YouTube Video Subtitles Scraper

Extracts subtitles and metadata from public YouTube videos. Outputs structured data (JSON, CSV, Excel) suitable for analysis, AI training, or integration into other workflows.

Overview

This actor scrapes captions from YouTube videos. For each video, it retrieves:
* Subtitle text with start timestamps and duration.
* Video metadata: title, description, author, tags, length, and URL.
* Caption language and type (auto-generated or manual).

It runs on the Apify platform, requiring no local setup. You can run it via the web interface or integrate it programmatically using the Apify API or client libraries (e.g., apify-client for Python).

Key Features

• Extracts Both Caption Types: Supports both manual (user-provided) and auto-generated (ASR) subtitles.
• Structured Output: Returns clean data with timestamps, text, and video info.
• Multiple Export Formats: Results can be downloaded as JSON, CSV, XLSX, or HTML.
• Bulk Processing: Can handle multiple video URLs in a single run.
• Developer Integration: Easy to automate using the Apify API, CLI, or SDKs (Python, Node.js).
• Language Handling: Captions are extracted in their available languages.

How to Use

Via Apify Console (Web Interface)

1. Go to the actor's page on the Apify Store: YouTube Video Subtitles Scraper.
2. Click "Try for free" or "Start".
3. In the Input tab, configure your run:
   • Paste one or more YouTube video URLs into the videoURLs field.
   • (Optional) Adjust other parameters like language or includeAutoGenerated.
4. Click "Start".
5. Once finished, download your dataset from the "Dataset" tab in your preferred format.

Via API/CLI (Programmatic)

Use the Apify API or a client to run the actor. Here's a basic example using the Python client (pip install apify-client):

from apify_client import ApifyClient

client = ApifyClient("YOUR_APIFY_TOKEN")

run_input = {
    "videoURLs": ["https://www.youtube.com/watch?v=EXAMPLE"],
    "language": "en",
    "includeAutoGenerated": True,
}

run = client.actor("actor_id").call(run_input=run_input)

# Fetch results
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item)

Input / Output

Input Configuration

The actor accepts a JSON object with these key parameters:

• videoURLs (Array, Required): List of YouTube video URLs.
• language (String, Optional): Preferred language code (e.g., 'en', 'es'). Defaults to the video's primary language.
• includeAutoGenerated (Boolean, Optional): If true, includes auto-generated (ASR) captions when manual ones are unavailable. Default is true.

Example input:

{
  "videoURLs": [
    "https://www.youtube.com/watch?v=dQw4w9WgXcQ",
    "https://www.youtube.com/watch?v=EXAMPLE2"
  ],
  "language": "en"
}

Output Data

The dataset contains an item for each video. Each item includes the video's metadata and an array of its subtitles.

Example output structure (JSON):

{
  "videoUrl": "https://www.youtube.com/watch?v=EXAMPLE",
  "videoTitle": "Example Video Title",
  "videoDescription": "Full video description...",
  "author": "Channel Name",
  "length": "10:30",
  "tags": ["tag1", "tag2"],
  "subtitles": [
    {
      "text": "This is the first subtitle line.",
      "start": "0:00:01.500",
      "duration": "3.0s",
      "language": "en"
    },
    {
      "text": "This is the second one.",
      "start": "0:00:05.000",
      "duration": "2.5s",
      "language": "en"
    }
  ]
}