# YouTube Comments Extractor (`scraper_guru/youtube-comments-extractor`) Actor Scrape YouTube comments and replies with full nested trees from any video URL. Perfect for AI training data, sentiment analysis, and brand monitoring. - **URL**: https://apify.com/scraper\_guru/youtube-comments-extractor.md - **Developed by:** [LIAICHI MUSTAPHA](https://apify.com/scraper_guru) (community) - **Categories:** Developer tools, Videos, Lead generation - **Stats:** 1 total users, 0 monthly users, 0.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $5.00 / 1,000 results This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. 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 Comments & Replies Extractor The fastest, most cost-effective way to extract deep, nested comment trees from YouTube videos. Built specifically for AI engineers, data scientists, and brand monitors who need **high-volume**, **clean**, and **structured** YouTube discussion data without the bloat, cost, and slow speeds of heavy browser automation. --- ### 💎 Why use this Actor? YouTube comments are a goldmine for sentiment analysis, product feedback, and AI training data. However, extracting them usually requires spinning up slow, expensive headless browsers (like Puppeteer or Playwright). **This Actor is different:** - ⚡ **Extremely Fast:** Skips the browser entirely. It communicates directly with YouTube's internal APIs natively in Python. - 💰 **Highly Cost-Effective:** Because it doesn't render full web pages, it consumes a fraction of the memory (Compute Units) compared to standard scrapers. - 🌳 **Deep Nesting:** Grabs top-level comments *and* their deeply nested reply chains instantly. - 🤖 **AI-Ready Format:** Outputs flat, structured JSON ready to be piped directly into Pandas, AI agents, LLMs, or your database. --- ### 🎯 Primary Use Cases 1. **Brand & PR Monitoring:** Understand exactly what audiences are saying about your product reviews or announcements in real-time. 2. **Sentiment Analysis:** Export massive discussion threads to train your NLP models or run through LLM sentiment classifiers. 3. **Lead Generation & Audience Research:** Find out who's commenting on your competitors' videos to discover your target audience's pain points. 4. **AI Training Data:** Amass huge datasets of conversational, human-written text interactions (comments vs. replies). --- ### ⚙️ Input Configuration The actor's configuration is simple and intuitive: | Field | Type | Description | |---|---|---| | **Start URLs** | `Array` | A list of YouTube Video URLs you want to scrape. | | **Max Comments Per Video** | `Integer` | The maximum number of comments to extract per video. (Set very high to attempt full extraction). | | **Sort Mode** | `Dropdown` | Choose either **Top Comments** (default) or **Newest First**. | | **Proxy Configuration** | `Proxy` | **Residential Proxies** are highly recommended and selected by default to prevent YouTube's bot-blocking limits. | --- ### 📊 Output Data Structure The Actor pushes a clean, flat JSON object for every comment/reply into the default dataset. **Example Output:** ```json { "cid": "UgwoNqeCenhrmvft8LN4AaABAg", "text": "who’s watching this in march 2026", "time": "1 month ago", "author": "@tech_enthusiast_4794", "channel": "UCOoPn99OOMxS7WqaBIzCwJg", "votes": "1.5K", "reply": false, "photo": "https://yt3.ggpht.com/...", "heart": false, "time_parsed": 1711234567, "video_url": "https://www.youtube.com/watch?v=kOHB85vDuow" } ```` #### Response Field Breakdown: - `cid`: Unique Comment ID. - `text`: The actual text of the comment. - `time`: The raw time string provided by YouTube (e.g., "3 hours ago"). - `author`: The username/handle of the commenter. - `channel`: The unique Channel ID of the commenter. - `votes`: The string representation of upvotes. - `reply`: Boolean indicating if this is a reply to another comment (`true`) or a top-level comment (`false`). - `video_url`: The source URL so you can join datasets across multiple videos. *** ### 💡 Pro Tips for Best Results 1. **Always Use Residential Proxies:** YouTube is actively monitoring for datacenter IPs. The standard Apify Residential Proxy pool guarantees your scraping won't get interrupted. 2. **Sort by "Newest":** If you are running a continuous monitoring job (e.g., daily scraping via Apify Schedules), sorting by Newest ensures you only grab the latest data without paying to re-read old top comments. > **Feedback or Feature Requests?** > Drop a message in the Issues tab! We constantly update and tune the internal API handlers to adapt to YouTube's latest infrastructure changes. # Actor input Schema ## `startUrls` (type: `array`): List of YouTube video URLs. ## `maxCommentsPerVideo` (type: `integer`): Maximum number of comments to extract per video. Leave it very high to extract all. ## `sort` (type: `string`): Sorting mode for comments. ## `proxyConfiguration` (type: `object`): Select proxies to be used by your scraper. Residential proxies are highly recommended to bypass YouTube bot detection. ## Actor input object example ```json { "maxCommentsPerVideo": 100, "sort": "top", "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } } ``` # Actor output Schema ## `comments` (type: `string`): Dataset containing the extracted YouTube comments and metadata. # 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 = { "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } }; // Run the Actor and wait for it to finish const run = await client.actor("scraper_guru/youtube-comments-extractor").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 = { "proxyConfiguration": { "useApifyProxy": True, "apifyProxyGroups": ["RESIDENTIAL"], } } # Run the Actor and wait for it to finish run = client.actor("scraper_guru/youtube-comments-extractor").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 '{ "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } }' | apify call scraper_guru/youtube-comments-extractor --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=scraper_guru/youtube-comments-extractor", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "YouTube Comments Extractor", "description": "Scrape YouTube comments and replies with full nested trees from any video URL. Perfect for AI training data, sentiment analysis, and brand monitoring.", "version": "1.0", "x-build-id": "SLsy0vTNc2bFw2QBQ" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/scraper_guru~youtube-comments-extractor/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-scraper_guru-youtube-comments-extractor", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/scraper_guru~youtube-comments-extractor/runs": { "post": { "operationId": "runs-sync-scraper_guru-youtube-comments-extractor", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/scraper_guru~youtube-comments-extractor/run-sync": { "post": { "operationId": "run-sync-scraper_guru-youtube-comments-extractor", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "startUrls", "proxyConfiguration" ], "properties": { "startUrls": { "title": "Start URLs", "type": "array", "description": "List of YouTube video URLs.", "items": { "type": "object", "required": [ "url" ], "properties": { "url": { "type": "string", "title": "URL of a web page", "format": "uri" } } } }, "maxCommentsPerVideo": { "title": "Max Comments Per Video", "minimum": 1, "type": "integer", "description": "Maximum number of comments to extract per video. Leave it very high to extract all.", "default": 100 }, "sort": { "title": "Sort Mode", "enum": [ "top", "new" ], "type": "string", "description": "Sorting mode for comments.", "default": "top" }, "proxyConfiguration": { "title": "Proxy configuration", "type": "object", "description": "Select proxies to be used by your scraper. Residential proxies are highly recommended to bypass YouTube bot detection.", "default": { "useApifyProxy": true, "apifyProxyGroups": [ "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 } } } } } } } } } } ```