The merge windows kept coming because finishing a track rewrote all 15 MB of
library.json. Both machines did that, so Syncthing saw two edits to one big
file between syncs and produced a conflict file roughly once per song — and
the merge then took max() of the two counts, discarding whichever side had
played less. The .resolved/ backups showed the last nine library.json merges
were ~98% play counts plus exactly one real edit, with the same ~45 tracks
disagreeing every time and the count only creeping down over a day.
library.json now holds only a base count. Each machine owns
plays/<machine-id>.json with its own per-track totals, and the effective count
is base + the sum of every journal. Only the owner writes its journal, so play
data can't conflict; the journal stores totals rather than an append log, so
there's no compaction step to double-count in; and a machine still on older
code keeps bumping its own base, which stays additive with our journal.
Two places carry the whole hazard, and both are pinned by tests: save_tracks
writes journal.base_fields(), never the Track's effective count, and
PlayJournal.load must be given a base-valued library — which is why
reload_from_disk folds the journals onto the disk copy before reconciling.
On the real 21k library: three plays write 83 bytes and leave library.json
untouched.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01M8Mzze7shr5pZoEgKQU5NW
travandClaude Opus 5
2d961c0c9e