feat: add job runs chart and scrollable reading lists on dashboard
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Deploy with Docker Compose / deploy (push) Successful in 1m5s
- Add multi-line chart showing job runs over time by type (scan, rebuild, thumbnails, other) with the same day/week/month toggle - Limit currently reading and recently read lists to 3 visible items with a scrollbar for overflow - Fix NUMERIC→BIGINT cast for SUM/COALESCE in jobs SQL queries Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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@@ -106,6 +106,15 @@ pub struct MonthlyReading {
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pub books_read: i64,
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}
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#[derive(Serialize, ToSchema)]
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pub struct JobTimePoint {
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pub label: String,
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pub scan: i64,
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pub rebuild: i64,
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pub thumbnail: i64,
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pub other: i64,
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}
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#[derive(Serialize, ToSchema)]
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pub struct StatsResponse {
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pub overview: StatsOverview,
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@@ -118,6 +127,7 @@ pub struct StatsResponse {
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pub by_library: Vec<LibraryStats>,
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pub top_series: Vec<TopSeries>,
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pub additions_over_time: Vec<MonthlyAdditions>,
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pub jobs_over_time: Vec<JobTimePoint>,
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pub metadata: MetadataStats,
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}
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@@ -555,6 +565,125 @@ pub async fn get_stats(
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})
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.collect();
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// Jobs over time (with gap filling, grouped by type category)
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let jobs_rows = match period {
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"day" => {
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sqlx::query(
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r#"
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SELECT
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TO_CHAR(d.dt, 'YYYY-MM-DD') AS label,
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COALESCE(SUM(cnt.c) FILTER (WHERE cnt.cat = 'scan'), 0)::BIGINT AS scan,
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COALESCE(SUM(cnt.c) FILTER (WHERE cnt.cat = 'rebuild'), 0)::BIGINT AS rebuild,
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COALESCE(SUM(cnt.c) FILTER (WHERE cnt.cat = 'thumbnail'), 0)::BIGINT AS thumbnail,
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COALESCE(SUM(cnt.c) FILTER (WHERE cnt.cat = 'other'), 0)::BIGINT AS other
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FROM generate_series(CURRENT_DATE - INTERVAL '6 days', CURRENT_DATE, '1 day') AS d(dt)
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LEFT JOIN (
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SELECT
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finished_at::date AS dt,
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CASE
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WHEN type = 'scan' THEN 'scan'
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WHEN type IN ('rebuild', 'full_rebuild', 'rescan') THEN 'rebuild'
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WHEN type IN ('thumbnail_rebuild', 'thumbnail_regenerate') THEN 'thumbnail'
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ELSE 'other'
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END AS cat,
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COUNT(*) AS c
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FROM index_jobs
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WHERE status IN ('success', 'failed')
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AND finished_at >= CURRENT_DATE - INTERVAL '6 days'
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GROUP BY finished_at::date, cat
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) cnt ON cnt.dt = d.dt
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GROUP BY d.dt
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ORDER BY label ASC
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"#,
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)
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.fetch_all(&state.pool)
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.await?
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}
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"week" => {
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sqlx::query(
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r#"
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SELECT
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TO_CHAR(d.dt, 'YYYY-MM-DD') AS label,
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COALESCE(SUM(cnt.c) FILTER (WHERE cnt.cat = 'scan'), 0)::BIGINT AS scan,
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COALESCE(SUM(cnt.c) FILTER (WHERE cnt.cat = 'rebuild'), 0)::BIGINT AS rebuild,
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COALESCE(SUM(cnt.c) FILTER (WHERE cnt.cat = 'thumbnail'), 0)::BIGINT AS thumbnail,
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COALESCE(SUM(cnt.c) FILTER (WHERE cnt.cat = 'other'), 0)::BIGINT AS other
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FROM generate_series(
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DATE_TRUNC('week', NOW() - INTERVAL '2 months'),
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DATE_TRUNC('week', NOW()),
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'1 week'
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) AS d(dt)
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LEFT JOIN (
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SELECT
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DATE_TRUNC('week', finished_at) AS dt,
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CASE
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WHEN type = 'scan' THEN 'scan'
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WHEN type IN ('rebuild', 'full_rebuild', 'rescan') THEN 'rebuild'
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WHEN type IN ('thumbnail_rebuild', 'thumbnail_regenerate') THEN 'thumbnail'
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ELSE 'other'
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END AS cat,
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COUNT(*) AS c
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FROM index_jobs
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WHERE status IN ('success', 'failed')
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AND finished_at >= DATE_TRUNC('week', NOW() - INTERVAL '2 months')
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GROUP BY DATE_TRUNC('week', finished_at), cat
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) cnt ON cnt.dt = d.dt
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GROUP BY d.dt
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ORDER BY label ASC
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"#,
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)
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.fetch_all(&state.pool)
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.await?
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}
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_ => {
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sqlx::query(
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r#"
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SELECT
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TO_CHAR(d.dt, 'YYYY-MM') AS label,
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COALESCE(SUM(cnt.c) FILTER (WHERE cnt.cat = 'scan'), 0)::BIGINT AS scan,
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COALESCE(SUM(cnt.c) FILTER (WHERE cnt.cat = 'rebuild'), 0)::BIGINT AS rebuild,
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COALESCE(SUM(cnt.c) FILTER (WHERE cnt.cat = 'thumbnail'), 0)::BIGINT AS thumbnail,
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COALESCE(SUM(cnt.c) FILTER (WHERE cnt.cat = 'other'), 0)::BIGINT AS other
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FROM generate_series(
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DATE_TRUNC('month', NOW()) - INTERVAL '11 months',
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DATE_TRUNC('month', NOW()),
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'1 month'
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) AS d(dt)
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LEFT JOIN (
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SELECT
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DATE_TRUNC('month', finished_at) AS dt,
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CASE
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WHEN type = 'scan' THEN 'scan'
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WHEN type IN ('rebuild', 'full_rebuild', 'rescan') THEN 'rebuild'
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WHEN type IN ('thumbnail_rebuild', 'thumbnail_regenerate') THEN 'thumbnail'
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ELSE 'other'
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END AS cat,
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COUNT(*) AS c
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FROM index_jobs
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WHERE status IN ('success', 'failed')
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AND finished_at >= DATE_TRUNC('month', NOW()) - INTERVAL '11 months'
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GROUP BY DATE_TRUNC('month', finished_at), cat
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) cnt ON cnt.dt = d.dt
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GROUP BY d.dt
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ORDER BY label ASC
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"#,
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)
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.fetch_all(&state.pool)
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.await?
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}
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};
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let jobs_over_time: Vec<JobTimePoint> = jobs_rows
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.iter()
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.map(|r| JobTimePoint {
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label: r.get("label"),
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scan: r.get("scan"),
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rebuild: r.get("rebuild"),
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thumbnail: r.get("thumbnail"),
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other: r.get("other"),
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})
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.collect();
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Ok(Json(StatsResponse {
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overview,
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reading_status,
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@@ -566,6 +695,7 @@ pub async fn get_stats(
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by_library,
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top_series,
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additions_over_time,
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jobs_over_time,
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metadata,
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}))
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}
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