The youtube_transcript_api Python library is great — until YouTube bans your server's IP. VidProxy is the hosted REST API alternative: same one-call simplicity, no IP management, no blocked requests, no self-hosting maintenance.
# Running on Render, Railway, Heroku, AWS Lambda, or any cloud host:
youtube_transcript_api._errors.TranscriptsDisabled:
Could not retrieve a transcript for the video ...
youtube_transcript_api._errors.NoTranscriptFound:
No transcripts were found for any of the requested ...
# Or the silent one — requests hang, then timeout with no useful error
requests.exceptions.ConnectionError: HTTPSConnectionPool ...
Max retries exceededThese errors don't mean the video has no transcript. They mean YouTube blocked your server's IP address. The library makes direct HTTP requests to YouTube from your cloud host — and data center IPs get rate-limited or blocked, especially at volume.
The error messages are misleading. TranscriptsDisabled and NoTranscriptFound both get thrown when the underlying fetch fails due to an IP block, even when the video has perfectly good auto-generated captions. Check the same video in a browser — the transcript is right there.
from youtube_transcript_api import YouTubeTranscriptApi
def get_transcript(video_id: str) -> str:
try:
transcript = YouTubeTranscriptApi.get_transcript(video_id)
return " ".join(chunk["text"] for chunk in transcript)
except Exception as e:
# Could be IP block, rate limit, or actual unavailability
# No way to tell which without digging into error internals
raiseimport os
import requests
VIDPROXY_API_KEY = os.environ["VIDPROXY_API_KEY"]
def get_transcript(video_id: str) -> str:
r = requests.get(
"https://vidproxy.pro/api/transcript",
params={"video_id": video_id},
headers={"X-API-Key": VIDPROXY_API_KEY},
)
data = r.json()
if not data["available"]:
return ""
return data["text"]
# Same response shape — segments with text, start, duration:
# data["segments"] = [{"text": "...", "start": 18.08, "duration": 2.56}, ...]data["text"] is the full plain-text transcript, data["segments"] is the timestamped array. Drop-in for any code that consumed the library's output format.
| Capability | youtube_transcript_api (Python) | VidProxy |
|---|---|---|
| Reliability | ||
| Works on Render / Railway / Heroku | ✕ IP gets blocked | ✓ Always |
| Works on AWS Lambda / GCF | ✕ Shared IP ranges blocked | ✓ HTTP call, no IP exposure |
| Works in local dev / scripts | ✓ Usually fine | ✓ Always |
| Rotating proxy required | Often required | No |
| Uptime SLA | ✕ Best effort, open source | ✓ Managed service |
| Data & Format | ||
| Full plain-text transcript | ✓ | ✓ |
| Timestamped segments (start + duration) | ✓ | ✓ |
| Auto-generated captions | ✓ | ✓ |
| Multi-language transcript selection | ✓ | ✕ English only (roadmap) |
| Beyond On-Demand | ||
| Channel monitoring — push on new video | ✕ | ✓ Webhook delivery |
| Webhook payload includes transcript | ✕ | ✓ |
| AI summary + key takeaways | ✕ | ✓ Pro / Agency |
| Keyword alerts on transcript content | ✕ | ✓ Pro / Agency |
| Setup & Maintenance | ||
| pip install | ✓ | ✕ HTTP call, no package needed |
| Proxy management required | In production: yes | No |
| Works from any language / platform | ✕ Python only | ✓ Any HTTP client |
| Cost | Free (+ proxy costs in prod) | Free tier / from $9/mo |
The youtube_transcript_api Python library is a well-built open source project. It works reliably from your local machine or home IP — YouTube doesn't bother blocking residential traffic the same way it blocks data center ranges.
The problems start the moment you deploy. Cloud providers (Render, Railway, Heroku, AWS, GCP, Azure) run from shared IP pools that YouTube has already catalogued as scraper infrastructure. Your requests start failing — usually with misleading error messages — and the only fix is a proxy layer.
VidProxy also goes beyond on-demand lookups. If you need to monitor a channel and get transcripts pushed to your app automatically when new videos drop, that's a separate feature entirely — no polling required.
pip install requestsexport VIDPROXY_API_KEY=your_api_key_hereimport os, requests
r = requests.get(
"https://vidproxy.pro/api/transcript",
params={"video_id": "dQw4w9WgXcQ"},
headers={"X-API-Key": os.environ["VIDPROXY_API_KEY"]},
)
data = r.json()
# Plain text
print(data["text"])
# Timestamped segments
for seg in data["segments"]:
print(f"[{seg['start']:.1f}s] {seg['text']}")
# Credits remaining this month
print(data["credits_remaining"])r = requests.get(
"https://vidproxy.pro/api/transcript",
params={"url": "https://youtube.com/watch?v=dQw4w9WgXcQ"},
headers={"X-API-Key": os.environ["VIDPROXY_API_KEY"]},
)YouTube detects requests originating from data center IP ranges — the same ranges used by Render, Railway, AWS, GCP, and every other cloud provider. The library makes direct requests from your server, which exposes your host's IP. VidProxy routes through infrastructure that doesn't trigger YouTube's blocks.
No. VidProxy is a REST API — you call it with any HTTP client (requests, httpx, aiohttp, curl). No package to install, no Python dependency to maintain.
Yes — use httpx or aiohttp instead of requests. The API is a standard HTTP GET, so any async HTTP client works fine.
The API returns "available": false. You're not charged a credit. If YouTube explicitly disabled captions for that video, the response also includes "disabled": true. No exception thrown — just check the flag.
Free: 10/month. Starter ($9/mo): 500/month. Pro ($29/mo): 2,500/month. Agency ($79/mo): 10,000/month. Failed lookups (unavailable transcripts) don't count against your quota.
Yes, with the rate limit in mind: 60 requests/minute on free and Starter, 300/minute on Pro and Agency. For large batch jobs, Pro or Agency is the right tier.
Absolutely — many teams do exactly that. Use the library in local dev (where your IP isn't blocked) and VidProxy in staging and production.
Free tier, no credit card. Works from Render, Railway, Lambda, anywhere.
No credit card · 10 free lookups/month · Cancel anytime