# Youtube Comments (`shareze001/youtube-comments`) Actor This tool extracts comments from YouTube videos, providing details such as the author, content, likes, replies, and more. It supports sorting options like top comments or newest first. The results are returned in a structured JSON format for easy integration and analysis. - **URL**: https://apify.com/shareze001/youtube-comments.md - **Developed by:** [shareze](https://apify.com/shareze001) (community) - **Categories:** Videos, Social media, Integrations - **Stats:** 3 total users, 1 monthly users, 100.0% runs succeeded, 1 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 ## YouTube Comments Scraper This tool is designed to scrape comments from a specific YouTube video. It retrieves detailed information about the comments, including the author, content, likes, replies, and more. ### How to Use #### 1. Input Configuration The tool requires an input JSON object to define the scraping parameters. The structure of the input is as follows: ```json { "videoId": "7bjYAnSLBZo", "size": 10, "sort_by": "top" } ```` - **`videoId`**: (Required) The YouTube video ID, e.g., `https://www.youtube.com/watch?v=7bjYAnSLBZo` -> `7bjYAnSLBZo`. - **`size`**: (Required) The number of comments to retrieve. Default is 10. Minimum is 1. - **`sort_by`**: (Optional) Sort comments by: - `top`: Top comments (default). - `newest`: Newest comments first. #### 2. Output Data The tool returns an array of objects containing information about the comments. The structure of each object is as follows: ```json { "authorChannelId": "UC123456789", "authorName": "Example Author", "authorAvatarThumbnailUrl": "https://example.com/avatar.jpg", "authorIsVerified": true, "commentId": "abc123", "content": "This is an example comment.", "publishedTime": "2025-10-01", "likeCount": 100, "replyCount": 5 } ``` - **`authorChannelId`**: The unique ID of the comment authorโ€™s channel. - **`authorName`**: The name of the comment author. - **`authorAvatarThumbnailUrl`**: The URL of the authorโ€™s avatar thumbnail. - **`authorIsVerified`**: Whether the author is verified. - **`commentId`**: The unique ID of the comment. - **`content`**: The content of the comment. - **`publishedTime`**: The time the comment was published. - **`likeCount`**: The number of likes the comment received. - **`replyCount`**: The number of replies to the comment. #### 3. Running the Tool 1. Deploy the tool on the Apify platform. 2. Provide the input JSON in the tool's input configuration. 3. Run the tool to scrape comments from the specified YouTube video. 4. Retrieve the output dataset containing the comment details. #### Notes - This tool uses YouTube's public interface and may be subject to rate limits or restrictions. - Ensure that the input `videoId` is valid and corresponds to an existing YouTube video. - The tool is optimized for performance but may require adjustments based on YouTube's response behavior. # Actor input Schema ## `videoId` (type: `string`): YouTube video ID, e.g., https://www.youtube.com/watch?v=7bjYAnSLBZo -> 7bjYAnSLBZo ## `size` (type: `integer`): comment size ## `sort_by` (type: `string`): Sort comments by, either by top comments or newest first ## Actor input object example ```json { "videoId": "7bjYAnSLBZo", "size": 10, "sort_by": "top" } ``` # 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 = { "videoId": "7bjYAnSLBZo", "size": 10, "sort_by": "top" }; // Run the Actor and wait for it to finish const run = await client.actor("shareze001/youtube-comments").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 = { "videoId": "7bjYAnSLBZo", "size": 10, "sort_by": "top", } # Run the Actor and wait for it to finish run = client.actor("shareze001/youtube-comments").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 '{ "videoId": "7bjYAnSLBZo", "size": 10, "sort_by": "top" }' | apify call shareze001/youtube-comments --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=shareze001/youtube-comments", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Youtube Comments", "description": "This tool extracts comments from YouTube videos, providing details such as the author, content, likes, replies, and more. It supports sorting options like top comments or newest first. The results are returned in a structured JSON format for easy integration and analysis.", "version": "0.0", "x-build-id": "V5hEQNJvClQyM4FM3" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/shareze001~youtube-comments/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-shareze001-youtube-comments", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/shareze001~youtube-comments/runs": { "post": { "operationId": "runs-sync-shareze001-youtube-comments", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/shareze001~youtube-comments/run-sync": { "post": { "operationId": "run-sync-shareze001-youtube-comments", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "videoId", "size", "sort_by" ], "properties": { "videoId": { "title": "videoId", "type": "string", "description": "YouTube video ID, e.g., https://www.youtube.com/watch?v=7bjYAnSLBZo -> 7bjYAnSLBZo" }, "size": { "title": "size", "minimum": 1, "type": "integer", "description": "comment size", "default": 10 }, "sort_by": { "title": "Sort by", "enum": [ "top", "newest" ], "type": "string", "description": "Sort comments by, either by top comments or newest first", "default": "top" } } }, "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 } } } } } } } } } } ```