# Youtube User Channel Scraper (`solid-scraper/youtube-user-channel-scraper`) Actor 🔍 Scrape YouTube data fast with Channel Scraper! Get key channel info, audiences, and insights for research, SEO, and competitor analysis. 🚀 Perfect for marketers, agencies, and creators—streamline workflows and find opportunities instantly! ✅ - **URL**: https://apify.com/solid-scraper/youtube-user-channel-scraper.md - **Developed by:** [SolidScraper](https://apify.com/solid-scraper) (community) - **Categories:** SEO tools, Social media, Lead generation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $2.99 / 1,000 results This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage. 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 ### Youtube User Channel Scraper 🔍 **Youtube User Channel Scraper** helps you scrape YouTube channel details like subscribers, video count, view count, join date, socials/links, and more. If you’re looking for a **YouTube channel scraper** or **YouTube user scraper** for **channel analytics**, this tool turns public web data into structured results—perfect for marketers, researchers, and data analysts who need faster **YouTube channel data extraction** at scale. Whether you’re building prospect lists, researching creators, or enriching datasets for reporting, this **YouTube channel scraping tool** saves you hours of manual work. --- ### Why choose Youtube User Channel Scraper? | Feature | Benefit | |---|---| | ✅ **Scrapes full channel metadata** | Extracts channelId, title, description, stats (views/videos/subscribers), join date, country, and more in one run | | ✅ **Input flexibility (Channel IDs or URLs)** | Lets you provide **ids** (comma-separated) and/or **start_urls** to scrape multiple channels | | ✅ **Built-in resilience with retries + fallbacks** | Includes retries for more reliable scraping when requests fail temporarily | | ✅ **Proxy support for reliability** | Uses built-in proxy support to improve consistency across large batches | | ✅ **Structured JSON output** | Produces clear, typed fields (counts as numbers, booleans for verified/email indicators) for easy export | | ✅ **Designed for scale** | Processes URLs in sequence so you can run batch scrapes with predictable behavior | --- ### Key features - 🌐 **YouTube channel URL scraper support:** Accepts `start_urls` containing YouTube channel URLs (and normalizes them for scraping) - 🆔 **Channel ID ingestion:** Uses the `ids` input as a comma-separated list and converts each ID into a channel URL to scrape - 📊 **Channel analytics scraper output:** Extracts `subscriberCount`, `videoCount`, and `viewCount` as numeric values - 🧾 **Complete metadata extraction:** Captures `title`, `description`, `joinDate`, `country`, `avatar`, and `banner` - 🔒 **Verified and email-status indicators:** Returns `verified` and `hasbusinessEmail` (business email availability flag) - 🔗 **Socials/links capture:** Extracts `links` (title + link) from the channel data when available - 💾 **Clean, structured dataset records:** Outputs a consistent JSON object per channel for easy downstream processing - 🔄 **Resilient fetching:** Includes up to 3 retries per channel request with delays between attempts --- ### Input Provide input via an `input.json` file. Example structure: ```json { "ids": "UCyBD3P9YOFWNIMTuDzqeObg", "start_urls": [ { "url": "https://www.youtube.com/@BBCNews" } ] } ```` #### Input Fields | Field | Required | Description | |---|---:|---| | `ids` | ❌ | A comma-separated list of YouTube Channel IDs (for example: `UCyBD3P9YOFWNIMTuDzqeObg`). The actor converts each ID into a channel URL to scrape. | | `start_urls` | ❌ | A list of YouTube channel URLs to scrape (for example: `https://www.youtube.com/@BBCNews`). The actor processes these first in the order you provide them. | *** ### Output The actor saves each scraped channel’s data as a JSON object into the Apify dataset (one record per channel). Example output record: ```json { "channelId": "UCyBD3P9YOFWNIMTuDzqeObg", "avatar": "https://example.com/avatar.jpg", "banner": "https://example.com/banner.jpg", "title": "Channel title", "verified": 1, "hasbusinessEmail": 0, "joinDate": "Jan 1, 2020", "country": "United States", "viewCount": 1234567, "videoCount": 89, "subscriberCount": 456789, "description": "Channel description", "links": [ { "title": "Website", "link": "example.com" } ], "indexUrl": "http://www.youtube.com/channel/UCyBD3P9YOFWNIMTuDzqeObg", "channelUrl": "https://www.youtube.com/channel/UCyBD3P9YOFWNIMTuDzqeObg" } ``` #### Output Fields | Field | Type | Description | |---|---|---| | `channelId` | string | The scraped channel ID | | `avatar` | string | URL to the channel avatar image | | `banner` | string | URL to the channel banner image | | `title` | string | Channel title | | `verified` | number | `1` if the channel appears verified, otherwise `0` | | `hasbusinessEmail` | number | `1` if business email is available, otherwise `0` | | `joinDate` | string | null | Channel join date (cleaned text) | | `country` | string | null | Country associated with the channel (when available) | | `viewCount` | number | Total view count (parsed into an integer) | | `videoCount` | number | Total number of videos (parsed into an integer) | | `subscriberCount` | number | Subscriber count (parsed into an integer) | | `description` | string | null | Channel description (and fallback description if needed) | | `links` | array | null | Array of extracted channel links (each has `title` and `link`) | | `indexUrl` | string | null | A normalized “index URL” form derived from channel data | | `channelUrl` | string | null | The channel URL derived from channel ID / metadata | *** ### How to use Youtube User Channel Scraper (via Apify Console) 1. **Open Apify Console**\ Log in at https://console.apify.com and open the **Actors** section. 2. **Find Youtube User Channel Scraper**\ Search for **Youtube User Channel Scraper** and open the actor page. 3. **Go to the INPUT tab**\ Enter your scrape targets using the built-in input form. 4. **Add your Channel IDs or URLs**\ Use either (or both):\ • `ids` as a comma-separated list of channel IDs\ • `start_urls` as a list of channel URLs (processed first, in UI order) 5. **(Optional) Use proxy support automatically**\ This actor uses built-in proxy support for reliability; you don’t configure proxy settings in the input. 6. **Start the run**\ Click **Run**. Watch the logs to see each channel being fetched and whether metadata extraction succeeds. 7. **Open the OUTPUT dataset**\ After completion, open the dataset and export the results as JSON/CSV from the dataset viewer. No coding required—get accurate **YouTube user profile scraper**-style channel data in minutes. *** ### Advanced features & SEO optimization - 🔄 **Robust retry logic for reliability:** Uses retries (up to 3 attempts) with delays when requests fail, which helps stabilize bulk **YouTube channel email scraper**-adjacent enrichment workflows that depend on consistent retrieval. - 🧭 **Input normalization for URLs:** Normalizes common YouTube channel URL variations so your **YouTube channel URL scraper** inputs work more smoothly. - 📥 **Returns structured channel stats for analytics:** Outputs subscriber/video/view counts as integers for clean **YouTube channel analytics scraper** reporting. - 🧩 **Resilient metadata extraction paths:** Extracts metadata from multiple internal page data locations (so fields like `description`, `banner`, and `links` have better odds of being captured). - 📊 **Designed for “scrape YouTube channel data” pipelines:** Friendly for marketers and researchers who want to plug results into spreadsheets, BI tools, or CRM enrichment. *** ### Best use cases - 📈 **Lead generation enrichment:** Build outreach lists by collecting structured creator/channel metrics and profile details from public sources. - 🧠 **Creator research & benchmarking:** Compare multiple channels using consistent fields like `subscriberCount`, `viewCount`, and `videoCount`. - 🗺️ **Geographic audience analysis:** Use `country` and join date to segment channels for studies and targeting. - 🧾 **Data analyst reporting:** Export channel metadata for dashboards without manual collection. - 🤝 **Partnership discovery:** Identify channels with `verified` status and business email availability flags (`hasbusinessEmail`) to prioritize outreach. - 🧑‍💻 **Developer-friendly datasets:** Turn **YouTube channel scraper API**-style outputs into automation workflows that expect stable JSON fields. - 🔍 **Channel metadata cleanup:** Standardize results across multiple **YouTube user channel scraper** inputs (IDs and URLs) into one uniform dataset. *** ### Technical specifications - **Supported Input Formats** - ✅ `ids`: comma-separated YouTube Channel IDs - ✅ `start_urls`: array of YouTube channel URLs - **Proxy Support** - ✅ Built-in proxy support is used automatically to improve scraping reliability - **Retry Mechanism** - ✅ Up to **3 attempts** per channel fetch when failures occur - **Dataset Structure** - ✅ One JSON record per successfully processed channel, pushed via `Actor.push_data` with `charged_event_name="result"` in the code - **Rate Limits & Performance** - ⚠️ Processing time depends on network conditions and target page responsiveness - **Limitations** - ❌ If `ytInitialData` content cannot be extracted from a channel page, the actor logs the failure and skips pushing metadata for that channel *** ### FAQ #### ✅ What does Youtube User Channel Scraper return? It returns a JSON object per channel with fields such as `channelId`, `title`, `description`, `joinDate`, `country`, `subscriberCount`, `videoCount`, `viewCount`, `links`, `verified`, and `hasbusinessEmail`. #### ✅ Can I provide YouTube channel URLs instead of channel IDs? Yes. You can use `start_urls` with YouTube channel URLs. The actor also supports channel IDs via the `ids` field. #### ❓ In what order are channels processed? The actor processes `start_urls` first (in the same order you provide them), then processes `ids` second. #### ❌ Does the actor require any special login? No login credentials are part of the actor input. It scrapes publicly available page data. #### 💻 Can I integrate the output into my pipeline? Yes. The dataset output is structured JSON, making it suitable for exporting to JSON/CSV and feeding into analytics, ETL, or enrichment workflows. #### 🛡️ How reliable is it for batch jobs? It includes retries (up to 3 attempts) and uses built-in proxy support to improve reliability when scraping multiple channels. #### ⚖️ Is this tool legal to use? It collects information from **publicly accessible sources**. Compliance with laws (for example GDPR/CCPA where applicable) and platform terms is your responsibility. #### 🔎 Does it scrape emails specifically? This actor returns a business email availability indicator as `hasbusinessEmail` (a flag). It does not output an email field in the dataset. *** ### Support & feature requests Want to improve **Youtube User Channel Scraper** for your YouTube channel data extraction workflow? 💡 - 💡 **Feature Requests:** Tell us what you want next—e.g., more fields, batch export enhancements, or additional normalization for URL inputs. - 📧 **Contact:** Email . Your feedback directly shapes future improvements to the actor and its usefulness for **YouTube channel scraper** and **YouTube user scraper** use cases. *** ### *Final thoughts on Youtube User Channel Scraper* 🎯 *If you need a clean, structured way to scrape YouTube channel data, this is one of the most comprehensive options for YouTube metadata extraction.*\ *Try **Youtube User Channel Scraper** today and scale your channel research faster than manual collection.* *** ### Disclaimer **This tool accesses publicly accessible sources only.** It does not access private profiles, authenticated data, or password-protected pages. You are responsible for complying with applicable laws and regulations (including GDPR/CCPA where relevant), as well as platform terms of service and any anti-spam or data usage rules. For data removal requests, contact . Please use **Youtube User Channel Scraper** responsibly, ethically, and for legitimate purposes only. # Actor input Schema ## `ids` (type: `string`): Comma-separated list of YouTube Channel IDs (e.g. UCyBD3P9YOFWNIMTuDzqeObg) ## `start_urls` (type: `array`): List of YouTube channel URLs to scrape. ## Actor input object example ```json { "ids": "UCyBD3P9YOFWNIMTuDzqeObg", "start_urls": [ { "url": "https://www.youtube.com/@BBCNews" } ] } ``` # 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 = { "ids": "UCyBD3P9YOFWNIMTuDzqeObg", "start_urls": [ { "url": "https://www.youtube.com/@BBCNews" } ] }; // Run the Actor and wait for it to finish const run = await client.actor("solid-scraper/youtube-user-channel-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 = { "ids": "UCyBD3P9YOFWNIMTuDzqeObg", "start_urls": [{ "url": "https://www.youtube.com/@BBCNews" }], } # Run the Actor and wait for it to finish run = client.actor("solid-scraper/youtube-user-channel-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 '{ "ids": "UCyBD3P9YOFWNIMTuDzqeObg", "start_urls": [ { "url": "https://www.youtube.com/@BBCNews" } ] }' | apify call solid-scraper/youtube-user-channel-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=solid-scraper/youtube-user-channel-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Youtube User Channel Scraper", "description": "🔍 Scrape YouTube data fast with Channel Scraper! Get key channel info, audiences, and insights for research, SEO, and competitor analysis. 🚀 Perfect for marketers, agencies, and creators—streamline workflows and find opportunities instantly! ✅", "version": "0.1", "x-build-id": "DgJkUA4I7Uf5cf1St" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/solid-scraper~youtube-user-channel-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-solid-scraper-youtube-user-channel-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/solid-scraper~youtube-user-channel-scraper/runs": { "post": { "operationId": "runs-sync-solid-scraper-youtube-user-channel-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/solid-scraper~youtube-user-channel-scraper/run-sync": { "post": { "operationId": "run-sync-solid-scraper-youtube-user-channel-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "ids": { "title": "Channel IDs", "type": "string", "description": "Comma-separated list of YouTube Channel IDs (e.g. UCyBD3P9YOFWNIMTuDzqeObg)" }, "start_urls": { "title": "Start URLs", "type": "array", "description": "List of YouTube channel URLs to scrape.", "items": { "type": "object", "required": [ "url" ], "properties": { "url": { "type": "string", "title": "URL of a web page", "format": "uri" } } } } } }, "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 } } } } } } } } } } ```