The next generation MusicBrainz tagger

Navigation

Verified details

These details have been verified by PyPI
Maintainers
Avatar for metabrainz from gravatar.com metabrainz Avatar for phw from gravatar.com phw Avatar for sambhav_kothari from gravatar.com sambhav_kothari Avatar for Wieland.Hoffmann from gravatar.com Wieland.Hoffmann

Unverified details

These details have not been verified by PyPI
Project links
Meta
  • License: GNU General Public License v2 or later (GPLv2+)
  • Tags MusicBrainz, metadata, tagger, picard
  • Requires: Python ~=3.7
Classifiers

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

Verified details

These details have been verified by PyPI
Maintainers
Avatar for metabrainz from gravatar.com metabrainz Avatar for phw from gravatar.com phw Avatar for sambhav_kothari from gravatar.com sambhav_kothari Avatar for Wieland.Hoffmann from gravatar.com Wieland.Hoffmann

Unverified details

These details have not been verified by PyPI
Project links
Meta
  • License: GNU General Public License v2 or later (GPLv2+)
  • Tags MusicBrainz, metadata, tagger, picard
  • Requires: Python ~=3.7
Classifiers

Release history Release notifications | RSS feed

2.12.3

2.12.2

2.12.1

2.12

2.11

2.11.0rc1 pre-release

2.10

2.10.0rc1 pre-release

2.9.2

2.9.1

2.9

2.9.0b3 pre-release

2.9.0b2 pre-release

2.9.0b1 pre-release

This version

2.9.0a1 pre-release

2.8.5

2.8.4

2.8.3

2.8.2

2.8.1

2.8

2.8.0rc2 pre-release

2.8.0rc1 pre-release

2.7.3

2.7.2

2.7.1

2.7

2.7.0b3 pre-release

2.7.0b2 pre-release

2.7.0b1 pre-release

2.6.4

2.6.3

2.6.2

2.6.1

2.6

2.6.0b3 pre-release

2.6.0b2 pre-release

2.6.0b1 pre-release

2.5.6

2.5.5

2.5.4

2.5.3

2.5.2

2.5.1

2.5

2.5.0b1 pre-release

2.4.4

2.4.3

2.4.2

2.4.1

2.4

2.4.0b2 pre-release

2.4.0b1 pre-release

2.3.2

2.3.1

2.3

2.3.0rc1 pre-release

2.3.0b1 pre-release

2.3.0a1 pre-release

2.2.3

2.2.2

2.2.1

2.2

2.2.0.dev4 pre-release

2.1.3

2.1.2

2.1.1

2.1

2.0.4

2.0.3

2.0.2

2.0

0.12.1

Download files

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

Source Distribution

picard-2.9.0a1.tar.gz (4.6 MB view details)

Uploaded Source

Built Distributions

picard-2.9.0a1-cp311-cp311-win_amd64.whl (2.9 MB view details)

Uploaded CPython 3.11 Windows x86-64

picard-2.9.0a1-cp311-cp311-macosx_10_9_universal2.whl (2.9 MB view details)

Uploaded CPython 3.11 macOS 10.9+ universal2 (ARM64, x86-64)

picard-2.9.0a1-cp310-cp310-win_amd64.whl (2.9 MB view details)

Uploaded CPython 3.10 Windows x86-64

picard-2.9.0a1-cp310-cp310-macosx_11_0_x86_64.whl (2.9 MB view details)

Uploaded CPython 3.10 macOS 11.0+ x86-64

picard-2.9.0a1-cp39-cp39-win_amd64.whl (2.9 MB view details)

Uploaded CPython 3.9 Windows x86-64

picard-2.9.0a1-cp39-cp39-macosx_11_0_x86_64.whl (2.9 MB view details)

Uploaded CPython 3.9 macOS 11.0+ x86-64

picard-2.9.0a1-cp38-cp38-win_amd64.whl (2.9 MB view details)

Uploaded CPython 3.8 Windows x86-64

picard-2.9.0a1-cp38-cp38-macosx_10_15_x86_64.whl (2.9 MB view details)

Uploaded CPython 3.8 macOS 10.15+ x86-64

picard-2.9.0a1-cp37-cp37m-win_amd64.whl (2.9 MB view details)

Uploaded CPython 3.7m Windows x86-64

picard-2.9.0a1-cp37-cp37m-macosx_10_15_x86_64.whl (2.9 MB view details)

Uploaded CPython 3.7m macOS 10.15+ x86-64

File details

Details for the file picard-2.9.0a1.tar.gz.

File metadata

  • Download URL: picard-2.9.0a1.tar.gz
  • Upload date:
  • Size: 4.6 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.8.15

File hashes

Hashes for picard-2.9.0a1.tar.gz
Algorithm Hash digest
SHA256 7d0587b699380ce4aec9644271993572d0955c3d57c5256c8e1ddf65b22e420d
MD5 7ffcdacee0dc8023094bdfe47fb39622
BLAKE2b-256 64811f2f93bdf63221b29ae1745d7ae11fd170f5909c3c95f1442f487788a64f

See more details on using hashes here.

File details

Details for the file picard-2.9.0a1-cp311-cp311-win_amd64.whl.

File metadata

File hashes

Hashes for picard-2.9.0a1-cp311-cp311-win_amd64.whl
Algorithm Hash digest
SHA256 e502521b8d7b2cecb9612e58b68588754c9174260420426248c1370ca82a4e31
MD5 9bd361cfc41a34cee769f11e7e2a0b5a
BLAKE2b-256 45f948ec84506494ff5e993c67097754f239cdebadc16b186b3d691237b7d243

See more details on using hashes here.

File details

Details for the file picard-2.9.0a1-cp311-cp311-macosx_10_9_universal2.whl.

File metadata

File hashes

Hashes for picard-2.9.0a1-cp311-cp311-macosx_10_9_universal2.whl
Algorithm Hash digest
SHA256 364f1cbe93c326954652baca2ea15cdaf632bd30894e4bfa18ca0d296a74b20b
MD5 29207a7f055377c3a286b2b38b2c68eb
BLAKE2b-256 2c7227ceffbf3c6856cb8e9a42a0884c99b53bf52e964c59792ca5d45ab2767a

See more details on using hashes here.

File details

Details for the file picard-2.9.0a1-cp310-cp310-win_amd64.whl.

File metadata

File hashes

Hashes for picard-2.9.0a1-cp310-cp310-win_amd64.whl
Algorithm Hash digest
SHA256 77f60253176c8bbd709f58025f27687a89f727eeda974aded4308a8f678c131c
MD5 aa85b77695c636bf4dedf2f6f3dc6f45
BLAKE2b-256 da87f412e93e863f11f3252f24de4d9cdd3c0120367bf423bf383af19be8eb9b

See more details on using hashes here.

File details

Details for the file picard-2.9.0a1-cp310-cp310-macosx_11_0_x86_64.whl.

File metadata

File hashes

Hashes for picard-2.9.0a1-cp310-cp310-macosx_11_0_x86_64.whl
Algorithm Hash digest
SHA256 b9ca9cc25b26958065a75fe395f1ded1243949822ea996f4a5bbbac9aaf805b6
MD5 c5be41e6e97cce86511ac01d9e6e519e
BLAKE2b-256 354020680dd961841007855daadcf400ed36851415eecbd9e206802372c65409

See more details on using hashes here.

File details

Details for the file picard-2.9.0a1-cp39-cp39-win_amd64.whl.

File metadata

  • Download URL: picard-2.9.0a1-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/4.0.2 CPython/3.9.13

File hashes

Hashes for picard-2.9.0a1-cp39-cp39-win_amd64.whl
Algorithm Hash digest
SHA256 a26125520c8b5c4b50f2808920219c144f6bb1af03d04ce057638cbf6a0a875b
MD5 5a2c716328ba4f97a57ea332d56150c5
BLAKE2b-256 49d4332adb2069f1264adaeb60f3d6c95df0e59c1ae39481665cea7ad2bec446

See more details on using hashes here.

File details

Details for the file picard-2.9.0a1-cp39-cp39-macosx_11_0_x86_64.whl.

File metadata

File hashes

Hashes for picard-2.9.0a1-cp39-cp39-macosx_11_0_x86_64.whl
Algorithm Hash digest
SHA256 6f1ad3467fa57ad1368b0b8df296551e61a58d385b8bbf70ba2888ffe9bc710b
MD5 245d382d0e12e470675fad8b6166e513
BLAKE2b-256 fa365adee60cbebabcfac2c33ac97785dc90d8ee3c62bf79107ed613eb577085

See more details on using hashes here.

File details

Details for the file picard-2.9.0a1-cp38-cp38-win_amd64.whl.

File metadata

  • Download URL: picard-2.9.0a1-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/4.0.2 CPython/3.8.10

File hashes

Hashes for picard-2.9.0a1-cp38-cp38-win_amd64.whl
Algorithm Hash digest
SHA256 953068e90d4b1a21da893e5aa46b191a7e555259d8b311dcf5503fb29d5bc2c5
MD5 77de86216faa0609d530af6236c6071a
BLAKE2b-256 e0451b7676ff8947af3dfa70abd953eb73ed567c92c3265af934e3008e854f82

See more details on using hashes here.

File details

Details for the file picard-2.9.0a1-cp38-cp38-macosx_10_15_x86_64.whl.

File metadata

File hashes

Hashes for picard-2.9.0a1-cp38-cp38-macosx_10_15_x86_64.whl
Algorithm Hash digest
SHA256 68eb84ca8740356f710327a3003ef56bb7c2a2eea7709d510184696b7961227f
MD5 c2cb493f3cc7157a0c902cb6b37fabae
BLAKE2b-256 dcd0cc60bc69bab0bdd9884120eb5110272778879fd52c876d545ee7ffa61ecd

See more details on using hashes here.

File details

Details for the file picard-2.9.0a1-cp37-cp37m-win_amd64.whl.

File metadata

  • Download URL: picard-2.9.0a1-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/4.0.2 CPython/3.7.9

File hashes

Hashes for picard-2.9.0a1-cp37-cp37m-win_amd64.whl
Algorithm Hash digest
SHA256 db104a1fc2c0fb8410d6440ac0b9cfa16f70f3fcd2af75974063c48b7fdec254
MD5 462b0362072fd6d808086ed86385b334
BLAKE2b-256 662a216181e3e192ec4c0101eb017470e319ac67d8d8e4eec34c6dfc52b869da

See more details on using hashes here.

File details

Details for the file picard-2.9.0a1-cp37-cp37m-macosx_10_15_x86_64.whl.

File metadata

File hashes

Hashes for picard-2.9.0a1-cp37-cp37m-macosx_10_15_x86_64.whl
Algorithm Hash digest
SHA256 affeedf689fa5528a9750df7ab23b5182ed669f721dfc7a2cd418741969f5e46
MD5 277560104d7ee820b1cee3057b189810
BLAKE2b-256 ef6aeffe184da995485fca7c5560d48f92030278405cef8c02ce2f91a5f7d803

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