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YouTube Transcript

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Get full transcripts and timestamped captions from YouTube videos. Paste video URLs or IDs, choose a language, and export clean text and segments as JSON, CSV or Excel. No YouTube API key required.

Pricing

from $1.50 / 1,000 results

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ali raza

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3 days ago

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YouTube Transcript Scraper in Python

An Apify Actor that extracts transcripts (captions) from YouTube videos in Python, with no YouTube API key required. You pass in video URLs or IDs via input, which is defined by the input schema. For each video the Actor stores the full transcript text plus timestamped segments in a dataset, where you can download them as JSON, CSV, Excel and more.

The Actor uses HTTPX2 to call YouTube's internal (InnerTube) API the same way the Android app does, so no browser or HTML parsing is needed.

Included features

Apify SDK for Python - a toolkit for building Apify Actors and scrapers in Python
Input schema - define and easily validate a schema for your Actor's input
Dataset - store structured data where each object stored has the same attributes
Apify Proxy - optional proxy support, since YouTube often blocks datacenter IPs
HTTPX2 - library for making asynchronous HTTP requests in Python

Input

Field	Type	Description
`videoUrls`	array	Video URLs (`watch`, `youtu.be`, `shorts`, `embed`) or bare 11-character video IDs.
`language`	string	Preferred caption language code, e.g. `en`, `es`, `de`. Falls back to any available track. Default `en`.
`country`	string	Two-letter country code sent to YouTube. Default `US`.
`proxyConfiguration`	object	Proxy settings. Residential proxies are the most reliable option.

Example:

{
  "videoUrls": [
    "https://www.youtube.com/watch?v=JpA6KCHK5tM",
    "https://youtu.be/JpA6KCHK5tM"
  ],
  "language": "en",
  "country": "US",
  "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": ["RESIDENTIAL"] }
}

Output

One dataset item per video:

{
  "videoId": "JpA6KCHK5tM",
  "url": "https://www.youtube.com/watch?v=JpA6KCHK5tM",
  "language": "en",
  "segmentCount": 123,
  "text": "Full transcript as a single string...",
  "segments": [
    { "start": 0.0, "text": "First caption line" },
    { "start": 4.5, "text": "Second caption line" }
  ]
}

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