Files
DarkRoom/core/dr-catalog/src/lib.rs
T
dtourolleandClaude Opus 5 2147eaa6a5 Put a keyword on a photograph, not only search for one
The catalog has been able to *find* by keyword since v1 — query.rs joins the
keywords table, matches it exactly, and substring-matches it for free text — and
nothing anywhere could ever put a word there. A user could filter to a keyword
they had no way to apply.

This is the missing half: create, rename, delete, list, assign, unassign, and
the two reads a panel needs. Bulk-only for assignment, because keywording a
selection is the common case rather than the exception — the photographer picks
out the frames with the puffin in them and applies "puffin" once, in one
transaction.

Schema v6 adds `keyword_terms`, and deliberately does *not* touch the v1 join.
The assignment keeps the word as text because the catalog is a rebuildable index
and the durable copies of that fact — the sidecar, XMP dc:subject — both carry a
string; a foreign key would mean a catalog rebuilt from sidecars had to invent
identity rows before it could record anything, and would break the query path
that already works. So the text is the fact, and the new table is only the
identity a rename and a deletion can be keyed on.

`keyword_terms.name` carries no unique index, which looks like an oversight and
is not: two devices that each type "Iceland" are both right until they meet, and
a constraint would abort the merge at that moment. Uniqueness is converged upon
instead — create resolves an existing name, fuse_duplicates collapses a
cross-device pair onto the smaller uuid.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
2026-08-22 15:50:49 +02:00

448 lines
16 KiB
Rust

//! TRACES: FR-CAT-2 | FR-CAT-4 | FR-CAT-6 | NFR-P1
//! The catalog: a rebuildable index over the library.
//!
//! Not a source of truth. Sidecars next to the images hold the authoritative
//! edit state (ARCH §6.12), and this file is deletable at any time — rebuilt
//! by rescanning sources and reading sidecars. That inversion is deliberate:
//! darktable maintains both a database and sidecars while achieving the
//! reliability of neither.
//!
//! # What lives here
//!
//! - [`schema`] — tables and forward-only migrations
//! - [`scan`] — incremental discovery that prunes unchanged directories
//! - [`walk`] — those decisions driven against real storage, local or SAF
//! - [`query`] — selectors compiled to indexed SQL, windowed for the grid
//! - [`collections`] — the collection tree and membership the UI edits
//! - [`keywords`] — the keyword vocabulary and what it is assigned to
//! - [`jobs`] — the durable background work queue
//! - [`trash`] — soft delete to a folder, then permanent delete
//! - [`merge`] / [`sync`] — cross-device merging of collections and keywords
//!
//! # The one thing everything is designed around
//!
//! **Work is proportional to what changed, or to what the user is looking at —
//! never to library size.** A 50k-image library that has not changed costs one
//! metadata probe per folder to verify (§scan), no thumbnails to regenerate
//! (§jobs coalescing), and no rule evaluation per grid cell (materialised
//! `tier_desired`).
use std::path::Path;
use dr_types::{Availability, ImageId};
use rusqlite::Connection;
pub mod cache;
pub mod collections;
pub mod error;
pub mod jobs;
pub mod keywords;
pub mod merge;
pub mod query;
pub mod rating;
pub mod scan;
pub mod schema;
pub mod sync;
pub mod trash;
pub mod walk;
pub use cache::{Budget, Cache, DEFAULT_BUDGET_BYTES};
pub use collections::{Collection, CollectionKind, TreeRow};
pub use error::CatalogError;
pub use jobs::{Job, JobKind, Priority};
pub use keywords::{Coverage, Keyword, KeywordId, SelectionKeyword};
pub use merge::MergeReport;
pub use query::{Query, Sort};
pub use rating::{Judgement, MAX_RATING};
pub use scan::{DirAction, DirState, EntryAction, ScanOutcome};
pub use trash::{TrashedImage, TRASH_DIR};
pub use walk::{ensure_root, scan_root, RootKind, ScanProgress, ScanReport};
/// One row of the library grid.
///
/// Exactly what a cell draws and nothing more — no join per cell, and
/// availability reads a materialised column rather than evaluating cache rules
/// (ARCH §9.5).
#[derive(Debug, Clone, PartialEq, Eq)]
pub struct GridRow {
pub id: ImageId,
pub name: String,
pub availability: Availability,
/// UTC seconds. `None` until EXIF has been read.
pub captured_at: Option<i64>,
/// Minutes east of UTC, for rendering the photographer's local time.
pub captured_offset: Option<i32>,
/// 0 = nothing, 1 = stat-only, 2 = full EXIF.
pub metadata_state: u8,
}
/// A count of images in one time bucket, for the timeline scrubber.
#[derive(Debug, Clone, Copy, PartialEq, Eq)]
pub struct TimeBucket {
/// UTC seconds at the bucket's start.
pub start: i64,
pub count: u32,
}
/// Time bucket size.
#[derive(Debug, Clone, Copy, PartialEq, Eq)]
pub enum Granularity {
Year,
Month,
Day,
Hour,
}
impl Granularity {
/// SQLite `strftime` format that collapses a timestamp to this bucket.
///
/// Applied to **local** time, not UTC: "everything from 3 August" means
/// the photographer's 3 August, which is why `captured_offset` is stored
/// alongside the UTC timestamp.
/// Public so a caller that must build its own bucketing query — one
/// joining collection membership, say — buckets identically to
/// [`Catalog::timeline_range`] rather than reimplementing the format.
pub fn strftime(self) -> &'static str {
match self {
Granularity::Year => "%Y",
Granularity::Month => "%Y-%m",
Granularity::Day => "%Y-%m-%d",
Granularity::Hour => "%Y-%m-%dT%H",
}
}
/// A sensible bucket size for a span of seconds, so the UI need not guess.
pub fn for_span(seconds: i64) -> Self {
const DAY: i64 = 86_400;
match seconds {
s if s > 5 * 365 * DAY => Granularity::Year,
s if s > 90 * DAY => Granularity::Month,
s if s > 2 * DAY => Granularity::Day,
_ => Granularity::Hour,
}
}
}
/// A connection to the catalog.
pub struct Catalog {
conn: Connection,
}
impl Catalog {
/// Open or create a catalog, migrating it forward if needed.
pub fn open(path: &Path) -> Result<Self, CatalogError> {
let conn = Connection::open(path)?;
schema::configure(&conn)?;
let from = schema::migrate(&conn)?;
// A migration adds a column; it cannot know what the value should be
// for rows that already existed. Backfilling on open is what stops
// those rows being silently partial.
for (what, n) in schema::backfill(&conn)? {
log::info!("backfilled {what} for {n} row(s) (schema was v{from})");
}
Ok(Catalog { conn })
}
/// An in-memory catalog, for tests and for a throwaway import preview.
pub fn in_memory() -> Result<Self, CatalogError> {
let conn = Connection::open_in_memory()?;
schema::configure(&conn)?;
schema::migrate(&conn)?;
schema::backfill(&conn)?;
Ok(Catalog { conn })
}
/// Escape hatch for modules that need raw access. Not part of the UI-facing
/// surface.
pub fn connection(&self) -> &Connection {
&self.conn
}
/// How many images match.
///
/// Returned alongside the first window so the grid can size its scrollbar
/// and paint in one round trip.
pub fn count(&self, q: &Query, now: i64) -> Result<usize, CatalogError> {
let c = query::compile(&q.filter, now);
let sql = query::count_sql(&c);
let n: i64 =
self.conn
.query_row(&sql, rusqlite::params_from_iter(c.params.iter()), |r| {
r.get(0)
})?;
Ok(n as usize)
}
/// Fetch one window of results.
///
/// Never returns the whole catalog: FR-CAT-4 requires memory bounded
/// independently of library size.
pub fn window(
&self,
q: &Query,
range: std::ops::Range<usize>,
now: i64,
) -> Result<Vec<GridRow>, CatalogError> {
let c = query::compile(&q.filter, now);
let sql = query::window_sql(q, &c);
let mut params = c.params.clone();
params.push(rusqlite::types::Value::Integer(range.len() as i64));
params.push(rusqlite::types::Value::Integer(range.start as i64));
let mut stmt = self.conn.prepare(&sql)?;
let rows = stmt
.query_map(rusqlite::params_from_iter(params.iter()), |r| {
let source_ref: String = r.get(1)?;
let avail: i64 = r.get(2)?;
Ok(GridRow {
id: ImageId(r.get::<_, i64>(0)? as u64),
name: source_ref
.rsplit(['/', ':'])
.next()
.unwrap_or(&source_ref)
.to_string(),
availability: decode_availability(avail),
captured_at: r.get(3)?,
captured_offset: r.get::<_, Option<i64>>(4)?.map(|v| v as i32),
metadata_state: r.get::<_, i64>(5)? as u8,
})
})?
.collect::<Result<Vec<_>, _>>()?;
Ok(rows)
}
/// Counts per time bucket, for the timeline scrubber.
///
/// One grouped aggregate over the `images_captured` index — not 50k rows
/// handed to the UI to bucket itself.
pub fn timeline(
&self,
q: &Query,
g: Granularity,
now: i64,
) -> Result<Vec<TimeBucket>, CatalogError> {
let c = query::compile(&q.filter, now);
// Bucketed in local time: captured_offset is minutes east of UTC, and
// NULL falls back to UTC rather than dropping the row.
let sql = format!(
"SELECT min(captured_at) AS start,
count(*) AS n
FROM images
-- A shadowed JPEG is the same frame as its RAW; counting both
-- would double every paired shot in the histogram.
WHERE {} AND captured_at IS NOT NULL AND shadowed_by IS NULL
GROUP BY strftime('{}', captured_at + coalesce(captured_offset, 0) * 60,
'unixepoch')
ORDER BY start ASC",
c.where_sql,
g.strftime()
);
let mut stmt = self.conn.prepare(&sql)?;
let rows = stmt
.query_map(rusqlite::params_from_iter(c.params.iter()), |r| {
Ok(TimeBucket {
start: r.get(0)?,
count: r.get::<_, i64>(1)? as u32,
})
})?
.collect::<Result<Vec<_>, _>>()?;
Ok(rows)
}
/// Counts per time bucket, bounded to a date range.
///
/// What a zoomed timeline needs: [`timeline`](Self::timeline) always spans
/// the whole library, so zooming in would return the same coarse buckets
/// with the ends cropped rather than finer detail over a narrower span.
pub fn timeline_range(
&self,
q: &Query,
g: Granularity,
from: i64,
to: i64,
now: i64,
) -> Result<Vec<TimeBucket>, CatalogError> {
let c = query::compile(&q.filter, now);
let sql = format!(
"SELECT min(captured_at) AS start,
count(*) AS n
FROM images
WHERE {} AND captured_at IS NOT NULL AND shadowed_by IS NULL
AND captured_at >= ?{} AND captured_at <= ?{}
GROUP BY strftime('{}', captured_at + coalesce(captured_offset, 0) * 60,
'unixepoch')
ORDER BY start ASC",
c.where_sql,
c.params.len() + 1,
c.params.len() + 2,
g.strftime()
);
let mut params = c.params.clone();
params.push(rusqlite::types::Value::Integer(from));
params.push(rusqlite::types::Value::Integer(to));
let mut stmt = self.conn.prepare(&sql)?;
let rows = stmt
.query_map(rusqlite::params_from_iter(params.iter()), |r| {
Ok(TimeBucket {
start: r.get(0)?,
count: r.get::<_, i64>(1)? as u32,
})
})?
.collect::<Result<Vec<_>, _>>()?;
Ok(rows)
}
/// Merge a downloaded remote catalog's collections into this one.
///
/// See [`sync`] for why only collections cross over.
pub fn merge_remote_catalog(&self, remote: &Path) -> Result<MergeReport, CatalogError> {
sync::merge_remote(&self.conn, remote)
}
/// Write a consistent snapshot ready to upload.
pub fn snapshot_for_upload(&self, dest: &Path) -> Result<(), CatalogError> {
sync::snapshot_for_upload(&self.conn, dest)
}
}
fn decode_availability(v: i64) -> Availability {
match v {
1 => Availability::Preview,
2 => Availability::Original,
3 => Availability::Offline,
_ => Availability::MetadataOnly,
}
}
#[cfg(test)]
mod tests {
use super::*;
use dr_types::Selector;
fn seeded() -> Catalog {
let cat = Catalog::in_memory().unwrap();
let c = cat.connection();
c.execute(
"INSERT INTO roots(id, kind, label) VALUES (1, 'local', 'lib')",
[],
)
.unwrap();
// Three images across two days, one with no EXIF read yet.
for (id, name, captured, state) in [
(1i64, "a.CR3", Some(1_000_000i64), 2i64),
(2, "b.CR3", Some(1_100_000), 2),
(3, "c.CR3", None, 1),
] {
c.execute(
"INSERT INTO images(id, root_id, source_ref, captured_at, metadata_state, added_at)
VALUES (?1, 1, ?2, ?3, ?4, 0)",
rusqlite::params![id, name, captured, state],
)
.unwrap();
}
cat
}
#[test]
fn count_and_window_agree() {
let cat = seeded();
let q = Query::default();
assert_eq!(cat.count(&q, 0).unwrap(), 3);
assert_eq!(cat.window(&q, 0..10, 0).unwrap().len(), 3);
}
#[test]
fn window_is_bounded_by_the_requested_range() {
// FR-CAT-4: memory independent of catalog size.
let cat = seeded();
let rows = cat.window(&Query::default(), 0..2, 0).unwrap();
assert_eq!(rows.len(), 2);
}
#[test]
fn paging_covers_every_row_exactly_once() {
let cat = seeded();
let q = Query::default();
let mut seen = Vec::new();
for start in (0..3).step_by(2) {
seen.extend(cat.window(&q, start..start + 2, 0).unwrap());
}
let mut ids: Vec<u64> = seen.iter().map(|r| r.id.0).collect();
ids.sort_unstable();
assert_eq!(ids, vec![1, 2, 3]);
}
#[test]
fn an_image_without_capture_time_sorts_last_not_first() {
// Otherwise a freshly scanned library leads with whatever has not been
// read yet, which looks like corruption to the user.
let cat = seeded();
let rows = cat.window(&Query::default(), 0..10, 0).unwrap();
assert_eq!(rows.last().unwrap().id, ImageId(3));
}
#[test]
fn metadata_state_reaches_the_grid() {
// The grid needs it to distinguish "no photos on this date" from
// "EXIF not read yet" (FR-NC-6c's honesty principle).
let cat = seeded();
let rows = cat.window(&Query::default(), 0..10, 0).unwrap();
let pending = rows.iter().find(|r| r.id == ImageId(3)).unwrap();
assert_eq!(pending.metadata_state, 1);
}
#[test]
fn a_filter_narrows_the_count() {
let cat = seeded();
let q = Query {
filter: Selector::Text("a.CR3".into()),
..Default::default()
};
assert_eq!(cat.count(&q, 0).unwrap(), 1);
}
#[test]
fn timeline_buckets_and_skips_unread_images() {
let cat = seeded();
let buckets = cat
.timeline(&Query::default(), Granularity::Day, 0)
.unwrap();
// Two images with timestamps, one day apart in UTC; the third has no
// capture time and cannot be placed on a timeline at all.
let total: u32 = buckets.iter().map(|b| b.count).sum();
assert_eq!(total, 2);
}
#[test]
fn timeline_granularity_follows_the_span() {
const DAY: i64 = 86_400;
assert_eq!(Granularity::for_span(10 * 365 * DAY), Granularity::Year);
assert_eq!(Granularity::for_span(120 * DAY), Granularity::Month);
assert_eq!(Granularity::for_span(10 * DAY), Granularity::Day);
assert_eq!(Granularity::for_span(3600), Granularity::Hour);
}
#[test]
fn names_are_derived_for_both_paths_and_saf_ids() {
let cat = Catalog::in_memory().unwrap();
let c = cat.connection();
c.execute(
"INSERT INTO roots(id, kind, label) VALUES (1, 'saf', 'tree')",
[],
)
.unwrap();
c.execute(
"INSERT INTO images(id, root_id, source_ref, added_at)
VALUES (1, 1, 'primary:DCIM/Camera/IMG_1.CR3', 0)",
[],
)
.unwrap();
let rows = cat.window(&Query::default(), 0..10, 0).unwrap();
assert_eq!(rows[0].name, "IMG_1.CR3");
}
}