All-in-one music manager: scrapes albums, artists and songs from musicbrainz and automatically download them from youtube.
Project description
Music Dragon
Desktop application written in Python3 + PyQt5 with a spotify-likish interface that can be used to search artists, albums and songs and automatically download and tag those with one click.
Supports Linux and Windows (experimental).
Features
- Search artists, albums or songs (
musicbrainz
) - Automatically download single songs or entire albums from youtube with a single click (
youtube_dl
) - Manually download any song or playlist from youtube by pasting its URL
- Automatically fetch images of songs and albums
- Automatically tag downloaded songs using musicbrainz and youtube metadata, with a configurable tagging pattern
- Show and manage local songs
- Automatically recognize whether songs and albums have already been downloaded (the border of the song/album's cover changes accordingly)
- Play songs, either locally or directly from youtube stream
What it looks like
INSTALLATION
Linux
pip install music-dragon
Windows
Using pip:
pip install music-dragon
Otherwise:
- Clone the repository
- Follow the instructions at .\other\pyinstaller_data\windows\README.txt:
- Place the ffmpeg binaries (ffmpeg, ffplay, ffprobe) in .\other\pyinstaller_data\windows\ffmpeg
- Place the content of the VLC folder in .\other\pyinstaller_data\windows\vlc
- Compile with .\scripts\build-windows-exe.cmd
- Run the executable in .\dist\main\main.exe
USAGE
music-dragon
TODO
- Improve UI
- Allow manual tagging of local songs (
eyed3
) - Solve some known bugs
- Refactor
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
music-dragon-0.9.tar.gz
(228.8 kB
view details)
File details
Details for the file music-dragon-0.9.tar.gz
.
File metadata
- Download URL: music-dragon-0.9.tar.gz
- Upload date:
- Size: 228.8 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.0 CPython/3.10.5
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 2dd366a7dc30806637418e39ea5e59765017c07f136aa9dd0c9c2bbcae91d127 |
|
MD5 | a4483a6f98bbb645141d6f5c2b7af9f2 |
|
BLAKE2b-256 | d733170f6b5dcfaebeee2fd18329ee355df9777428dd04eec0ab3810935b6922 |