bvandeusen
60533073ad
The recommendation metrics table was observable but not actionable: raw source strings (album:<uuid> one-offs) drowned the stable surfaces, and manual plays were excluded so skip rates had no control group. - SQL: include NULL-source rows (the baseline) and carry completion_n so family merges can weight avg_completion correctly. - Handler buckets raw sources into stable families (radio:<uuid> → Radio, album:/artist: → direct plays, etc.) grouped by surface intent: go-to / discovery / direct — each band judged against its job, since discovery mixes are expected to skip hotter. Families under 20 plays are flagged low-confidence, not hidden. - Settings card renders the baseline row and per-surface deltas in percentage points vs baseline (worse-than-baseline deltas in danger color), intent hint copy per group, low-data rows dimmed. - Pure-unit test for the bucketing/merge; DB test updated to the new contract (baseline included, radio:<uuid> collapse). Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01TsF3cNoKrqCYsU78cXC8U6
78 lines
2.4 KiB
Go
78 lines
2.4 KiB
Go
// Code generated by sqlc. DO NOT EDIT.
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// versions:
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// sqlc v1.31.1
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// source: recommendation_metrics.sql
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package dbq
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import (
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"context"
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"github.com/jackc/pgx/v5/pgtype"
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)
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const recommendationSourceMetricsForUser = `-- name: RecommendationSourceMetricsForUser :many
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SELECT
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pe.source,
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count(*)::bigint AS plays,
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count(*) FILTER (WHERE pe.was_skipped)::bigint AS skips,
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count(pe.completion_ratio)::bigint AS completion_n,
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COALESCE(avg(pe.completion_ratio), 0)::float8 AS avg_completion
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FROM play_events pe
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WHERE pe.user_id = $1
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AND pe.started_at > now() - ($2::float8 * INTERVAL '1 day')
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GROUP BY pe.source
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ORDER BY plays DESC
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`
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type RecommendationSourceMetricsForUserParams struct {
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UserID pgtype.UUID
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Column2 float64
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}
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type RecommendationSourceMetricsForUserRow struct {
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Source *string
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Plays int64
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Skips int64
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CompletionN int64
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AvgCompletion float64
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}
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// Recommendation observability (#796 phase 4). Per-source play outcomes so the
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// operator can see whether each recommendation surface is landing and tune the
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// taste weights. Source is stamped on play_events when a play is launched from
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// a recommendation surface; NULL means the user picked the track manually —
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// those rows are INCLUDED here as the baseline control group the surfaces are
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// judged against (milestone #127: delta-vs-baseline is what makes the numbers
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// actionable). Raw source strings are bucketed into stable surface families in
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// the Go handler; completion_n is carried so family merges can weight
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// avg_completion correctly.
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// $1 user_id, $2 window_days. plays/skips are counts; avg_completion is the
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// mean completion ratio over the completion_n plays that recorded one.
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func (q *Queries) RecommendationSourceMetricsForUser(ctx context.Context, arg RecommendationSourceMetricsForUserParams) ([]RecommendationSourceMetricsForUserRow, error) {
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rows, err := q.db.Query(ctx, recommendationSourceMetricsForUser, arg.UserID, arg.Column2)
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if err != nil {
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return nil, err
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}
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defer rows.Close()
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var items []RecommendationSourceMetricsForUserRow
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for rows.Next() {
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var i RecommendationSourceMetricsForUserRow
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if err := rows.Scan(
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&i.Source,
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&i.Plays,
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&i.Skips,
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&i.CompletionN,
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&i.AvgCompletion,
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); err != nil {
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return nil, err
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}
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items = append(items, i)
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}
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if err := rows.Err(); err != nil {
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return nil, err
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}
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return items, nil
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}
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