metabrainz/picard

Features

• Music Metadata Integration - Retrieves accurate artist and album information from community databases to organize and update audio tags.
• Audio File Handling - Reads and writes metadata tags for common audio formats including MP3, FLAC, and WAV.
• Scripted File Transfers - Transfers music files to target directories based on automated naming and organization scripts.
• Album Clustering - Groups individual audio files into logical album units to facilitate batch metadata lookups and matching.
• Automated File Naming - MusicBrainz Picard defines specific naming conventions and tag formats using a scripting language.
• Metadata Transformation Scripts - MusicBrainz Picard applies user-defined scripts written in a custom language to transform metadata and file naming during tagging.
• Automated File Organizers - Automatically renames and moves music files into structured folder hierarchies based on metadata scripts.
• Metadata Tagging - Writes retrieved community metadata to audio files and optionally triggers renaming or moving.
• Audio Tagging - Uses format-specific libraries to read and write metadata tags across diverse audio containers.
• Acoustic Fingerprinting Systems - Implements sonic fingerprinting to identify unknown audio files by matching them against a community database.
• Crowdsourced Metadata Databases - Queries a community-curated music database using lookup keys to retrieve accurate album and track metadata.
• Automation Scripting Engines - Provides a custom scripting engine for automating metadata transformations and file renaming.
• Tag-Based File Renamers - Renames music files automatically using embedded metadata tags according to configurable scripts.
• Audio Metadata Editors - Reads and writes metadata tags across various audio formats including MP3, FLAC, and WAV.
• Audio Fingerprinting - Identifies unknown music files by generating sonic fingerprints and matching them against a recording database.
• Metadata Tagging - Identifies and tags audio files using the MusicBrainz community music database.
• Metadata Automators - MusicBrainz Picard modifies music metadata automatically upon loading data from external databases.
• Music Metadata Retrieval - Searches metadata databases for albums matching selected files to retrieve and display track listings.
• Extensible Plugin Architectures - Implements a framework that allows plugins to hook into the tagging pipeline for new metadata and automation.
• Format Abstraction Interfaces - Provides a unified abstraction layer for reading and writing tags across multiple audio formats.
• Tagging Pipeline Extensions - Extends the metadata pipeline with custom scripts and community plugins to support new formats and automation.
• Third-Party Plugins - Provides a plugin architecture that allows third-party extensions to add new metadata sources and audio format support.
• Hook-Based Plugin Systems - Loads plugins into specific lifecycle hooks to modify metadata and integrate new cover art sources.
• Metadata-Based Clustering - Groups unprocessed audio files into clusters based on metadata to facilitate batch lookup and tagging.
• CD Table of Contents Matching - Matches ripped audio files to specific album releases using CD table of contents and database lookups.
• Fingerprint Submissions - Allows users to contribute generated acoustic fingerprints to community databases to improve music identification.
• Collaborative Database Contributions - Submits disc IDs and acoustic fingerprints to community databases for collaborative improvement.
• Python Plugin Integrations - Integrates Python scripts to allow for flexible metadata modification and support for new audio formats.
• Metadata Pre-population - Pre-populates artist, track, and timing data to simplify adding new recordings to the global database.
• Release Submissions - Enables sending groups of audio files as new release entries to a community music database.
• Physical Media Metadata Retrieval - Loads track data from physical CDs and applies matching metadata from a community database.
• Scripting Context Providers - MusicBrainz Picard provides access to system data like dates and track counts for use in script logic.
• Variable Interpolators - MusicBrainz Picard inserts metadata values into tags and file names using percent-wrapped variables.
• Batch Processing - Processes batches of audio files by forwarding paths to a running application instance.
• Audio Track Previews - MusicBrainz Picard provides an integrated player to preview audio tracks before or after tagging.
• Cover Art Embedding - Inserts cover art images from online sources directly into audio files.
• Media Album Organization - Groups individual audio files into logical albums and propagates shared metadata across all tracks.
• Album Art Retrievals - Finds and attaches album cover art from online sources to music files.
• Multi-Value Metadata Processing - MusicBrainz Picard joins, slices, and deduplicates multi-value tags using dedicated processing functions.
• Automatic Track Identification - Links individual audio files to exact tracks on a specific release for precise metadata tagging.
• Disc ID Matching - Links a physical CD disc ID to a corresponding release in a community database.
• Log Parsing - Parses CD ripper log files to extract the table of contents for accurate database lookups.
• Custom Scripting Functions - MusicBrainz Picard introduces new functions for use within naming and metadata engines.
• Plugin-Based Architectures - Features a plugin-based architecture that allows extending the tagging pipeline with new metadata sources.
• Data Difference Views - MusicBrainz Picard provides a side-by-side view of original and proposed tag values before writing to files.
• Audio and Video - Automated music tagging and metadata tool.
• Audio Tools - Tool to automatically identify, tag, and organize music.
• Audio Utilities - Identifies and tags music files.
• Audio Video Tools - Listed in the “Audio Video Tools” section of the Awesome Mac awesome list.

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