Plans 013 and 014, the album page that prompted them, and the smaller fixes they turned up. Changelog, largest first. ## The local library is shaped like files, not like MusicBrainz `audio_files` carries its own tags and points at `albums` and `artists`; `file_genres` is the one real many-to-many. `recordings`, `release_group_recordings`, `artist_credit`, `artist_credit_artist`, `recording_genres`, `release_groups` and `release_to_rg` are gone from the local side, and with them a six-way join in every read, a `MIN(release_group_id)` subquery in eleven queries and a first-credited-artist subquery in nine. Measured on a real 25,966-file library, every many-to-many that model expressed was 1:1 in the data. - Ownership is a file. `GetFilePathsByRecordingMBIDs`, `LibraryMBIDIndex.CheckMBIDs`, `collectLibraryEntities` and `pruneStaleLocalCrossReferences` all join `audio_files`, so the 812 orphaned recordings, 216 release groups and 260 artists that library carried are now structurally impossible. - One projection: every track query selects from the `track_metadata` view, one row type, one mapper. Nine hand-rolled copies had drifted far enough to report different years on different screens. - `library_id = 0` means every library, so each list query exists once instead of scoped and unscoped with a branch at every call site. - No migration chain. `sql/schemas/` is the one description of the shape; `sql/migrations/`, `applyMigrations` and `schema_migrations` are squashed away, along with the drift between them that had sqlc generating against a stale schema. - `database.InsertTestTrack` is the one test seeder; twenty test files had been assembling the old FK chain each in its own order. ## The catalog stores its ids as bytes `explore_index`'s three 36-char MBID columns and its entity-type text are 16 raw bytes and a small integer. The table and its six indexes go 780 MB to 405 MB on a real 2,052,200-row catalog, which is why a fresh install is ~0.6 GB rather than ~1.0 GB. - `backend/explore/mbid.go` is the only place the encoding is known; everything above it speaks dashed strings. - `CHECK(length(mbid) = 16)` makes a stringly write fail at the insert rather than silently returning no rows, since SQLite does not coerce between TEXT and BLOB. - The importer asks the artifact what encoding it carries and converts on the way in, so the artifact already published keeps working and no format bump is needed. - `indexRowColumns`/`scanIndexRow` replace four copies of a 22-column list, and `TestStoredEncodingRoundTrips` sweeps every read path. ## An album page that says how much of the album is yours - One question, asked once: is there a file. `filePaths` is filled by a single batched lookup when the tracklist settles, and the badge, the Play count, the dimmed rows and every menu item read it — replacing four claims of decreasing confidence that could show a green tick on an album whose every action did nothing. - Play, Play 7 of 12, or no play button at all. - `total_tracks` on `explore_index` (~2 bytes over 400,677 release groups) and on `audio_files` from tags that have always carried it: a complete MBID-matched album now makes no catalog call at all, where it used to spend the most expensive request the app makes. - A merged cluster shows the running order the most releases agree on, and the version list marks the release you own rather than standing a synthetic entry in for it. - `AlbumReleasesFailed`: a slow fetch is no longer reported as a failed one by a 12-second timer. - Rows not in the library are dimmed in place (with `aria-disabled`) instead of the owned ones wearing a green tick and a legend. ## Caches and cover art get ceilings - Only the three tiers of a cover are stored; the full-resolution copy nothing rendered was 1,134 MB of a 1.4 GB covers directory. - One artist portrait is downloaded and the rest are remembered as URLs — 4.1 GB of a 5.3 GB cache was candidates no code path reads. - `browsedArtBudget` and `httpCacheBudget` bound what an age cannot: the same install held art for 5,770 artists in a 1,301-artist library. - `OrphanedArtistImagesJob` joined a bare MBID onto a sharded directory, so it deleted the rows that were the only record of the files it left behind. `explore.ArtistImageDir` is that layout's one definition now. ## The autotag queue asks whether there is work `tagging_items` was a row per album folder, not a queue, and no query read the `tag_status` column that held the answer. The four queue queries ask the files, which matters most where it is least visible: `startPrefetch` was scoring every album in a tagged library against MusicBrainz. ## Phantom playlist tracks resolve in place An M3U8 imported before its files leaves phantom rows; they now match by path and fall back to position, keep their place in the playlist when resolved, and pair best-first so two phantoms cannot claim the same file. ## Playing a track plays the list it is in Double-click, and Play on a single row's menu, queue the list as displayed with `startIndex` on that row — the album page and the track list used to queue one track and discard the album around it. A multi-row selection still plays exactly itself. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01AfVYUVExXsx1nSWrXN8mAh
304 lines
7.6 KiB
Go
304 lines
7.6 KiB
Go
package explore
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import (
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"context"
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"database/sql"
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"math/rand/v2"
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)
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// mixBatchSize is how many tracks one GenerateMix call returns.
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const mixBatchSize = 30
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// mixGenreBoost is added to a candidate's similarity weight for each
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// genre it shares with the seed, biasing the pick toward tracks that
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// match on both artist and tag rather than artist alone.
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const mixGenreBoost = 0.5
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// mixSimilarArtistsPerSeed caps how many similar artists are expanded
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// per distinct seed artist, so a seed with an unusually long tail in
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// similar_artist_map doesn't turn one fallback trigger into hundreds
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// of queries.
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const mixSimilarArtistsPerSeed = 15
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// mixSession is a dynamic mix in progress: the seed it was built from
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// (fixed for the life of the session, so successive batches don't
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// drift away from what the session started as) and what it has
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// already handed out, so a batch doesn't repeat a track that just
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// played.
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type mixSession struct {
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seedPaths []string
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played map[string]bool
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}
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// GenerateMix returns the next batch of tracks for a dynamic-mix queue
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// fallback, built by expanding the seed's artists to their similar
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// artists (weighted by how often each appears in the seed, sharpened
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// by shared genre tags) and restricting candidates to what is actually
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// in the library — a queue can only play files that exist.
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//
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// continuing extends the current mix session — regenerating from its
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// original seed rather than seedPaths — instead of starting a fresh
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// one. Pass false whenever the queue that just exhausted was not
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// itself a mix batch (a real selection just ran out); pass true when
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// it was (the mix keeps going indefinitely). label names the batch
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// after its most-represented seed artist, for the "Playing from" UI.
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func (e *Service) GenerateMix(
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ctx context.Context,
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seedPaths []string,
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continuing bool,
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) (paths []string, label string, err error) {
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e.mixMu.Lock()
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defer e.mixMu.Unlock()
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if !continuing || e.mix == nil {
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e.mix = &mixSession{seedPaths: seedPaths, played: map[string]bool{}}
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}
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seed := e.mix.seedPaths
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if len(seed) == 0 {
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return nil, "", nil
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}
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artistCounts, topArtistName, genres := e.mixSeedProfile(ctx, seed)
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if len(artistCounts) == 0 {
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return nil, "", nil
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}
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candidates := e.mixCandidates(ctx, artistCounts, genres, seed, e.mix.played)
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// The session has played through everything this seed can offer —
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// rather than dead-ending an "indefinite" mix, start handing out
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// repeats.
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if len(candidates) == 0 && len(e.mix.played) > 0 {
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candidates = e.mixCandidates(ctx, artistCounts, genres, seed, nil)
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}
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if len(candidates) == 0 {
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return nil, "", nil
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}
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picked := weightedSample(candidates, mixBatchSize)
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for _, p := range picked {
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e.mix.played[p] = true
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}
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if topArtistName != "" {
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label = "a mix inspired by " + topArtistName
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} else {
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label = "a dynamic mix"
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}
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return picked, label, nil
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}
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// mixSeedProfile tallies the seed's artists by frequency, its genre
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// tags, and names the most-represented artist for the UI label.
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func (e *Service) mixSeedProfile(
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ctx context.Context,
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seedPaths []string,
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) (artistCounts map[string]int, topArtistName string, genres map[string]bool) {
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artistCounts = map[string]int{}
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artistNames := map[string]string{}
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genres = map[string]bool{}
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for _, p := range seedPaths {
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artist, err := e.db.ReadQueries.GetArtistByFilePath(ctx, p)
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if err == nil && artist.ArtistMbid != "" {
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artistCounts[artist.ArtistMbid]++
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artistNames[artist.ArtistMbid] = artist.ArtistName
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}
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}
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for _, names := range e.genresByPath(ctx, seedPaths) {
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for _, g := range names {
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genres[g] = true
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}
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}
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var topCount int
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for mbid, count := range artistCounts {
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if count > topCount {
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topCount = count
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topArtistName = artistNames[mbid]
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}
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}
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return artistCounts, topArtistName, genres
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}
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// mixCandidates builds the weighted pool of library tracks to draw a
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// batch from: every owned track by a similar artist, weighted by that
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// artist's similarity score times how often the seed artist it came
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// from appears in the seed, boosted for a shared genre tag, excluding
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// the seed itself and anything already excluded (typically what the
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// mix has already played).
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func (e *Service) mixCandidates(
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ctx context.Context,
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artistCounts map[string]int,
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seedGenres map[string]bool,
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seedPaths []string,
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exclude map[string]bool,
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) map[string]float64 {
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excludeSeed := make(map[string]bool, len(seedPaths))
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for _, p := range seedPaths {
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excludeSeed[p] = true
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}
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candidates := map[string]float64{}
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// Every candidate path's genres, in one query. This used to be a
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// single-row lookup *per candidate* inside two nested loops -
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// twenty seed artists by twenty similar artists by thirty paths is
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// twelve thousand queries to assemble one mix.
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pathGenres := e.genresByPath(ctx, e.similarArtistPaths(ctx, artistCounts))
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for seedArtistMBID, count := range artistCounts {
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similar, err := e.SimilarArtists(seedArtistMBID)
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if err != nil {
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continue
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}
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if len(similar) > mixSimilarArtistsPerSeed {
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similar = similar[:mixSimilarArtistsPerSeed]
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}
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for _, s := range similar {
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if s.ArtistMBID == "" {
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continue
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}
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paths, err := e.db.ReadQueries.GetFilePathsByArtistMBID(
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ctx,
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sql.NullString{String: s.ArtistMBID, Valid: true},
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)
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if err != nil {
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continue
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}
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weight := s.Score * float64(count)
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for _, p := range paths {
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if excludeSeed[p] || exclude[p] {
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continue
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}
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for _, g := range pathGenres[p] {
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if seedGenres[g] {
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weight += mixGenreBoost
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break
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}
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}
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candidates[p] += weight
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}
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}
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}
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return candidates
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}
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// genresByPath returns the genres of many files in one query.
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func (e *Service) genresByPath(
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ctx context.Context, paths []string,
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) map[string][]string {
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out := make(map[string][]string, len(paths))
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if len(paths) == 0 {
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return out
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}
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rows, err := e.db.ReadQueries.GetGenreNamesByFilePaths(ctx, paths)
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if err != nil {
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return out
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}
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for _, row := range rows {
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out[row.FilePath] = append(out[row.FilePath], row.Name)
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}
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return out
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}
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// similarArtistPaths collects every owned file by an artist similar to
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// one of the seeds, so their genres can be fetched in one go.
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func (e *Service) similarArtistPaths(
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ctx context.Context, artistCounts map[string]int,
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) []string {
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var paths []string
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for seedArtistMBID := range artistCounts {
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similar, err := e.SimilarArtists(seedArtistMBID)
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if err != nil {
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continue
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}
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if len(similar) > mixSimilarArtistsPerSeed {
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similar = similar[:mixSimilarArtistsPerSeed]
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}
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for _, sim := range similar {
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if sim.ArtistMBID == "" {
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continue
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}
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p, err := e.db.ReadQueries.GetFilePathsByArtistMBID(
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ctx, sql.NullString{String: sim.ArtistMBID, Valid: true},
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)
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if err != nil {
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continue
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}
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paths = append(paths, p...)
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}
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}
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return paths
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}
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// weightedSample picks up to n distinct keys from weights without
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// replacement, biased toward higher weight (roulette-wheel selection).
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// A key with zero or negative weight is never picked.
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func weightedSample(weights map[string]float64, n int) []string {
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type entry struct {
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key string
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weight float64
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}
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pool := make([]entry, 0, len(weights))
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var total float64
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for k, w := range weights {
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if w <= 0 {
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continue
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}
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pool = append(pool, entry{k, w})
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total += w
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}
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picked := make([]string, 0, min(n, len(pool)))
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for len(picked) < n && len(pool) > 0 {
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r := rand.Float64() * total
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idx := 0
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for i, e := range pool {
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r -= e.weight
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if r <= 0 {
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idx = i
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break
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}
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}
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picked = append(picked, pool[idx].key)
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total -= pool[idx].weight
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pool = append(pool[:idx], pool[idx+1:]...)
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}
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return picked
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}
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