bvandeusen
1a7515e6ea
Per-source play outcomes so the operator can see whether each recommendation
surface is landing and tune the now-operator-tunable taste weights.
Server:
- query RecommendationSourceMetricsForUser: groups the user's play_events by
source (system-playlist surface), reporting plays / skips / avg completion
over a window; NULL-source (library/radio) plays excluded.
- GET /api/me/recommendation-metrics?days=30 (default 30, capped 365) →
{window_days, sources:[{source, plays, skips, skip_rate, avg_completion}]}.
- handler test: 401 unauth; per-source aggregation + NULL-source exclusion +
skip_rate / avg_completion math.
Web:
- lib/api/metrics.ts: query + friendly source labels.
- settings page gains a "Recommendation metrics" card (table of surface / plays
/ skip rate / avg completion), with loading/error/empty states.
- settings tests mock the new query (manual subscribe-store, hoisting-safe).
Note: You-might-like plays aren't source-tagged (it's a Home row, not a system
playlist), so this covers For-You / Discover / the mixes. Tagging YML plays
would be a client follow-up.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
74 lines
2.1 KiB
Go
74 lines
2.1 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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COALESCE(
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avg(pe.completion_ratio) FILTER (WHERE pe.completion_ratio IS NOT NULL),
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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.source IS NOT NULL
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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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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 system-playlist surface ('for_you' | 'discover' | the discovery mixes);
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// NULL for library / radio / user-playlist plays, which are excluded here.
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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 plays that recorded one (0 when none did).
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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.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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