper results to retrieve (1-50). | | `useApifyProxy` | boolean | `false` | Enable residential proxies for YouTube Scraper scraping. | | `apifyProxyGroups` | array | `["RESIDENTIAL"]` | Proxy groups to use (e.g., `["RESIDENTIAL"]`). | **Example input JSON:** ```json { "searchQuery": "technology news", "maxResults": 15, "useApifyProxy": true, "apifyProxyGroups": ["RESIDENTIAL"] } ```` *** ### πŸ“€ Output The scraper outputs detailed **YouTube Scraper data** in JSON format. Each record includes: | Field | Type | Description | |-----------------------|---------|-------------| | `query` | string | The original search query for YouTube Scraper. | | `timestamp` | string | Timestamp of the YouTube Scraper scrape. | | `totalResults` | integer | Number of YouTube Scraper results retrieved. | | `video` | array | Array of YouTube Scraper video objects. | | `channel` | array | Array of YouTube Scraper channel objects. | **Video Object Fields:** | Field | Type | Description | |-----------------------|---------|-------------| | `videoId` | string | Unique ID of the YouTube Scraper video. | | `url` | string | URL to the YouTube Scraper video. | | `title` | string | Title of the YouTube Scraper video. | | `thumbnail` | string | Thumbnail URL for the YouTube Scraper video. | | `description` | string | Description snippet of the YouTube Scraper video. | | `channelName` | string | Name of the YouTube Scraper channel. | | `channelId` | string | ID of the YouTube Scraper channel. | | `isChannelVerified` | boolean | Verification status of the YouTube Scraper channel. | | `publishedTime` | string | Human-readable publication time. | | `viewH` | string | Formatted view count (e.g., "1.2M views"). | | `view` | integer | Raw view count for the YouTube Scraper video. | | `durationH` | string | Formatted duration (e.g., "10 minutes"). | | `duration` | integer | Raw duration in seconds. | **Example output for YouTube Scraper results:** ```json { "query": "advanced", "timestamp": "2025-02-14T12:00:00Z", "totalResults": 15, "video": [ { "videoId": "3B_oB2YrLvk", "url": "https://www.youtube.com/watch?v=3B_oB2YrLvk", "title": "Advanced F2L Tutorial (CFOP)", "thumbnail": "https://i.ytimg.com/vi/3B_oB2YrLvk/hq720.jpg?sqp=-oaymwEcCNAFEJQDSFXyq4qpAw4IARUAAIhCGAFwAcABBg==&rs=AOn4CLA1W8iPVQ77_Rzr05ARwP8Zt9GKfA", "description": "N/A", "channelName": "J Perm", "channelId": "UCqTVfT9JQqhA6_Hi_h_h97Q", "isChannelVerified": false, "publishedTime": "N/A", "viewH": "6.5M views", "view": 6529425, "durationH": "8 minutes, 35 seconds", "duration": 515 } ], "channel": [ { "channelId": "UCexample", "url": "https://www.youtube.com/channel/UCexample", "channelName": "Tech Channel", "username": "techchannel", "avatar": "https://example.com/avatar.jpg", "isChannelVerified": true, "subscriberH": "500K subscribers", "description": "Channel dedicated to tech news" } ] } ``` *** ### 🧰 Technical Stack - **Core Library:** – YouTube search and data extraction - **Proxy Support:** Apify Proxy with RESIDENTIAL support for reliability - **Data Processing:** JSON formatting, metadata enrichment - **Platform:** Apify Actor – serverless, scalable, integrated with Dataset and Key‑Value Store - **Deployment:** One‑click run on Apify Console or via REST API *** ### 🎯 Use Cases - **SEO Research** – Research YouTube keyword rankings and video performance. - **Content Strategy** – Analyze what content ranks for specific keywords. - **Competitive Analysis** – Research competitor videos and channels. - **Trend Analysis** – Identify trending videos and topics on YouTube. - **Video Performance Research** – Analyze view counts and engagement metrics. - **Channel Research** – Research YouTube channels in your niche. - **Keyword Ranking** – Track keyword rankings and SERP positions on YouTube. - **Market Research** – Research market trends through YouTube search results. - **Lead Generation** – Identify relevant channels and creators in your niche. - **Influencer Research** – Find influencers and creators in your space. - **Content Ideas** – Get inspiration from trending videos in your niche. - **Video Optimization** – Research how successful videos are titled and described. - **Academic Research** – Collect YouTube search data for research studies. - **Social Media Research** – Research social media trends through YouTube. *** ### πŸš€ Quick Start 1. **Open in Apify Console** – visit the Actor page and click Try for free. 2. **Enter search query** – provide a YouTube search query (e.g., "machine learning"). 3. **Set result limit** – choose between 1-50 results to retrieve. 4. **Enable proxies** – optional; enable for more reliable scraping. 5. **Click Start** – the Actor will scrape YouTube search results. 6. **View Results** – check the dataset for video and channel data. 7. **Analyze Data** – use metrics for research and strategy. 8. **Export** – download the results as JSON, CSV, or Excel. You can also call this Actor programmatically via Apify SDK or REST API – ideal for automated YouTube research and trend tracking. *** ### πŸ’Ž Why This Scraper? | Feature | Benefit | |---------|---------| | βœ… Comprehensive data | Get videos, channels, and metrics in one call. | | βœ… Human-readable format | View counts and durations in easy-to-read format. | | βœ… Batch processing | Get up to 50 results in a single run. | | βœ… Residential proxies | Bypass restrictions – reliable access. | | βœ… Channel verification | Get channel verification status and info. | | βœ… Rich metadata | Thumbnails, descriptions, timestamps. | | βœ… Fast results | Quick API queries and processing. | | βœ… Apify ecosystem | Seamless integration with other Actors, triggers, and webhooks. | ### πŸ“¦ Changelog - Initial release of YouTube Scraper - Search query support for YouTube results - Video and channel data extraction - Metadata enrichment (thumbnails, descriptions, verification status) - Human-readable formatting for view counts and durations - Batch processing (up to 50 results) - Residential proxy support for reliability - Channel verification status detection - Published time formatting - Error handling with detailed error messages - Automatic dataset integration - Full Apify Actor integration *** ### πŸ§‘β€πŸ’» Support & Feedback - **Issues & Ideas:** Open a ticket on the Apify Actor issue tracker - **Contributions:** Pull requests are welcome via the GitHub repository - **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 *** ### πŸ’° Pricing - **Free** for basic usage on Apify platform - **Paid plans** available for higher limits and priority support - **Proxy credits** consumed based on residential proxy usage ### πŸŽ‰ Get Started Today **Begin scraping YouTube search results now!** Use YouTube Scraper for: - πŸ” Keyword Research - πŸ“Š SEO Analysis - 🎯 Trend Analysis - πŸ’‘ Content Strategy - πŸ† Competitive Analysis **Perfect for:** - Content Creators - SEO Specialists - Researchers - Marketing Professionals - Analysts *** **Last Updated:** February 2025\ **Status:** Active Development\ **Support:** 24/7 Customer Support Available\ **Platform:** Apify *** ### πŸ“š Related Tools For comprehensive YouTube analysis and research, explore our full suite of tools: - YouTube Comment Scraper - YouTube Video Analytics Scraper - YouTube Advanced Metadata Scraper - All-in-One Media Downloader - Ultimate Video Info Fetcher # Actor input Schema ## `searchQuery` (type: `string`): YouTube search term (e.g., 'minecraft', 'cooking tutorials') ## `maxResults` (type: `integer`): Number of videos to scrape (1-50) ## `useApifyProxy` (type: `boolean`): Enable Apify proxy for scraping ## `apifyProxyGroups` (type: `array`): Proxy pool type ## Actor input object example ```json { "searchQuery": "minecraft", "maxResults": 20, "useApifyProxy": false, "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 = { "searchQuery": "minecraft" }; // Run the Actor and wait for it to finish const run = await client.actor("datapilot/youtube-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 = { "searchQuery": "minecraft" } # Run the Actor and wait for it to finish run = client.actor("datapilot/youtube-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 '{ "searchQuery": "minecraft" }' | apify call datapilot/youtube-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=datapilot/youtube-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Youtube Scraper", "description": "This script scrapes YouTube search results using . It fetches the top 20 videos for a given query, extracts video and channel details (title, views, duration, publish time, thumbnails), formats the data, saves it as a JSON file", "version": "0.0", "x-build-id": "LSdNhdNUWpxZkh6s3" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/datapilot~youtube-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-datapilot-youtube-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/datapilot~youtube-scraper/runs": { "post": { "operationId": "runs-sync-datapilot-youtube-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/datapilot~youtube-scraper/run-sync": { "post": { "operationId": "run-sync-datapilot-youtube-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "searchQuery" ], "properties": { "searchQuery": { "title": "Search Query", "type": "string", "description": "YouTube search term (e.g., 'minecraft', 'cooking tutorials')" }, "maxResults": { "title": "Maximum Results", "minimum": 1, "maximum": 50, "type": "integer", "description": "Number of videos to scrape (1-50)", "default": 20 }, "useApifyProxy": { "title": "Use Apify Proxy", "type": "boolean", "description": "Enable Apify proxy for scraping", "default": false }, "apifyProxyGroups": { "title": "Apify Proxy Groups", "uniqueItems": true, "type": "array", "description": "Proxy pool type", "items": { "type": "string", "enum": [ "RESIDENTIAL", "DATACENTER" ] }, "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 } } } } } } } } } } ```