feat: add data pipeline with parallel loading, aggregation, and cache integration
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>
This commit is contained in:
261
internal/pipeline/aggregator.go
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261
internal/pipeline/aggregator.go
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@@ -0,0 +1,261 @@
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package pipeline
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import (
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"sort"
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"strings"
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"time"
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"cburn/internal/config"
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"cburn/internal/model"
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)
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// Aggregate computes summary statistics from a slice of session stats,
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// filtered to sessions within the given time range.
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func Aggregate(sessions []model.SessionStats, since, until time.Time) model.SummaryStats {
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filtered := FilterByTime(sessions, since, until)
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var stats model.SummaryStats
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activeDays := make(map[string]struct{})
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for _, s := range filtered {
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stats.TotalSessions++
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stats.TotalPrompts += s.UserMessages
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stats.TotalAPICalls += s.APICalls
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stats.TotalDurationSecs += s.DurationSecs
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stats.InputTokens += s.InputTokens
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stats.OutputTokens += s.OutputTokens
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stats.CacheCreation5mTokens += s.CacheCreation5mTokens
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stats.CacheCreation1hTokens += s.CacheCreation1hTokens
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stats.CacheReadTokens += s.CacheReadTokens
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stats.EstimatedCost += s.EstimatedCost
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if !s.StartTime.IsZero() {
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day := s.StartTime.Local().Format("2006-01-02")
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activeDays[day] = struct{}{}
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}
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}
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stats.ActiveDays = len(activeDays)
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stats.TotalBilledTokens = stats.InputTokens + stats.OutputTokens +
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stats.CacheCreation5mTokens + stats.CacheCreation1hTokens
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// Cache hit rate
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totalCacheInput := stats.CacheReadTokens + stats.CacheCreation5mTokens +
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stats.CacheCreation1hTokens + stats.InputTokens
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if totalCacheInput > 0 {
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stats.CacheHitRate = float64(stats.CacheReadTokens) / float64(totalCacheInput)
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}
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// Cache savings (sum across all models found in sessions)
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for _, s := range filtered {
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for modelName, mu := range s.Models {
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stats.CacheSavings += config.CalculateCacheSavings(modelName, mu.CacheReadTokens)
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}
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}
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// Per-active-day rates
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if stats.ActiveDays > 0 {
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days := float64(stats.ActiveDays)
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stats.CostPerDay = stats.EstimatedCost / days
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stats.TokensPerDay = int64(float64(stats.TotalBilledTokens) / days)
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stats.SessionsPerDay = float64(stats.TotalSessions) / days
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stats.PromptsPerDay = float64(stats.TotalPrompts) / days
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stats.MinutesPerDay = float64(stats.TotalDurationSecs) / 60 / days
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}
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return stats
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}
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// AggregateDays computes per-day statistics from sessions.
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func AggregateDays(sessions []model.SessionStats, since, until time.Time) []model.DailyStats {
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filtered := FilterByTime(sessions, since, until)
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dayMap := make(map[string]*model.DailyStats)
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for _, s := range filtered {
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if s.StartTime.IsZero() {
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continue
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}
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dayKey := s.StartTime.Local().Format("2006-01-02")
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ds, ok := dayMap[dayKey]
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if !ok {
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t, _ := time.ParseInLocation("2006-01-02", dayKey, time.Local)
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ds = &model.DailyStats{Date: t}
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dayMap[dayKey] = ds
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}
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ds.Sessions++
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ds.Prompts += s.UserMessages
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ds.APICalls += s.APICalls
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ds.DurationSecs += s.DurationSecs
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ds.InputTokens += s.InputTokens
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ds.OutputTokens += s.OutputTokens
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ds.CacheCreation5m += s.CacheCreation5mTokens
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ds.CacheCreation1h += s.CacheCreation1hTokens
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ds.CacheReadTokens += s.CacheReadTokens
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ds.EstimatedCost += s.EstimatedCost
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}
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// Convert to sorted slice (most recent first)
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days := make([]model.DailyStats, 0, len(dayMap))
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for _, ds := range dayMap {
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days = append(days, *ds)
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}
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sort.Slice(days, func(i, j int) bool {
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return days[i].Date.After(days[j].Date)
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})
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return days
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}
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// AggregateModels computes per-model statistics from sessions.
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func AggregateModels(sessions []model.SessionStats, since, until time.Time) []model.ModelStats {
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filtered := FilterByTime(sessions, since, until)
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modelMap := make(map[string]*model.ModelStats)
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totalCalls := 0
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for _, s := range filtered {
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for modelName, mu := range s.Models {
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ms, ok := modelMap[modelName]
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if !ok {
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ms = &model.ModelStats{Model: modelName}
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modelMap[modelName] = ms
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}
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ms.APICalls += mu.APICalls
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ms.InputTokens += mu.InputTokens
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ms.OutputTokens += mu.OutputTokens
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ms.CacheCreation5m += mu.CacheCreation5mTokens
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ms.CacheCreation1h += mu.CacheCreation1hTokens
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ms.CacheReadTokens += mu.CacheReadTokens
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ms.EstimatedCost += mu.EstimatedCost
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totalCalls += mu.APICalls
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}
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}
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// Compute share percentages and sort by cost descending
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models := make([]model.ModelStats, 0, len(modelMap))
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for _, ms := range modelMap {
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if totalCalls > 0 {
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ms.SharePercent = float64(ms.APICalls) / float64(totalCalls) * 100
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}
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models = append(models, *ms)
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}
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sort.Slice(models, func(i, j int) bool {
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return models[i].EstimatedCost > models[j].EstimatedCost
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})
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return models
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}
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// AggregateProjects computes per-project statistics from sessions.
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func AggregateProjects(sessions []model.SessionStats, since, until time.Time) []model.ProjectStats {
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filtered := FilterByTime(sessions, since, until)
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projMap := make(map[string]*model.ProjectStats)
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for _, s := range filtered {
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ps, ok := projMap[s.Project]
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if !ok {
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ps = &model.ProjectStats{Project: s.Project}
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projMap[s.Project] = ps
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}
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ps.Sessions++
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ps.Prompts += s.UserMessages
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ps.TotalTokens += s.InputTokens + s.OutputTokens +
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s.CacheCreation5mTokens + s.CacheCreation1hTokens
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ps.EstimatedCost += s.EstimatedCost
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}
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// Sort by cost descending
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projects := make([]model.ProjectStats, 0, len(projMap))
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for _, ps := range projMap {
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projects = append(projects, *ps)
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}
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sort.Slice(projects, func(i, j int) bool {
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return projects[i].EstimatedCost > projects[j].EstimatedCost
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})
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return projects
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}
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// AggregateHourly computes prompt counts by hour of day.
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func AggregateHourly(sessions []model.SessionStats, since, until time.Time) []model.HourlyStats {
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filtered := FilterByTime(sessions, since, until)
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hours := make([]model.HourlyStats, 24)
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for i := range hours {
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hours[i].Hour = i
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}
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// We attribute all prompts and tokens to the session's start hour
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for _, s := range filtered {
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if s.StartTime.IsZero() {
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continue
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}
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h := s.StartTime.Local().Hour()
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hours[h].Prompts += s.UserMessages
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hours[h].Sessions++
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hours[h].Tokens += s.InputTokens + s.OutputTokens
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}
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return hours
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}
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// FilterByTime returns sessions whose start time falls within [since, until).
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func FilterByTime(sessions []model.SessionStats, since, until time.Time) []model.SessionStats {
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if since.IsZero() && until.IsZero() {
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return sessions
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}
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var result []model.SessionStats
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for _, s := range sessions {
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if s.StartTime.IsZero() {
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continue
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}
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if !since.IsZero() && s.StartTime.Before(since) {
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continue
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}
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if !until.IsZero() && !s.StartTime.Before(until) {
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continue
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}
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result = append(result, s)
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}
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return result
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}
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// FilterByProject returns sessions matching the project substring.
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func FilterByProject(sessions []model.SessionStats, project string) []model.SessionStats {
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if project == "" {
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return sessions
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}
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var result []model.SessionStats
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for _, s := range sessions {
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if containsIgnoreCase(s.Project, project) {
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result = append(result, s)
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}
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}
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return result
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}
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// FilterByModel returns sessions that have at least one API call to the given model.
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func FilterByModel(sessions []model.SessionStats, modelFilter string) []model.SessionStats {
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if modelFilter == "" {
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return sessions
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}
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var result []model.SessionStats
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for _, s := range sessions {
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for m := range s.Models {
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if containsIgnoreCase(m, modelFilter) {
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result = append(result, s)
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break
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}
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}
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}
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return result
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}
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func containsIgnoreCase(s, substr string) bool {
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return strings.Contains(strings.ToLower(s), strings.ToLower(substr))
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}
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92
internal/pipeline/bench_test.go
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92
internal/pipeline/bench_test.go
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@@ -0,0 +1,92 @@
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package pipeline
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import (
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"os"
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"path/filepath"
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"testing"
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"cburn/internal/source"
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"cburn/internal/store"
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)
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func BenchmarkLoad(b *testing.B) {
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homeDir, _ := os.UserHomeDir()
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claudeDir := filepath.Join(homeDir, ".claude")
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b.ResetTimer()
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for i := 0; i < b.N; i++ {
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result, err := Load(claudeDir, true, nil)
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if err != nil {
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b.Fatal(err)
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}
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_ = result
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}
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}
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func BenchmarkParseFile(b *testing.B) {
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homeDir, _ := os.UserHomeDir()
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claudeDir := filepath.Join(homeDir, ".claude")
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files, err := source.ScanDir(claudeDir)
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if err != nil {
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b.Fatal(err)
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}
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// Find the largest file for worst-case benchmarking
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var biggest source.DiscoveredFile
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var biggestSize int64
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for _, f := range files {
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info, err := os.Stat(f.Path)
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if err != nil {
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continue
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}
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if info.Size() > biggestSize {
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biggestSize = info.Size()
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biggest = f
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}
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}
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b.Logf("Benchmarking largest file: %s (%.1f KB)", biggest.Path, float64(biggestSize)/1024)
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b.ResetTimer()
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for i := 0; i < b.N; i++ {
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result := source.ParseFile(biggest)
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if result.Err != nil {
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b.Fatal(result.Err)
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}
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}
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}
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func BenchmarkScanDir(b *testing.B) {
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homeDir, _ := os.UserHomeDir()
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claudeDir := filepath.Join(homeDir, ".claude")
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b.ResetTimer()
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for i := 0; i < b.N; i++ {
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files, err := source.ScanDir(claudeDir)
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if err != nil {
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b.Fatal(err)
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}
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_ = files
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}
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}
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func BenchmarkLoadWithCache(b *testing.B) {
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homeDir, _ := os.UserHomeDir()
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claudeDir := filepath.Join(homeDir, ".claude")
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cache, err := store.Open(CachePath())
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if err != nil {
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b.Fatal(err)
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}
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defer cache.Close()
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b.ResetTimer()
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for i := 0; i < b.N; i++ {
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cr, err := LoadWithCache(claudeDir, true, cache, nil)
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if err != nil {
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b.Fatal(err)
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}
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_ = cr
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}
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}
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177
internal/pipeline/incremental.go
Normal file
177
internal/pipeline/incremental.go
Normal file
@@ -0,0 +1,177 @@
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package pipeline
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import (
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"fmt"
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"os"
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"path/filepath"
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"runtime"
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"sync"
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"sync/atomic"
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"cburn/internal/source"
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"cburn/internal/store"
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)
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// CachedLoadResult extends LoadResult with cache metadata.
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type CachedLoadResult struct {
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LoadResult
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CacheHits int
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Reparsed int
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}
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// LoadWithCache discovers, diffs against cache, parses only changed files,
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// and returns the combined result set.
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func LoadWithCache(claudeDir string, includeSubagents bool, cache *store.Cache, progressFn ProgressFunc) (*CachedLoadResult, error) {
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// Discover files
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files, err := source.ScanDir(claudeDir)
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if err != nil {
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return nil, fmt.Errorf("scanning %s: %w", claudeDir, err)
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}
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if len(files) == 0 {
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return &CachedLoadResult{}, nil
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}
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// Filter subagents if requested
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var toProcess []source.DiscoveredFile
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if includeSubagents {
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toProcess = files
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} else {
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for _, f := range files {
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if !f.IsSubagent {
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toProcess = append(toProcess, f)
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}
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}
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}
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result := &CachedLoadResult{
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LoadResult: LoadResult{
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TotalFiles: len(toProcess),
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ProjectCount: source.CountProjects(files),
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},
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}
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if len(toProcess) == 0 {
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return result, nil
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}
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// Get tracked files from cache
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tracked, err := cache.GetTrackedFiles()
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if err != nil {
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return nil, fmt.Errorf("reading cache: %w", err)
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}
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// Diff: partition into changed and unchanged
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var toReparse []source.DiscoveredFile
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var unchanged []string // file paths that haven't changed
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for _, f := range toProcess {
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info, err := os.Stat(f.Path)
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if err != nil {
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continue
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}
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cached, ok := tracked[f.Path]
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if ok && cached.MtimeNs == info.ModTime().UnixNano() && cached.SizeBytes == info.Size() {
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unchanged = append(unchanged, f.Path)
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} else {
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toReparse = append(toReparse, f)
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}
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}
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result.CacheHits = len(unchanged)
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result.Reparsed = len(toReparse)
|
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|
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// Load cached sessions
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if len(unchanged) > 0 {
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cached, err := cache.LoadAllSessions()
|
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if err != nil {
|
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return nil, fmt.Errorf("loading cached sessions: %w", err)
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}
|
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|
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// Filter to only sessions from unchanged files
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unchangedSet := make(map[string]struct{}, len(unchanged))
|
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for _, p := range unchanged {
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unchangedSet[p] = struct{}{}
|
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}
|
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for _, s := range cached {
|
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if _, ok := unchangedSet[s.FilePath]; ok {
|
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result.Sessions = append(result.Sessions, s)
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result.ParsedFiles++
|
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}
|
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}
|
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}
|
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|
||||
// Parse changed files
|
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if len(toReparse) > 0 {
|
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numWorkers := runtime.GOMAXPROCS(0)
|
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if numWorkers < 1 {
|
||||
numWorkers = 4
|
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}
|
||||
if numWorkers > len(toReparse) {
|
||||
numWorkers = len(toReparse)
|
||||
}
|
||||
|
||||
work := make(chan int, len(toReparse))
|
||||
results := make([]source.ParseResult, len(toReparse))
|
||||
var wg sync.WaitGroup
|
||||
var processed atomic.Int64
|
||||
|
||||
for i := range toReparse {
|
||||
work <- i
|
||||
}
|
||||
close(work)
|
||||
|
||||
wg.Add(numWorkers)
|
||||
for w := 0; w < numWorkers; w++ {
|
||||
go func() {
|
||||
defer wg.Done()
|
||||
for idx := range work {
|
||||
results[idx] = source.ParseFile(toReparse[idx])
|
||||
n := processed.Add(1)
|
||||
if progressFn != nil {
|
||||
progressFn(int(n)+result.CacheHits, result.TotalFiles)
|
||||
}
|
||||
}
|
||||
}()
|
||||
}
|
||||
|
||||
wg.Wait()
|
||||
|
||||
// Collect and cache results
|
||||
for i, pr := range results {
|
||||
if pr.Err != nil {
|
||||
result.FileErrors++
|
||||
continue
|
||||
}
|
||||
result.ParsedFiles++
|
||||
result.ParseErrors += pr.ParseErrors
|
||||
|
||||
if pr.Stats.APICalls > 0 || pr.Stats.UserMessages > 0 {
|
||||
result.Sessions = append(result.Sessions, pr.Stats)
|
||||
|
||||
// Save to cache
|
||||
info, err := os.Stat(toReparse[i].Path)
|
||||
if err == nil {
|
||||
_ = cache.SaveSession(pr.Stats, info.ModTime().UnixNano(), info.Size())
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
return result, nil
|
||||
}
|
||||
|
||||
// CacheDir returns the platform-appropriate cache directory.
|
||||
func CacheDir() string {
|
||||
if xdg := os.Getenv("XDG_CACHE_HOME"); xdg != "" {
|
||||
return filepath.Join(xdg, "cburn")
|
||||
}
|
||||
home, _ := os.UserHomeDir()
|
||||
return filepath.Join(home, ".cache", "cburn")
|
||||
}
|
||||
|
||||
// CachePath returns the full path to the cache database.
|
||||
func CachePath() string {
|
||||
return filepath.Join(CacheDir(), "metrics.db")
|
||||
}
|
||||
117
internal/pipeline/loader.go
Normal file
117
internal/pipeline/loader.go
Normal file
@@ -0,0 +1,117 @@
|
||||
package pipeline
|
||||
|
||||
import (
|
||||
"fmt"
|
||||
"runtime"
|
||||
"sync"
|
||||
"sync/atomic"
|
||||
|
||||
"cburn/internal/model"
|
||||
"cburn/internal/source"
|
||||
)
|
||||
|
||||
// LoadResult holds the output of the full data loading pipeline.
|
||||
type LoadResult struct {
|
||||
Sessions []model.SessionStats
|
||||
TotalFiles int
|
||||
ParsedFiles int
|
||||
ParseErrors int
|
||||
FileErrors int
|
||||
ProjectCount int
|
||||
}
|
||||
|
||||
// ProgressFunc is called during loading to report progress.
|
||||
// current is the number of files processed so far, total is the total count.
|
||||
type ProgressFunc func(current, total int)
|
||||
|
||||
// Load discovers and parses all session files from the Claude data directory.
|
||||
// It uses a bounded worker pool for parallel parsing.
|
||||
func Load(claudeDir string, includeSubagents bool, progressFn ProgressFunc) (*LoadResult, error) {
|
||||
// Discover files
|
||||
files, err := source.ScanDir(claudeDir)
|
||||
if err != nil {
|
||||
return nil, fmt.Errorf("scanning %s: %w", claudeDir, err)
|
||||
}
|
||||
|
||||
if len(files) == 0 {
|
||||
return &LoadResult{}, nil
|
||||
}
|
||||
|
||||
// Filter subagents if requested
|
||||
var toProcess []source.DiscoveredFile
|
||||
if includeSubagents {
|
||||
toProcess = files
|
||||
} else {
|
||||
for _, f := range files {
|
||||
if !f.IsSubagent {
|
||||
toProcess = append(toProcess, f)
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
result := &LoadResult{
|
||||
TotalFiles: len(toProcess),
|
||||
ProjectCount: source.CountProjects(files),
|
||||
}
|
||||
|
||||
if len(toProcess) == 0 {
|
||||
return result, nil
|
||||
}
|
||||
|
||||
// Parallel parsing with bounded worker pool
|
||||
numWorkers := runtime.GOMAXPROCS(0)
|
||||
if numWorkers < 1 {
|
||||
numWorkers = 4
|
||||
}
|
||||
if numWorkers > len(toProcess) {
|
||||
numWorkers = len(toProcess)
|
||||
}
|
||||
|
||||
type indexedResult struct {
|
||||
idx int
|
||||
result source.ParseResult
|
||||
}
|
||||
|
||||
work := make(chan int, len(toProcess))
|
||||
results := make([]source.ParseResult, len(toProcess))
|
||||
var wg sync.WaitGroup
|
||||
var processed atomic.Int64
|
||||
|
||||
// Feed work
|
||||
for i := range toProcess {
|
||||
work <- i
|
||||
}
|
||||
close(work)
|
||||
|
||||
// Spawn workers
|
||||
wg.Add(numWorkers)
|
||||
for w := 0; w < numWorkers; w++ {
|
||||
go func() {
|
||||
defer wg.Done()
|
||||
for idx := range work {
|
||||
results[idx] = source.ParseFile(toProcess[idx])
|
||||
n := processed.Add(1)
|
||||
if progressFn != nil {
|
||||
progressFn(int(n), len(toProcess))
|
||||
}
|
||||
}
|
||||
}()
|
||||
}
|
||||
|
||||
wg.Wait()
|
||||
|
||||
// Collect results
|
||||
for _, pr := range results {
|
||||
if pr.Err != nil {
|
||||
result.FileErrors++
|
||||
continue
|
||||
}
|
||||
result.ParsedFiles++
|
||||
result.ParseErrors += pr.ParseErrors
|
||||
if pr.Stats.APICalls > 0 || pr.Stats.UserMessages > 0 {
|
||||
result.Sessions = append(result.Sessions, pr.Stats)
|
||||
}
|
||||
}
|
||||
|
||||
return result, nil
|
||||
}
|
||||
Reference in New Issue
Block a user