Skip to main content

The next generation MusicBrainz tagger

Project description

MusicBrainz Picard

Github Actions Status Codacy Grade

MusicBrainz Picard is a cross-platform (Linux, macOS, Windows) audio tagging application. It is the official MusicBrainz tagger.

Picard supports the majority of audio file formats, is capable of using audio fingerprints (AcoustIDs), performing CD lookups and disc ID submissions, and it has excellent Unicode support. Additionally, there are several plugins available that extend Picard's features.

When tagging files, Picard uses an album-oriented approach. This approach allows it to utilize the MusicBrainz data as effectively as possible and correctly tag your music. For more information, see the illustrated quick start guide to tagging and the documentation.

Features

  • Multiple formats: Picard supports all popular music formats, including MP3, FLAC, OGG, M4A, WMA, WAV, and more.
  • AcoustID: Picard uses AcoustID audio fingerprints, allowing files to be identified by the actual music, even if they have no metadata.
  • Comprehensive database: Picard uses the open and community-maintained MusicBrainz database to provide accurate information about millions of music releases.
  • CD lookups: Picard can lookup entire music CDs with a click.
  • Plugin support: If you need a particular feature, you can choose from a selection of available plugins or write your own.
  • Scripting: A flexible and powerful, yet easy to learn, scripting language allows you to exactly specify how your music files will be named and how the tags will look like.
  • Cover Art: Picard can find and download the correct cover art for your albums.
  • Open Source: Picard is licensed under the GNU General Public License 2.0 or later, and is hosted on GitHub where it is actively developed.

Installation

Binary downloads are available on the Picard download page.

INSTALL.md has instructions on building this codebase.

Support and issue reporting

Please report all bugs and feature requests in the MusicBrainz issue tracker. If you need support in using Picard please read the documentation first and have a look at the MusicBrainz community forums.

Trivia

Picard is named after Captain Jean-Luc Picard from the TV series Star Trek: The Next Generation.

Project details


Release history Release notifications | RSS feed

This version

2.8

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

picard-2.8.tar.gz (4.5 MB view details)

Uploaded Source

Built Distributions

picard-2.8-cp310-cp310-win_amd64.whl (2.9 MB view details)

Uploaded CPython 3.10 Windows x86-64

picard-2.8-cp39-cp39-win_amd64.whl (2.9 MB view details)

Uploaded CPython 3.9 Windows x86-64

picard-2.8-cp39-cp39-macosx_10_15_x86_64.whl (2.9 MB view details)

Uploaded CPython 3.9 macOS 10.15+ x86-64

picard-2.8-cp38-cp38-win_amd64.whl (2.9 MB view details)

Uploaded CPython 3.8 Windows x86-64

picard-2.8-cp38-cp38-macosx_10_15_x86_64.whl (2.9 MB view details)

Uploaded CPython 3.8 macOS 10.15+ x86-64

picard-2.8-cp37-cp37m-win_amd64.whl (2.9 MB view details)

Uploaded CPython 3.7m Windows x86-64

picard-2.8-cp37-cp37m-macosx_10_15_x86_64.whl (2.9 MB view details)

Uploaded CPython 3.7m macOS 10.15+ x86-64

picard-2.8-cp36-cp36m-win_amd64.whl (2.9 MB view details)

Uploaded CPython 3.6m Windows x86-64

picard-2.8-cp36-cp36m-macosx_10_14_x86_64.whl (2.9 MB view details)

Uploaded CPython 3.6m macOS 10.14+ x86-64

File details

Details for the file picard-2.8.tar.gz.

File metadata

  • Download URL: picard-2.8.tar.gz
  • Upload date:
  • Size: 4.5 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.0 CPython/3.8.12

File hashes

Hashes for picard-2.8.tar.gz
Algorithm Hash digest
SHA256 49b926453698dbfd1b9781c52824022d50212e938a2aa2a4be8233a5ee377833
MD5 1909772e6bf61a5f4e3af9eedbb5a6eb
BLAKE2b-256 c9d49e6811a1d443fd5e1180f0a7765585cd1e1701bf3098d712ba3cc553e143

See more details on using hashes here.

File details

Details for the file picard-2.8-cp310-cp310-win_amd64.whl.

File metadata

  • Download URL: picard-2.8-cp310-cp310-win_amd64.whl
  • Upload date:
  • Size: 2.9 MB
  • Tags: CPython 3.10, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.0 CPython/3.10.4

File hashes

Hashes for picard-2.8-cp310-cp310-win_amd64.whl
Algorithm Hash digest
SHA256 4414b1ccb114b83b2e8db4db9fdf24c47ec3080f560e2e3ca7498cc5c06ef55f
MD5 0f7159b1762be45d844197c56f07816e
BLAKE2b-256 5da443219eae112d95024605e6c4e50c9c4f8686347e414b02f4109017fb729b

See more details on using hashes here.

File details

Details for the file picard-2.8-cp39-cp39-win_amd64.whl.

File metadata

  • Download URL: picard-2.8-cp39-cp39-win_amd64.whl
  • Upload date:
  • Size: 2.9 MB
  • Tags: CPython 3.9, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.0 CPython/3.9.12

File hashes

Hashes for picard-2.8-cp39-cp39-win_amd64.whl
Algorithm Hash digest
SHA256 cb636830cc3bdb17348edf67885eefd3ac5019fecab434e639f33ed0b42dba76
MD5 2b7cb2b1d1b91c0ea12e7f8389823670
BLAKE2b-256 9049f9574e0e12908103207122bb4d0a403a35ee2be19316bd0a0a9c6d96632f

See more details on using hashes here.

File details

Details for the file picard-2.8-cp39-cp39-macosx_10_15_x86_64.whl.

File metadata

File hashes

Hashes for picard-2.8-cp39-cp39-macosx_10_15_x86_64.whl
Algorithm Hash digest
SHA256 f8fb5c53388ac8db320a4cb81da464ff630b7c057a24c6624fbb30f6106a1a1f
MD5 5b9c3a55b58aa7e98218094325b29c9f
BLAKE2b-256 2e6ac308e1ec4c7309c22f4f09832198d776cc96fe787d3bf83914bbca1dea76

See more details on using hashes here.

File details

Details for the file picard-2.8-cp38-cp38-win_amd64.whl.

File metadata

  • Download URL: picard-2.8-cp38-cp38-win_amd64.whl
  • Upload date:
  • Size: 2.9 MB
  • Tags: CPython 3.8, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.0 CPython/3.8.10

File hashes

Hashes for picard-2.8-cp38-cp38-win_amd64.whl
Algorithm Hash digest
SHA256 7fbd266d6ea8f5e869dbe763984805e24a36db69dd655e1bf90df18f2a6b00c4
MD5 78a103e23b614ae8a867eded8a81308d
BLAKE2b-256 f50be3d17fddd29320fa42393a7c554a64968d05f514f5b3d73389750b1a9875

See more details on using hashes here.

File details

Details for the file picard-2.8-cp38-cp38-macosx_10_15_x86_64.whl.

File metadata

File hashes

Hashes for picard-2.8-cp38-cp38-macosx_10_15_x86_64.whl
Algorithm Hash digest
SHA256 d9eaa295d10ff9e909455246a07d0e2ca91cd17e87543bbdc4ee2405180c9232
MD5 c067e92dbb4540daf4a3e3aafcfeaca7
BLAKE2b-256 2d1e081288f5bd10f454323c22d9f0cc91c257df1e42c7b16d51d2012ad19dd8

See more details on using hashes here.

File details

Details for the file picard-2.8-cp37-cp37m-win_amd64.whl.

File metadata

  • Download URL: picard-2.8-cp37-cp37m-win_amd64.whl
  • Upload date:
  • Size: 2.9 MB
  • Tags: CPython 3.7m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.0 CPython/3.7.9

File hashes

Hashes for picard-2.8-cp37-cp37m-win_amd64.whl
Algorithm Hash digest
SHA256 26f519a62a1179fb57b35a7944d9e72e53417dbaf3f3a25f8b50cb64979db811
MD5 efb1e3a396123427845b40539816143f
BLAKE2b-256 29c76554118bdabc3be6d3a3b6f512dee61552a2b5e3cd3f16516371fe041499

See more details on using hashes here.

File details

Details for the file picard-2.8-cp37-cp37m-macosx_10_15_x86_64.whl.

File metadata

File hashes

Hashes for picard-2.8-cp37-cp37m-macosx_10_15_x86_64.whl
Algorithm Hash digest
SHA256 6b3d72e45e3715dc2807a7d89a6bc6f70a215a49dedacd45c9bcc8acf82e21bd
MD5 182e5a796db1cff0c18ec869556b0eb6
BLAKE2b-256 0d7091e147a742780f827c5c1d43b7ead5a58936b1477811b8d150371f790ef5

See more details on using hashes here.

File details

Details for the file picard-2.8-cp36-cp36m-win_amd64.whl.

File metadata

  • Download URL: picard-2.8-cp36-cp36m-win_amd64.whl
  • Upload date:
  • Size: 2.9 MB
  • Tags: CPython 3.6m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.8.0 pkginfo/1.8.2 readme-renderer/34.0 requests/2.27.1 requests-toolbelt/0.9.1 urllib3/1.26.9 tqdm/4.64.0 importlib-metadata/4.8.3 keyring/23.4.1 rfc3986/1.5.0 colorama/0.4.4 CPython/3.6.8

File hashes

Hashes for picard-2.8-cp36-cp36m-win_amd64.whl
Algorithm Hash digest
SHA256 6470a0ed591c7edab6faf3496d39a2609a0205a42e22bdddb72a2ac19a5a98f8
MD5 136ad90bdc749c6ca59ce92686312fd2
BLAKE2b-256 cbc1f1ff6d1560f0216a35451acd8fdc8e2e705577acfaf9243c37951fe83a00

See more details on using hashes here.

File details

Details for the file picard-2.8-cp36-cp36m-macosx_10_14_x86_64.whl.

File metadata

  • Download URL: picard-2.8-cp36-cp36m-macosx_10_14_x86_64.whl
  • Upload date:
  • Size: 2.9 MB
  • Tags: CPython 3.6m, macOS 10.14+ x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.8.0 pkginfo/1.8.2 readme-renderer/34.0 requests/2.27.1 requests-toolbelt/0.9.1 urllib3/1.26.9 tqdm/4.64.0 importlib-metadata/4.8.3 keyring/23.4.1 rfc3986/1.5.0 colorama/0.4.4 CPython/3.6.15

File hashes

Hashes for picard-2.8-cp36-cp36m-macosx_10_14_x86_64.whl
Algorithm Hash digest
SHA256 ba7a02d02192b60e0f0ba2971b871b7c3ef054b4fc601a1d40482e8277e89492
MD5 9976c9e7925100c30cf80e02a7203156
BLAKE2b-256 925ff6a42c99e7716a837c646a10617834c747c4f57dbe65fe0bb61d97a9830f

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page