24454247a3
Implement the pipeline layer that orchestrates discovery, parsing,
caching, and aggregation:
- pipeline/loader.go: Load() discovers session files via ScanDir,
optionally filters out subagent files, then parses all files in
parallel using a bounded worker pool sized to GOMAXPROCS. Workers
read from a pre-filled channel (no contention on dispatch) and
report progress via an atomic counter and callback. LoadResult
tracks total files, parsed files, parse errors, and file errors.
- pipeline/aggregator.go: Five aggregation functions, all operating
on time-filtered session slices:
* Aggregate: computes SummaryStats across all sessions — total
tokens (5 types), estimated cost, cache savings (summed per-model
via config.CalculateCacheSavings), cache hit rate, and per-active-
day rates (cost, tokens, sessions, prompts, minutes).
* AggregateDays: groups sessions by local calendar date, sorted
most-recent-first.
* AggregateModels: groups by normalized model name with share
percentages, sorted by cost descending.
* AggregateProjects: groups by project name, sorted by cost.
* AggregateHourly: distributes prompt/session/token counts across
24 hour buckets (attributed to session start hour).
Also provides FilterByTime, FilterByProject, FilterByModel with
case-insensitive substring matching.
- pipeline/incremental.go: LoadWithCache() implements the incremental
loading strategy — compares discovered files against the cache's
file_tracker (mtime_ns + size), loads unchanged sessions from
SQLite, and only reparses files that changed. Reparsed results
are immediately saved back to cache. CacheDir/CachePath follow
XDG_CACHE_HOME convention (~/.cache/cburn/metrics.db).
- pipeline/bench_test.go: Benchmarks for ScanDir, ParseFile (worst-
case largest file), full Load, and LoadWithCache to measure the
incremental cache speedup.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2.4 KiB
2.4 KiB