Dashboard detail, library filtering/pagination, simplified playlist times,

job descriptions

Dashboard: format breakdown (FLAC/MP3/etc. counts), approximate library
size (bitrate*length/8, same approximation `beet stats` itself uses --
verified to match its "100.5 GiB" output exactly against the real
library), and a credential auth-state summary per scope (configured y/n
plus, for Bandcamp, cookie expiry parsed locally from the stored cookie
jar -- deliberately not a live network probe like pipeline-status.sh's
Qobuz check, since this renders on every dashboard load).

Library: was one unfiltered page dumping all 4072 tracks. Added search
(artist/title/album), playlist and format filter dropdowns, and real
SQL-level pagination (LIMIT/OFFSET, not fetch-everything-then-slice).
beets_service gained count_items()/distinct_formats() to support this.

Playlists: cron_expr is still the stored/scheduled representation, but the
UI now shows and edits a plain daily time picker instead of raw cron
syntax -- every playlist schedule today is a simple daily HH:MM anyway.
playlist_service.cron_to_time()/time_to_cron() convert at the router
boundary; verified round-trip against all real playlist cron values.

Jobs: each maintenance job now shows a short one-line description of what
it actually does (MAINTENANCE_JOB_DESCRIPTIONS), and "next run" is
formatted consistently with playlists' time style (HH:MM, with a day
qualifier for non-today runs -- maintenance jobs can be weekly/monthly,
unlike playlists' plain daily schedule).

Verified end-to-end against the real production data (4072 tracks, 100.5
GiB, real credentials): stats/format-breakdown/search/pagination all
correct, all 7 credential scopes report configured with Bandcamp's real
cookie expiry (325 days), and a full authenticated page-render sweep
(dashboard, library with every filter combination, playlist detail,
jobs) all returned 200 with no template errors.
This commit is contained in:
andrew
2026-07-08 15:39:22 -06:00
parent ee21251f3e
commit c87ddc2649
13 changed files with 355 additions and 34 deletions
+98 -11
View File
@@ -34,22 +34,74 @@ def _row_to_dict(row: sqlite3.Row) -> dict:
return d
def query_items(grouping: str | None = None) -> list[dict]:
"""All items, optionally filtered to one playlist's grouping tag."""
def query_items(
grouping: str | None = None,
search: str | None = None,
format: str | None = None,
limit: int | None = None,
offset: int = 0,
) -> list[dict]:
"""Items, optionally filtered by playlist grouping, a free-text search
over artist/title/album, and/or exact format match. limit/offset give
SQL-level pagination -- the library has thousands of tracks, so this
must not be a fetch-everything-then-slice-in-Python operation."""
if not db_exists():
return []
cols = ", ".join(_ITEM_COLUMNS)
where = []
params: list = []
if grouping is not None:
where.append("grouping = ?")
params.append(grouping)
if format is not None:
where.append("format = ?")
params.append(format)
if search:
where.append("(artist LIKE ? OR title LIKE ? OR albumartist LIKE ?)")
like = f"%{search}%"
params.extend([like, like, like])
where_sql = f"WHERE {' AND '.join(where)}" if where else ""
limit_sql = ""
if limit is not None:
limit_sql = "LIMIT ? OFFSET ?"
params.extend([limit, offset])
conn = _connect()
try:
if grouping is not None:
cur = conn.execute(f"SELECT {cols} FROM items WHERE grouping = ?", (grouping,))
else:
cur = conn.execute(f"SELECT {cols} FROM items")
cur = conn.execute(
f"SELECT {cols} FROM items {where_sql} ORDER BY artist, album, track {limit_sql}",
params,
)
return [_row_to_dict(row) for row in cur.fetchall()]
finally:
conn.close()
def count_items(grouping: str | None = None, search: str | None = None, format: str | None = None) -> int:
"""Matching row count for query_items()'s filters -- for pagination."""
if not db_exists():
return 0
where = []
params: list = []
if grouping is not None:
where.append("grouping = ?")
params.append(grouping)
if format is not None:
where.append("format = ?")
params.append(format)
if search:
where.append("(artist LIKE ? OR title LIKE ? OR albumartist LIKE ?)")
like = f"%{search}%"
params.extend([like, like, like])
where_sql = f"WHERE {' AND '.join(where)}" if where else ""
conn = _connect()
try:
return conn.execute(f"SELECT COUNT(*) FROM items {where_sql}", params).fetchone()[0]
finally:
conn.close()
def get_item(item_id: int) -> dict | None:
if not db_exists():
return None
@@ -63,20 +115,55 @@ def get_item(item_id: int) -> dict | None:
def stats() -> dict:
"""Cheap summary for the dashboard and for migration-verification
(compare against `beet stats` during Stage 0 cutover)."""
"""Summary for the dashboard: total tracks, format breakdown, storage
estimate (bitrate*length/8, same approximation `beet stats` itself
uses -- not a filesystem stat() pass over every file), and groupings."""
if not db_exists():
return {"db_exists": False, "total_tracks": 0, "groupings": []}
return {
"db_exists": False,
"total_tracks": 0,
"groupings": [],
"formats": [],
"total_bytes": 0,
}
conn = _connect()
try:
total = conn.execute("SELECT COUNT(*) FROM items").fetchone()[0]
rows = conn.execute(
grouping_rows = conn.execute(
"SELECT DISTINCT grouping FROM items WHERE grouping IS NOT NULL AND grouping != ''"
).fetchall()
format_rows = conn.execute(
"SELECT format, COUNT(*) as n FROM items "
"WHERE format IS NOT NULL AND format != '' "
"GROUP BY format ORDER BY n DESC"
).fetchall()
total_bytes = conn.execute(
"SELECT SUM(length * bitrate) / 8 FROM items WHERE length IS NOT NULL AND bitrate IS NOT NULL"
).fetchone()[0] or 0
return {
"db_exists": True,
"total_tracks": total,
"groupings": sorted(r[0] for r in rows),
"groupings": sorted(r[0] for r in grouping_rows),
"formats": [{"format": r["format"], "count": r["n"]} for r in format_rows],
"total_bytes": int(total_bytes),
}
finally:
conn.close()
def distinct_formats() -> list[str]:
"""For the library page's format filter dropdown."""
if not db_exists():
return []
conn = _connect()
try:
rows = conn.execute(
"SELECT DISTINCT format FROM items WHERE format IS NOT NULL AND format != '' ORDER BY format"
).fetchall()
return [r[0] for r in rows]
finally:
conn.close()