Import, maintain and export tag metadata to/from audio files and a dynamically created SQLite table. Automates incremental tag cleanup, enrichment and standardisation for your digital audio library at scale using pre-scripted SQL queries, achieving quality and consistency throughout your music collection in a manner not possible with a tagger.
Implement argv to enable passing of switches determining which metadata enhancement routines are run and to enable pointing to source/target root folder rather than using only current dir and hard-coded defaults.
Current table names do not follow a convention making it harder to know which to refer to. Decide on naming convention and implement. e.g. use utility_ or _info as a prefix for all utility tables.
Most efficient method is likely to involve using a transformation function in Pandas to enable scalar updates and quick honing in on deltas requiring updates to alib.
Undo MusicBrainz' unholy mess of handling classical composers by shoving them into the album name. Starting point would be to build a table of composer names where GENRE = Classical, then working from there.
For reissues and remasters investigate how music servers handle this (principally Logitehmediaserver or whatever it gets renamed to) and implement accordingly.
Create optional function to strip enhanced metadata from album names ... will be useful when a music server properly leverages VERSION, bit depth and sample rate information in order to differentiate releases from one another.
Add MusicBrainz identifiers to all LABEL, WORK & PART tags leveraging a download of tables from the MusicBrainz database. Codebase already enriches from existing metadata in alib or leverages musicbrainz table if present - extend to include above mentioned metadata.