# YouTube Transcript Pro - Office Edition (`vigilant_arboretum/youtube-transcript-pro`) Actor Bulk YouTube transcript extractor with job tracking, timestamps, and stats. - **URL**: https://apify.com/vigilant\_arboretum/youtube-transcript-pro.md - **Developed by:** [Aman Bhawsar](https://apify.com/vigilant_arboretum) (community) - **Categories:** Videos - **Stats:** 3 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $1.00 / 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 Transcript Pro — Office Edition Bulk YouTube transcript & subtitle extractor for content teams, research, and AI training datasets. ### Features - Bulk URL processing (watch, youtu.be, shorts, embed) - 100+ languages - Optional timestamped output (`[mm:ss] text`) - Job tracking — every run gets a unique `job_id` and optional `job_label` - Per-video stats: line count, word count, duration - Run summary saved to key-value store as `JOB_SUMMARY` ### Run limits (Office edition) To keep runs fast and lightweight, this edition caps each execution: - **Max 5 videos per run** — extra URLs are trimmed with a log notice. - **Max 3 minutes runtime** — any video beyond this is skipped and reported in the summary as `stopped_by_timeout: true`. For larger bulk jobs, split the input across multiple runs. ### Input | Field | Type | Description | |---|---|---| | `urls` | array (required) | YouTube video URLs | | `language` | string | Preferred subtitle language code (default: `en`) | | `jobLabel` | string | Optional label for this batch (team/project name) | | `includeTimestamps` | boolean | Prefix each line with `[mm:ss]` | ### Output (per video) ```json { "job_id": "JOB-20260405XXXXXX-AB12", "job_label": "marketing-q2", "video_id": "dQw4w9WgXcQ", "url": "https://...", "language": "en", "line_count": 142, "word_count": 980, "duration_sec": 213, "extracted_at": "2026-04-05T...Z", "transcript": "...", "lines": ["..."], "raw": [...] } ```` ### Run Summary After every run, a `JOB_SUMMARY` record is written to the default key-value store containing totals, success/failure counts, and timing. # Actor input Schema ## `urls` (type: `array`): List of YouTube video URLs to extract transcripts from (max 5 per run). ## `language` (type: `string`): Preferred transcript language code (e.g. en, hi, es, fr). ## `includeTimestamps` (type: `boolean`): Add \[MM:SS] timestamps before each transcript line. ## `jobLabel` (type: `string`): Optional label to tag this job for easy identification. ## Actor input object example ```json { "urls": [ "https://www.youtube.com/watch?v=dQw4w9WgXcQ" ], "language": "en", "includeTimestamps": false } ``` # 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 = { "urls": [ "https://www.youtube.com/watch?v=dQw4w9WgXcQ" ], "language": "en" }; // Run the Actor and wait for it to finish const run = await client.actor("vigilant_arboretum/youtube-transcript-pro").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 = { "urls": ["https://www.youtube.com/watch?v=dQw4w9WgXcQ"], "language": "en", } # Run the Actor and wait for it to finish run = client.actor("vigilant_arboretum/youtube-transcript-pro").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 '{ "urls": [ "https://www.youtube.com/watch?v=dQw4w9WgXcQ" ], "language": "en" }' | apify call vigilant_arboretum/youtube-transcript-pro --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=vigilant_arboretum/youtube-transcript-pro", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "YouTube Transcript Pro - Office Edition", "description": "Bulk YouTube transcript extractor with job tracking, timestamps, and stats.", "version": "0.0", "x-build-id": "UQZcrH8jabHes50LB" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/vigilant_arboretum~youtube-transcript-pro/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-vigilant_arboretum-youtube-transcript-pro", "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/vigilant_arboretum~youtube-transcript-pro/runs": { "post": { "operationId": "runs-sync-vigilant_arboretum-youtube-transcript-pro", "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/vigilant_arboretum~youtube-transcript-pro/run-sync": { "post": { "operationId": "run-sync-vigilant_arboretum-youtube-transcript-pro", "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": [ "urls" ], "properties": { "urls": { "title": "YouTube URLs", "type": "array", "description": "List of YouTube video URLs to extract transcripts from (max 5 per run).", "items": { "type": "string" } }, "language": { "title": "Language", "type": "string", "description": "Preferred transcript language code (e.g. en, hi, es, fr).", "default": "en" }, "includeTimestamps": { "title": "Include Timestamps", "type": "boolean", "description": "Add [MM:SS] timestamps before each transcript line.", "default": false }, "jobLabel": { "title": "Job Label", "type": "string", "description": "Optional label to tag this job for easy identification." } } }, "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 } } } } } } } } } } ```