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 ~=3.6
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 ~=3.6
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

2.9.0a1 pre-release

2.8.5

2.8.4

2.8.3

2.8.2

This version

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-2.8.1.tar.gz (4.5 MB view details)

Uploaded Source

Built Distributions

picard-2.8.1-cp310-cp310-win_amd64.whl (2.9 MB view details)

Uploaded CPython 3.10 Windows x86-64

picard-2.8.1-cp39-cp39-win_amd64.whl (2.9 MB view details)

Uploaded CPython 3.9 Windows x86-64

picard-2.8.1-cp39-cp39-macosx_10_15_x86_64.whl (2.9 MB view details)

Uploaded CPython 3.9 macOS 10.15+ x86-64

picard-2.8.1-cp38-cp38-win_amd64.whl (2.9 MB view details)

Uploaded CPython 3.8 Windows x86-64

picard-2.8.1-cp38-cp38-macosx_10_15_x86_64.whl (2.9 MB view details)

Uploaded CPython 3.8 macOS 10.15+ x86-64

picard-2.8.1-cp37-cp37m-win_amd64.whl (2.9 MB view details)

Uploaded CPython 3.7m Windows x86-64

picard-2.8.1-cp37-cp37m-macosx_10_15_x86_64.whl (2.9 MB view details)

Uploaded CPython 3.7m macOS 10.15+ x86-64

picard-2.8.1-cp36-cp36m-win_amd64.whl (2.9 MB view details)

Uploaded CPython 3.6m Windows x86-64

picard-2.8.1-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-2.8.1.tar.gz.

File metadata

  • Download URL: picard-2.8.1.tar.gz
  • Upload date:
  • Size: 4.5 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.8.12

File hashes

Hashes for picard-2.8.1.tar.gz
Algorithm Hash digest
SHA256 1d763e202ada325ed713c1d216bb1a97b2a13ad5b1a819825ef7022489e670ad
MD5 abba8f9f46a8ca0a0ddc57487e72efd1
BLAKE2b-256 1db73e9262d48caa65a9a5e327eb322397e566cca344dfa2ce4c3c6ed6609eb1

See more details on using hashes here.

File details

Details for the file picard-2.8.1-cp310-cp310-win_amd64.whl.

File metadata

  • Download URL: picard-2.8.1-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/4.0.1 CPython/3.10.4

File hashes

Hashes for picard-2.8.1-cp310-cp310-win_amd64.whl
Algorithm Hash digest
SHA256 7fe77a20916aeb9a801ccd2dc583ff8e952059aa241974c71ee7d6b89e63884e
MD5 3d1af01e218d91ed68f450c33b4d0d4d
BLAKE2b-256 73947633e8169fc5ed96829f3cd3c42033035d2ef73e3fc12be83185f4a30e7d

See more details on using hashes here.

File details

Details for the file picard-2.8.1-cp39-cp39-win_amd64.whl.

File metadata

  • Download URL: picard-2.8.1-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/4.0.1 CPython/3.9.13

File hashes

Hashes for picard-2.8.1-cp39-cp39-win_amd64.whl
Algorithm Hash digest
SHA256 3237af3ec4c917de22acb47c34cee444e2a3af665d9293b7f3a336822e4e583a
MD5 f1fbdfb44d33edd3197a115ff8b9863c
BLAKE2b-256 9f2c89f7f9435e5d3b692d886480842424349f927cb1affc1dd56c72e286d3ef

See more details on using hashes here.

File details

Details for the file picard-2.8.1-cp39-cp39-macosx_10_15_x86_64.whl.

File metadata

File hashes

Hashes for picard-2.8.1-cp39-cp39-macosx_10_15_x86_64.whl
Algorithm Hash digest
SHA256 89980f34db8069463a52e452744cec8dd113da1b22dc1ba47a72929a3c910b76
MD5 5a6080eeef43cc432d657aa6494a5f32
BLAKE2b-256 9723a712e4464e6bc81acc28b78eb8ffbf7d1bc9def161de9da1fd9d0d0a9a0b

See more details on using hashes here.

File details

Details for the file picard-2.8.1-cp38-cp38-win_amd64.whl.

File metadata

  • Download URL: picard-2.8.1-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/4.0.1 CPython/3.8.10

File hashes

Hashes for picard-2.8.1-cp38-cp38-win_amd64.whl
Algorithm Hash digest
SHA256 0dfb4c64d42bffc2d5b75c35b25de15d67135aff23401ecde245c165b2e4dddb
MD5 7a203a56dcd1f1f04e376123b3c44983
BLAKE2b-256 40ef94aaf87f6918729ef8e0573d6e32c1dc4b162f04f841825ca42d76ca4e76

See more details on using hashes here.

File details

Details for the file picard-2.8.1-cp38-cp38-macosx_10_15_x86_64.whl.

File metadata

File hashes

Hashes for picard-2.8.1-cp38-cp38-macosx_10_15_x86_64.whl
Algorithm Hash digest
SHA256 c7278a378631f70d8026a3361fd2e61a9423ff56cb22cf685822abcd3728445e
MD5 c73769006b45e8254fb781ccdce94d22
BLAKE2b-256 c49f4cc7e569ae645e25bba2471ef2be0f27acd34fa6619f00dfb196eb6255bc

See more details on using hashes here.

File details

Details for the file picard-2.8.1-cp37-cp37m-win_amd64.whl.

File metadata

  • Download URL: picard-2.8.1-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/4.0.1 CPython/3.7.9

File hashes

Hashes for picard-2.8.1-cp37-cp37m-win_amd64.whl
Algorithm Hash digest
SHA256 f573ef58ebe1860de31fe801631a6a457f3f05f4f2bf138c7fd7fdc416ff34b3
MD5 388e548e918358bddda6efbceb64516f
BLAKE2b-256 8b1900bb983b132c76fba1cf4654a5a508d78f8ee109825b9e5445922c1b725e

See more details on using hashes here.

File details

Details for the file picard-2.8.1-cp37-cp37m-macosx_10_15_x86_64.whl.

File metadata

File hashes

Hashes for picard-2.8.1-cp37-cp37m-macosx_10_15_x86_64.whl
Algorithm Hash digest
SHA256 9d767fcbac6af523527126bd8151b37748e34034e8cebbc25b2ae28a13db78cd
MD5 c8777d8c971ecb959ad57343352072d5
BLAKE2b-256 c59d632668148bdc4fdc9318ab409a9d9c02dfc6914f22cae8e57c678e214db7

See more details on using hashes here.

File details

Details for the file picard-2.8.1-cp36-cp36m-win_amd64.whl.

File metadata

  • Download URL: picard-2.8.1-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-2.8.1-cp36-cp36m-win_amd64.whl
Algorithm Hash digest
SHA256 d309086480d0a423ed58fafddd152e05ee701e9327f1949cb25a67e34b1112de
MD5 e048124cb67efe953a886be1944def69
BLAKE2b-256 dabad493f1541b78f119c015d6f9cf3f5a21a50d6ac67dcc535209bd41577b05

See more details on using hashes here.

File details

Details for the file picard-2.8.1-cp36-cp36m-macosx_10_14_x86_64.whl.

File metadata

  • Download URL: picard-2.8.1-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-2.8.1-cp36-cp36m-macosx_10_14_x86_64.whl
Algorithm Hash digest
SHA256 07c6520aaa3a18644047bac82f066c37f137682e5802ce4660cf0f857d75020d
MD5 3a8c4de6b85bf544c3a3e797055336af
BLAKE2b-256 bb524c84fd4f022d62fd64e14fcf55f9aa746e8b74158a58dc64944a12a5f058

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