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* refactor(model): extract canonical 128-bit base62 id codec * feat(model): generate random ids as canonical 128-bit base62 values * feat(scanner): emit legacy PIDs in canonical base62 encoding * feat(db): add id canonicalization transform for the uniform-ids migration * feat(db): migrate all ids to canonical 128-bit base62 encoding * fix(db): canonicalize ids in junction tables and JSON columns * chore(jellyfin): update id-family notes for uniform canonical ids * test(ids): harden codec input contract and migration edge coverage * refactor(model): use log.Fatal for Encode128 contract guard per project convention * fix(db): force full rescan after id migration for legacy PID configs * test(db): guard id-column inventory against schema drift * refactor(ids): compile-time Encode128 contract and unified column rewrite helper * refactor(db): apply review feedback to id migration Filter empty strings in collectColumn's SQL, reuse a prepared statement for rewriteColumn updates, and clarify the legacy ID functions' comment now that they emit the canonical encoding. * feat(auth): split session and public-link JWT secrets, rotating sessions on id migration * test(subsonic): initialize public token secret in helpers suite The suite sets auth.TokenAuth directly instead of calling auth.Init, so the new PublicTokenAuth was nil whenever Ginkgo's spec order ran a helpers spec before any spec that calls auth.Init, panicking in publicurl.ImageURL. * refactor(db): inline canonicalID into its only consumer, the uniform-ids migration * refactor(model): rename Encode128/Decode128 to Encode/Decode With every id now exactly 128 bits, the width suffix is redundant; the package-qualified id.Encode/id.Decode carries the same information. * test(db): make the id-columns guard classify JSON columns too The guard only inspected columns named id/pid/*_id, so it could not see ids embedded in JSON. Widen it to *_ids and to every JSON column, and drive the "covered" set from a new embeddedIDColumns list instead of the inline calls in the migration. Every JSON column the schema has now carries a verdict. The four denormalized caches -- media_file/album.participants, media_file/album.tags, album.folder_ids and artist.similar_artists -- hold only artist, tag and folder ids. Those all come from id.NewHash, whose 22-char base62 encoding of a 128-bit MD5 is already in canonical range, so canonicalID is the identity on them and the migration correctly leaves them alone. A new codec test pins that invariant, since the exemptions depend on it. Verified on a copy of a 727MB/96k-track production database: canonicalizing those four columns changed zero rows, and artist, tag and folder ids were themselves unchanged by the migration (only media_file ids moved, 95108 of 96666).
49 lines
1.0 KiB
Go
49 lines
1.0 KiB
Go
package id
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import (
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"crypto/md5"
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"crypto/rand"
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"fmt"
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"math/big"
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"strings"
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)
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func NewRandom() string {
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var b [16]byte
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_, _ = rand.Read(b[:])
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return Encode(b)
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}
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// Encode renders a 16-byte value as the canonical 22-char zero-padded base62 id.
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func Encode(b [16]byte) string {
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return fmt.Sprintf("%022s", new(big.Int).SetBytes(b[:]).Text(62))
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}
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// Decode is the exact inverse of Encode.
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func Decode(s string) ([]byte, error) {
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if len(s) != 22 {
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return nil, fmt.Errorf("invalid id length %d", len(s))
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}
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v, ok := new(big.Int).SetString(s, 62)
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if !ok || v.Sign() < 0 {
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return nil, fmt.Errorf("invalid base62 id %q", s)
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}
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if v.BitLen() > 128 {
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return nil, fmt.Errorf("id %q overflows 128 bits", s)
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}
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return v.FillBytes(make([]byte, 16)), nil
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}
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func NewHash(data ...string) string {
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hash := md5.New()
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for _, d := range data {
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hash.Write([]byte(d))
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hash.Write([]byte(string('\u200b')))
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}
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return Encode([16]byte(hash.Sum(nil)))
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}
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func NewTagID(name, value string) string {
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return NewHash(strings.ToLower(name), strings.ToLower(value))
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}
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