youtubetranscriptdevapi 0.1.1

Official Python SDK for YouTubeTranscript.dev — extract, transcribe, and translate YouTube video transcripts

YouTubeTranscript Python SDK

Official Python client for the YouTubeTranscript.dev API
Extract, transcribe, and translate YouTube video transcripts.

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Installation

pip install youtubetranscriptdevapi

Quick Start

from youtubetranscript import YouTubeTranscript

yt = YouTubeTranscript("your_api_key")

# Extract transcript
result = yt.transcribe("dQw4w9WgXcQ")

print(f"Segments: {len(result.segments)}")
print(f"Duration: {result.duration:.0f}s")
print(f"Words: {result.word_count}")

for seg in result.segments[:5]:
    print(f"[{seg.start_formatted}] {seg.text}")

Get your free API key at youtubetranscript.dev/dashboard

Features

# Translate to any language
result = yt.transcribe("dQw4w9WgXcQ", language="es")

# Choose caption source
result = yt.transcribe("dQw4w9WgXcQ", source="manual")

# Format options
result = yt.transcribe("dQw4w9WgXcQ", format={"timestamp": True, "words": True})

# Batch — up to 100 videos at once
batch = yt.batch(["video1", "video2", "video3"])
for t in batch.completed:
    print(f"{t.video_id}: {t.word_count} words")

# ASR audio transcription (for videos without captions)
job = yt.transcribe_asr("video_without_captions")
result = yt.wait_for_job(job.job_id)  # polls until complete
print(result.text)

# Export formats
print(result.to_srt())       # SRT subtitles
print(result.to_vtt())       # WebVTT subtitles
print(result.to_plain_text())       # Plain text
print(result.to_timestamped_text()) # Text with timestamps

# Search within transcript
matches = result.search("keyword")

# Account stats
stats = yt.stats()
print(f"Credits: {stats.credits_remaining}")

# History
history = yt.list_transcripts(search="python tutorial", limit=5)

Async Client

import asyncio
from youtubetranscript import AsyncYouTubeTranscript

async def main():
    async with AsyncYouTubeTranscript("your_api_key") as yt:
        # Single
        result = await yt.transcribe("dQw4w9WgXcQ")

        # Concurrent
        results = await asyncio.gather(
            yt.transcribe("video1"),
            yt.transcribe("video2"),
            yt.transcribe("video3"),
        )

asyncio.run(main())

Error Handling

from youtubetranscript import YouTubeTranscript
from youtubetranscript.exceptions import (
    NoCaptionsError,
    AuthenticationError,
    InsufficientCreditsError,
    RateLimitError,
)

yt = YouTubeTranscript("your_api_key")

try:
    result = yt.transcribe("some_video")
except NoCaptionsError:
    # No captions — try ASR
    job = yt.transcribe_asr("some_video")
    result = yt.wait_for_job(job.job_id)
except AuthenticationError:
    print("Check your API key")
except InsufficientCreditsError:
    print("Top up at youtubetranscript.dev/pricing")
except RateLimitError as e:
    print(f"Rate limited — retry after {e.retry_after}s")

API Reference

YouTubeTranscript(api_key, *, base_url, timeout, max_retries)

Method	Description
transcribe(video, *, language, source, format)	Extract transcript
transcribe_asr(video, *, language, webhook_url)	ASR audio transcription
get_job(job_id)	Check ASR job status
wait_for_job(job_id, *, poll_interval, timeout)	Poll until ASR completes
batch(video_ids, *, language)	Batch extract (up to 100)
get_batch(batch_id)	Check batch status
list_transcripts(*, search, language, status, limit, page)	Browse history
get_transcript(video_id, *, language, source)	Get saved transcript
stats()	Account credits & usage
delete_transcript(*, video_id, ids)	Delete transcripts

Transcript object

Property/Method	Description
segments	List of Segment objects
text	Full transcript as string
video_id	YouTube video ID
language	Transcript language
word_count	Total word count
duration	Total duration in seconds
to_srt()	Export as SRT
to_vtt()	Export as WebVTT
to_plain_text()	Plain text export
to_timestamped_text()	Text with [MM:SS] timestamps
search(query)	Find segments by text

Segment object

Property	Description
text	Segment text
start	Start time (seconds)
end	End time (seconds)
duration	Duration (seconds)
start_formatted	"MM:SS" format
start_hms	"HH:MM:SS" format

Credit Costs

Operation	Cost
Captions extraction	1 credit
Translation	1 credit per 2,500 chars
ASR audio transcription	1 credit per 90 seconds
Re-fetch owned transcript	Free

License

MIT — see LICENSE

Links

• Website
• PyPI
• API Docs
• Dashboard
• Pricing