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🌟 YouTube Video Transcript Scraper

👁 Build
👁 Version
👁 License
👁 Apify

Accurate, timestamped transcripts for full-length YouTube videos — chapters, subtitles, and multi-language support.

📖 Overview

This Actor extracts clean, timestamped transcripts from full-length YouTube videos (standard watch URLs, youtu.be, and /watch?v= formats). It's designed for longer content: works with multiple caption tracks, handles chapters, and produces export-ready captions (SRT/VTT) alongside structured JSON suitable for analytics and LLM pipelines.

💡 Why Full-Video Focus?

• Full videos often contain chapters, multiple speakers, and longer dialogues — transcripts must preserve timing and structure.
• Supports official captions when available and high-quality ASR fallbacks when not.
• Produces SRT/VTT, plain text, and structured JSON for downstream processing.

🔧 Key Features

• ✅ Multi-format URL normalization (/watch?v=, youtu.be).
• ✅ Prefer official caption tracks; fallback to ASR extraction when captions are missing.
• ✅ Preserve chapters and video metadata (title, duration, thumbnails).
• ✅ Export as JSON, plain text, SRT, and VTT.
• ✅ Optional speaker diarization and language detection.
• ✅ Configurable chunking for very long videos and resume/retry support.
• ✅ Proxy-compatible and production-ready for large-scale jobs.

⚡ Quick Start — Console

1. Open the Actor on Apify Console.
2. Paste one or more YouTube video URLs into the input (watch links or youtu.be links accepted).
3. Click Run — results appear in the Dataset and Files (SRT/VTT) tabs.

⚙️ Quick Start — CLI & Python

CLI

$apify call neuro-scraper/youtube-transcript-fetcher --input ./videos_input.json

Python (apify-client)

from apify_client import ApifyClient
client = ApifyClient('<APIFY_TOKEN>')
run = client.actor('neuro-scraper/youtube-transcript-fetcher').call(
 run_input={
"startUrls":[{"url":"https://www.youtube.com/watch?v=EXAMPLE"}],
"workers":3,
"exportFormats":["json","srt","vtt"]
}
)
for item in client.dataset(run['defaultDatasetId']).list_items()['items']:
print(item['Transcript']['plain_text'][:400])

📝 Inputs (Video-focused)

Example input (Console JSON):

{
"startUrls":[
{"url":"https://www.youtube.com/watch?v=abcd1234"},
{"url":"https://youtu.be/abcd1234"}
],
"workers":5,
"exportFormats":["json","srt","vtt"],
"speakerDiarization":true,
"proxyConfiguration":{"useApifyProxy":true}
}

📄 Outputs

Each Dataset item contains rich metadata and multiple transcript representations. Example:

{
"inputUrl":"https://www.youtube.com/watch?v=abcd1234",
"fetchedAt":"2025-11-04T10:00:00Z",
"success":true,
"video":{
"title":"Example Video",
"duration":3720,
"chapters":[
{"title":"Intro","start":0},
{"title":"Main topic","start":60}
]
},
"Transcript":{
"plain_text":"Full transcript text...",
"with_timestamps":[
{"text":"Hello and welcome to the show.","start":0.2,"end":4.5},
{"text":"Today we'll talk about...","start":5.0,"end":9.3}
],
"speaker_segments":[
{"speaker":"Speaker 1","start":0.2,"end":4.5,"text":"Hello and welcome to the show."}
]
},
"files":{
"srt":"runs/<runId>/files/abcd1234.srt",
"vtt":"runs/<runId>/files/abcd1234.vtt"
}
}

Notes: Files (SRT/VTT) are attached to the run and accessible from the Files tab for easy download.

🔑 Environment Variables

• APIFY_TOKEN — required for authentication.
• HTTP_PROXY, HTTPS_PROXY — optional custom proxies.
• APIFY_PROXY_PASSWORD — use with Apify Proxy.

Store credentials securely as secrets — never in plaintext.

▶️ How to Run (short checklist)

1. Open Apify Console → Actors → YouTube Transcript Fetcher.
2. Provide video URLs (watch or youtu.be), set desired export formats, and toggle options.
3. Run and inspect Dataset and Files tabs for JSON/SRT/VTT outputs.

🛠 Logs & Troubleshooting

• No transcript available — video may lack captions and audio quality may be too poor for ASR.
• Partial transcripts — long videos may be chunked; check run logs for retry or chunk status.
• Timeouts / failures — lower workers or increase timeouts; enable proxy if region-restricted.

Monitor real-time logs in the Console Run Log panel for detailed error messages.

⏱ Scheduling & Webhooks

• Schedule daily or weekly runs for channel-level ingestion.
• Use Webhooks to push transcript files or Dataset updates to downstream systems (storage, search index, or ML pipelines).

🔟 Changelog

• 1.0.0 — 2025-11-04: Initial release — full-video support.

📝 Notes & TODO

• TODO: Add example of chapter-aware summarization pipeline.
• TODO: Improve speaker diarization accuracy with optional external ASR.

✅ Final note

This README is designed for researchers, media teams, and engineers who need robust, exportable transcripts from full-length YouTube videos — suitable for analytics, captioning, and training data generation.