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YouTube Helper

🇫🇷 · 🇬🇧

CI License: BSD-3-Clause Python Local-first

YouTube Helper belongs to a collection of libraries called AI Helpers developed for building Artificial Intelligence.

The Promise

Local-first by design. youtube-helper runs entirely on your machine: it fetches only the media you ask for, and your data is never uploaded to a third-party service. No telemetry, no account, no cloud lock-in. You own the whole pipeline. Part of the AI Helpers suite: sovereignty over your data through local-first open source.

(youtube-helper does reach the internet: it downloads media from the source site you point it at. The promise is about no exfiltration and no telemetry, nothing about you or your requests is ever sent anywhere except the site hosting the media you asked for.)

🌍 AI Helpers

logo

YouTube Helper is a Python library that provides utility functions for downloading videos, audio, and thumbnails from platforms like YouTube, Vimeo, and DailyMotion. It does the actual fetching through yt-dlp, an open-source tool that already knows how to talk to hundreds of video sites, each with its own quirks; youtube-helper wraps it in one consistent Python interface so you never have to learn those quirks yourself. It also supports post-processing tasks such as converting or merging media files with ffmpeg, the standard command-line tool for reading, converting, and combining audio and video.

Documentation

💻 Documentation

🗺️ Landscape

📋 Examples

Features

Downloads (to disk), in youtube_helper.main:

  • download_video(url, output_path) / download_audio(url, output_path) / download_thumbnail(url, output_path).
  • video_url_meta_data(url) / is_valid_video_url(url) for cheap metadata probes.
  • default_ytdlp_options(verbose, ...) for customisable yt-dlp options.

Stream catalog and direct-URL resolution, in youtube_helper.streaming:

  • resolve_direct_url(url, prefer="audio"|"video"): a quick "give me one direct ffmpeg-ready URL".
  • list_video_streams(url): enumerate every video format yt-dlp finds (codec, resolution, fps, bitrate, and more).
  • pick_video_stream(url, prefer_codec=, prefer_format=, max_fps=, language=, cookies_from_browser=): constrained picker, returns one VideoStreamInfo ready to feed video_helper.extract_frames.
  • extract_frames_stream(url, ..., **extract_frames_kwargs): one-call composition of pick_video_stream and video_helper.extract_frames. It auto-wires headers and forwards any extract_frames kwarg (destination, device, batch_size, output_width, frame_step, and more), the shortest path from a YouTube, Vimeo, or Twitch URL to ML-ready frames.
  • The audio stream catalog and picker intentionally live in podcast-helper, the suite's single owner for audio PCM streaming.

No-API engagement metadata, in youtube_helper.branding:

  • channel_info(url) / channel_videos(url, max_videos, include_shorts, include_lives): a channel snapshot plus a paginated video list, with normalised engagement metrics on a cross-platform schema.
  • video_engagement(url) / engagement_batch([urls]): per-video views, likes, comments, and channel follower count, with a tolerant batched variant.
  • video_subtitles(url, output_dir, langs=("fr","en")): auto-subtitle download.
  • video_comments(url, max_count, cookies_from_browser="firefox"|"chrome"|...): a comments sample.
  • is_short(meta) / ensure_recent_ytdlp(min_version): helpers.
  • Built on yt-dlp's public metadata only: no Google Data API, no Vimeo API, no OAuth, no quota. In plain terms, the official platform APIs require you to register an application, obtain credentials through OAuth (the login handshake that proves your app is allowed to act on a user's behalf), and stay under a quota (a hard cap on how many requests you can make per day). Reading the same public page a browser sees needs none of that: no account to register, no key to request, no daily ceiling to run into.

Installation

Prerequisites: Python 3.10-3.13, git, yt-dlp, and ffmpeg, cross-platform:

  • 🍎 macOS (Homebrew): brew install python git yt-dlp ffmpeg
  • 🐧 Ubuntu/Debian: sudo apt update && sudo apt install -y python3 python3-pip git yt-dlp ffmpeg
  • 🪟 Windows (PowerShell): winget install Python.Python.3.12 Git.Git yt-dlp.yt-dlp Gyan.FFmpeg

Optional — Tor (only needed for the download resilience fallback #3):

  • 🍎 macOS (Homebrew): brew install tor && brew services start tor
  • 🐧 Ubuntu/Debian: sudo apt update && sudo apt install -y tor (the package's systemd service starts automatically; if not, sudo systemctl enable --now tor)
  • 🪟 Windows: choco install tor (Chocolatey), then run tor in a terminal — or install the Tor Browser and set YOUTUBE_HELPER_TOR_PROXY=socks5h://127.0.0.1:9150 (its bundled proxy listens on 9150, not the standalone daemon's default 9050)

We recommend using Python environments. Check this link if you're unfamiliar with setting one up: 🥸 Tech tips.

From PyPI (recommended)

pip install youtube-helper

# Optional surfaces
pip install "youtube-helper[cli]"       # click-based CLI twin
pip install "youtube-helper[api]"       # FastAPI HTTP surface

From source (no PyPI)

git clone https://github.com/warith-harchaoui/youtube-helper.git
cd youtube-helper
pip install -e .

# Optional surfaces
pip install -e ".[cli]"
pip install -e ".[api]"

Usage

For the full catalog of recipes (downloads, stream catalog / picker, direct-URL resolver, composing with video-helper, branding metadata, subtitles & comments), see 📋 EXAMPLES.md.

Quick start: download a video, extract metadata, and download the audio:

import youtube_helper as yth
import video_helper as vh
import audio_helper as ah
import os_helper as osh
import os

osh.verbosity(0)

# Example YouTube URL
youtube_url = "https://www.youtube.com/watch?v=YE7VzlLtp-4"

folder = "yt_tests"
os.makedirs(folder, exist_ok=True)

# Download a video
video = "big-buck-bunny.mp4"
video = os.path.join(folder, video)
yth.download_video(youtube_url, video)

# Extract metadata from the video URL
metadata = yth.video_url_meta_data(youtube_url)
print(metadata["title"])
# Big Buck Bunny

print(metadata["duration"])
# 597

print(metadata["description"])
# Big Buck Bunny tells the story of a giant rabbit with a heart bigger than himself. When one sunny day three rodents rudely harass him, something snaps... and the rabbit ain't no bunny anymore! In the typical cartoon tradition he prepares the nasty rodents a comical revenge.
# 
# Licensed under the Creative Commons Attribution license
# 
# http://www.bigbuckbunny.org/

print(metadata["channel"])
# Blender

details = vh.video_dimensions(video)
print(details)
# {'width': 1280, 'height': 720, 'duration': 596.458, 'frame_rate': 24.0, 'has_sound': True}

# Download the audio from the video
audio = "big-buck-bunny.mp3"
audio = os.path.join(folder, audio)
yth.download_audio(youtube_url, audio)

audio, sample_rate = ah.load_audio(audio)
print(sample_rate)
# 44100

Download resilience

Every yt-dlp call in youtube_helper.main (metadata, thumbnail, audio, video) retries automatically when the normal approach gets blocked (rate-limiting, bot checks, IP bans):

  1. Normal: the default request, as configured by default_ytdlp_options.
  2. Browser User-Agent: retried with a fully-populated, up-to-date desktop Chrome User-Agent and matching headers. Override with the YOUTUBE_HELPER_USER_AGENT environment variable.
  3. Tor: retried again over a local Tor SOCKS proxy. Tor routes the request through a chain of relays before it reaches the site, so the site sees a different, unrelated IP address instead of yours; a block keyed on your IP no longer applies. A SOCKS proxy is simply a local relay point a program can send its traffic through instead of connecting directly, which is how an application hands its requests off to Tor. Configured as socks5h://127.0.0.1:9050 by default (DNS lookups are routed through Tor too, so the site name itself is never leaked outside the tunnel). Requires a Tor daemon (the background process that runs the relay chain) running locally; see the per-OS install commands under Installation. Override the proxy URL with YOUTUBE_HELPER_TOR_PROXY.

If all three fail, the original error from the last attempt is raised.

Legal and Ethical Use

YouTube Helper is a thin wrapper around yt-dlp and ffmpeg. You are responsible for how you use it. Only download or process media that you own, that is in the public domain or under a permissive license (e.g. Creative Commons), or for which you have explicit permission from the rights holder. Respect each platform's Terms of Service and any applicable copyright, privacy, and data-protection laws in your jurisdiction. The authors provide this library for legitimate uses such as personal archiving, accessibility, research, and content you have rights to, not for circumventing access controls or redistributing copyrighted material.

Multi-surface exposure

youtube-helper is not just a library: the same functions are exposed as two command-line interfaces (CLIs, programs you drive by typing commands rather than writing Python), a FastAPI HTTP surface (the same functions reachable over the network as a small web service), MCP tools (the Model Context Protocol, a standard that lets an AI agent call a program's functions directly, the same way a human would call them from the command line), and a browser GUI (a point-and-click page). Four doors onto the same underlying code, so a script, a web service, an AI agent, and a human at a browser can all reach the exact same download logic:

# Python library (default)
import youtube_helper as yth

# argparse-based CLI (installed automatically)
youtube-helper metadata     --url https://www.youtube.com/watch?v=YE7VzlLtp-4
youtube-helper audio        --url https://www.youtube.com/watch?v=YE7VzlLtp-4 --output out.mp3
youtube-helper resolve      --url https://www.youtube.com/watch?v=YE7VzlLtp-4 --prefer audio
youtube-helper channel-info --url https://www.youtube.com/@blender

# click-based CLI twin (needs the [cli] extra)
pip install "youtube-helper[cli]"
youtube-helper-click metadata --url https://www.youtube.com/watch?v=YE7VzlLtp-4

# FastAPI HTTP surface (needs the [api] extra)
pip install "youtube-helper[api]"
uvicorn youtube_helper.api:app --port 8000
# → OpenAPI docs at http://localhost:8000/docs

# Browser GUI (needs the [api] extra): paste a URL, pick audio or video
uvicorn youtube_helper.api:app --port 8000
# → open http://localhost:8000/gui  (or just http://localhost:8000/)

# MCP tools (needs the [mcp] extra): same app, plus an /mcp endpoint
pip install "youtube-helper[mcp]"
youtube-helper-mcp

Download bench GUI (GET /gui): a single self-contained page (Tailwind via CDN + vanilla JS, no build step). Paste a YouTube (or any yt-dlp-supported) URL, choose audio (with a sample rate) or video, hit Download, and the result plays inline with a download link. It POSTs to the same /audio / /video endpoints, zero extra server logic. Local-first: the page only talks to your local API.

See TRIGGERS.md for the exhaustive catalogue of what fires each operation.

Docker image:

docker build -t youtube-helper .
docker run --rm -p 8000:8000 youtube-helper

A richer GUI plan (video library board, channel comparator, batch downloader) lives in GUI.md.

Author

Acknowledgements

Special thanks to Mohamed Chelali and Bachir Zerroug for fruitful discussions.

License

This project is licensed under the BSD-3-Clause License. See the LICENSE file for details.

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