yt-meta 0.2.5

A lightweight YouTube metadata library.

yt-meta

A Python library for finding video and channel metadata from YouTube.

Purpose

This library is designed to provide a simple and efficient way to collect metadata for YouTube videos and channels, such as titles, view counts, likes, and descriptions. It is built to support data analysis, research, or any application that needs structured information from YouTube.

Installation

This project uses uv for package management. You can install yt-meta from PyPI:

uv pip install yt-meta

To enable persistent caching, you need to install an optional dependency:

# For disk-based caching
uv pip install "yt-meta[persistent_cache]"

Inspiration

This project extends the great youtube-comment-downloader library, inheriting its session management while adding additional metadata capabilities.

Core Features

The library offers several ways to fetch metadata.

1. Get Video Metadata

Fetches comprehensive metadata for a specific YouTube video.

Example:

from yt_meta import YtMeta

client = YtMeta()
video_url = "https://www.youtube.com/watch?v=B68agR-OeJM"
metadata = client.get_video_metadata(video_url)
print(f"Title: {metadata['title']}")

2. Get Channel Metadata

Fetches metadata for a specific YouTube channel.

Example:

from yt_meta import YtMeta

client = YtMeta()
channel_url = "https://www.youtube.com/@samwitteveenai"
channel_metadata = client.get_channel_metadata(channel_url)
print(f"Channel Name: {channel_metadata['title']}")

3. Get All Videos from a Channel

Returns a generator that yields metadata for all videos on a channel's "Videos" tab, handling pagination automatically.

Example:

import itertools
from yt_meta import YtMeta

client = YtMeta()
channel_url = "https://www.youtube.com/@AI-Makerspace/videos"
videos_generator = client.get_channel_videos(channel_url)

# Print the first 5 videos
for video in itertools.islice(videos_generator, 5):
    print(f"- {video['title']} (ID: {video['video_id']})")

4. Get All Videos from a Playlist

Returns a generator that yields metadata for all videos in a playlist, handling pagination automatically.

Example:

import itertools
from yt_meta import YtMeta

client = YtMeta()
playlist_id = "PL-osiE80TeTt2d9bfVyTiXJA-UTHn6WwU"
videos_generator = client.get_playlist_videos(playlist_id)

# Print the first 5 videos
for video in itertools.islice(videos_generator, 5):
    print(f"- {video['title']} (ID: {video['video_id']})")

Caching

yt-meta includes a flexible caching system to improve performance and avoid re-fetching data from YouTube.

Default In-Memory Cache

By default, YtMeta uses a simple in-memory dictionary to cache results. This cache is temporary and only lasts for the lifetime of the client instance.

client = YtMeta()
# The first call will fetch from the network
meta1 = client.get_video_metadata("some_url") 
# This second call will be instant, served from the in-memory cache
meta2 = client.get_video_metadata("some_url") 

Persistent Caching

For caching results across different runs or scripts, you can provide a persistent, dictionary-like object to the client. The library provides an optional diskcache integration for this purpose.

First, install the necessary extra:

uv pip install "yt-meta[persistent_cache]"

Then, instantiate a diskcache.Cache object and pass it to the client:

from yt_meta import YtMeta
from diskcache import Cache

# The cache object can be any dict-like object.
# Here, we use diskcache for a persistent, file-based cache.
persistent_cache = Cache(".my_yt_meta_cache")

client = YtMeta(cache=persistent_cache)

# The first time this script runs, it will be slow (fetches from network).
# Subsequent runs will be very fast, reading directly from the disk cache.
metadata = client.get_video_metadata("some_url")

Any object that implements the MutableMapping protocol (e.g., __getitem__, __setitem__, __delitem__) can be used as a cache. See examples/features/19_alternative_caching_sqlite.py for a demonstration using sqlitedict.

5. Filtering Videos

The library provides a powerful filtering system via the filters argument, available on both get_channel_videos and get_playlist_videos. This allows you to find videos matching specific criteria.

Two-Stage Filtering: Fast vs. Slow

The library uses an efficient two-stage filtering process:

• Fast Filters: Applied first, using metadata that is available on the main channel or playlist page (e.g., title, view_count). This is very efficient.
• Slow Filters: Applied second, only on videos that pass the fast filters. This requires fetching full metadata for each video individually, which is much slower.

The client automatically detects when a slow filter is used and sets fetch_full_metadata=True for you.

Supported Fields and Operators:

Field	Supported Operators	Filter Type
title	contains, re, eq	Fast
description_snippet	contains, re, eq	Fast
view_count	gt, gte, lt, lte, eq	Fast
duration_seconds	gt, gte, lt, lte, eq	Fast
publish_date	gt, gte, lt, lte, eq	Fast
like_count	gt, gte, lt, lte, eq	Slow (Automatic full metadata fetch)
category	contains, re, eq	Slow (Automatic full metadata fetch)
keywords	contains_any, contains_all	Slow (Automatic full metadata fetch)
full_description	contains, re, eq	Slow (Automatic full metadata fetch)

Example: Basic Filtering (Fast)

This example finds popular, short videos. Since both view_count and duration_seconds are fast filters, this query is very efficient.

import itertools
from yt_meta import YtMeta

client = YtMeta()
channel_url = "https://www.youtube.com/@TED/videos"

# Find videos over 1M views AND shorter than 5 minutes (300s)
adv_filters = {
    "view_count": {"gt": 1_000_000},
    "duration_seconds": {"lt": 300}
}

# This is fast because both view_count and duration are available
# in the basic metadata returned from the main channel page.
videos = client.get_channel_videos(
    channel_url,
    filters=adv_filters
)

for video in itertools.islice(videos, 5):
    views = video.get('view_count', 0)
    duration = video.get('duration_seconds', 0)
    print(f"- {video.get('title')} ({views:,} views, {duration}s)")

Example: Filtering by Date

The easiest way to filter by date is to use the start_date and end_date arguments. The library also optimizes this for channels by stopping the search early once videos are older than the specified start_date.

You can provide datetime.date objects or a relative date string (e.g., "30d", "6 months ago").

Using datetime.date objects:

from datetime import date
from yt_meta import YtMeta
import itertools

client = YtMeta()
channel_url = "https://www.youtube.com/@samwitteveenai/videos"

# Get videos from a specific window
start = date(2024, 1, 1)
end = date(2024, 3, 31)

videos = client.get_channel_videos(
    channel_url,
    start_date=start,
    end_date=end
)

for video in itertools.islice(videos, 5):
    p_date = video.get('publish_date', 'N/A')
    print(f"- {video.get('title')} (Published: {p_date})")

Using relative date strings:

from yt_meta import YtMeta
import itertools

client = YtMeta()
channel_url = "https://www.youtube.com/@samwitteveenai/videos"

recent_videos = client.get_channel_videos(
    channel_url,
    start_date="6 months ago"
)

for video in itertools.islice(recent_videos, 5):
    p_date = video.get('publish_date', 'N/A')
    print(f"- {video.get('title')} (Published: {p_date})")

Important Note on Playlist Filtering: When filtering a playlist by date, the library must fetch metadata for all videos first, as playlists are not guaranteed to be chronological. This can be very slow for large playlists.

Logging

yt-meta uses Python's logging module to provide insights into its operations. To see the log output, you can configure a basic logger.

Example:

import logging

# Configure logging to print INFO-level messages
logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(name)s - %(levelname)s - %(message)s')

# Now, when you use the client, you will see logs
# ...

API Reference

YtMeta(cache: Optional[MutableMapping] = None)

The main client for interacting with the library. It inherits from youtube-comment-downloader and handles session management.

• cache: An optional dictionary-like object to use for caching. If None, a temporary in-memory cache is used.

get_video_metadata(youtube_url: str) -> dict

Fetches comprehensive metadata for a single YouTube video.

• youtube_url: The full URL of the YouTube video.
• Returns: A dictionary containing metadata such as title, description, view_count, like_count, publish_date, category, and more.
• Raises: VideoUnavailableError if the video page cannot be fetched or the video is private/deleted.

get_channel_metadata(channel_url: str) -> dict

Fetches metadata for a specific channel. Results are cached.

• channel_url: The URL of the channel.
• Returns: A dictionary with channel metadata like title, description, subscriber_count, vanity_url, etc.
• Raises: VideoUnavailableError, MetadataParsingError.

get_channel_videos(channel_url: str, ..., stop_at_video_id: str = None, max_videos: int = -1) -> Generator[dict, None, None]

Yields metadata for videos from a channel.

• start_date: The earliest date for videos to include (e.g., date(2023, 1, 1) or "30d").
• end_date: The latest date for videos to include.
• fetch_full_metadata: If True, fetches detailed metadata for every video. Automatically enabled if a "slow filter" is used.
• filters: A dictionary of advanced filter conditions (see above).
• stop_at_video_id: Stops fetching when this video ID is found.
• max_videos: The maximum number of videos to return.

get_playlist_videos(playlist_id: str, ..., stop_at_video_id: str = None, max_videos: int = -1) -> Generator[dict, None, None]

Yields metadata for videos from a playlist.

• start_date: The earliest date for videos to include (e.g., date(2023, 1, 1) or "30d").
• end_date: The latest date for videos to include.
• fetch_full_metadata: If True, fetches detailed metadata for every video.
• filters: A dictionary of advanced filter conditions.
• stop_at_video_id: Stops fetching when this video ID is found.
• max_videos: The maximum number of videos to return.

clear_cache()

Clears all items from the configured cache (both in-memory and persistent).

Error Handling

The library uses custom exceptions to signal specific error conditions.

YtMetaError

The base exception for all errors in this library.

MetadataParsingError

Raised when the necessary metadata (e.g., the ytInitialData JSON object) cannot be found or parsed from the YouTube page. This can happen if YouTube changes its page structure.

VideoUnavailableError

Raised when a video or channel page cannot be fetched. This could be due to a network error, a deleted/private video, or an invalid URL.