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Author SHA1 Message Date
stumpylogandClaude Sonnet 5 a10f8fc81f chore: remove benchmark-commands spec/plan docs now that work is complete
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
2026-09-09 07:42:25 -07:00
stumpylogandClaude Sonnet 5 5ac6ae52de Fix: apply final-review fix wave (safety guard, date spread, MariaDB explain, history fields, memory footprint, minors)
Final whole-branch review before this tooling branch settles: add a
required --yes-i-know-this-wipes-the-database confirmation flag ahead of
--reset (it deletes ALL users/groups/documents in the target DB, not just
benchmark-created ones); spread seeded documents' created dates over a
3-year window instead of leaving them all on one default date; fix
capture_explain() to use MariaDB's ANALYZE syntax instead of Postgres-only
EXPLAIN ANALYZE (verified against real MariaDB 12.3 -- the old code was a
silent 1064 syntax error); record db_vendor/document_count in run/profile
history entries; shrink SeededData's memory footprint at scale by
returning counts instead of full ORM instance tuples; and a handful of
minor fixes (storage_path assignment, --explain warning instead of silent
no-op, harness.py repeat<1 guard, type annotations). All changes verified
against real Postgres and MariaDB containers on the VM, not just SQLite.

Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
2026-09-09 07:42:25 -07:00
stumpylogandClaude Sonnet 5 235be8d15f Fix: correct /api/tags/ endpoint URL in benchmarking skill
The skill documentation stated that run benchmarks /api/tags/ but
src/paperless_benchmark/endpoints.py actually uses
/api/tags/?page_size=100000. Update the skill's Command reference
section to match the actual endpoint definition.

Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
2026-09-09 07:42:25 -07:00
stumpylog 69af169575 docs(benchmark): add paperless-benchmarking skill 2026-09-09 07:42:25 -07:00
stumpylog 6aecbac2c4 fix(benchmark): fully clear users/groups on reset, grant perf_target model perms 2026-09-09 07:42:25 -07:00
stumpylogandClaude Sonnet 5 0bc7221e12 docs: add Task 10 (quirk fixes) and Task 11 (skill) to benchmark plan
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
2026-09-09 07:42:25 -07:00
stumpylog 95474bf1ae fix(benchmark): reuse seeded data in profile instead of reseeding
_handle_profile unconditionally called seed_benchmark_dataset every
run, colliding with an IntegrityError against data seeded by a prior
seed/profile call. Look up the existing perf_target user instead,
matching _handle_run's already-correct pattern, and raise a
CommandError pointing at `seed` if no dataset exists.

Scenario.run/queryset_for_explain now take a User directly instead of
a SeededData, since only data.users[0] (perf_target) was ever used.

profile no longer seeds, so it drops the --tier dependency: the
printed line and history entry no longer include a tier/(tier=...)
suffix, and --tier's help text now only mentions `seed`.
2026-09-09 07:42:24 -07:00
stumpylog e9bedd9343 feat(benchmark): add manage.py benchmark command (seed/run/profile/list-scenarios) 2026-09-09 07:42:24 -07:00
stumpylog cee6519a06 feat(benchmark): add pluggable profile-scenario registry 2026-09-09 07:42:24 -07:00
stumpylog c7b94952d2 feat(benchmark): add timed API endpoint scenarios 2026-09-09 07:42:24 -07:00
stumpylogandClaude Sonnet 5 bfae3ef82d docs: add implementation plan for benchmark management commands
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
2026-09-09 07:42:24 -07:00
stumpylog 7b90eb5069 feat(benchmark): add local JSONL results history log 2026-09-09 07:42:24 -07:00
stumpylog e15dad04bb feat(benchmark): add tiered dataset seeding 2026-09-09 07:42:24 -07:00
stumpylog d0731ce892 feat(benchmark): add per-backend reset and explain helpers 2026-09-09 07:42:24 -07:00
stumpylog dda0c93e80 feat(benchmark): add run_profile timing harness 2026-09-09 07:42:24 -07:00
stumpylogandClaude Sonnet 5 a09ea28636 feat(benchmark): scaffold paperless_benchmark app
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
2026-09-09 07:42:24 -07:00
stumpylogandClaude Sonnet 5 d5a9c502fc docs: add design spec for benchmark management commands
Merges the standalone run_benchmarks.py/seed_benchmark_data.py scripts
and the tools/profiling branch's Postgres-only harness into one
cross-backend `manage.py benchmark` command suite.

Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
2026-09-09 07:42:24 -07:00
64 changed files with 2255 additions and 3560 deletions
@@ -0,0 +1,187 @@
---
name: paperless-benchmarking
description: Use when profiling paperless-ngx performance, running `manage.py benchmark`, investigating a slow query or endpoint, or deciding whether a profiling finding should become a permanent registered scenario. Covers command reference, the fork/merge-back branch workflow for perf investigations, and how to read query-plan output.
---
# Paperless-ngx Benchmarking
This repo has a built-in benchmarking/profiling tool: `manage.py benchmark`, in
the `paperless_benchmark` Django app. It replaces ad hoc standalone scripts —
use it instead of writing new one-off seed/timing scripts.
## Command reference
```
manage.py benchmark seed --tier {home,medium,large} [--reset --yes-i-know-this-wipes-the-database] [--seed N]
manage.py benchmark run --repeat 5 [--label baseline]
manage.py benchmark profile <scenario_name> [--repeat 5] [--explain]
manage.py benchmark list-scenarios
```
- **`seed`** builds a realistic dataset at one of three scales: `home` (500
documents — fast, use this for iteration), `medium` (20,000 — the default
when `--tier` is omitted; a multi-minute seed), `large` (360,000 — matches
the scale reported in real large-install bug reports; slow, only use it
when a finding needs confirming at real scale). `--reset` wipes any
previously-seeded benchmark data first — but it is destructive and
irreversible: it deletes **all** users, **all** groups, and **all**
documents/tags/correspondents/document types/storage paths in the target
database, not just benchmark-created rows. Only run it against a disposable
benchmark database, never a real install. Because of that, `--reset` also
requires passing `--yes-i-know-this-wipes-the-database` in the same
invocation, or the command raises an error and does nothing. Omit both
flags if you want to layer more data onto an existing seed instead. `seed`
creates two named users, `perf_target` (mixed owned/shared documents,
realistic guardian permission grants) and `perf_admin` (superuser), plus a
general user/group pool with realistic permission-row ratios.
- **`run`** times the 3 built-in API endpoint benchmarks
(`/api/documents/`, `/api/documents/?page_size=50`, `/api/tags/?page_size=100000`) for both
`perf_target` and `perf_admin`, reporting min/median/max wall-clock and SQL
query count. Requires `seed` to have already run — it reuses that data, it
does not seed its own.
- **`profile`** times one named scenario from the registry (see
`list-scenarios`) via best-of-N repeat timing and SQL query count, against
`perf_target`. `--explain` additionally captures and prints the query plan:
real `EXPLAIN ANALYZE` execution stats on PostgreSQL/MariaDB, or
`EXPLAIN QUERY PLAN` (plan only, no real timing/row counts — clearly labeled
as such) on SQLite. Like `run`, `profile` requires `seed` to have already
run — it does not seed its own data either.
- Every `run`/`profile` invocation appends a JSON line to
`benchmark_results/history.jsonl` at the repo root (local-only, gitignored —
never commit this file). Use it to compare a `before`/`after` pair across
two invocations without hand-copying numbers.
- Full chain example: `seed --reset` once, then `run` and `profile` as many
times as you want against that same seeded data — no need to reseed between
them.
## Adding a new scenario
A "scenario" is a named, registered query/operation that `profile` can time
and explain. To add one, edit `src/paperless_benchmark/scenarios.py`: write a
`_<name>_run(user)` function (returns whatever `run_profile` should time) and
optionally a `_<name>_queryset(user)` function (returns the `QuerySet` for
`--explain` to analyze), then `register(Scenario(name=..., describe=...,
run=..., queryset_for_explain=...))` at module level. Both functions receive
the already-seeded `perf_target` user — they should not seed their own data.
## Branch workflow
`tools/benchmark-management-commands` is a **long-lived tooling branch**, not
a feature branch that gets merged and closed:
1. It is periodically brought up to date with `dev` (merge `dev` into it) so
the tooling doesn't drift from the schema/codebase it profiles. Do this
before starting a new investigation if it's been a while since the last
sync.
2. **Every performance investigation forks its own branch from
`tools/benchmark-management-commands`** (not from `dev`). Do the
investigation there: write throwaway profiling code, try fixes, capture
before/after numbers.
3. **That investigation branch never merges into `dev` or production.** Its
only job is to produce evidence and, optionally, a reusable scenario.
4. If the investigation turns up a scenario worth keeping permanently (see
"When to graduate a scenario" below), open a PR that adds **just that
scenario** back into `tools/benchmark-management-commands` — not the rest
of the investigation branch's throwaway code.
5. Any actual production fix the investigation motivates (e.g. an ORM query
change) goes into its own normal feature branch off `dev`, following the
project's regular contribution process — profiling evidence informs that
PR's description, but the profiling code itself does not travel with it.
## Reading query-plan output
- **PostgreSQL** `EXPLAIN ANALYZE`: look for `Seq Scan` on a large table
(missing index), a large gap between `rows=N` (planner's estimate) and the
actual row count in parentheses (stale statistics or a bad cardinality
estimate), and nested-loop joins driven by an outer relation with many
rows (usually the N+1 pattern this tool exists to catch).
- **MariaDB**: verified against a real MariaDB 12.3 container that MariaDB
does NOT accept MySQL 8.0.18+'s `EXPLAIN ANALYZE` syntax (it's a 1064
syntax error) -- `capture_explain()` instead runs MariaDB's own
`ANALYZE <statement>` form (no `EXPLAIN` keyword), which returns a
tabular plan with real per-row execution columns: `rows` (estimate) vs.
`r_rows` (actual), and `filtered` vs. `r_filtered`. A large gap between
`rows` and `r_rows`, or `type: ALL` (full table scan) on a large table,
are the signals to look for -- the same underlying concerns as Postgres's
`Seq Scan`/estimate-vs-actual gap, just in MariaDB's column-based output
instead of Postgres's nested-tree text format.
- **SQLite** `EXPLAIN QUERY PLAN`: no real timing/row-count data, only the
chosen access path (`SCAN` vs `SEARCH`, which index if any). Useful for
confirming an index is even being considered, not for judging real-world
cost — corroborate any SQLite finding against Postgres/MariaDB before
trusting it, since planner behavior differs meaningfully between them.
- Compare query **count**, not just timing, between before/after: a fix that
keeps the same wall-clock time but drops query count from O(n) to O(1) is
still a real, durable improvement — timing alone is noisy and
environment-dependent, query count is not.
## Cleaning up after an interrupted run
If a `seed`/`run`/`profile` invocation gets killed mid-run (Ctrl-C, `kill -9`,
a timed-out SSH session, etc.), check whether it left anything behind before
trusting the next benchmark's numbers. This was verified for real: a
`benchmark seed --tier large --reset ...` was started against both a fresh
PostgreSQL 18 container and a fresh MariaDB 12.3 container and `kill -9`'d a
few seconds into document seeding. In both cases, the database-side
connection disappeared immediately -- no stuck backend, no lingering query,
no held lock was observed in either backend once the killed process's PID
was confirmed gone. That said, this was one interruption point (mid
bulk-seed, between chunks); a run killed mid-query, or a driver/network
hiccup that doesn't cleanly close the socket, could behave differently, so
still check before trusting a number if any run in the session was
interrupted:
- **PostgreSQL**: look for leftover connections against the benchmark
database:
```sql
SELECT pid, state, query, query_start
FROM pg_stat_activity
WHERE datname = current_database() AND pid <> pg_backend_pid();
```
If a stuck backend shows up, clear it with:
```sql
SELECT pg_terminate_backend(pid)
FROM pg_stat_activity
WHERE datname = current_database() AND pid <> pg_backend_pid();
```
- **MariaDB**: look for leftover connections/queries:
```sql
SHOW FULL PROCESSLIST;
```
If a stuck connection shows up (anything other than your current admin
session), clear it with:
```sql
KILL <id>;
```
A stray connection left running concurrently with a subsequent benchmark run
would add real, contaminating load (extra queries competing for the same
rows, possibly held locks slowing the next run's timings) -- cheap to rule
out, expensive to silently trust a number that was actually measured
alongside a zombie connection.
## When to graduate a one-off finding into a permanent scenario
Register a scenario (rather than leaving it as throwaway code on the
investigation branch) when **both** are true:
- The query pattern is one this codebase is likely to regress on again (e.g.
it involves a permission-check join, a bulk operation, or anything else
with an easy-to-reintroduce N+1) — not a one-time fluke specific to this
investigation.
- Re-running it later, against a fresh seed, would still produce a
meaningful signal (it doesn't depend on investigation-specific throwaway
data or a fix that's already permanently landed and can't regress the same
way).
If a finding doesn't meet both bars, keep it as disposable code on the
investigation branch and let the branch's evidence (captured in the PR
description of whatever production fix it motivates) be the permanent
record instead.
+3
View File
@@ -115,3 +115,6 @@ celerybeat-schedule*
# Git worktree local folder
.worktrees
# Benchmark tooling output (local only, never committed)
/benchmark_results/
@@ -1,58 +0,0 @@
#!/command/with-contenv /usr/bin/bash
# shellcheck shell=bash
declare -r log_prefix="[init-compile-bytecode]"
# PYTHONDONTWRITEBYTECODE=1 is set for the whole container. This unit compiles a
# scoped set of libraries anyway, to speed up startup without bloating image size.
# Handle the people using a read only file system
if [[ "${S6_READ_ONLY_ROOT}" == "1" ]]; then
echo "${log_prefix} S6_READ_ONLY_ROOT=1, skipping (nothing to write bytecode to)"
exit 0
fi
# When running as a non-root user, site-packages is still root-owned and unwritable,
# so this step would just fail loudly on every container start. Skip it.
if [[ -n "${USER_IS_NON_ROOT}" ]]; then
echo "${log_prefix} USER_IS_NON_ROOT is set, skipping (site-packages is not writable)"
exit 0
fi
declare -r site_packages="$(python3 -c 'import site; print(site.getsitepackages()[0])')"
# Deliberately scoped to packages that paperless.settings/paperless/__init__.py import
# unconditionally on every manage.py invocation (Django itself, the always-loaded
# INSTALLED_APPS, and celery). This is NOT "compile everything" - the optional AI stack
# (torch, llama-index, sentence-transformers, ...) is intentionally excluded since it is
# lazy-imported and large.
declare -a scope=(
"${PAPERLESS_SRC_DIR}"
"${site_packages}/django"
"${site_packages}/celery"
"${site_packages}/kombu"
"${site_packages}/rest_framework"
"${site_packages}/django_filters"
"${site_packages}/whitenoise"
"${site_packages}/corsheaders"
"${site_packages}/django_extensions"
"${site_packages}/guardian"
"${site_packages}/allauth"
"${site_packages}/drf_spectacular"
"${site_packages}/drf_spectacular_sidecar"
"${site_packages}/treenode"
"${site_packages}/compression_middleware"
)
declare -a existing_scope=()
for path in "${scope[@]}"; do
[[ -d "${path}" ]] && existing_scope+=("${path}")
done
echo "${log_prefix} Compiling bytecode for: ${existing_scope[*]}"
declare -r start_seconds=${SECONDS}
if ! PYTHONDONTWRITEBYTECODE= python3 -m compileall -q "${existing_scope[@]}"; then
echo "${log_prefix} WARNING: compileall reported errors (read-only filesystem or unwritable site-packages?); continuing without a bytecode cache"
fi
echo "${log_prefix} Done in $((SECONDS - start_seconds))s"
@@ -1 +0,0 @@
oneshot
@@ -1 +0,0 @@
/etc/s6-overlay/s6-rc.d/init-compile-bytecode/run
-9
View File
@@ -1200,15 +1200,6 @@ still perform some basic text pre-processing before matching.
Defaults to true, enabling the feature.
#### [`PAPERLESS_CLASSIFIER_MATCH_THRESHOLD=<float>`](#PAPERLESS_CLASSIFIER_MATCH_THRESHOLD) {#PAPERLESS_CLASSIFIER_MATCH_THRESHOLD}
: Sets the minimum confidence score (0.0-1.0) required for the automatic
classifier to assign a correspondent, document type, or storage path to a
document. Predictions below this threshold are discarded and the field is
left unassigned, preventing low-confidence guesses from being applied.
Defaults to 0.6.
#### [`PAPERLESS_DATE_PARSER_LANGUAGES=<lang>`](#PAPERLESS_DATE_PARSER_LANGUAGES) {#PAPERLESS_DATE_PARSER_LANGUAGES}
: Specifies which language Paperless should use when parsing dates from documents.
+203 -250
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@@ -112,22 +112,6 @@
<pngx-input-check i18n-title title="Use 'slim' sidebar (icons only)" formControlName="slimSidebarEnabled"></pngx-input-check>
<p class="mb-2 mt-3" i18n>Sidebar items to show:</p>
@for (option of sidebarItemOptions; track option.id) {
<div class="form-check">
<input
class="form-check-input"
type="checkbox"
[id]="'sidebar-item-setting-' + option.id"
[checked]="isSidebarItemShown(option.id)"
(change)="toggleSidebarItem(option.id, $event.target.checked)"
/>
<label class="form-check-label" [for]="'sidebar-item-setting-' + option.id">
{{ option.label }}
</label>
</div>
}
</div>
</div>
@@ -24,7 +24,7 @@ import {
SystemStatus,
SystemStatusItemStatus,
} from 'src/app/data/system-status'
import { HideableSidebarItemID, SETTINGS_KEYS } from 'src/app/data/ui-settings'
import { SETTINGS_KEYS } from 'src/app/data/ui-settings'
import { IfOwnerDirective } from 'src/app/directives/if-owner.directive'
import { IfPermissionsDirective } from 'src/app/directives/if-permissions.directive'
import { PermissionsGuard } from 'src/app/guards/permissions.guard'
@@ -209,45 +209,6 @@ describe('SettingsComponent', () => {
fixture.detectChanges()
}
it('supports configuring sidebar items and canceling changes', () => {
completeSetup()
component.toggleSidebarItem(HideableSidebarItemID.Workflows, false)
fixture.detectChanges()
expect(component.settingsForm.value.sidebarHiddenItems).toContain(
HideableSidebarItemID.Workflows
)
settingsService.updateSidebarItemVisibility(
HideableSidebarItemID.Mail,
false
)
expect(component.settingsForm.value.sidebarHiddenItems).toContain(
HideableSidebarItemID.Mail
)
component.reset()
expect(component.settingsForm.value.sidebarHiddenItems).not.toContain(
HideableSidebarItemID.Workflows
)
expect(component.settingsForm.value.sidebarHiddenItems).not.toContain(
HideableSidebarItemID.Mail
)
})
it('enables sidebar item controls on general settings until destroyed', () => {
completeSetup()
expect(settingsService.organizingSidebarItems()).toBe(true)
component.ngOnDestroy()
expect(settingsService.organizingSidebarItems()).toBe(false)
})
it('should support tabbed settings & change URL, prevent navigation if dirty confirmation rejected', async () => {
completeSetup()
const navigateSpy = jest.spyOn(router, 'navigate')
@@ -288,7 +249,6 @@ describe('SettingsComponent', () => {
it('should support save local settings updating appearance settings and calling API, show error', () => {
completeSetup()
component.toggleSidebarItem(HideableSidebarItemID.Workflows, false)
const toastErrorSpy = jest.spyOn(toastService, 'showError')
const toastSpy = jest.spyOn(toastService, 'show')
const storeSpy = jest.spyOn(settingsService, 'storeSettings')
@@ -307,10 +267,7 @@ describe('SettingsComponent', () => {
expect(toastErrorSpy).toHaveBeenCalled()
expect(storeSpy).toHaveBeenCalled()
expect(appearanceSettingsSpy).not.toHaveBeenCalled()
expect(setSpy).toHaveBeenCalledTimes(34)
expect(setSpy).toHaveBeenCalledWith(SETTINGS_KEYS.SIDEBAR_HIDDEN_ITEMS, [
HideableSidebarItemID.Workflows,
])
expect(setSpy).toHaveBeenCalledTimes(33)
// succeed
storeSpy.mockReturnValueOnce(of(true))
@@ -39,12 +39,7 @@ import {
SystemStatus,
SystemStatusItemStatus,
} from 'src/app/data/system-status'
import {
GlobalSearchType,
HIDEABLE_SIDEBAR_ITEM_IDS,
HideableSidebarItemID,
SETTINGS_KEYS,
} from 'src/app/data/ui-settings'
import { GlobalSearchType, SETTINGS_KEYS } from 'src/app/data/ui-settings'
import { User } from 'src/app/data/user'
import { IfPermissionsDirective } from 'src/app/directives/if-permissions.directive'
import { CustomDatePipe } from 'src/app/pipes/custom-date.pipe'
@@ -107,14 +102,6 @@ const documentDetailFieldOptions = [
{ id: DocumentDetailFieldID.Tags, label: $localize`Tags` },
]
const sidebarItemLabels: Record<HideableSidebarItemID, string> = {
[HideableSidebarItemID.Dashboard]: $localize`Dashboard`,
[HideableSidebarItemID.SavedViews]: $localize`Saved Views`,
[HideableSidebarItemID.Workflows]: $localize`Workflows`,
[HideableSidebarItemID.Mail]: $localize`Mail`,
[HideableSidebarItemID.Documentation]: $localize`Documentation`,
}
@Component({
selector: 'pngx-settings',
templateUrl: './settings.component.html',
@@ -162,7 +149,6 @@ export class SettingsComponent
bulkEditApplyOnClose: new FormControl(null),
documentListItemPerPage: new FormControl(null),
slimSidebarEnabled: new FormControl(null),
sidebarHiddenItems: new FormControl<HideableSidebarItemID[]>([]),
darkModeUseSystem: new FormControl(null),
darkModeEnabled: new FormControl(null),
darkModeInvertThumbs: new FormControl(null),
@@ -200,7 +186,6 @@ export class SettingsComponent
store: BehaviorSubject<any>
storeSub: Subscription
sidebarItemsSub: Subscription
isDirty$: Observable<boolean>
isDirty: boolean = false
unsubscribeNotifier: Subject<any> = new Subject()
@@ -218,10 +203,6 @@ export class SettingsComponent
public readonly PdfEditorEditMode = PdfEditorEditMode
public readonly documentDetailFieldOptions = documentDetailFieldOptions
public readonly sidebarItemOptions = HIDEABLE_SIDEBAR_ITEM_IDS.map((id) => ({
id,
label: sidebarItemLabels[id],
}))
get systemStatusHasErrors(): boolean {
const status = this.systemStatus()
@@ -249,10 +230,6 @@ export class SettingsComponent
constructor() {
super()
this.sidebarItemsSub =
this.settings.sidebarHiddenItemsEditingChanged.subscribe((hiddenItems) =>
this.settingsForm.controls.sidebarHiddenItems.setValue(hiddenItems)
)
this.settings.settingsSaved.subscribe(() => {
if (!this.savePending) this.initialize()
this.savedViewsService.maybeRefreshDocumentCounts()
@@ -302,21 +279,14 @@ export class SettingsComponent
this.activatedRoute.paramMap.subscribe((paramMap) => {
const section = paramMap.get('section')
let navID = SettingsNavIDs.General
if (section) {
const navIDKey: string = Object.keys(SettingsNavIDs).find(
(navID) => navID.toLowerCase() == section
)
if (navIDKey) {
navID = SettingsNavIDs[navIDKey]
this.activeNavID.set(SettingsNavIDs[navIDKey])
}
}
this.activeNavID.set(navID)
this.settings.sidebarHiddenItemsEditing.set(
navID === SettingsNavIDs.General
? [...this.settingsForm.controls.sidebarHiddenItems.value]
: null
)
})
}
@@ -340,7 +310,6 @@ export class SettingsComponent
SETTINGS_KEYS.DOCUMENT_LIST_SIZE
),
slimSidebarEnabled: this.settings.get(SETTINGS_KEYS.SLIM_SIDEBAR),
sidebarHiddenItems: this.settings.get(SETTINGS_KEYS.SIDEBAR_HIDDEN_ITEMS),
darkModeUseSystem: this.settings.get(SETTINGS_KEYS.DARK_MODE_USE_SYSTEM),
darkModeEnabled: this.settings.get(SETTINGS_KEYS.DARK_MODE_ENABLED),
darkModeInvertThumbs: this.settings.get(
@@ -467,12 +436,6 @@ export class SettingsComponent
this.settingsForm.patchValue(currentFormValue)
}
if (this.settings.organizingSidebarItems()) {
this.settings.sidebarHiddenItemsEditing.set([
...this.settingsForm.controls.sidebarHiddenItems.value,
])
}
if (this.canViewSystemStatus) {
this.systemStatusService.get().subscribe((status) => {
this.systemStatus.set(status)
@@ -481,18 +444,8 @@ export class SettingsComponent
}
ngOnDestroy() {
this.settings.sidebarHiddenItemsEditing.set(null)
if (this.isDirty) this.settings.updateAppearanceSettings() // in case user changed appearance but didn't save
this.storeSub && this.storeSub.unsubscribe()
this.sidebarItemsSub.unsubscribe()
}
isSidebarItemShown(item: HideableSidebarItemID): boolean {
return !(this.settingsForm.value.sidebarHiddenItems || []).includes(item)
}
toggleSidebarItem(item: HideableSidebarItemID, checked: boolean): void {
this.settings.updateSidebarItemVisibility(item, checked)
}
public saveSettings() {
@@ -520,10 +473,6 @@ export class SettingsComponent
SETTINGS_KEYS.SLIM_SIDEBAR,
this.settingsForm.value.slimSidebarEnabled
)
this.settings.set(
SETTINGS_KEYS.SIDEBAR_HIDDEN_ITEMS,
this.settingsForm.value.sidebarHiddenItems
)
this.settings.set(
SETTINGS_KEYS.DARK_MODE_USE_SYSTEM,
this.settingsForm.value.darkModeUseSystem
@@ -683,11 +632,6 @@ export class SettingsComponent
reset() {
this.settingsForm.patchValue(this.store.getValue())
if (this.settings.organizingSidebarItems()) {
this.settings.sidebarHiddenItemsEditing.set([
...this.settingsForm.controls.sidebarHiddenItems.value,
])
}
}
clearThemeColor() {
@@ -86,15 +86,12 @@
}
<div class="sidebar-sticky pt-3 pb-1 d-flex flex-column justify-space-around">
<ul class="nav flex-column">
<li class="nav-item app-link position-relative" [class.d-none]="settingsService.sidebarItemIsHidden(HideableSidebarItemID.Dashboard) && !settingsService.organizingSidebarItems()">
<a class="nav-link" [class.opacity-50]="settingsService.sidebarItemIsHidden(HideableSidebarItemID.Dashboard)" [class.pe-5]="settingsService.organizingSidebarItems() && !slimSidebarEnabled && !slimSidebarAnimating()" routerLink="dashboard" routerLinkActive="active" (click)="closeMenu()"
<li class="nav-item app-link">
<a class="nav-link" routerLink="dashboard" routerLinkActive="active" (click)="closeMenu()"
ngbPopover="Dashboard" i18n-ngbPopover [disablePopover]="!slimSidebarPopoversEnabled" placement="end"
container="body" triggers="mouseenter:mouseleave" popoverClass="popover-slim">
<i-bs class="me-2" name="house"></i-bs><span class="nav-link-label"><ng-container i18n>Dashboard</ng-container></span>
</a>
@if (settingsService.organizingSidebarItems()) {
<pngx-input-switch class="position-absolute top-50 end-0 translate-middle-y me-1" [class.d-none]="slimSidebarEnabled || slimSidebarAnimating()" [compact]="true" title="Dashboard" i18n-title [ngModel]="!settingsService.sidebarItemIsHidden(HideableSidebarItemID.Dashboard)" (ngModelChange)="toggleSidebarItem(HideableSidebarItemID.Dashboard, $event)"></pngx-input-switch>
}
</li>
<li class="nav-item app-link" *pngxIfPermissions="{ action: PermissionAction.View, type: PermissionType.Document }">
<a class="nav-link" routerLink="documents" routerLinkActive="active"
@@ -240,38 +237,29 @@
</div>
</li>
}
<li class="nav-item app-link position-relative" [class.d-none]="settingsService.sidebarItemIsHidden(HideableSidebarItemID.SavedViews) && !settingsService.organizingSidebarItems()" *pngxIfPermissions="{ action: PermissionAction.View, type: PermissionType.SavedView }">
<a class="nav-link" [class.opacity-50]="settingsService.sidebarItemIsHidden(HideableSidebarItemID.SavedViews)" [class.pe-5]="settingsService.organizingSidebarItems() && !slimSidebarEnabled && !slimSidebarAnimating()" routerLink="savedviews" routerLinkActive="active" (click)="closeMenu()"
<li class="nav-item app-link" *pngxIfPermissions="{ action: PermissionAction.View, type: PermissionType.SavedView }">
<a class="nav-link" routerLink="savedviews" routerLinkActive="active" (click)="closeMenu()"
ngbPopover="Saved Views" i18n-ngbPopover [disablePopover]="!slimSidebarPopoversEnabled" placement="end"
container="body" triggers="mouseenter:mouseleave" popoverClass="popover-slim">
<i-bs class="me-2" name="window-stack"></i-bs><span class="nav-link-label"><ng-container i18n>Saved Views</ng-container></span>
</a>
@if (settingsService.organizingSidebarItems()) {
<pngx-input-switch class="position-absolute top-50 end-0 translate-middle-y me-1" [class.d-none]="slimSidebarEnabled || slimSidebarAnimating()" [compact]="true" title="Saved Views" i18n-title [ngModel]="!settingsService.sidebarItemIsHidden(HideableSidebarItemID.SavedViews)" (ngModelChange)="toggleSidebarItem(HideableSidebarItemID.SavedViews, $event)"></pngx-input-switch>
}
</li>
<li class="nav-item app-link position-relative" [class.d-none]="settingsService.sidebarItemIsHidden(HideableSidebarItemID.Workflows) && !settingsService.organizingSidebarItems()"
<li class="nav-item app-link"
*pngxIfPermissions="{ action: PermissionAction.View, type: PermissionType.Workflow }"
tourAnchor="tour.workflows">
<a class="nav-link" [class.opacity-50]="settingsService.sidebarItemIsHidden(HideableSidebarItemID.Workflows)" [class.pe-5]="settingsService.organizingSidebarItems() && !slimSidebarEnabled && !slimSidebarAnimating()" routerLink="workflows" routerLinkActive="active" (click)="closeMenu()"
<a class="nav-link" routerLink="workflows" routerLinkActive="active" (click)="closeMenu()"
ngbPopover="Workflows" i18n-ngbPopover [disablePopover]="!slimSidebarPopoversEnabled" placement="end"
container="body" triggers="mouseenter:mouseleave" popoverClass="popover-slim">
<i-bs class="me-2" name="boxes"></i-bs><span class="nav-link-label"><ng-container i18n>Workflows</ng-container></span>
</a>
@if (settingsService.organizingSidebarItems()) {
<pngx-input-switch class="position-absolute top-50 end-0 translate-middle-y me-1" [class.d-none]="slimSidebarEnabled || slimSidebarAnimating()" [compact]="true" title="Workflows" i18n-title [ngModel]="!settingsService.sidebarItemIsHidden(HideableSidebarItemID.Workflows)" (ngModelChange)="toggleSidebarItem(HideableSidebarItemID.Workflows, $event)"></pngx-input-switch>
}
</li>
<li class="nav-item app-link position-relative" [class.d-none]="settingsService.sidebarItemIsHidden(HideableSidebarItemID.Mail) && !settingsService.organizingSidebarItems()" *pngxIfPermissions="{ action: PermissionAction.View, type: PermissionType.MailAccount }"
<li class="nav-item app-link" *pngxIfPermissions="{ action: PermissionAction.View, type: PermissionType.MailAccount }"
tourAnchor="tour.mail">
<a class="nav-link" [class.opacity-50]="settingsService.sidebarItemIsHidden(HideableSidebarItemID.Mail)" [class.pe-5]="settingsService.organizingSidebarItems() && !slimSidebarEnabled && !slimSidebarAnimating()" routerLink="mail" routerLinkActive="active" (click)="closeMenu()" ngbPopover="Mail"
<a class="nav-link" routerLink="mail" routerLinkActive="active" (click)="closeMenu()" ngbPopover="Mail"
i18n-ngbPopover [disablePopover]="!slimSidebarPopoversEnabled" placement="end" container="body"
triggers="mouseenter:mouseleave" popoverClass="popover-slim">
<i-bs class="me-2" name="envelope"></i-bs><span class="nav-link-label"><ng-container i18n>Mail</ng-container></span>
</a>
@if (settingsService.organizingSidebarItems()) {
<pngx-input-switch class="position-absolute top-50 end-0 translate-middle-y me-1" [class.d-none]="slimSidebarEnabled || slimSidebarAnimating()" [compact]="true" title="Mail" i18n-title [ngModel]="!settingsService.sidebarItemIsHidden(HideableSidebarItemID.Mail)" (ngModelChange)="toggleSidebarItem(HideableSidebarItemID.Mail, $event)"></pngx-input-switch>
}
</li>
<li class="nav-item app-link" *pngxIfPermissions="{ action: PermissionAction.Delete, type: PermissionType.Document }">
<a class="nav-link" routerLink="trash" routerLinkActive="active" (click)="closeMenu()" ngbPopover="Trash"
@@ -334,16 +322,13 @@
</a>
</li>
}
<li class="nav-item mt-2 position-relative" [class.d-none]="settingsService.sidebarItemIsHidden(HideableSidebarItemID.Documentation) && !settingsService.organizingSidebarItems()" tourAnchor="tour.outro">
<a class="text-muted small d-flex align-items-center flex-wrap text-decoration-none nav-anchor" [class.opacity-50]="settingsService.sidebarItemIsHidden(HideableSidebarItemID.Documentation)" [class.pe-5]="settingsService.organizingSidebarItems() && !slimSidebarEnabled && !slimSidebarAnimating()"
<li class="nav-item mt-2" tourAnchor="tour.outro">
<a class="text-muted small d-flex align-items-center flex-wrap text-decoration-none nav-anchor"
target="_blank" rel="noopener noreferrer" href="https://docs.paperless-ngx.com" ngbPopover="Documentation"
i18n-ngbPopover [disablePopover]="!slimSidebarPopoversEnabled" placement="end" container="body"
triggers="mouseenter:mouseleave" popoverClass="popover-slim">
<i-bs class="d-flex me-2" name="question-circle"></i-bs><span><ng-container i18n>Documentation</ng-container></span>
</a>
@if (settingsService.organizingSidebarItems()) {
<pngx-input-switch class="position-absolute top-50 end-0 translate-middle-y me-1" [class.d-none]="slimSidebarEnabled || slimSidebarAnimating()" [compact]="true" title="Documentation" i18n-title [ngModel]="!settingsService.sidebarItemIsHidden(HideableSidebarItemID.Documentation)" (ngModelChange)="toggleSidebarItem(HideableSidebarItemID.Documentation, $event)"></pngx-input-switch>
}
</li>
<li class="nav-item" [class.visually-hidden]="slimSidebarEnabled">
<div class="text-muted small d-flex align-items-center flex-wrap nav-label">
@@ -15,7 +15,7 @@ import { provideUiTour } from 'ngx-ui-tour-ng-bootstrap'
import { of, throwError } from 'rxjs'
import { routes } from 'src/app/app-routing.module'
import { SavedView } from 'src/app/data/saved-view'
import { HideableSidebarItemID, SETTINGS_KEYS } from 'src/app/data/ui-settings'
import { SETTINGS_KEYS } from 'src/app/data/ui-settings'
import { IfPermissionsDirective } from 'src/app/directives/if-permissions.directive'
import { PermissionsGuard } from 'src/app/guards/permissions.guard'
import {
@@ -287,82 +287,6 @@ describe('AppFrameComponent', () => {
jest.useRealTimers()
})
it('should hide configured sidebar items', () => {
settingsService.set(SETTINGS_KEYS.SIDEBAR_HIDDEN_ITEMS, [
HideableSidebarItemID.Dashboard,
HideableSidebarItemID.Workflows,
])
fixture.detectChanges()
expect(
fixture.nativeElement.querySelector('[routerLink="dashboard"]')
.parentElement.classList
).toContain('d-none')
expect(
fixture.nativeElement.querySelector('[routerLink="workflows"]')
.parentElement.classList
).toContain('d-none')
expect(
fixture.nativeElement.querySelector('[routerLink="mail"]').parentElement
.classList
).not.toContain('d-none')
})
it('should show hidden items and visibility switches while customizing', () => {
settingsService.set(SETTINGS_KEYS.SIDEBAR_HIDDEN_ITEMS, [
HideableSidebarItemID.Dashboard,
])
settingsService.sidebarHiddenItemsEditing.set([
HideableSidebarItemID.Dashboard,
])
fixture.detectChanges()
expect(
fixture.nativeElement.querySelectorAll('pngx-input-switch').length
).toBe(5)
expect(
fixture.nativeElement.querySelector('[routerLink="dashboard"]')
.parentElement.classList
).not.toContain('d-none')
expect(
fixture.nativeElement.querySelector('[routerLink="dashboard"]').classList
).toContain('opacity-50')
settingsService.set(SETTINGS_KEYS.SLIM_SIDEBAR, true)
fixture.detectChanges()
expect(
Array.from(
fixture.nativeElement.querySelectorAll('pngx-input-switch')
).every((toggle: HTMLElement) => toggle.classList.contains('d-none'))
).toBe(true)
expect(
fixture.nativeElement.querySelector('[routerLink="dashboard"]').classList
).not.toContain('pe-5')
settingsService.set(SETTINGS_KEYS.SLIM_SIDEBAR, false)
component.slimSidebarAnimating.set(true)
fixture.detectChanges()
expect(
Array.from(
fixture.nativeElement.querySelectorAll('pngx-input-switch')
).every((toggle: HTMLElement) => toggle.classList.contains('d-none'))
).toBe(true)
component.slimSidebarAnimating.set(false)
fixture.detectChanges()
expect(
Array.from(
fixture.nativeElement.querySelectorAll('pngx-input-switch')
).every((toggle: HTMLElement) => !toggle.classList.contains('d-none'))
).toBe(true)
expect(
fixture.nativeElement.querySelector('[routerLink="dashboard"]').classList
).toContain('pe-5')
})
it('should show error on toggle slim sidebar if store settings fails', () => {
jest.spyOn(console, 'warn').mockImplementation(() => {})
const toastSpy = jest.spyOn(toastService, 'showError')
@@ -7,7 +7,6 @@ import {
} from '@angular/cdk/drag-drop'
import { NgClass } from '@angular/common'
import { Component, HostListener, inject, OnInit, signal } from '@angular/core'
import { FormsModule } from '@angular/forms'
import { ActivatedRoute, Router, RouterModule } from '@angular/router'
import {
NgbCollapseModule,
@@ -22,11 +21,7 @@ import { Observable } from 'rxjs'
import { first } from 'rxjs/operators'
import { Document } from 'src/app/data/document'
import { SavedView } from 'src/app/data/saved-view'
import {
CollapsibleSection,
HideableSidebarItemID,
SETTINGS_KEYS,
} from 'src/app/data/ui-settings'
import { CollapsibleSection, SETTINGS_KEYS } from 'src/app/data/ui-settings'
import { IfPermissionsDirective } from 'src/app/directives/if-permissions.directive'
import { ComponentCanDeactivate } from 'src/app/guards/dirty-doc.guard'
import { DocumentTitlePipe } from 'src/app/pipes/document-title.pipe'
@@ -53,7 +48,6 @@ import { ChatComponent } from '../chat/chat/chat.component'
import { BrandMarkComponent } from '../common/logo/brand-mark/brand-mark.component'
import { LogoComponent } from '../common/logo/logo.component'
import { ProfileEditDialogComponent } from '../common/profile-edit-dialog/profile-edit-dialog.component'
import { SwitchComponent } from '../common/input/switch/switch.component'
import { DocumentDetailComponent } from '../document-detail/document-detail.component'
import { ComponentWithPermissions } from '../with-permissions/with-permissions.component'
import { GlobalSearchComponent } from './global-search/global-search.component'
@@ -82,8 +76,6 @@ const SCROLL_THRESHOLD = 16
NgxBootstrapIconsModule,
DragDropModule,
TourNgBootstrap,
FormsModule,
SwitchComponent,
],
})
export class AppFrameComponent
@@ -106,7 +98,6 @@ export class AppFrameComponent
readonly isMenuCollapsed = signal(true)
readonly slimSidebarAnimating = signal(false)
readonly mobileSearchHidden = signal(false)
readonly HideableSidebarItemID = HideableSidebarItemID
private readonly versionSetting = this.settingsService.getSignal<string>(
SETTINGS_KEYS.VERSION
)
@@ -204,10 +195,6 @@ export class AppFrameComponent
}, 200) // slightly longer than css animation for slim sidebar
}
toggleSidebarItem(item: HideableSidebarItemID, visible: boolean): void {
this.settingsService.updateSidebarItemVisibility(item, visible)
}
toggleAttributesSections(event?: Event): void {
event?.preventDefault()
event?.stopPropagation()
@@ -1,6 +1,6 @@
<div [class.mb-3]="!compact">
<div [class.row]="!compact">
@if (!horizontal && !compact) {
<div class="mb-3">
<div class="row">
@if (!horizontal) {
<div class="d-flex align-items-center position-relative hidden-button-container col-md-3">
<label class="form-label" [for]="inputId" [ngbTooltip]="showUnsetNote && isUnset ? tipContent: null" placement="end">
{{title}}
@@ -17,8 +17,8 @@
}
<div [ngClass]="{'align-items-center': horizontal, 'd-flex': horizontal}">
<div class="form-check form-switch">
<input #inputField type="checkbox" class="form-check-input" [id]="inputId" [(ngModel)]="value" [ngModelOptions]="{standalone: true}" (change)="onChange(value)" (blur)="onTouched()" [disabled]="disabled" [attr.aria-label]="compact ? title : null">
@if (horizontal && !compact) {
<input #inputField type="checkbox" class="form-check-input" [id]="inputId" [(ngModel)]="value" [ngModelOptions]="{standalone: true}" (change)="onChange(value)" (blur)="onTouched()" [disabled]="disabled">
@if (horizontal) {
<label class="form-check-label" [class.text-muted]="showUnsetNote && isUnset" [for]="inputId" [ngbTooltip]="showUnsetNote && isUnset ? tipContent: null" placement="end">
{{title}}
@if (showUnsetNote && isUnset) {
@@ -48,14 +48,4 @@ describe('SwitchComponent', () => {
component.value = undefined
expect(component.isUnset).toBeTruthy()
})
it('should support a compact layout', () => {
component.compact = true
component.title = 'Test switch'
fixture.detectChanges()
expect(fixture.nativeElement.querySelector('.mb-3')).toBeNull()
expect(fixture.nativeElement.querySelector('.row')).toBeNull()
expect(input.getAttribute('aria-label')).toEqual('Test switch')
})
})
@@ -25,9 +25,6 @@ export class SwitchComponent extends AbstractInputComponent<boolean> {
@Input()
showUnsetNote: boolean = false
@Input()
compact: boolean = false
constructor() {
super()
}
-16
View File
@@ -24,16 +24,6 @@ export enum CollapsibleSection {
ATTRIBUTES = 'attributes',
}
export enum HideableSidebarItemID {
Dashboard = 'dashboard',
SavedViews = 'saved_views',
Workflows = 'workflows',
Mail = 'mail',
Documentation = 'documentation',
}
export const HIDEABLE_SIDEBAR_ITEM_IDS = Object.values(HideableSidebarItemID)
export const PAPERLESS_GREEN_HEX = '#17541f'
export const SETTINGS_KEYS = {
@@ -66,7 +56,6 @@ export const SETTINGS_KEYS = {
NOTES_ENABLED: 'general-settings:notes-enabled',
AUDITLOG_ENABLED: 'general-settings:auditlog-enabled',
SLIM_SIDEBAR: 'general-settings:slim-sidebar',
SIDEBAR_HIDDEN_ITEMS: 'general-settings:sidebar:hidden-items',
ATTRIBUTES_SECTIONS_COLLAPSED:
'general-settings:attributes-sections-collapsed',
UPDATE_CHECKING_ENABLED: 'general-settings:update-checking:enabled',
@@ -138,11 +127,6 @@ export const SETTINGS: UiSetting[] = [
type: 'boolean',
default: false,
},
{
key: SETTINGS_KEYS.SIDEBAR_HIDDEN_ITEMS,
type: 'array',
default: [],
},
{
key: SETTINGS_KEYS.ATTRIBUTES_SECTIONS_COLLAPSED,
type: 'array',
@@ -14,11 +14,7 @@ import { CustomFieldDataType } from '../data/custom-field'
import { DEFAULT_DISPLAY_FIELDS, DisplayField } from '../data/document'
import { SavedView } from '../data/saved-view'
import { RemoteOCRModeConfig } from '../data/paperless-config'
import {
HideableSidebarItemID,
SETTINGS_KEYS,
UiSettings,
} from '../data/ui-settings'
import { SETTINGS_KEYS, UiSettings } from '../data/ui-settings'
import { PermissionsService } from './permissions.service'
import { CustomFieldsService } from './rest/custom-fields.service'
import { SettingsService } from './settings.service'
@@ -234,35 +230,6 @@ describe('SettingsService', () => {
expect(notesEnabled()).toBeFalsy()
})
it('updates sidebar item visibility', () => {
httpTestingController
.expectOne(`${environment.apiBaseUrl}ui_settings/`)
.flush(ui_settings)
expect(
settingsService.sidebarItemIsHidden(HideableSidebarItemID.Workflows)
).toBe(false)
settingsService.updateSidebarItemVisibility(
HideableSidebarItemID.Workflows,
false
)
expect(
settingsService.sidebarItemIsHidden(HideableSidebarItemID.Workflows)
).toBe(true)
expect(settingsService.get(SETTINGS_KEYS.SIDEBAR_HIDDEN_ITEMS)).toEqual([])
settingsService.updateSidebarItemVisibility(
HideableSidebarItemID.Workflows,
true
)
expect(
settingsService.sidebarItemIsHidden(HideableSidebarItemID.Workflows)
).toBe(false)
})
it('updates setting signals when settings are reinitialized', () => {
let req = httpTestingController.expectOne(
`${environment.apiBaseUrl}ui_settings/`
@@ -24,7 +24,6 @@ import { DEFAULT_DISPLAY_FIELDS, DisplayField } from '../data/document'
import { RemoteOCRModeConfig } from '../data/paperless-config'
import { SavedView } from '../data/saved-view'
import {
HideableSidebarItemID,
PAPERLESS_GREEN_HEX,
SETTINGS,
SETTINGS_KEYS,
@@ -314,18 +313,6 @@ export class SettingsService {
readonly globalDropzoneEnabled = signal(true)
readonly globalDropzoneActive = signal(false)
readonly organizingSidebarSavedViews = signal(false)
readonly sidebarHiddenItemsEditing = signal<HideableSidebarItemID[] | null>(
null
)
readonly organizingSidebarItems = computed(
() => this.sidebarHiddenItemsEditing() !== null
)
readonly sidebarHiddenItemsEditingChanged = new EventEmitter<
HideableSidebarItemID[]
>()
readonly hiddenSidebarItems = this.getSignal<HideableSidebarItemID[]>(
SETTINGS_KEYS.SIDEBAR_HIDDEN_ITEMS
)
readonly allDisplayFields = signal<Array<{ id: DisplayField; name: string }>>(
DEFAULT_DISPLAY_FIELDS
@@ -762,29 +749,6 @@ export class SettingsService {
return this.storeSettings()
}
sidebarItemIsHidden(item: HideableSidebarItemID): boolean {
return (
this.sidebarHiddenItemsEditing() ?? this.hiddenSidebarItems()
).includes(item)
}
updateSidebarItemVisibility(
item: HideableSidebarItemID,
visible: boolean
): void {
const hiddenItems = new Set(
this.sidebarHiddenItemsEditing() ?? this.hiddenSidebarItems()
)
if (visible) {
hiddenItems.delete(item)
} else {
hiddenItems.add(item)
}
const updatedHiddenItems = [...hiddenItems]
this.sidebarHiddenItemsEditing.set(updatedHiddenItems)
this.sidebarHiddenItemsEditingChanged.emit(updatedHiddenItems)
}
updateSavedViewsVisibility(
dashboardVisibleViewIds: number[],
sidebarVisibleViewIds: number[]
-1
View File
@@ -28,7 +28,6 @@ class DocumentsConfig(AppConfig):
document_consumption_finished.connect(set_storage_path)
document_consumption_finished.connect(add_to_index)
document_consumption_finished.connect(run_workflows_added)
document_consumption_finished.connect(add_to_index)
document_consumption_finished.connect(add_or_update_document_in_llm_index)
document_updated.connect(run_workflows_updated)
document_updated.connect(send_websocket_document_updated)
+40 -49
View File
@@ -2,7 +2,6 @@ from __future__ import annotations
import logging
import tempfile
import uuid
from pathlib import Path
from typing import TYPE_CHECKING
from typing import Literal
@@ -28,7 +27,7 @@ from documents.models import DocumentType
from documents.models import PaperlessTask
from documents.models import StoragePath
from documents.models import Tag
from documents.permissions import set_permissions_for_objects
from documents.permissions import set_permissions_for_object
from documents.plugins.helpers import DocumentsStatusManager
from documents.tasks import bulk_update_documents
from documents.tasks import consume_file
@@ -299,55 +298,53 @@ def modify_custom_fields(
) -> Literal["OK"]:
qs = Document.objects.filter(id__in=doc_ids).only("pk")
affected_docs = list(qs.values_list("pk", flat=True))
# Ensure add_custom_fields is a list of (int, value) tuples, supports old API
# Ensure add_custom_fields is a list of tuples, supports old API
add_custom_fields = (
[(int(field), value) for field, value in add_custom_fields.items()]
add_custom_fields.items()
if isinstance(add_custom_fields, dict)
else [(int(field), None) for field in add_custom_fields]
else [(field, None) for field in add_custom_fields]
)
# Resolved once, instead of re-querying the same field for every document
custom_fields_by_id: dict[int, CustomField] = CustomField.objects.in_bulk(
[field_id for field_id, _ in add_custom_fields],
)
# Passed to update_or_create() below rather than a bare id, so the FK is
# cached on the created instance and auditlog's post_save receiver does
# not reload it per row. Only needed for additions. content is deferred:
# the one field here that is both large and unused.
docs_by_id: dict[int, Document] = (
Document.objects.defer("content").in_bulk(affected_docs)
if add_custom_fields
else {}
)
custom_fields = CustomField.objects.filter(
id__in=[int(field) for field, _ in add_custom_fields],
).distinct()
for field_id, value in add_custom_fields:
custom_field = custom_fields_by_id[field_id]
value_field = CustomFieldInstance.TYPE_TO_DATA_STORE_NAME_MAP[
custom_field.data_type
]
is_doclink = custom_field.data_type == CustomField.FieldDataType.DOCUMENTLINK
for doc_id in affected_docs:
if is_doclink and value and doc_id in value:
# Prevent self-linking
continue
defaults = {}
custom_field = custom_fields.get(id=field_id)
if custom_field:
value_field = CustomFieldInstance.TYPE_TO_DATA_STORE_NAME_MAP[
custom_field.data_type
]
defaults[value_field] = value
if (
custom_field.data_type == CustomField.FieldDataType.DOCUMENTLINK
and value
and doc_id in value
):
# Prevent self-linking
continue
CustomFieldInstance.objects.update_or_create(
document=docs_by_id[doc_id],
field=custom_field,
defaults={value_field: value},
document_id=doc_id,
field_id=field_id,
defaults=defaults,
)
if is_doclink:
reflect_doclinks(docs_by_id[doc_id], custom_field, value)
if custom_field.data_type == CustomField.FieldDataType.DOCUMENTLINK:
doc = Document.objects.get(id=doc_id)
reflect_doclinks(doc, custom_field, value)
# For doc link fields that are being removed, remove symmetrical links.
# select_related avoids a per-instance reload of the document and field.
# For doc link fields that are being removed, remove symmetrical links
for doclink_being_removed_instance in CustomFieldInstance.objects.filter(
document_id__in=affected_docs,
field__id__in=remove_custom_fields,
field__data_type=CustomField.FieldDataType.DOCUMENTLINK,
value_document_ids__isnull=False,
).select_related("field", "document"):
):
for target_doc_id in doclink_being_removed_instance.value:
remove_doclink(
document=doclink_being_removed_instance.document,
document=Document.objects.get(
id=doclink_being_removed_instance.document.id,
),
field=doclink_being_removed_instance.field,
target_doc_id=target_doc_id,
)
@@ -382,7 +379,7 @@ def delete(doc_ids: list[int]) -> Literal["OK"]:
)
delete_ids = list({*doc_ids, *version_ids})
Document.objects.filter(id__in=delete_ids).delete(transaction_id=uuid.uuid4())
Document.objects.filter(id__in=delete_ids).delete()
from documents.search import get_backend
@@ -433,13 +430,10 @@ def set_permissions(
else:
qs.update(owner=owner)
for doc in qs:
set_permissions_for_object(permissions=set_permissions, object=doc, merge=merge)
affected_docs = list(qs.values_list("pk", flat=True))
set_permissions_for_objects(
permissions=set_permissions,
model=Document,
pks=affected_docs,
merge=merge,
)
bulk_update_documents.apply_async(
kwargs={"document_ids": affected_docs},
@@ -1183,13 +1177,10 @@ def remove_doclink(
"""
Removes a 'symmetrical' link to `document` from the target document's existing custom field instance
"""
# select_related: a signal receiver (auditlog) touches .document/.field on
# the save() below, without this that is a per-call reload query
target_doc_field_instance = (
CustomFieldInstance.objects.filter(document_id=target_doc_id, field=field)
.select_related("document", "field")
.first()
)
target_doc_field_instance = CustomFieldInstance.objects.filter(
document_id=target_doc_id,
field=field,
).first()
if (
target_doc_field_instance is not None
and document.id in target_doc_field_instance.value
+28 -66
View File
@@ -34,27 +34,6 @@ from paperless.signed_pickle import signed_pickle_loads
logger = logging.getLogger("paperless.classifier")
def _predict_with_threshold(classifier, X, threshold: float) -> int | None:
"""
Return the predicted class id, or None if:
- the prediction is -1 (no match), or
- the winning class probability is below the configured threshold.
Using predict_proba() instead of predict() lets us apply a minimum-confidence
cutoff so that uncertain predictions are discarded rather than assigned.
"""
probas = classifier.predict_proba(X)[0]
best_idx = int(probas.argmax())
best_class = int(classifier.classes_[best_idx])
if best_class == -1:
return None
if threshold > 0.0 and probas[best_idx] < threshold:
return None
return best_class
ADVANCED_TEXT_PROCESSING_ENABLED = (
settings.NLTK_LANGUAGE is not None and settings.NLTK_ENABLED
)
@@ -123,8 +102,7 @@ class DocumentClassifier:
# v8 - Added storage path classifier
# v9 - Changed from hashing to time/ids for re-train check
# v10 - HMAC-signed model file
# v11 - Use sample_weight for balanced training; predict_proba with threshold
FORMAT_VERSION = 11
FORMAT_VERSION = 10
HMAC_SIZE = 32 # SHA-256 digest length
@@ -346,13 +324,6 @@ class DocumentClassifier:
from sklearn.preprocessing import LabelBinarizer
from sklearn.preprocessing import MultiLabelBinarizer
# MLPClassifier does not support class_weight directly
# (https://github.com/scikit-learn/scikit-learn/issues/9113), so we use
# compute_sample_weight to balance classes during training and prevent
# over-represented correspondents from dominating predictions.
# https://scikit-learn.org/stable/modules/generated/sklearn.utils.class_weight.compute_sample_weight.html
from sklearn.utils.class_weight import compute_sample_weight
# Step 2: vectorize data
logger.debug("Vectorizing data...")
notify("Vectorizing document content...")
@@ -398,7 +369,7 @@ class DocumentClassifier:
self.tags_binarizer = MultiLabelBinarizer()
labels_tags_vectorized = self.tags_binarizer.fit_transform(labels_tags)
self.tags_classifier = MLPClassifier(tol=0.01, random_state=0)
self.tags_classifier = MLPClassifier(tol=0.01)
self.tags_classifier.fit(data_vectorized, labels_tags_vectorized)
else:
self.tags_classifier = None
@@ -409,12 +380,8 @@ class DocumentClassifier:
notify(
f"Training correspondent classifier ({num_correspondents} correspondent(s))...",
)
self.correspondent_classifier = MLPClassifier(tol=0.01, random_state=0)
self.correspondent_classifier.fit(
data_vectorized,
labels_correspondent,
sample_weight=compute_sample_weight("balanced", labels_correspondent),
)
self.correspondent_classifier = MLPClassifier(tol=0.01)
self.correspondent_classifier.fit(data_vectorized, labels_correspondent)
else:
self.correspondent_classifier = None
logger.debug(
@@ -426,12 +393,8 @@ class DocumentClassifier:
notify(
f"Training document type classifier ({num_document_types} type(s))...",
)
self.document_type_classifier = MLPClassifier(tol=0.01, random_state=0)
self.document_type_classifier.fit(
data_vectorized,
labels_document_type,
sample_weight=compute_sample_weight("balanced", labels_document_type),
)
self.document_type_classifier = MLPClassifier(tol=0.01)
self.document_type_classifier.fit(data_vectorized, labels_document_type)
else:
self.document_type_classifier = None
logger.debug(
@@ -443,11 +406,10 @@ class DocumentClassifier:
"Training storage paths classifier...",
)
notify(f"Training storage path classifier ({num_storage_paths} path(s))...")
self.storage_path_classifier = MLPClassifier(tol=0.01, random_state=0)
self.storage_path_classifier = MLPClassifier(tol=0.01)
self.storage_path_classifier.fit(
data_vectorized,
labels_storage_path,
sample_weight=compute_sample_weight("balanced", labels_storage_path),
)
else:
self.storage_path_classifier = None
@@ -584,24 +546,24 @@ class DocumentClassifier:
def predict_correspondent(self, content: str) -> int | None:
if self.correspondent_classifier:
X = self._vectorize(content)
predicted_id = _predict_with_threshold(
self.correspondent_classifier,
X,
settings.CLASSIFIER_MATCH_THRESHOLD,
)
return predicted_id
return None
correspondent_id = self.correspondent_classifier.predict(X)
if correspondent_id != -1:
return correspondent_id
else:
return None
else:
return None
def predict_document_type(self, content: str) -> int | None:
if self.document_type_classifier:
X = self._vectorize(content)
predicted_id = _predict_with_threshold(
self.document_type_classifier,
X,
settings.CLASSIFIER_MATCH_THRESHOLD,
)
return predicted_id
return None
document_type_id = self.document_type_classifier.predict(X)
if document_type_id != -1:
return document_type_id
else:
return None
else:
return None
def predict_tags(self, content: str) -> list[int]:
from sklearn.utils.multiclass import type_of_target
@@ -627,10 +589,10 @@ class DocumentClassifier:
def predict_storage_path(self, content: str) -> int | None:
if self.storage_path_classifier:
X = self._vectorize(content)
predicted_id = _predict_with_threshold(
self.storage_path_classifier,
X,
settings.CLASSIFIER_MATCH_THRESHOLD,
)
return predicted_id
return None
storage_path_id = self.storage_path_classifier.predict(X)
if storage_path_id != -1:
return storage_path_id
else:
return None
else:
return None
@@ -156,15 +156,6 @@ class FileStabilityTracker:
logger.debug(f"File disappeared during stability check: {path}")
continue
# Stable, but empty: some scanners create a zero byte placeholder
# and only write the page some time later. Consuming it now can
# only fail so drop it and let the writer's next event
# (or the periodic rescan) bring it back once it has content
if not tracked.last_size:
to_remove.append(path)
logger.debug("Ignoring stable but empty file: %s", path)
continue
# File is stable, we can return it
to_yield.append(path)
logger.info(f"File is stable: {path}")
+2 -24
View File
@@ -1,5 +1,4 @@
import datetime
import uuid
from pathlib import Path
from typing import Final
@@ -375,7 +374,6 @@ class Document(SoftDeleteModel, ModelWithOwner): # type: ignore[django-manager-
If the queryset already annotated ``effective_content``, that value is used.
"""
# Here to avoid circular import
from documents.versioning import LATEST_VERSION_CONTENT_PREFETCH_ATTR
from documents.versioning import sort_versions_newest_first
from documents.versioning import versions_newest_first
@@ -385,19 +383,6 @@ class Document(SoftDeleteModel, ModelWithOwner): # type: ignore[django-manager-
if self.root_document_id is not None or self.pk is None:
return self.content
latest_version_prefetch = getattr(
self,
LATEST_VERSION_CONTENT_PREFETCH_ATTR,
None,
)
if latest_version_prefetch is not None:
# Empty list means prefetch ran and found no versions — use own content.
return (
latest_version_prefetch[0].content
if latest_version_prefetch
else self.content
)
prefetched_cache = getattr(self, "_prefetched_objects_cache", None)
prefetched_versions = (
prefetched_cache.get("versions")
@@ -529,20 +514,13 @@ class Document(SoftDeleteModel, ModelWithOwner): # type: ignore[django-manager-
def delete(
self,
*args,
transaction_id=None,
**kwargs,
):
# Versions must share the root's transaction ID so they are restored
# together by django-softdelete.
if transaction_id is None:
transaction_id = uuid.uuid4()
# If deleting a root document, move all its versions to trash as well.
if self.root_document_id is None:
Document.objects.filter(root_document=self).delete(
transaction_id=transaction_id,
)
Document.objects.filter(root_document=self).delete()
return super().delete(
*args,
transaction_id=transaction_id,
**kwargs,
)
-173
View File
@@ -173,179 +173,6 @@ def set_permissions_for_object(
)
def _resolve_permissions(codenames: set[str], ctype: ContentType) -> list[Permission]:
"""
Resolves `codenames` to Permission rows, raising like the single-object
assign_perm() this bulk path replaces does (via a `.get()` internally)
if any codename doesn't exist -- e.g. a client-supplied action name that
was never validated (BulkEditObjectsSerializer._validate_permissions
calls validate_set_permissions() only for its side-effecting id checks
and discards the filtered dict it returns, so an unrecognized action key
reaches this function as-is). A plain `.filter()` with no existence
check would otherwise silently build zero rows and no-op instead of
reporting the bad input.
"""
permission_objs = list(
Permission.objects.filter(content_type=ctype, codename__in=codenames),
)
missing = codenames - {p.codename for p in permission_objs}
if missing:
raise Permission.DoesNotExist(
f"Permission matching query does not exist for codename(s): "
f"{', '.join(sorted(missing))}",
)
return permission_objs
def _apply_bulk_permission_entry(
*,
perm_model: type[UserObjectPermission] | type[GroupObjectPermission],
identity_model: type[User] | type[Group],
identity_field: str,
ids: list[int],
codename: str,
permission_objs: list[Permission],
ctype: ContentType,
object_pks: list[str],
merge: bool,
) -> None:
# Only the ids are needed to build permission rows (via `<field>_id=`),
# so avoid fetching full User/Group rows for identities that may not
# even end up being granted anything new.
add_ids = set(
identity_model.objects.filter(id__in=ids).values_list("id", flat=True),
)
if not merge:
existing_ids = set(
perm_model.objects.filter(
content_type=ctype,
object_pk__in=object_pks,
permission__codename=codename,
)
.values_list(f"{identity_field}_id", flat=True)
.distinct(),
)
remove_ids = existing_ids - add_ids
if remove_ids:
perm_model.objects.filter(
content_type=ctype,
object_pk__in=object_pks,
permission__codename=codename,
**{f"{identity_field}_id__in": remove_ids},
).delete()
if not add_ids:
return
rows = [
perm_model(
content_type=ctype,
object_pk=pk,
permission=permission_obj,
**{f"{identity_field}_id": identity_id},
)
for permission_obj in permission_objs
for pk in object_pks
for identity_id in add_ids
]
# ignore_conflicts skips only rows that already exist as an exact
# (identity, permission, object) match -- the same de-dup the
# underlying (user|group, permission, object_pk) unique constraint
# already enforces for the single-object assign_perm() this replaces,
# so it doesn't change what counts as "already granted". batch_size
# caps how many rows go into a single INSERT statement.
perm_model.objects.bulk_create(rows, ignore_conflicts=True, batch_size=1000)
def set_permissions_for_objects(
permissions: dict,
model: type[Model],
pks: QuerySet | list,
*,
merge: bool = False,
) -> None:
"""
Bulk equivalent of set_permissions_for_object: applies the same
permission changes to every object identified by `pks` at once.
Takes a model + pks (rather than model instances) deliberately -- the
permission rows built below only ever need `pk`, `content_type`, and
identity ids, so callers shouldn't have to fetch full rows (with every
other field) just to hand them to this function.
Deliberately does not use guardian's queryset/list-aware assign_perm:
passing a list as the object routes to bulk_assign_perm, which skips
creating a direct permission row for anyone who already has the
permission via ANY group membership (it checks
ObjectPermissionChecker.has_perm, which is group-inheritance-aware) --
unlike the single-object assign_perm this replaces, which always
ensures a direct row via get_or_create regardless of group-derived
access. Losing that guarantee would mean a later revocation of the
group's grant silently strips access an admin explicitly asked to be
direct. Bulk-creating rows straight against the permission models
instead (see _apply_bulk_permission_entry) preserves the original
always-create-a-direct-row semantics while still batching every object
and every identity into one query per action, rather than one query per
(object, user) pair.
"""
object_pks = [str(pk) for pk in pks]
if not object_pks: # pragma: no cover
return
model_name = model.__name__.lower()
ctype = ContentType.objects.get_for_model(model)
# Every action is resolved up front, before anything is written, so an
# unrecognized action name (see _resolve_permissions) aborts the whole
# call instead of leaving the actions ahead of it already applied --
# BulkEditObjectsSerializer lets unknown keys through and its view turns
# the exception into a 400, so a half-applied change would otherwise be
# reported to the client as a failure.
permissions_by_action: dict[str, list[Permission]] = {}
for action, entry in permissions.items():
if "users" not in entry and "groups" not in entry:
continue
implied_codenames = {f"{action}_{model_name}"}
if action == "change":
# change gives view too
implied_codenames.add(f"view_{model_name}")
permissions_by_action[action] = _resolve_permissions(
implied_codenames,
ctype,
)
for action, entry in permissions.items():
codename = f"{action}_{model_name}"
permission_objs = permissions_by_action.get(action, [])
if "users" in entry:
_apply_bulk_permission_entry(
perm_model=UserObjectPermission,
identity_model=User,
identity_field="user",
ids=entry["users"],
codename=codename,
permission_objs=permission_objs,
ctype=ctype,
object_pks=object_pks,
merge=merge,
)
if "groups" in entry:
_apply_bulk_permission_entry(
perm_model=GroupObjectPermission,
identity_model=Group,
identity_field="group",
ids=entry["groups"],
codename=codename,
permission_objs=permission_objs,
ctype=ctype,
object_pks=object_pks,
merge=merge,
)
def permitted_object_ids(
user: User | None,
model: type[Model],
+24 -32
View File
@@ -89,7 +89,6 @@ from documents.templating.utils import convert_format_str_to_template_format
from documents.templating.workflows import validate_workflow_template
from documents.validators import uri_validator
from documents.validators import url_validator
from documents.versioning import has_prefetched_effective_content
from documents.versioning import sort_versions_newest_first
if TYPE_CHECKING:
@@ -1153,14 +1152,8 @@ class DocumentSerializer(
def to_representation(self, instance):
doc = super().to_representation(instance)
if "content" in self.fields and has_prefetched_effective_content(instance):
# Only resolve version-aware content when it's cheap: an SQL
# annotation or a versions prefetch is already on the instance.
# A caller that set up neither (e.g. TrashView, GlobalSearchView,
# which build their own querysets) gets the document's own,
# unresolved content instead of paying for an extra per-instance
# query -- same as before effective_content resolution existed.
doc["content"] = instance.get_effective_content() or ""
if "content" in self.fields and hasattr(instance, "effective_content"):
doc["content"] = getattr(instance, "effective_content") or ""
if self.truncate_content and "content" in self.fields:
doc["content"] = doc.get("content")[0:550]
return doc
@@ -1254,31 +1247,30 @@ class DocumentSerializer(
validated_data["tags"] = list(final_tags)
if validated_data.get("remove_inbox_tags"):
current_tag_ids = {t.pk for t in instance.tags.all()}
tags = (
validated_data["tags"]
tag_ids_being_added = (
[
tag.id
for tag in validated_data["tags"]
if tag not in instance.tags.all()
]
if "tags" in validated_data
else list(instance.tags.all())
else []
)
# Tags newly added in this update, plus their ancestors, are kept
keep_ids: set[int] = set()
for tag in tags:
if tag.pk not in current_tag_ids:
keep_ids.add(tag.pk)
keep_ids.update(int(pk) for pk in tag.get_ancestors_pks())
# Remove inbox tags and their descendants, except those being kept
remove_ids: set[int] = set()
for inbox_tag in (
Tag.objects.filter(is_inbox_tag=True)
.exclude(pk__in=keep_ids)
.only("pk", "tn_descendants_pks")
):
remove_ids.add(inbox_tag.pk)
remove_ids.update(int(pk) for pk in inbox_tag.get_descendants_pks())
validated_data["tags"] = [t for t in tags if t.pk not in remove_ids]
inbox_tags_not_being_added = Tag.objects.filter(is_inbox_tag=True).exclude(
id__in=tag_ids_being_added,
)
if "tags" in validated_data:
validated_data["tags"] = [
tag
for tag in validated_data["tags"]
if tag not in inbox_tags_not_being_added
]
else:
validated_data["tags"] = [
tag
for tag in instance.tags.all()
if tag not in inbox_tags_not_being_added
]
if settings.AUDIT_LOG_ENABLED:
with set_actor(self.user):
-36
View File
@@ -38,42 +38,6 @@ class TestChatStreamingViewInputValidation(APITestCase):
)
assert resp.status_code == status.HTTP_400_BAD_REQUEST
def test_answer_is_not_compressed(self) -> None:
"""
GIVEN:
- A client that accepts compressed responses
WHEN:
- It asks the chat endpoint a question
THEN:
- The answer is streamed unencoded, chunk for chunk
The stream compressors buffer, so a compressed answer arrives in one
piece. The view cannot opt out by flagging the request: DRF's request
wrapper proxies reads but keeps writes to itself, so the flag never
reaches the Django request the middleware sees.
"""
chunks = [f"token{i} " for i in range(40)]
with (
mock.patch(
"documents.views.AIConfig",
return_value=self._mock_ai_enabled(),
),
mock.patch(
"documents.views.stream_chat_with_documents",
return_value=iter(chunks),
),
):
resp = self.client.post(
"/api/documents/chat/",
{"q": "What is in my archive?"},
format="json",
HTTP_ACCEPT_ENCODING="gzip, deflate, br, zstd",
)
assert resp.status_code == status.HTTP_200_OK
assert not resp.has_header("Content-Encoding")
assert list(resp.streaming_content) == [c.encode() for c in chunks]
def test_missing_question_is_rejected(self) -> None:
with mock.patch(
"documents.views.AIConfig",
-65
View File
@@ -2,15 +2,10 @@ import datetime
import json
from unittest import mock
from django.contrib.auth.models import Group
from django.contrib.auth.models import Permission
from django.contrib.auth.models import User
from django.db import connection
from django.test import override_settings
from django.test.utils import CaptureQueriesContext
from guardian.shortcuts import assign_perm
from guardian.shortcuts import get_groups_with_perms
from guardian.shortcuts import get_users_with_perms
from rest_framework import status
from rest_framework.test import APITestCase
@@ -847,66 +842,6 @@ class TestBulkEditObjects(APITestCase):
self.assertEqual(response.status_code, status.HTTP_200_OK)
self.assertEqual(StoragePath.objects.count(), 0)
def test_bulk_objects_set_permissions_batched_across_object_count(
self,
) -> None:
"""
GIVEN:
- Many tags are being bulk-edited to set permissions at once
WHEN:
- bulk_edit_objects API endpoint is called with set_permissions
operation over a small batch vs. a much larger one
THEN:
- Permissions are applied correctly at both scales
- Query count does not grow with the number of tags, i.e. each
user/group is applied across all tags with one batched call
rather than one call per (tag, identity) pair
"""
group1 = Group.objects.create(name="perm-group")
permissions = {
"view": {"users": [self.user1.id, self.user2.id], "groups": [group1.id]},
"change": {"users": [self.user1.id], "groups": [group1.id]},
}
def run_with_n_tags(n: int) -> int:
tags = [Tag.objects.create(name=f"perm-tag-{n}-{i}") for i in range(n)]
with CaptureQueriesContext(connection) as ctx:
response = self.client.post(
"/api/bulk_edit_objects/",
json.dumps(
{
"objects": [t.id for t in tags],
"object_type": "tags",
"operation": "set_permissions",
"permissions": permissions,
"merge": False,
},
),
content_type="application/json",
)
self.assertEqual(response.status_code, status.HTTP_200_OK)
for tag in tags:
self.assertEqual(get_users_with_perms(tag).count(), 2)
self.assertEqual(get_groups_with_perms(tag).count(), 1)
return len(ctx.captured_queries)
small_batch_queries = run_with_n_tags(5)
large_batch_queries = run_with_n_tags(50)
# A tolerance rather than equality, matching the N+1 check in
# test_views.py: bulk_create's batch_size caps rows per INSERT, so a
# large enough selection does legitimately add statements, and the
# per-process ContentType cache makes the first run carry an extra
# query. Neither can hide a regression to per-object assignment,
# which would be ~10x the small-batch count here.
self.assertLessEqual(
large_batch_queries,
small_batch_queries + 5,
"Permission assignment appears to scale with object count: "
f"{small_batch_queries} queries for 5 tags vs. "
f"{large_batch_queries} for 50",
)
def test_bulk_objects_delete_all_filtered(self) -> None:
"""
GIVEN:
-62
View File
@@ -207,65 +207,3 @@ class TestTrashAPI(DirectoriesMixin, APITestCase):
)
self.assertEqual(resp.status_code, status.HTTP_400_BAD_REQUEST)
self.assertIn("have not yet been deleted", resp.data["documents"][0])
def _make_versioned_document(self) -> tuple[Document, list[Document]]:
root = Document.objects.create(
title="root",
content="root-content",
checksum="root",
mime_type="application/pdf",
)
versions = [
Document.objects.create(
title=f"v{index}",
content=f"v{index}-content",
checksum=f"v{index}",
mime_type="application/pdf",
root_document=root,
version_index=index,
)
for index in range(1, 3)
]
return root, versions
def test_api_trash_restore_document_restores_its_versions(self) -> None:
"""
GIVEN:
- Existing document with two versions
WHEN:
- API request to delete the document
- API request to restore it from the trash
THEN:
- Only the document itself is listed in the trash
- A version cannot be restored without its root
- The document is restored together with all of its versions
"""
root, versions = self._make_versioned_document()
self.client.force_login(user=self.user)
self.client.delete(f"/api/documents/{root.pk}/")
self.assertEqual(Document.deleted_objects.count(), 3)
resp = self.client.get("/api/trash/")
self.assertEqual(resp.status_code, status.HTTP_200_OK)
self.assertEqual(resp.data["count"], 1)
self.assertEqual(resp.data["results"][0]["id"], root.pk)
# A version cannot be restored while its root remains in the trash.
resp = self.client.post(
"/api/trash/",
{"action": "restore", "documents": [versions[0].pk]},
)
self.assertEqual(resp.status_code, status.HTTP_400_BAD_REQUEST)
self.assertIn("Restore the root document", resp.data["documents"][0])
resp = self.client.post(
"/api/trash/",
{"action": "restore", "documents": [root.pk]},
)
self.assertEqual(resp.status_code, status.HTTP_200_OK)
self.assertEqual(Document.deleted_objects.count(), 0)
self.assertCountEqual(
Document.objects.filter(root_document=root).values_list("id", flat=True),
[version.pk for version in versions],
)
-181
View File
@@ -5,11 +5,8 @@ from unittest import mock
import pikepdf
from django.contrib.auth.models import Group
from django.contrib.auth.models import Permission
from django.contrib.auth.models import User
from django.db import connection
from django.test import TestCase
from django.test.utils import CaptureQueriesContext
from guardian.shortcuts import assign_perm
from guardian.shortcuts import get_groups_with_perms
from guardian.shortcuts import get_users_with_perms
@@ -22,7 +19,6 @@ from documents.models import Document
from documents.models import DocumentType
from documents.models import StoragePath
from documents.models import Tag
from documents.permissions import set_permissions_for_objects
from documents.tests.utils import DirectoriesMixin
@@ -396,11 +392,6 @@ class TestBulkEdit(DirectoriesMixin, TestCase):
self.assertFalse(Document.objects.filter(id=self.doc1.id).exists())
self.assertFalse(Document.objects.filter(id=version.id).exists())
Document.deleted_objects.get(id=self.doc1.id).restore(strict=False)
self.assertTrue(Document.objects.filter(id=self.doc1.id).exists())
self.assertTrue(Document.objects.filter(id=version.id).exists())
def test_delete_version_document_keeps_root(self) -> None:
version = Document.objects.create(
checksum="A-v1",
@@ -519,178 +510,6 @@ class TestBulkEdit(DirectoriesMixin, TestCase):
)
self.assertEqual(groups_with_perms.count(), 2)
@mock.patch("documents.tasks.bulk_update_documents.apply_async")
def test_set_permissions_batched_across_document_count(
self,
m,
) -> None:
"""
GIVEN:
- Many documents are being bulk-edited to set permissions at once
WHEN:
- set_permissions runs over a small batch vs. a much larger one
THEN:
- Permissions are applied correctly at both scales
- Query count does not grow with the number of documents, i.e.
each user/group is applied across all documents with one
batched call rather than one call per (document, identity)
pair
"""
permissions = {
"view": {
"users": [self.user1.id, self.user2.id],
"groups": [self.group2.id],
},
"change": {
"users": [self.user1.id],
"groups": [self.group2.id],
},
}
def run_with_n_documents(n: int) -> int:
docs = [
Document.objects.create(checksum=f"perm-{n}-{i}", title=f"perm-{n}-{i}")
for i in range(n)
]
with CaptureQueriesContext(connection) as ctx:
bulk_edit.set_permissions(
[doc.id for doc in docs],
set_permissions=permissions,
owner=self.owner,
merge=False,
)
for doc in docs:
self.assertEqual(get_users_with_perms(doc).count(), 2)
self.assertEqual(get_groups_with_perms(doc).count(), 1)
return len(ctx.captured_queries)
small_batch_queries = run_with_n_documents(5)
large_batch_queries = run_with_n_documents(50)
# A tolerance rather than equality, matching the N+1 check in
# test_views.py: bulk_create's batch_size caps rows per INSERT, so a
# large enough selection does legitimately add statements, and the
# per-process ContentType cache makes the first run carry an extra
# query. Neither can hide a regression to per-document assignment,
# which would be ~10x the small-batch count here.
self.assertLessEqual(
large_batch_queries,
small_batch_queries + 5,
"Permission assignment appears to scale with document count: "
f"{small_batch_queries} queries for 5 documents vs. "
f"{large_batch_queries} for 50",
)
@mock.patch("documents.tasks.bulk_update_documents.apply_async")
def test_set_permissions_grants_direct_perm_even_if_already_granted_via_group(
self,
m,
) -> None:
"""
GIVEN:
- A user already has view access to a document via group
membership, with no direct grant of their own
WHEN:
- set_permissions explicitly grants that same user direct view
access via bulk_edit
THEN:
- A direct permission grant is created for the user, not skipped
because they already have equivalent access via the group
Regression test: guardian's queryset-aware assign_perm() (routed to
when the target is a list/queryset) skips creating a direct row for
anyone whose ObjectPermissionChecker.has_perm() already returns True
-- which includes group-derived access. The single-object assign_perm
this bulk path replaces has no such check; it always ensures a
direct row via get_or_create. Losing that guarantee would mean
revoking the group's grant later silently strips access that was
supposed to be explicit.
"""
self.doc1.owner = self.user1
self.doc1.save()
self.user1.groups.add(self.group1)
assign_perm("view_document", self.group1, self.doc1)
bulk_edit.set_permissions(
[self.doc1.id],
set_permissions={
"view": {"users": [self.user1.id], "groups": []},
},
merge=True,
)
direct_users = get_users_with_perms(
self.doc1,
only_with_perms_in=["view_document"],
with_group_users=False,
)
self.assertIn(self.user1, direct_users)
def test_set_permissions_for_objects_raises_for_unknown_action(self) -> None:
"""
GIVEN:
- An unrecognized permission action name with users to grant it
to
WHEN:
- set_permissions_for_objects is called
THEN:
- Permission.DoesNotExist is raised, not a silent no-op
Regression test: the endpoint that calls this
(BulkEditObjectPermissionsView) never actually validates action
names against the raw client-supplied permissions dict --
BulkEditObjectsSerializer._validate_permissions calls
validate_set_permissions() only for its side-effecting user/group id
checks and discards the filtered dict it returns -- so a bogus
action key reaches this function as-is. Resolving the Permission via
a bare `.filter()` (which returns empty instead of raising) would
silently drop the grant and report success.
"""
with self.assertRaises(Permission.DoesNotExist):
set_permissions_for_objects(
{"not_a_real_action": {"users": [self.user1.id], "groups": []}},
Document,
[self.doc1.pk],
)
def test_set_permissions_for_objects_unknown_action_applies_nothing(
self,
) -> None:
"""
GIVEN:
- A permissions dict with a valid action ordered ahead of an
unrecognized one
WHEN:
- set_permissions_for_objects is called
THEN:
- Permission.DoesNotExist is raised
- The valid action ahead of it is not applied either
Every action is resolved before any row is written, so a bad action
name cannot leave a half-applied change behind. That matters because
BulkEditObjectsView turns this exception into a 400: without the
up-front resolution the client would be told the request failed
while the leading action had already been committed.
"""
with self.assertRaises(Permission.DoesNotExist):
set_permissions_for_objects(
{
"view": {"users": [self.user1.id], "groups": []},
"not_a_real_action": {"users": [self.user1.id], "groups": []},
},
Document,
[self.doc1.pk],
)
self.assertNotIn(
self.user1,
get_users_with_perms(
self.doc1,
only_with_perms_in=["view_document"],
with_group_users=False,
),
)
@mock.patch("documents.models.Document.delete")
def test_delete_documents_old_uuid_field(self, m) -> None:
m.side_effect = Exception("Data too long for column 'transaction_id' at row 1")
-145
View File
@@ -3,7 +3,6 @@ import warnings
from pathlib import Path
from unittest import mock
import numpy as np
import pytest
from django.conf import settings
from django.test import TestCase
@@ -12,7 +11,6 @@ from django.test import override_settings
from documents.classifier import ClassifierModelCorruptError
from documents.classifier import DocumentClassifier
from documents.classifier import IncompatibleClassifierVersionError
from documents.classifier import _predict_with_threshold
from documents.classifier import load_classifier
from documents.models import Correspondent
from documents.models import Document
@@ -627,103 +625,6 @@ class TestClassifier(DirectoriesMixin, TestCase):
self.assertEqual(self.classifier.predict_storage_path(doc1.content), sp.pk)
self.assertIsNone(self.classifier.predict_storage_path(doc2.content))
def test_predict_rejects_prediction_below_match_threshold(self) -> None:
"""
GIVEN:
- Classifiers trained against test data with confident predictions
WHEN:
- CLASSIFIER_MATCH_THRESHOLD exceeds the model's confidence
THEN:
- Every predict_* method discards the match in favor of no match
"""
c1 = Correspondent.objects.create(
name="c1",
matching_algorithm=Correspondent.MATCH_AUTO,
)
dt1 = DocumentType.objects.create(
name="dt1",
matching_algorithm=DocumentType.MATCH_AUTO,
)
sp1 = StoragePath.objects.create(
name="sp1",
matching_algorithm=StoragePath.MATCH_AUTO,
)
doc1 = Document.objects.create(
title="doc1",
content="this is a document from c1",
correspondent=c1,
document_type=dt1,
storage_path=sp1,
checksum="A",
)
Document.objects.create(
title="doc2",
content="this is a document from no one",
checksum="B",
)
self.classifier.train()
predictors = {
"correspondent": self.classifier.predict_correspondent,
"document_type": self.classifier.predict_document_type,
"storage_path": self.classifier.predict_storage_path,
}
# No real prediction can reach a confidence this high, so this
# isolates the threshold check from the model's actual output.
with override_settings(CLASSIFIER_MATCH_THRESHOLD=0.999999):
for name, predict in predictors.items():
with self.subTest(field=name):
self.assertIsNone(predict(doc1.content))
def test_train_uses_balanced_sample_weight(self) -> None:
"""
GIVEN:
- A training set with correspondents, document types and storage paths
WHEN:
- The classifier is trained
THEN:
- Each MLP classifier is fit with balanced sample weights, so that
over-represented classes don't dominate predictions
"""
c1 = Correspondent.objects.create(
name="c1",
matching_algorithm=Correspondent.MATCH_AUTO,
)
dt1 = DocumentType.objects.create(
name="dt1",
matching_algorithm=DocumentType.MATCH_AUTO,
)
sp1 = StoragePath.objects.create(
name="sp1",
matching_algorithm=StoragePath.MATCH_AUTO,
)
Document.objects.create(
title="doc1",
content="this is a document from c1",
correspondent=c1,
document_type=dt1,
storage_path=sp1,
checksum="A",
)
Document.objects.create(
title="doc2",
content="this is a document from no one",
checksum="B",
)
with mock.patch(
"sklearn.utils.class_weight.compute_sample_weight",
return_value=None,
) as mocked_compute_sample_weight:
self.classifier.train()
self.assertEqual(mocked_compute_sample_weight.call_count, 3)
for call in mocked_compute_sample_weight.call_args_list:
self.assertEqual(call.args[0], "balanced")
def test_one_tag_predict(self) -> None:
t1 = Tag.objects.create(name="t1", matching_algorithm=Tag.MATCH_AUTO, pk=12)
@@ -909,52 +810,6 @@ class TestClassifier(DirectoriesMixin, TestCase):
load_classifier(raise_exception=True)
class _StubProbaClassifier:
"""
A fake scikit-learn classifier exposing just enough of the API for
`_predict_with_threshold`: `classes_` and `predict_proba`.
"""
def __init__(self, classes: list[int], probabilities: list[float]) -> None:
self.classes_ = np.array(classes)
self._probabilities = np.array([probabilities])
def predict_proba(self, X) -> np.ndarray:
return self._probabilities
@pytest.mark.parametrize(
("classes", "probabilities", "threshold", "expected"),
[
# confident prediction above the threshold is returned
([-1, 3], [0.1, 0.9], 0.6, 3),
# prediction below the threshold is discarded
([-1, 3], [0.45, 0.55], 0.6, None),
# boundary: exactly at the threshold is accepted, not discarded
([-1, 3], [0.4, 0.6], 0.6, 3),
# the winning class is the "no match" pseudo-class, regardless of its
# own confidence
([-1, 3], [0.99, 0.01], 0.0, None),
# threshold of 0.0 disables the confidence check entirely
([-1, 3], [0.45, 0.55], 0.0, 3),
],
)
def test_predict_with_threshold(classes, probabilities, threshold, expected) -> None:
classifier = _StubProbaClassifier(classes, probabilities)
result = _predict_with_threshold(classifier, X=None, threshold=threshold)
assert result == expected
def test_classifier_match_threshold_default() -> None:
"""
GIVEN:
- No PAPERLESS_CLASSIFIER_MATCH_THRESHOLD environment variable is set
THEN:
- The classifier match threshold defaults to 0.6
"""
assert settings.CLASSIFIER_MATCH_THRESHOLD == 0.6
def test_preprocess_content() -> None:
"""
GIVEN:
@@ -1,457 +0,0 @@
from __future__ import annotations
from types import SimpleNamespace
from typing import TYPE_CHECKING
import pytest
from django.db import connection
from django.test.utils import CaptureQueriesContext
from rest_framework import status
from documents.models import Document
from documents.tests.factories import DocumentFactory
from documents.versioning import LATEST_VERSION_CONTENT_PREFETCH_ATTR
from documents.versioning import has_prefetched_effective_content
from documents.versioning import latest_version_content_prefetch
from documents.views import DocumentViewSet
if TYPE_CHECKING:
from rest_framework.test import APIClient
class TestNeedsEffectiveContentAnnotation:
"""
DocumentViewSet._needs_effective_content_annotation() decides whether
the effective_content correlated subquery is worth attaching to the
queryset at all -- see TestDocumentListEffectiveContentAnnotation below
for why. This only checks that decision's own logic (a plain query-param
membership test), not that Django/DRF's filtering machinery works.
"""
@pytest.mark.parametrize(
("params", "expected"),
[
({}, False),
({"ordering": "-added"}, False),
({"tags__id__in": "1,2"}, False),
({"search": ""}, False),
({"search": " "}, False),
({"content__icontains": ""}, False),
({"search": "foo"}, True),
({"title_content": "foo"}, True),
({"content__istartswith": "foo"}, True),
({"content__iendswith": "foo"}, True),
({"content__icontains": "foo"}, True),
({"content__iexact": "foo"}, True),
],
)
def test_detects_content_filter_params(
self,
params: dict[str, str],
expected: bool, # noqa: FBT001
) -> None:
"""
GIVEN:
- A view bound to a request carrying the given query params
WHEN:
- Checking whether the effective_content annotation is needed
THEN:
- It is needed only for requests that actually filter on it
"""
view = DocumentViewSet()
view.request = SimpleNamespace(query_params=params)
assert view._needs_effective_content_annotation() is expected
class TestNeedsEffectiveContentPrefetch:
"""
DocumentViewSet._needs_effective_content_prefetch() decides whether the
single-version content prefetch is worth attaching. It has to read the
`fields` param exactly the way get_serializer() does, or a request whose
response includes content ends up without the prefetch and pays
get_effective_content()'s per-instance fallback instead.
"""
@pytest.mark.parametrize(
("params", "expected"),
[
pytest.param({}, True, id="no-fields-param-keeps-every-field"),
pytest.param({"fields": ""}, True, id="blank-fields-keeps-every-field"),
pytest.param(
{"fields": "id,content"},
True,
id="content-among-requested-fields",
),
pytest.param({"fields": "content"}, True, id="content-only"),
pytest.param({"fields": "id"}, False, id="content-not-requested"),
pytest.param(
{"fields": "id,title"},
False,
id="several-fields-without-content",
),
],
)
def test_detects_whether_content_can_reach_the_response(
self,
params: dict[str, str],
expected: bool, # noqa: FBT001
) -> None:
"""
GIVEN:
- A view bound to a request carrying the given query params
WHEN:
- Checking whether the content prefetch is needed
THEN:
- It is needed exactly when get_serializer() would emit content,
which treats a blank `fields` the same as an absent one
"""
view = DocumentViewSet()
view.request = SimpleNamespace(query_params=params)
assert view._needs_effective_content_prefetch() is expected
@pytest.mark.django_db
class TestDocumentListEffectiveContentAnnotation:
"""
DocumentViewSet.get_queryset() only attaches the effective_content
correlated subquery when a request actually filters on it. Attaching it
unconditionally re-executes it once per candidate row before the page's
LIMIT is applied -- fine on SQLite/Postgres, but pathological on
MariaDB's default cardinality estimation for the root_document_id
self-join once candidate counts get large (see the root_document_id /
effective_content perf investigation).
"""
def test_list_without_content_filter_skips_annotation_but_returns_latest_content(
self,
admin_client: APIClient,
) -> None:
"""
GIVEN:
- A root document whose latest version has different content
WHEN:
- Listing documents with no search/content-filter param
THEN:
- The response still reflects the latest version's content
- The database never evaluates effective_content per row
"""
root = DocumentFactory(content="old-root-content")
DocumentFactory(
root_document=root,
version_index=1,
content="new-version-content",
)
with CaptureQueriesContext(connection) as ctx:
response = admin_client.get("/api/documents/?fields=id,content")
assert response.status_code == status.HTTP_200_OK
assert response.data["results"] == [
{"id": root.id, "content": "new-version-content"},
]
assert not any(
"effective_content" in query["sql"] for query in ctx.captured_queries
)
@pytest.mark.parametrize(
"fields_param",
[
pytest.param("", id="blank-fields"),
pytest.param("id,content", id="content-requested"),
],
)
def test_content_resolves_without_a_query_per_document(
self,
admin_client: APIClient,
fields_param: str,
) -> None:
"""
GIVEN:
- One versioned root document, then two more
WHEN:
- Listing documents with a `fields` param that keeps content
THEN:
- Every root's content resolves to its latest version's
- The query count does not grow with the number of documents,
i.e. a blank `fields` does not skip the prefetch and fall back
to loading each root's deferred version content
"""
first = DocumentFactory(content="first-root-content")
DocumentFactory(
root_document=first,
version_index=1,
content="first-version-content",
)
with CaptureQueriesContext(connection) as one_document:
response = admin_client.get(f"/api/documents/?fields={fields_param}")
assert response.status_code == status.HTTP_200_OK
assert [r["content"] for r in response.data["results"]] == [
"first-version-content",
]
for index in range(2):
root = DocumentFactory(content=f"root-content-{index}")
DocumentFactory(
root_document=root,
version_index=1,
content=f"version-content-{index}",
)
with CaptureQueriesContext(connection) as three_documents:
response = admin_client.get(f"/api/documents/?fields={fields_param}")
assert response.status_code == status.HTTP_200_OK
assert sorted(r["content"] for r in response.data["results"]) == [
"first-version-content",
"version-content-0",
"version-content-1",
]
assert len(_get_document_queries(three_documents)) == len(
_get_document_queries(one_document),
)
def test_list_without_content_field_skips_prefetch_and_omits_content(
self,
admin_client: APIClient,
) -> None:
"""
GIVEN:
- A versioned root document
WHEN:
- Listing documents without asking for content
THEN:
- Content is neither serialized nor resolved
- Nothing pays for the prefetch or the per-instance fallback
"""
root = DocumentFactory(content="root-content")
DocumentFactory(
root_document=root,
version_index=1,
content="version-content",
)
with CaptureQueriesContext(connection) as ctx:
response = admin_client.get("/api/documents/?fields=id")
assert response.status_code == status.HTTP_200_OK
assert response.data["results"] == [{"id": root.id}]
assert _get_effective_content_fallback_queries(ctx) == []
# Only the list query itself reads a content column: no extra query
# for the skipped prefetch, none for a per-instance fallback
content_queries = [
query
for query in ctx.captured_queries
if '"documents_document"."content"' in query["sql"]
]
assert len(content_queries) == 1
def test_latest_version_content_prefetch_carries_only_the_newest_version(
self,
) -> None:
"""
GIVEN:
- A root document with two versions
WHEN:
- Fetching the root through latest_version_content_prefetch()
THEN:
- The prefetch carries only the single newest version, not every
historical version's content (the whole point of not reusing
the metadata-only "versions" prefetch for this)
"""
root = DocumentFactory(content="root-content")
DocumentFactory(
root_document=root,
version_index=1,
content="older-version-content",
)
DocumentFactory(
root_document=root,
version_index=2,
content="newest-version-content",
)
fetched_root = (
Document.objects.filter(pk=root.pk)
.prefetch_related(
latest_version_content_prefetch(),
)
.get()
)
latest = getattr(fetched_root, LATEST_VERSION_CONTENT_PREFETCH_ATTR)
assert [v.content for v in latest] == ["newest-version-content"]
class TestHasPrefetchedEffectiveContent:
"""
DocumentSerializer.to_representation() only calls get_effective_content()
when has_prefetched_effective_content() says it's cheap -- otherwise a
caller that never set up an annotation or prefetch (TrashView,
GlobalSearchView, which build their own querysets and don't display
content at all) would pay for a per-instance query nobody asked for.
"""
def test_false_with_no_annotation_or_prefetch(self) -> None:
"""
GIVEN:
- A document the ORM never annotated or prefetched for
WHEN:
- Asking whether its effective content is already resolved
THEN:
- It is not, so the serializer must leave it alone
"""
document = DocumentFactory.build()
assert has_prefetched_effective_content(document) is False
def test_true_with_effective_content_annotation(self) -> None:
"""
GIVEN:
- A document carrying the queryset's effective_content annotation
WHEN:
- Asking whether its effective content is already resolved
THEN:
- It is, straight off the annotation
"""
document = DocumentFactory.build()
document.effective_content = "resolved"
assert has_prefetched_effective_content(document) is True
def test_true_with_lean_prefetch_attr_even_when_empty(self) -> None:
"""
GIVEN:
- A document the lean content prefetch ran for, finding no versions
WHEN:
- Asking whether its effective content is already resolved
THEN:
- It is: an empty prefetch is an answer, not a missing one
"""
document = DocumentFactory.build()
setattr(document, LATEST_VERSION_CONTENT_PREFETCH_ATTR, [])
assert has_prefetched_effective_content(document) is True
def test_true_with_metadata_versions_prefetch_cache(self) -> None:
"""
GIVEN:
- A document carrying only the metadata "versions" prefetch
WHEN:
- Asking whether its effective content is already resolved
THEN:
- It is, via get_effective_content()'s prefetch-cache branch
"""
document = DocumentFactory.build()
document._prefetched_objects_cache = {"versions": []}
assert has_prefetched_effective_content(document) is True
def _get_document_queries(
ctx: CaptureQueriesContext,
) -> list[dict[str, str]]:
"""
The queries a list request spends on the documents themselves, i.e.
everything but the one-time django_content_type lookup guardian's
permission filtering makes. That lookup is process-cached, and the
autouse fixture in conftest clears the cache before every test, so it
lands in whichever request happens to run first and never repeats --
counting it makes a request look like it costs one query more than the
identical request after it.
"""
return [q for q in ctx.captured_queries if '"django_content_type"' not in q["sql"]]
def _get_effective_content_fallback_queries(
ctx: CaptureQueriesContext,
) -> list[dict[str, str]]:
"""
Document.get_effective_content()'s per-instance fallback (no annotation,
no prefetch) is a `.values_list("content", flat=True).first()` query --
a SELECT of just the content column. Distinct from get_versions()'s own,
unrelated per-instance metadata query (id/checksum/added/etc, no
content) run to build the "versions" response field, which isn't part
of what this test file covers.
"""
return [
q
for q in ctx.captured_queries
if q["sql"].startswith('SELECT "documents_document"."content" FROM')
]
@pytest.mark.django_db
class TestTrashAndGlobalSearchEffectiveContentIsNeverPerInstance:
"""
TrashView and GlobalSearchView serialize Document instances with
DocumentSerializer too, but build their querysets independently of
DocumentViewSet.get_queryset(). TrashView doesn't display content at all,
so it keeps the document's own unresolved content; GlobalSearchView
annotates effective_content itself, so it shows the latest version's.
Neither should ever fall back to a per-instance query.
"""
def test_trash_list_shows_unresolved_content_with_no_extra_query(
self,
admin_client: APIClient,
) -> None:
"""
GIVEN:
- A trashed root document whose own content differs from what a
version would have had (also trashed, deletion cascades)
WHEN:
- Listing trash
THEN:
- The response shows the document's own content
- Nothing ever queries for versions to resolve it
"""
root = DocumentFactory(content="own-content")
DocumentFactory(
root_document=root,
version_index=1,
content="version-content",
)
root.delete()
with CaptureQueriesContext(connection) as ctx:
response = admin_client.get("/api/trash/")
assert response.status_code == status.HTTP_200_OK
[result] = [r for r in response.data["results"] if r["id"] == root.id]
assert result["content"] == "own-content"
assert _get_effective_content_fallback_queries(ctx) == []
def test_global_search_db_only_shows_latest_version_content_with_no_extra_query(
self,
admin_client: APIClient,
) -> None:
"""
GIVEN:
- A root document, findable by title, whose own content differs
from its latest version's
WHEN:
- Using the global search endpoint's db_only mode
THEN:
- The response shows the latest version's content, resolved by
GlobalSearchView's own effective_content annotation
- There is no per-instance fallback query
"""
root = DocumentFactory(title="findme", content="own-content")
DocumentFactory(
root_document=root,
version_index=1,
content="version-content",
)
with CaptureQueriesContext(connection) as ctx:
response = admin_client.get(
"/api/search/?query=findme&db_only=true",
)
assert response.status_code == status.HTTP_200_OK
[result] = [d for d in response.data["documents"] if d["id"] == root.id]
assert result["content"] == "version-content"
assert _get_effective_content_fallback_queries(ctx) == []
+1 -5
View File
@@ -110,7 +110,7 @@ class TestDocument(TestCase):
checksum="checksum",
mime_type="application/pdf",
)
version = Document.objects.create(
Document.objects.create(
root_document=root,
correspondent=root.correspondent,
title="Version",
@@ -124,10 +124,6 @@ class TestDocument(TestCase):
self.assertEqual(Document.objects.count(), 0)
self.assertEqual(Document.deleted_objects.count(), 2)
root.restore(strict=False)
self.assertTrue(Document.objects.filter(pk=version.pk).exists())
def test_file_name(self) -> None:
doc = Document(
mime_type="application/pdf",
@@ -136,23 +136,6 @@ def wait_for_mock_call(
return False
def sleep_past_stability(
owner: FileStabilityTracker | ConsumerThread,
*,
windows: float = 1.5,
) -> None:
"""
Block until a tracked file's stability window has certainly elapsed.
Args:
owner: The tracker, or the consumer thread running one, whose
configured stability delay sets the wait.
windows: How many stability windows to wait, giving slop for a slow
or loaded test runner.
"""
sleep(owner.stability_delay * windows)
class TestTrackedFile:
"""Tests for the TrackedFile dataclass."""
@@ -278,56 +261,6 @@ class TestFileStabilityTracker:
assert len(stable) == 0
assert stability_tracker.pending_count == 1
def test_get_stable_files_skips_empty_file(
self,
stability_tracker: FileStabilityTracker,
tmp_path: Path,
) -> None:
"""
GIVEN:
- A zero byte file, tracked and past its stability delay
WHEN:
- Stable files are collected
THEN:
- The file is not yielded for consumption
- The file is dropped from tracking rather than held, so an
abandoned placeholder does not keep the watch loop awake
"""
empty = tmp_path / "scan.pdf"
empty.write_bytes(b"")
stability_tracker.track(empty, Change.added)
sleep_past_stability(stability_tracker)
stable = list(stability_tracker.get_stable_files())
assert stable == []
assert stability_tracker.pending_count == 0
def test_empty_file_is_yielded_once_content_arrives(
self,
stability_tracker: FileStabilityTracker,
tmp_path: Path,
) -> None:
"""
GIVEN:
- A zero byte file which was dropped from tracking while empty
WHEN:
- The writer fills the file and a new event re-tracks it
THEN:
- The file is yielded for consumption once it is stable
"""
target = tmp_path / "scan.pdf"
target.write_bytes(b"")
stability_tracker.track(target, Change.added)
sleep_past_stability(stability_tracker)
assert list(stability_tracker.get_stable_files()) == []
target.write_bytes(b"%PDF-1.4 content")
stability_tracker.track(target, Change.modified)
sleep_past_stability(stability_tracker)
assert list(stability_tracker.get_stable_files()) == [target]
def test_get_stable_files_deleted_during_check(self, temp_file: Path) -> None:
"""Test deleted file is not returned during stability check."""
tracker = FileStabilityTracker(stability_delay=0.1)
@@ -946,51 +879,6 @@ class TestCommandWatch:
mock_consume_file_delay.apply_async.assert_called()
def test_scanner_placeholder_is_not_consumed_while_empty(
self,
consumption_dir: Path,
sample_pdf: Path,
mock_consume_file_delay: MagicMock,
start_consumer: Callable[..., ConsumerThread],
) -> None:
"""
GIVEN:
- A scanner which creates a zero byte placeholder and only writes
the page some time later (GH discussion #13969)
WHEN:
- The placeholder sits untouched well past the stability delay
- The scanner then writes the real content
THEN:
- The empty placeholder is never queued, as it could only fail
with "Unsupported mime type inode/x-empty"
- The file is queued exactly once, when the content lands
"""
thread = start_consumer(stability_delay=0.2)
target = consumption_dir / "scan.pdf"
target.write_bytes(b"") # the scanner's placeholder
# Well past the stability delay: the old behaviour queued it here.
sleep_past_stability(thread, windows=5)
if thread.exception:
raise thread.exception
assert mock_consume_file_delay.apply_async.call_count == 0
shutil.copy(sample_pdf, target) # the scanner finishes the page
assert wait_for_mock_call(
mock_consume_file_delay.apply_async,
timeout_s=5.0,
)
if thread.exception:
raise thread.exception
assert mock_consume_file_delay.apply_async.call_count == 1
queued_doc = mock_consume_file_delay.apply_async.call_args.kwargs["kwargs"][
"input_doc"
]
assert queued_doc.original_file.name == "scan.pdf"
def test_ignores_macos_files(
self,
consumption_dir: Path,
-39
View File
@@ -2,7 +2,6 @@ from unittest import mock
from django.contrib.auth.models import Permission
from django.contrib.auth.models import User
from rest_framework import status
from rest_framework.test import APITestCase
from documents import bulk_edit
@@ -109,44 +108,6 @@ class TestTagHierarchy(DirectoriesMixin, APITestCase):
self.document.refresh_from_db()
assert self.document.tags.count() == 0
def test_remove_inbox_tags_removes_nested_children(self) -> None:
inbox = Tag.objects.create(name="Inbox", is_inbox_tag=True)
nested = Tag.objects.create(name="Nested", tn_parent=inbox)
self.document.add_nested_tags([nested])
resp = self.client.patch(
f"/api/documents/{self.document.pk}/",
{"title": "new title", "remove_inbox_tags": True},
format="json",
)
assert resp.status_code == status.HTTP_200_OK
self.document.refresh_from_db()
assert self.document.tags.count() == 0
# A subsequent save must not re-add the inbox tag as an ancestor
resp = self.client.patch(
f"/api/documents/{self.document.pk}/",
{"title": "another title", "tags": [], "remove_inbox_tags": True},
format="json",
)
assert resp.status_code == status.HTTP_200_OK
self.document.refresh_from_db()
assert self.document.tags.count() == 0
def test_remove_inbox_tags_keeps_inbox_when_nested_child_added(self) -> None:
inbox = Tag.objects.create(name="Inbox", is_inbox_tag=True)
nested = Tag.objects.create(name="Nested", tn_parent=inbox)
self.document.add_nested_tags([inbox])
self.client.patch(
f"/api/documents/{self.document.pk}/",
{"tags": [nested.pk], "remove_inbox_tags": True},
format="json",
)
self.document.refresh_from_db()
tags = set(self.document.tags.values_list("pk", flat=True))
assert tags == {inbox.pk, nested.pk}
def test_bulk_edit_respects_hierarchy(self) -> None:
bulk_edit.add_tag([self.document.pk], self.child.pk)
self.document.refresh_from_db()
-33
View File
@@ -32,7 +32,6 @@ from documents.signals.handlers import update_llm_suggestions_cache
from documents.tests.utils import DirectoriesMixin
from documents.tests.utils import read_streaming_response
from paperless.models import ApplicationConfiguration
from paperless_ai.exceptions import LLMProviderError
from paperless_ai.exceptions import LLMTimeoutError
@@ -738,38 +737,6 @@ class TestAISuggestions(DirectoriesMixin, TestCase):
get_llm_suggestion_cache(self.document.pk, backend="openai-like"),
)
@patch("documents.views.get_ai_document_classification")
@override_settings(
AI_ENABLED=True,
LLM_BACKEND="openai-like",
)
def test_ai_suggestions_with_llm_provider_error(
self,
mock_get_ai_classification,
) -> None:
mock_get_ai_classification.side_effect = LLMProviderError(
"confidential provider response",
)
self.client.force_login(user=self.user)
response = self.client.get(
f"/api/documents/{self.document.pk}/ai_suggestions/",
)
self.assertEqual(response.status_code, status.HTTP_502_BAD_GATEWAY)
self.assertEqual(
response.json(),
{
"ai": [
"AI backend rejected the request. Check logs for details.",
],
},
)
self.assertNotIn("confidential provider response", response.content.decode())
self.assertIsNone(
get_llm_suggestion_cache(self.document.pk, backend="openai-like"),
)
@patch("documents.views.get_ai_document_classification")
@override_settings(
AI_ENABLED=True,
-65
View File
@@ -7,12 +7,9 @@ from typing import Any
from django.db.models import F
from django.db.models import OuterRef
from django.db.models import Prefetch
from django.db.models import QuerySet
from django.db.models import Subquery
from django.db.models import Window
from django.db.models.functions import Coalesce
from django.db.models.functions import RowNumber
from documents.models import Document
@@ -49,68 +46,6 @@ def annotate_effective_content(documents: QuerySet[Document]) -> QuerySet[Docume
)
LATEST_VERSION_CONTENT_PREFETCH_ATTR = "_latest_version_content_prefetch"
def latest_version_content_prefetch() -> Prefetch:
"""
A Prefetch for Document.versions scoped to just the newest version's
content, for get_effective_content()'s fallback when no SQL annotation
is present.
Deliberately not merged into a metadata-only "versions" prefetch (the one
used for the serialized versions list): that one fetches every historical
version of every document, and pulling full OCR content for versions
nobody will read wastes DB transfer/memory at scale. This one is windowed
down to a single row per root, then bounded by Prefetch's own IN-list to
whatever page/result set it's attached to -- one cheap bulk query total,
not one per document and not one per version.
"""
return Prefetch(
"versions",
queryset=(
Document.objects.filter(
root_document_id__isnull=False,
deleted_at__isnull=True,
)
.annotate(
rn=Window(
RowNumber(),
partition_by=F("root_document_id"),
order_by=[
F("version_index").desc(nulls_last=True),
F("id").desc(),
],
),
)
.filter(rn=1)
.only("id", "root_document_id", "content")
),
to_attr=LATEST_VERSION_CONTENT_PREFETCH_ATTR,
)
def has_prefetched_effective_content(document: Document) -> bool:
"""
True if document.get_effective_content() can answer without an extra
per-instance query -- an SQL ``effective_content`` annotation, the lean
latest_version_content_prefetch(), or the metadata-only "versions"
prefetch is already present on the instance.
Callers that haven't set any of those up (e.g. views that build their
own querysets independently of DocumentViewSet.get_queryset(), like
TrashView or GlobalSearchView) intentionally don't pay for version-aware
content resolution -- see DocumentSerializer.to_representation(), which
uses this to decide whether to call get_effective_content() at all.
"""
if hasattr(document, "effective_content"):
return True
if getattr(document, LATEST_VERSION_CONTENT_PREFETCH_ATTR, None) is not None:
return True
prefetched_cache = getattr(document, "_prefetched_objects_cache", None)
return isinstance(prefetched_cache, dict) and "versions" in prefetched_cache
def sort_versions_newest_first(documents: list[Document]) -> list[Document]:
"""
Same sorting as versions_newest_first()
+41 -120
View File
@@ -36,6 +36,7 @@ from django.db.migrations.recorder import MigrationRecorder
from django.db.models import Avg
from django.db.models import Case
from django.db.models import Count
from django.db.models import F
from django.db.models import IntegerField
from django.db.models import Max
from django.db.models import Model
@@ -136,14 +137,12 @@ from documents.filters import CustomFieldFilterSet
from documents.filters import DocumentFilterSet
from documents.filters import DocumentsOrderingFilter
from documents.filters import DocumentTypeFilterSet
from documents.filters import EffectiveContentFilter
from documents.filters import PaperlessTaskFilterSet
from documents.filters import PermittedObjectsFilter
from documents.filters import ShareLinkBundleFilterSet
from documents.filters import ShareLinkFilterSet
from documents.filters import StoragePathFilterSet
from documents.filters import TagFilterSet
from documents.filters import TitleContentFilter
from documents.mail import EmailAttachment
from documents.mail import send_email
from documents.matching import match_correspondents
@@ -180,7 +179,7 @@ from documents.permissions import has_perms_owner_aware
from documents.permissions import has_system_status_permission
from documents.permissions import permitted_document_ids
from documents.permissions import permitted_object_ids
from documents.permissions import set_permissions_for_objects
from documents.permissions import set_permissions_for_object
from documents.permissions import user_is_unrestricted
from documents.plugins.date_parsing import get_date_parser
from documents.schema import generate_object_with_permissions_schema
@@ -237,7 +236,6 @@ from documents.versioning import annotate_effective_content
from documents.versioning import get_latest_version_for_root
from documents.versioning import get_request_version_param
from documents.versioning import get_root_document
from documents.versioning import latest_version_content_prefetch
from documents.versioning import resolve_requested_version_for_root
from documents.versioning import versions_newest_first
from paperless import version
@@ -254,7 +252,6 @@ from paperless.views import StandardPagination
from paperless_ai.ai_classifier import get_ai_document_classification
from paperless_ai.ai_classifier import get_llm_output_language
from paperless_ai.chat import stream_chat_with_documents
from paperless_ai.exceptions import LLMProviderError
from paperless_ai.exceptions import LLMTimeoutError
from paperless_ai.matching import extract_unmatched_names
from paperless_ai.matching import match_correspondents_by_name
@@ -1086,59 +1083,12 @@ class DocumentViewSet(
],
}
@classmethod
def _content_filter_params(cls) -> tuple[str, ...]:
"""
Query params whose filtering needs effective_content evaluated in SQL
against every candidate row -- see
_needs_effective_content_annotation(). Derived rather than
hand-maintained so a new content-filtering param counts automatically.
"""
params = [
name
for name, f in DocumentFilterSet.declared_filters.items()
if isinstance(f, (TitleContentFilter, EffectiveContentFilter))
]
if "effective_content" in cls.search_fields:
params.append(SearchFilter().search_param)
return tuple(params)
def _needs_effective_content_annotation(self) -> bool:
# effective_content is a per-row correlated subquery resolving each
# document's latest version. Filtering *on* it forces the database to
# evaluate it for every candidate row before reaching the LIMIT, which
# the root_document_id self-join makes pathological on MariaDB
# specifically once real candidate counts get large; otherwise the
# "versions" prefetch + Document.get_effective_content() resolves only
# the page that survives pagination. Every param here is deprecated in
# favor of the Tantivy-backed search endpoint (see filters.py's
# TitleContentFilter/EffectiveContentFilter docs), so pay that cost
# only when one is actually used. Blank values don't count, matching
# how those filters themselves no-op on them -- an empty `?search=`
# applies no predicate.
params = self.request.query_params
return any(
params.get(param, "").strip() for param in self._content_filter_params()
)
def _requested_fields(self) -> list[str] | None:
# The sparse-fieldset `fields` param, as DynamicFieldsModelSerializer
# wants it: None means "no restriction, serialize everything", which
# a blank value means too. get_queryset() and get_serializer() both
# branch on this, and they have to read it identically -- a queryset
# that skips the content prefetch for a response that still
# serializes content reintroduces get_effective_content()'s
# per-instance fallback.
fields_param = self.request.query_params.get("fields")
return fields_param.split(",") if fields_param else None
def _needs_effective_content_prefetch(self) -> bool:
# The prefetch spares get_effective_content() a per-instance fallback
# query, but only earns itself when content can reach the response.
fields = self._requested_fields()
return fields is None or "content" in fields
def get_queryset(self):
latest_version_content = Subquery(
versions_newest_first(
Document.objects.filter(root_document=OuterRef("pk")),
).values("content")[:1],
)
# A correlated subquery avoids the LEFT JOIN + Count() this used to
# be, which forced a GROUP BY aggregate over every matching document
# before the query could even be sorted or limited.
@@ -1158,43 +1108,40 @@ class DocumentViewSet(
# ObjectFilter.filter(). A blanket .distinct() here forces the
# database to fully sort and dedupe every visible document before
# it can apply LIMIT, which is disastrous at scale.
prefetches = [
Prefetch(
"versions",
queryset=Document.objects.only(
"id",
"added",
"checksum",
"version_label",
"root_document_id",
"version_index",
),
),
"tags",
Prefetch(
"custom_fields",
queryset=CustomFieldInstance.objects.select_related("field"),
),
# NotesSerializer nests the author, this avoids query per note
Prefetch("notes", queryset=Note.objects.select_related("user")),
]
if self._needs_effective_content_prefetch():
prefetches.append(latest_version_content_prefetch())
queryset = (
return (
Document.objects.filter(root_document__isnull=True)
.order_by("-created", "-id")
.annotate(effective_content=Coalesce(latest_version_content, F("content")))
.annotate(num_notes=Coalesce(note_count, 0))
.select_related("correspondent", "storage_path", "document_type", "owner")
.prefetch_related(*prefetches)
.prefetch_related(
Prefetch(
"versions",
queryset=Document.objects.only(
"id",
"added",
"checksum",
"version_label",
"root_document_id",
"version_index",
),
),
"tags",
Prefetch(
"custom_fields",
queryset=CustomFieldInstance.objects.select_related("field"),
),
# NotesSerializer nests the author, this avoids query per note
Prefetch("notes", queryset=Note.objects.select_related("user")),
)
)
if self._needs_effective_content_annotation():
queryset = annotate_effective_content(queryset)
return queryset
def get_serializer(self, *args, **kwargs):
fields_param = self.request.query_params.get("fields", None)
fields = fields_param.split(",") if fields_param else None
truncate_content = self.request.query_params.get("truncate_content", "False")
kwargs.setdefault("context", self.get_serializer_context())
kwargs.setdefault("fields", self._requested_fields())
kwargs.setdefault("fields", fields)
kwargs.setdefault("truncate_content", truncate_content.lower() in ["true", "1"])
try:
full_perms = get_boolean(
@@ -1656,22 +1603,6 @@ class DocumentViewSet(
{"ai": [_("AI backend request timed out.")]},
status=status.HTTP_503_SERVICE_UNAVAILABLE,
)
except LLMProviderError:
logger.exception(
"AI backend rejected the request for document %s",
doc.pk,
)
return Response(
{
"ai": [
_(
"AI backend rejected the request. "
"Check logs for details.",
),
],
},
status=status.HTTP_502_BAD_GATEWAY,
)
set_llm_suggestions_cache(
doc.pk,
llm_suggestions,
@@ -2380,6 +2311,7 @@ class ChatStreamingView(GenericAPIView[Any]):
serializer_class = ChatStreamingSerializer
def post(self, request, *args, **kwargs):
request.compress_exempt = True
ai_config = AIConfig()
if not ai_config.ai_enabled:
return HttpResponseBadRequest("AI is required for this feature")
@@ -5018,12 +4950,12 @@ class BulkEditObjectsView(PassUserMixin):
qs_owner_update.update(owner=owner)
if "permissions" in serializer.validated_data:
set_permissions_for_objects(
permissions=permissions,
model=object_class,
pks=qs.values_list("pk", flat=True),
merge=merge,
)
for obj in qs:
set_permissions_for_object(
permissions=permissions,
object=obj,
merge=merge,
)
except Exception as e:
logger.warning(
@@ -5505,10 +5437,7 @@ class TrashView(ListModelMixin, PassUserMixin):
model = Document
# A version is listed separately only when its root is not in the trash.
queryset = Document.deleted_objects.exclude(
root_document_id__in=Document.deleted_objects.values("id"),
)
queryset = Document.deleted_objects.all()
def get(self, request: Request, format: str | None = None) -> Response:
self.serializer_class = DocumentSerializer
@@ -5539,15 +5468,7 @@ class TrashView(ListModelMixin, PassUserMixin):
return HttpResponseForbidden("Insufficient permissions")
action = serializer.validated_data.get("action")
if action == "restore":
restored = list(self.get_queryset().filter(id__in=doc_ids))
if len(restored) != len(doc_ids):
raise ValidationError(
{
"documents": [
"Restore the root document instead of one of its versions.",
],
},
)
restored = list(Document.deleted_objects.filter(id__in=doc_ids))
for doc in restored:
doc.restore(strict=False)
if restored:
File diff suppressed because it is too large Load Diff
-15
View File
@@ -1,23 +1,8 @@
from compression_middleware.middleware import CompressionMiddleware
from django.conf import settings
from paperless import version
class StreamAwareCompressionMiddleware(CompressionMiddleware):
"""
Bypasses compression for server-sent streams (text/event-stream).
See https://github.com/friedelwolff/django-compression-middleware/pull/7
"""
def process_response(self, request, response):
content_type = response.headers.get("Content-Type", "")
if content_type.startswith("text/event-stream"):
return response
return super().process_response(request, response)
class ApiVersionMiddleware:
def __init__(self, get_response):
self.get_response = get_response
+17 -10
View File
@@ -10,6 +10,7 @@ from pathlib import Path
from typing import Final
from urllib.parse import urlparse
from compression_middleware.middleware import CompressionMiddleware
from django.core.exceptions import ImproperlyConfigured
from django.utils.translation import gettext_lazy as _
from dotenv import load_dotenv
@@ -95,13 +96,6 @@ MODEL_FILE = get_path_from_env(
"PAPERLESS_MODEL_FILE",
DATA_DIR / "classification_model.pickle",
)
# Minimum confidence (0.0-1.0) for the ML classifier to assign a correspondent,
# document type, or storage path. 0.0 disables the threshold.
CLASSIFIER_MATCH_THRESHOLD: Final[float] = get_float_from_env(
"PAPERLESS_CLASSIFIER_MATCH_THRESHOLD",
0.6,
)
LLM_INDEX_DIR = DATA_DIR / "llm_index"
LLM_INDEX_LOCK = LLM_INDEX_DIR / "index.lock"
# Cross-process read/write lock guarding the LLM index compaction/migration
@@ -156,6 +150,7 @@ INSTALLED_APPS = [
"drf_spectacular",
"drf_spectacular_sidecar",
"treenode",
"paperless_benchmark.apps.PaperlessBenchmarkConfig",
*env_apps,
]
@@ -200,10 +195,22 @@ MIDDLEWARE = [
"allauth.account.middleware.AccountMiddleware",
]
# Optional to enable compression. The subclass leaves server-sent events
# uncompressed; see paperless.middleware.StreamAwareCompressionMiddleware.
# Optional to enable compression
if get_bool_from_env("PAPERLESS_ENABLE_COMPRESSION", "yes"): # pragma: no cover
MIDDLEWARE.insert(0, "paperless.middleware.StreamAwareCompressionMiddleware")
MIDDLEWARE.insert(0, "compression_middleware.middleware.CompressionMiddleware")
# Workaround to not compress streaming responses (e.g. chat).
# See https://github.com/friedelwolff/django-compression-middleware/pull/7
original_process_response = CompressionMiddleware.process_response
def patched_process_response(self, request, response):
if getattr(request, "compress_exempt", False):
return response
return original_process_response(self, request, response)
CompressionMiddleware.process_response = patched_process_response
ROOT_URLCONF = "paperless.urls"
@@ -1,54 +0,0 @@
from django.http import HttpResponse
from django.http import StreamingHttpResponse
from django.test import RequestFactory
from django.test import TestCase
from paperless.middleware import StreamAwareCompressionMiddleware
class TestStreamAwareCompressionMiddleware(TestCase):
def setUp(self) -> None:
super().setUp()
self.factory = RequestFactory()
self.middleware = StreamAwareCompressionMiddleware(lambda request: None)
def _request(self):
return self.factory.get(
"/api/documents/chat/",
HTTP_ACCEPT_ENCODING="gzip, deflate, br, zstd",
)
def test_event_stream_is_not_compressed(self) -> None:
"""
GIVEN:
- A server-sent event response produced chunk by chunk
WHEN:
- The compression middleware processes it
THEN:
- It is passed through unencoded, one wire chunk per source chunk
"""
chunks = [f"token{i} ".encode() for i in range(40)]
response = StreamingHttpResponse(
iter(chunks),
content_type="text/event-stream",
)
response = self.middleware.process_response(self._request(), response)
assert not response.has_header("Content-Encoding")
assert list(response.streaming_content) == chunks
def test_regular_response_is_still_compressed(self) -> None:
"""
GIVEN:
- An ordinary response large enough to be worth compressing
WHEN:
- The compression middleware processes it
THEN:
- It is compressed as before
"""
response = HttpResponse(b"a" * 5000, content_type="application/json")
response = self.middleware.process_response(self._request(), response)
assert response.has_header("Content-Encoding")
+47 -97
View File
@@ -4,24 +4,21 @@ from django.conf import settings
from django.contrib.auth.models import User
from documents.models import Document
from documents.permissions import permitted_object_ids
from documents.permissions import restrict_queryset_to_visible
from documents.permissions import user_is_unrestricted
from documents.permissions import get_objects_for_user_owner_aware
from paperless.config import AIConfig
from paperless_ai.base_model import ClassificationSuggestions
from paperless_ai.base_model import TaxonomyChoiceDict
from paperless_ai.base_model import classification_suggestions_to_model
from paperless_ai.client import AIClient
from paperless_ai.db import db_connection_released
from paperless_ai.indexing import _node_document_ids
from paperless_ai.indexing import retrieve_similar_nodes
from paperless_ai.indexing import truncate_content
from paperless_ai.prompts.context import ClassificationPromptContext
from paperless_ai.prompts.context import LocalizationPromptContext
from paperless_ai.prompts.context import RagContextPromptContext
from paperless_ai.prompts.render import render_prompt
from paperless_ai.taxonomy import SimilarDocument
from paperless_ai.taxonomy import TaxonomyCandidates
from paperless_ai.taxonomy import _node_document_weights
from paperless_ai.taxonomy import build_taxonomy_candidates
from paperless_ai.taxonomy import empty_taxonomy_candidates
from paperless_ai.taxonomy import format_taxonomy_for_prompt
@@ -40,48 +37,6 @@ logger = logging.getLogger("paperless_ai.rag_classifier")
TAXONOMY_CANDIDATE_TOP_K = 15
def _fulltext_similar_documents(
document: Document,
user: User | None,
top_k: int,
) -> list[SimilarDocument]:
"""Rank-based fallback when no embedding backend is configured. Uses
Tantivy's "More Like This" (term-overlap similarity) instead of vector
similarity - cruder, but far better than no candidates at all.
more_like_this_ids returns only a ranked ID list, no scores, so weight is
synthesized from rank (descending from top_k) rather than claiming a
similarity magnitude that doesn't exist. An unrestricted user (none, or an
active superuser - see user_is_unrestricted) is normalized to ``None``
before calling, since the backend's permission filter has no superuser
short-circuit of its own. Results are re-checked with
restrict_queryset_to_visible() since Tantivy's indexed permission fields
lag the DB via async reindexing.
"""
from documents.search import get_backend
unrestricted = user_is_unrestricted(user)
search_user = None if unrestricted else user
backend = get_backend()
similar_ids = backend.more_like_this_ids(
document.pk,
user=search_user,
limit=top_k,
)
if not unrestricted:
allowed_ids = set(
restrict_queryset_to_visible(
Document.objects.filter(pk__in=similar_ids),
user,
"view_document",
).values_list("pk", flat=True),
)
similar_ids = [doc_id for doc_id in similar_ids if doc_id in allowed_ids]
return [
SimilarDocument(document_id=doc_id, weight=float(top_k - rank))
for rank, doc_id in enumerate(similar_ids)
]
def get_language_name(language_code: str) -> str:
normalized_language_code = language_code.lower()
for code, name in settings.LANGUAGES:
@@ -181,52 +136,43 @@ def get_taxonomy_context(
user: User | None = None,
max_docs: int = 5,
) -> tuple[TaxonomyCandidates, str]:
"""One retrieval feeds both taxonomy candidates and RAG text context. Uses
vector similarity when an embedding backend is configured, otherwise
falls back to Tantivy full-text "More Like This" similarity - see
_fulltext_similar_documents. On any retrieval failure, degrades to empty
candidates/context rather than propagating the exception - neither a
vector-store outage nor a search-index issue should block classification,
only its context-assisted enrichment.
"""One retrieval feeds both taxonomy candidates and RAG text context.
On any retrieval failure, degrades to empty candidates/context rather than
propagating the exception - a vector-store outage should not block
classification, only its RAG-assisted enrichment.
"""
ai_config = AIConfig()
try:
if ai_config.llm_embedding_backend:
# None means "no restriction" to retrieve_similar_nodes. An
# unrestricted user (no user at all, or an active superuser -- see
# user_is_unrestricted) can see every document, so skip
# materializing every visible pk into a Python list and passing it
# through as an IN filter: for a large library that is a wasted
# quadratic scan in the vector store at best, and past ~32,763
# documents a hard sqlite3.OperationalError (SQLite's
# bound-parameter limit) at worst.
# permitted_object_ids() has its own superuser shortcut that would
# return every Document's id anyway, so this changes nothing about
# which documents are considered -- only how we get there.
visible_document_ids = (
None
if user_is_unrestricted(user)
else list(permitted_object_ids(user, Document, "view_document"))
)
nodes = retrieve_similar_nodes(
document,
top_k=TAXONOMY_CANDIDATE_TOP_K,
document_ids=visible_document_ids,
)
similar_documents = _node_document_weights(nodes)
else:
# See _fulltext_similar_documents: it applies its own permission
# filter via `user`, so no visible-document-id list is needed here.
similar_documents = _fulltext_similar_documents(
document,
user,
top_k=TAXONOMY_CANDIDATE_TOP_K,
# None means "no restriction" to retrieve_similar_nodes. A superuser
# (like no user at all) can see every document, so skip materializing
# every visible pk into a Python list and passing it through as an IN
# filter: for a large library that is a wasted quadratic scan in the
# vector store at best, and past ~32,763 documents a hard
# sqlite3.OperationalError (SQLite's bound-parameter limit) at worst.
# get_objects_for_user_owner_aware() would return every Document for a
# superuser anyway (guardian's own with_superuser shortcut), so this
# changes nothing about which documents are considered -- only how we
# get there.
visible_document_ids = (
None
if user is None or user.is_superuser
else list(
get_objects_for_user_owner_aware(
user,
"view_document",
Document,
).values_list("pk", flat=True),
)
)
nodes = retrieve_similar_nodes(
document,
top_k=TAXONOMY_CANDIDATE_TOP_K,
document_ids=visible_document_ids,
)
candidates = build_taxonomy_candidates(similar_documents, user)
candidates = build_taxonomy_candidates(nodes, user)
# similar_documents is already ordered by descending weight; don't lose it.
similar_document_ids = [s["document_id"] for s in similar_documents]
# ``nodes`` are already ordered by descending vector similarity; don't lose it.
similar_document_ids = list(dict.fromkeys(_node_document_ids(nodes)))
similar_documents_by_id = Document.objects.in_bulk(similar_document_ids)
similar_docs = [
similar_documents_by_id[document_id]
@@ -240,8 +186,8 @@ def get_taxonomy_context(
context_blocks.append(f"TITLE: {title}\n{text}")
except Exception:
logger.exception(
"Failed to retrieve similar-document context for document %s; "
"continuing without taxonomy candidates or similar-document context.",
"Failed to retrieve RAG neighbours for document %s; continuing "
"without taxonomy candidates or similar-document context.",
document.pk,
)
return empty_taxonomy_candidates(), ""
@@ -295,13 +241,17 @@ def get_ai_document_classification(
) -> ClassificationSuggestions:
ai_config = AIConfig()
candidates, context = get_taxonomy_context(document, user)
prompt = build_prompt_with_rag(
document,
ai_config,
candidates=candidates,
context=context,
)
if ai_config.llm_embedding_backend:
candidates, context = get_taxonomy_context(document, user)
prompt = build_prompt_with_rag(
document,
ai_config,
candidates=candidates,
context=context,
)
else:
candidates = empty_taxonomy_candidates()
prompt = build_prompt_without_rag(document, ai_config, candidates=candidates)
client = AIClient()
# Hand the pooled DB connection back while the (slow) LLM query runs so it
+4 -19
View File
@@ -22,7 +22,6 @@ from paperless.network import validate_outbound_http_url
from paperless_ai.base_model import ClassificationSuggestions
from paperless_ai.base_model import DocumentClassifierSchema
from paperless_ai.base_model import model_to_classification_suggestions
from paperless_ai.exceptions import LLMProviderError
from paperless_ai.exceptions import LLMTimeoutError
logger = logging.getLogger("paperless_ai.client")
@@ -40,6 +39,7 @@ LLM_SYSTEM_PROMPT = (
# openai-python rejects empty keys since 2.34.0, "fake" is the stand-in from
# llama-index's own OpenAILike docs https://docs.llamaindex.ai/en/stable/api_reference/llms/openai_like/
# TODO: remove pending resolution of https://github.com/openai/openai-python/issues/3224
PLACEHOLDER_API_KEY: Final = "fake"
@@ -132,7 +132,7 @@ class AIClient:
from llama_index.core.llms import ChatMessage
if self.settings.llm_backend == LLMBackend.OLLAMA:
with self._normalize_errors():
with self._normalize_timeouts():
result = self.llm.chat(
[ChatMessage(role="user", content=prompt)],
format=DocumentClassifierSchema.model_json_schema(),
@@ -153,7 +153,7 @@ class AIClient:
content=f"{prompt}\n\n"
f"Answer by calling the {tool.metadata.name} tool. Do not write the answer as text.",
)
with self._normalize_errors():
with self._normalize_timeouts():
result = self.llm.chat_with_tools(
tools=[tool],
user_msg=user_msg,
@@ -173,7 +173,7 @@ class AIClient:
)
@contextmanager
def _normalize_errors(self) -> Iterator[None]:
def _normalize_timeouts(self) -> Iterator[None]:
try:
yield
except httpx.TimeoutException as exc:
@@ -181,23 +181,8 @@ class AIClient:
except Exception as exc:
if self._is_openai_timeout(exc):
raise LLMTimeoutError from exc
if self._is_provider_error(exc):
raise LLMProviderError from exc
raise
def _is_provider_error(self, exc: Exception) -> bool:
if self.settings.llm_backend == LLMBackend.OLLAMA:
from ollama import ResponseError
return isinstance(exc, ResponseError)
if self.settings.llm_backend == LLMBackend.OPENAI_LIKE:
from openai import APIStatusError
return isinstance(exc, APIStatusError)
return False
def _is_openai_timeout(self, exc: Exception) -> bool:
if self.settings.llm_backend != LLMBackend.OPENAI_LIKE:
return False
-4
View File
@@ -1,6 +1,2 @@
class LLMTimeoutError(Exception):
pass
class LLMProviderError(Exception):
"""The LLM backend rejected the request."""
+17
View File
@@ -721,3 +721,20 @@ def retrieve_similar_nodes(
continue
filtered.append(node)
return filtered
def _node_document_ids(nodes: list["NodeWithScore"]) -> list[int]:
document_ids: list[int] = []
for node in nodes:
document_id = node.metadata.get("document_id")
if document_id is None: # pragma: no cover
# See the matching guard in retrieve_similar_nodes() above.
continue
try:
document_ids.append(int(document_id))
except ValueError: # pragma: no cover
logger.warning(
"Skipping LLM index result with invalid document_id %r.",
document_id,
)
return document_ids
+14 -31
View File
@@ -31,11 +31,6 @@ class TaxonomyCandidate(TypedDict):
weight: float
class SimilarDocument(TypedDict):
document_id: int
weight: float
class TaxonomyCandidates(TypedDict):
tags: list[TaxonomyCandidate]
document_types: list[TaxonomyCandidate]
@@ -54,10 +49,10 @@ def empty_taxonomy_candidates() -> TaxonomyCandidates:
)
def _node_document_weights(nodes: list["NodeWithScore"]) -> list[SimilarDocument]:
"""Sum each node's similarity score into its document_id (a document can
appear via multiple chunks/nodes) and return one SimilarDocument per
distinct document_id."""
def _node_document_weights(nodes: list["NodeWithScore"]) -> dict[int, float]:
"""document_id -> that node's similarity score, summed if a document_id
appears more than once across the retrieved nodes (e.g. multiple chunks
of the same source document)."""
weights: dict[int, float] = defaultdict(float)
for node in nodes:
document_id = node.metadata.get("document_id")
@@ -70,14 +65,7 @@ def _node_document_weights(nodes: list["NodeWithScore"]) -> list[SimilarDocument
weights[int(document_id)] += float(node.score or 0.0)
except (TypeError, ValueError): # pragma: no cover
continue
return sorted(
(
SimilarDocument(document_id=document_id, weight=weight)
for document_id, weight in weights.items()
),
key=lambda similar: similar["weight"],
reverse=True,
)
return weights
def _visible_ranked_candidates(
@@ -113,25 +101,20 @@ def _visible_ranked_candidates(
def build_taxonomy_candidates(
similar_documents: list[SimilarDocument],
nodes: list["NodeWithScore"],
user: User | None,
) -> TaxonomyCandidates:
"""Resolve each similar document's id to a live Document, read its
*current* tags/type/correspondent/storage_path via the ORM (never any
possibly-stale names an adapter's source might have cached), weight each
distinct taxonomy object by aggregate similarity weight, permission-filter
"""Resolve each neighbour node's document_id to a live Document, read its
*current* tags/type/correspondent/storage_path via the ORM (never the
possibly-stale names cached in vector-index node metadata), weight each
distinct taxonomy object by aggregate neighbour similarity, permission-filter
against what ``user`` can see, and return each category ranked by weight
and capped. ``similar_documents`` may come from either the vector-RAG
adapter or the full-text fallback adapter - both produce this same shape.
and capped.
"""
if not similar_documents:
return empty_taxonomy_candidates()
# Both adapters guarantee at most one SimilarDocument per document_id, so
# this never silently drops a duplicate's weight.
document_weights: dict[int, float] = {
s["document_id"]: s["weight"] for s in similar_documents
}
document_weights = _node_document_weights(nodes)
if not document_weights:
return empty_taxonomy_candidates()
# Only .tags.all() needs prefetching (a reverse M2M, one extra query for
# the whole batch). document_type/correspondent/storage_path are read
+22 -306
View File
@@ -1,5 +1,4 @@
import datetime
from collections.abc import Generator
from types import SimpleNamespace
from unittest.mock import MagicMock
from unittest.mock import patch
@@ -7,24 +6,18 @@ from unittest.mock import patch
import pytest
import pytest_mock
from django.test import override_settings
from guardian.shortcuts import assign_perm
from guardian.shortcuts import remove_perm
from documents.models import Document
from documents.search import TantivyBackend
from documents.tests.factories import DocumentFactory
from documents.tests.factories import TagFactory
from documents.tests.factories import UserFactory
from paperless.config import AIConfig
from paperless_ai.ai_classifier import TAXONOMY_CANDIDATE_TOP_K
from paperless_ai.ai_classifier import _fulltext_similar_documents
from paperless_ai.ai_classifier import build_localization_prompt
from paperless_ai.ai_classifier import build_prompt_with_rag
from paperless_ai.ai_classifier import build_prompt_without_rag
from paperless_ai.ai_classifier import get_ai_document_classification
from paperless_ai.ai_classifier import get_language_name
from paperless_ai.ai_classifier import get_taxonomy_context
from paperless_ai.taxonomy import SimilarDocument
from paperless_ai.taxonomy import TaxonomyCandidate
from paperless_ai.taxonomy import TaxonomyCandidates
@@ -227,10 +220,12 @@ def test_use_rag_if_configured(
@pytest.mark.django_db
@patch("paperless_ai.client.AIClient.run_llm_query")
@patch("paperless_ai.ai_classifier.build_prompt_with_rag")
@patch("paperless_ai.ai_classifier.build_prompt_without_rag")
@patch("paperless_ai.ai_classifier.AIConfig")
@override_settings(LLM_BACKEND="ollama", LLM_MODEL="some_model")
def test_use_rag_prompt_even_without_embedding_backend(
mock_build_prompt_with_rag,
def test_use_without_rag_if_not_configured(
mock_ai_config,
mock_build_prompt_without_rag,
mock_run_llm_query,
mock_document,
):
@@ -240,13 +235,13 @@ def test_use_rag_prompt_even_without_embedding_backend(
WHEN:
- get_ai_document_classification() is called
THEN:
- The RAG-context prompt builder is still used (fed by the full-text
fallback's context/candidates instead of the vector store's)
- The non-RAG prompt builder is used
"""
mock_build_prompt_with_rag.return_value = "Prompt with RAG"
mock_ai_config.return_value.llm_embedding_backend = None
mock_build_prompt_without_rag.return_value = "Prompt without RAG"
mock_run_llm_query.return_value = NESTED_SUGGESTIONS
get_ai_document_classification(mock_document)
mock_build_prompt_with_rag.assert_called_once()
mock_build_prompt_without_rag.assert_called_once()
@pytest.mark.django_db
@@ -325,7 +320,6 @@ def test_build_localization_prompt_preserves_unicode_characters():
@pytest.mark.django_db
@override_settings(LLM_EMBEDDING_BACKEND="huggingface")
def test_get_taxonomy_context_assembles_rag_text_and_candidates():
"""
GIVEN:
@@ -360,7 +354,6 @@ def test_get_taxonomy_context_assembles_rag_text_and_candidates():
@pytest.mark.django_db
@override_settings(LLM_EMBEDDING_BACKEND="huggingface")
def test_get_taxonomy_context_preserves_similarity_order_and_distinct_documents():
"""
GIVEN:
@@ -431,7 +424,6 @@ def test_get_taxonomy_context_preserves_similarity_order_and_distinct_documents(
@pytest.mark.django_db
@override_settings(LLM_EMBEDDING_BACKEND="huggingface")
def test_get_taxonomy_context_no_similar_docs():
"""
GIVEN:
@@ -455,67 +447,6 @@ def test_get_taxonomy_context_no_similar_docs():
}
@pytest.mark.django_db
def test_get_taxonomy_context_uses_fulltext_fallback_when_no_embedding_backend(
mocker: pytest_mock.MockerFixture,
) -> None:
"""
GIVEN:
- No LLM embedding backend is configured (the default test settings)
WHEN:
- get_taxonomy_context() is called
THEN:
- _fulltext_similar_documents() is called with the document, the user
and TAXONOMY_CANDIDATE_TOP_K
- retrieve_similar_nodes() (the vector path) is never called
"""
document = DocumentFactory.create(content="Some content")
mock_fulltext = mocker.patch(
"paperless_ai.ai_classifier._fulltext_similar_documents",
return_value=[],
)
mock_retrieve = mocker.patch("paperless_ai.ai_classifier.retrieve_similar_nodes")
get_taxonomy_context(document, user=None)
mock_fulltext.assert_called_once_with(
document,
None,
top_k=TAXONOMY_CANDIDATE_TOP_K,
)
mock_retrieve.assert_not_called()
@pytest.mark.django_db
@override_settings(LLM_EMBEDDING_BACKEND="huggingface")
def test_get_taxonomy_context_uses_vector_path_when_embedding_backend_configured(
mocker: pytest_mock.MockerFixture,
) -> None:
"""
GIVEN:
- An LLM embedding backend is configured
WHEN:
- get_taxonomy_context() is called
THEN:
- retrieve_similar_nodes() (the vector path) is called
- _fulltext_similar_documents() (the no-embedding-backend fallback)
is never called
"""
document = DocumentFactory.create(content="Some content")
mock_retrieve = mocker.patch(
"paperless_ai.ai_classifier.retrieve_similar_nodes",
return_value=[],
)
mock_fulltext = mocker.patch(
"paperless_ai.ai_classifier._fulltext_similar_documents",
)
get_taxonomy_context(document, user=None)
mock_retrieve.assert_called_once()
mock_fulltext.assert_not_called()
class TestGetTaxonomyContextVisibility:
"""get_taxonomy_context must not materialize every visible document id
for a user who can already see the whole library: a superuser (like no
@@ -528,7 +459,6 @@ class TestGetTaxonomyContextVisibility:
"""
@pytest.mark.django_db
@override_settings(LLM_EMBEDDING_BACKEND="huggingface")
def test_skips_permission_lookup_for_superuser(
self,
mocker: pytest_mock.MockerFixture,
@@ -547,18 +477,17 @@ class TestGetTaxonomyContextVisibility:
"paperless_ai.ai_classifier.retrieve_similar_nodes",
return_value=[],
)
mock_permitted = mocker.patch(
"paperless_ai.ai_classifier.permitted_object_ids",
mock_get_objects = mocker.patch(
"paperless_ai.ai_classifier.get_objects_for_user_owner_aware",
)
user = UserFactory.create(is_superuser=True)
get_taxonomy_context(document, user)
mock_permitted.assert_not_called()
mock_get_objects.assert_not_called()
assert mock_retrieve.call_args.kwargs["document_ids"] is None
@pytest.mark.django_db
@override_settings(LLM_EMBEDDING_BACKEND="huggingface")
def test_skips_permission_lookup_when_no_user(
self,
mocker: pytest_mock.MockerFixture,
@@ -577,17 +506,16 @@ class TestGetTaxonomyContextVisibility:
"paperless_ai.ai_classifier.retrieve_similar_nodes",
return_value=[],
)
mock_permitted = mocker.patch(
"paperless_ai.ai_classifier.permitted_object_ids",
mock_get_objects = mocker.patch(
"paperless_ai.ai_classifier.get_objects_for_user_owner_aware",
)
get_taxonomy_context(document, None)
mock_permitted.assert_not_called()
mock_get_objects.assert_not_called()
assert mock_retrieve.call_args.kwargs["document_ids"] is None
@pytest.mark.django_db
@override_settings(LLM_EMBEDDING_BACKEND="huggingface")
def test_restricts_to_visible_documents_for_non_superuser(
self,
mocker: pytest_mock.MockerFixture,
@@ -598,7 +526,7 @@ class TestGetTaxonomyContextVisibility:
WHEN:
- get_taxonomy_context() is called
THEN:
- The user's permitted document ids are looked up and passed to
- The user's visible document ids are looked up and passed to
retrieve_similar_nodes() as a restriction
"""
document = DocumentFactory.create(content="Some content")
@@ -606,232 +534,21 @@ class TestGetTaxonomyContextVisibility:
"paperless_ai.ai_classifier.retrieve_similar_nodes",
return_value=[],
)
mock_permitted = mocker.patch(
"paperless_ai.ai_classifier.permitted_object_ids",
return_value=[1, 2, 3],
mock_queryset = mocker.MagicMock()
mock_queryset.values_list.return_value = [1, 2, 3]
mock_get_objects = mocker.patch(
"paperless_ai.ai_classifier.get_objects_for_user_owner_aware",
return_value=mock_queryset,
)
user = UserFactory.create(is_superuser=False)
get_taxonomy_context(document, user)
mock_permitted.assert_called_once_with(user, Document, "view_document")
mock_get_objects.assert_called_once_with(user, "view_document", Document)
assert mock_retrieve.call_args.kwargs["document_ids"] == [1, 2, 3]
@pytest.mark.django_db
class TestFulltextSimilarDocuments:
"""_fulltext_similar_documents is the no-embedding-backend fallback: it
asks the Tantivy full-text index for "More Like This" neighbours instead
of the vector store, and synthesizes a rank-based weight since Tantivy's
more_like_this_ids returns only an ordered id list, no scores.
"""
@pytest.fixture
def fulltext_backend(
self,
mocker: pytest_mock.MockerFixture,
) -> Generator[TantivyBackend, None, None]:
"""An in-memory Tantivy backend, wired up as the module-level
singleton _fulltext_similar_documents resolves via get_backend()."""
backend = TantivyBackend(path=None)
backend.open()
mocker.patch("documents.search.get_backend", return_value=backend)
try:
yield backend
finally:
backend.close()
def test_ranks_by_rank_based_weight_descending(
self,
fulltext_backend: TantivyBackend,
) -> None:
"""
GIVEN:
- A source document and two similar documents indexed in Tantivy
WHEN:
- _fulltext_similar_documents() is called
THEN:
- Each result's weight reflects its rank (first result weighted
higher than the second), not a raw similarity score
"""
source = DocumentFactory.create(content="quarterly financial report details")
first = DocumentFactory.create(content="quarterly financial report details")
second = DocumentFactory.create(content="financial report")
for doc in (source, first, second):
fulltext_backend.add_or_update(doc)
result = _fulltext_similar_documents(source, user=None, top_k=5)
assert len(result) == 2
weight_by_id = {s["document_id"]: s["weight"] for s in result}
assert weight_by_id[first.pk] > weight_by_id[second.pk]
def test_excludes_source_document(
self,
fulltext_backend: TantivyBackend,
) -> None:
"""
GIVEN:
- A source document indexed in Tantivy with no other documents
WHEN:
- _fulltext_similar_documents() is called
THEN:
- An empty list is returned - the source document is never its
own similar document
"""
source = DocumentFactory.create(content="unique unrelated content")
fulltext_backend.add_or_update(source)
result = _fulltext_similar_documents(source, user=None, top_k=5)
assert result == []
def test_empty_index_returns_empty_list(
self,
fulltext_backend: TantivyBackend,
) -> None:
"""
GIVEN:
- A document that has never been indexed (fresh/empty Tantivy index)
WHEN:
- _fulltext_similar_documents() is called
THEN:
- An empty list is returned rather than raising
"""
source = DocumentFactory.create(content="never indexed")
result = _fulltext_similar_documents(source, user=None, top_k=5)
assert result == []
def test_respects_top_k_limit(
self,
fulltext_backend: TantivyBackend,
) -> None:
"""
GIVEN:
- A source document and four similar documents indexed
WHEN:
- _fulltext_similar_documents() is called with top_k=2
THEN:
- At most 2 results are returned
"""
source = DocumentFactory.create(content="shared overlapping keyword text")
fulltext_backend.add_or_update(source)
for _ in range(4):
fulltext_backend.add_or_update(
DocumentFactory.create(content="shared overlapping keyword text"),
)
result = _fulltext_similar_documents(source, user=None, top_k=2)
assert len(result) == 2
def test_result_shape_is_similar_document(
self,
fulltext_backend: TantivyBackend,
) -> None:
"""
GIVEN:
- A source document and one similar document indexed
WHEN:
- _fulltext_similar_documents() is called
THEN:
- Each result is a SimilarDocument (document_id + weight only)
"""
source = DocumentFactory.create(content="shared content phrase")
other = DocumentFactory.create(content="shared content phrase")
fulltext_backend.add_or_update(source)
fulltext_backend.add_or_update(other)
result = _fulltext_similar_documents(source, user=None, top_k=5)
# rank 0 (the only/best result) with top_k=5 -> weight = top_k - rank = 5.0,
# per the "first result gets top_k, the last gets 1" formula.
assert result == [SimilarDocument(document_id=other.pk, weight=5.0)]
def test_superuser_sees_other_users_documents(
self,
fulltext_backend: TantivyBackend,
) -> None:
"""
GIVEN:
- A source document owned by one user and a similar document
owned by a different user, with no sharing between them
WHEN:
- _fulltext_similar_documents() is called with a superuser
THEN:
- The other user's document is still returned as a similar
document - a superuser must not be narrowed by the backend's
owner-based permission filter
"""
owner = UserFactory.create()
other_owner = UserFactory.create()
superuser = UserFactory.create(is_superuser=True)
source = DocumentFactory.create(
content="shared content phrase",
owner=owner,
)
other = DocumentFactory.create(
content="shared content phrase",
owner=other_owner,
)
fulltext_backend.add_or_update(source)
fulltext_backend.add_or_update(other)
result = _fulltext_similar_documents(source, user=superuser, top_k=5)
assert [s["document_id"] for s in result] == [other.pk]
def test_excludes_stale_permitted_document_for_regular_user(
self,
fulltext_backend: TantivyBackend,
) -> None:
"""
GIVEN:
- A regular (non-superuser) user
- A similar document the user is permitted to view, and another
similar document indexed while the user still had view
permission but which has since had that permission revoked in
the database, i.e. the Tantivy index has stale permission data
WHEN:
- _fulltext_similar_documents() is called with that user
THEN:
- Only the still-permitted document is returned - the DB
re-check via restrict_queryset_to_visible() must catch the
document Tantivy's stale index still thinks is visible
"""
owner = UserFactory.create()
viewer = UserFactory.create(is_superuser=False)
source = DocumentFactory.create(
content="shared content phrase",
owner=owner,
)
permitted = DocumentFactory.create(
content="shared content phrase",
owner=owner,
)
now_private = DocumentFactory.create(
content="shared content phrase",
owner=owner,
)
assign_perm("view_document", viewer, permitted)
assign_perm("view_document", viewer, now_private)
fulltext_backend.add_or_update(source)
fulltext_backend.add_or_update(permitted)
fulltext_backend.add_or_update(now_private)
# Revoke access after indexing, without reindexing: the index still
# carries viewer as a permitted viewer for `now_private`.
remove_perm("view_document", viewer, now_private)
result = _fulltext_similar_documents(source, user=viewer, top_k=5)
assert [s["document_id"] for s in result] == [permitted.pk]
@pytest.mark.django_db
@override_settings(LLM_EMBEDDING_BACKEND="huggingface")
@patch("paperless_ai.ai_classifier.retrieve_similar_nodes")
def test_get_taxonomy_context_retrieval_failure_degrades_to_no_hints(mock_retrieve):
"""
@@ -858,7 +575,6 @@ def test_get_taxonomy_context_retrieval_failure_degrades_to_no_hints(mock_retrie
@pytest.mark.django_db
@override_settings(LLM_EMBEDDING_BACKEND="huggingface")
@patch("paperless_ai.ai_classifier.build_taxonomy_candidates")
@patch("paperless_ai.ai_classifier.retrieve_similar_nodes")
def test_get_taxonomy_context_candidate_building_failure_degrades_to_no_hints(
+5 -3
View File
@@ -1188,7 +1188,9 @@ class TestRetrieveSimilarNodesAgainstRealIndex:
nodes = indexing.retrieve_similar_nodes(a, document_ids=[b.id])
assert all(int(node.metadata["document_id"]) == b.id for node in nodes)
assert all(
document_id == b.id for document_id in indexing._node_document_ids(nodes)
)
def test_excludes_self(
self,
@@ -1210,7 +1212,7 @@ class TestRetrieveSimilarNodesAgainstRealIndex:
nodes = indexing.retrieve_similar_nodes(a, top_k=5)
assert {int(node.metadata["document_id"]) for node in nodes} == {b.id}
assert set(indexing._node_document_ids(nodes)) == {b.id}
def test_excludes_self_with_multiple_chunks(
self,
@@ -1233,4 +1235,4 @@ class TestRetrieveSimilarNodesAgainstRealIndex:
nodes = indexing.retrieve_similar_nodes(a, top_k=3)
assert {int(node.metadata["document_id"]) for node in nodes} == {b.id}
assert set(indexing._node_document_ids(nodes)) == {b.id}
-48
View File
@@ -4,7 +4,6 @@ from unittest.mock import MagicMock
from unittest.mock import patch
import httpx
import ollama
import openai
import pytest
from llama_index.core.llms.llm import ToolSelection
@@ -12,7 +11,6 @@ from llama_index.core.llms.llm import ToolSelection
from paperless_ai.client import LLM_SYSTEM_PROMPT
from paperless_ai.client import PLACEHOLDER_API_KEY
from paperless_ai.client import AIClient
from paperless_ai.exceptions import LLMProviderError
from paperless_ai.exceptions import LLMTimeoutError
@@ -216,52 +214,6 @@ def test_run_llm_query_openai_timeout_raises_local_error(
client.run_llm_query("test_prompt")
def test_run_llm_query_openai_status_error_raises_provider_error(
mock_ai_config,
mock_openai_llm,
):
mock_ai_config.llm_backend = "openai-like"
mock_ai_config.llm_model = "test_model"
mock_ai_config.llm_endpoint = "http://test-url"
request = httpx.Request("POST", "http://test-url/v1/chat/completions")
body = {"error": {"message": "Thinking mode does not support this tool_choice"}}
mock_openai_llm.return_value.chat_with_tools.side_effect = openai.BadRequestError(
"Error code: 400",
response=httpx.Response(400, request=request, json=body),
body=body,
)
client = AIClient()
with pytest.raises(LLMProviderError) as exc_info:
client.run_llm_query("test_prompt")
assert str(exc_info.value) == ""
assert isinstance(exc_info.value.__cause__, openai.BadRequestError)
def test_run_llm_query_ollama_response_error_raises_provider_error(
mock_ai_config,
mock_ollama_llm,
):
mock_ai_config.llm_backend = "ollama"
mock_ai_config.llm_model = "test_model"
mock_ai_config.llm_endpoint = "http://test-url"
response_error = ollama.ResponseError(
"confidential provider response",
status_code=400,
)
mock_ollama_llm.return_value.chat.side_effect = response_error
client = AIClient()
with pytest.raises(LLMProviderError) as exc_info:
client.run_llm_query("test_prompt")
assert str(exc_info.value) == ""
assert exc_info.value.__cause__ is response_error
def test_run_llm_query_httpx_timeout_raises_local_error(
mock_ai_config,
mock_ollama_llm,
+31 -33
View File
@@ -1,4 +1,5 @@
import json
from types import SimpleNamespace
import pytest
import pytest_mock
@@ -9,14 +10,14 @@ from documents.tests.factories import DocumentTypeFactory
from documents.tests.factories import StoragePathFactory
from documents.tests.factories import TagFactory
from documents.tests.factories import UserFactory
from paperless_ai.taxonomy import SimilarDocument
from paperless_ai.taxonomy import TaxonomyCandidates
from paperless_ai.taxonomy import build_taxonomy_candidates
from paperless_ai.taxonomy import format_taxonomy_for_prompt
def make_similar(document_id: int, weight: float) -> SimilarDocument:
return SimilarDocument(document_id=document_id, weight=weight)
def make_node(document_id: int, score: float) -> SimpleNamespace:
"""A stand-in for NodeWithScore: only ``.metadata``/``.score`` are read."""
return SimpleNamespace(metadata={"document_id": str(document_id)}, score=score)
@pytest.mark.django_db
@@ -52,9 +53,9 @@ class TestBuildTaxonomyCandidates:
doc_a.tags.add(tag)
doc_b = DocumentFactory.create()
doc_b.tags.add(tag)
similar_documents = [make_similar(doc_a.pk, 0.9), make_similar(doc_b.pk, 0.4)]
nodes = [make_node(doc_a.pk, 0.9), make_node(doc_b.pk, 0.4)]
result = build_taxonomy_candidates(similar_documents, user=None)
result = build_taxonomy_candidates(nodes, user=None)
assert len(result["tags"]) == 1
assert result["tags"][0]["id"] == tag.pk
@@ -79,9 +80,9 @@ class TestBuildTaxonomyCandidates:
document.tags.add(tag)
tag.name = "New Name"
tag.save()
similar_documents = [make_similar(document.pk, 0.5)]
nodes = [make_node(document.pk, 0.5)]
result = build_taxonomy_candidates(similar_documents, user=None)
result = build_taxonomy_candidates(nodes, user=None)
assert result["tags"][0]["name"] == "New Name"
@@ -101,9 +102,9 @@ class TestBuildTaxonomyCandidates:
document = DocumentFactory.create()
document.tags.add(tag)
tag.delete()
similar_documents = [make_similar(document.pk, 0.5)]
nodes = [make_node(document.pk, 0.5)]
result = build_taxonomy_candidates(similar_documents, user=None)
result = build_taxonomy_candidates(nodes, user=None)
assert result["tags"] == []
@@ -122,12 +123,9 @@ class TestBuildTaxonomyCandidates:
strong_doc.tags.add(strong_tag)
weak_doc = DocumentFactory.create()
weak_doc.tags.add(weak_tag)
similar_documents = [
make_similar(strong_doc.pk, 0.9),
make_similar(weak_doc.pk, 0.1),
]
nodes = [make_node(strong_doc.pk, 0.9), make_node(weak_doc.pk, 0.1)]
result = build_taxonomy_candidates(similar_documents, user=None)
result = build_taxonomy_candidates(nodes, user=None)
assert [c["name"] for c in result["tags"]] == ["Strong", "Weak"]
@@ -143,9 +141,9 @@ class TestBuildTaxonomyCandidates:
document = DocumentFactory.create()
for i in range(15):
document.tags.add(TagFactory.create(name=f"Tag{i}"))
similar_documents = [make_similar(document.pk, 0.5)]
nodes = [make_node(document.pk, 0.5)]
result = build_taxonomy_candidates(similar_documents, user=None)
result = build_taxonomy_candidates(nodes, user=None)
assert len(result["tags"]) == 10
@@ -159,12 +157,12 @@ class TestBuildTaxonomyCandidates:
- Only 5 correspondents are returned
"""
correspondents = CorrespondentFactory.create_batch(7)
similar_documents = [
make_similar(DocumentFactory.create(correspondent=c).pk, 0.5)
nodes = [
make_node(DocumentFactory.create(correspondent=c).pk, 0.5)
for c in correspondents
]
result = build_taxonomy_candidates(similar_documents, user=None)
result = build_taxonomy_candidates(nodes, user=None)
assert len(result["correspondents"]) == 5
@@ -179,9 +177,9 @@ class TestBuildTaxonomyCandidates:
"""
document_type = DocumentTypeFactory.create(name="Invoice")
document = DocumentFactory.create(document_type=document_type)
similar_documents = [make_similar(document.pk, 0.5)]
nodes = [make_node(document.pk, 0.5)]
result = build_taxonomy_candidates(similar_documents, user=None)
result = build_taxonomy_candidates(nodes, user=None)
assert len(result["document_types"]) == 1
assert result["document_types"][0]["id"] == document_type.pk
@@ -197,12 +195,12 @@ class TestBuildTaxonomyCandidates:
- Only 5 document_types are returned
"""
document_types = DocumentTypeFactory.create_batch(7)
similar_documents = [
make_similar(DocumentFactory.create(document_type=dt).pk, 0.5)
nodes = [
make_node(DocumentFactory.create(document_type=dt).pk, 0.5)
for dt in document_types
]
result = build_taxonomy_candidates(similar_documents, user=None)
result = build_taxonomy_candidates(nodes, user=None)
assert len(result["document_types"]) == 5
@@ -217,9 +215,9 @@ class TestBuildTaxonomyCandidates:
"""
storage_path = StoragePathFactory.create(name="Invoices")
document = DocumentFactory.create(storage_path=storage_path)
similar_documents = [make_similar(document.pk, 0.5)]
nodes = [make_node(document.pk, 0.5)]
result = build_taxonomy_candidates(similar_documents, user=None)
result = build_taxonomy_candidates(nodes, user=None)
assert len(result["storage_paths"]) == 1
assert result["storage_paths"][0]["id"] == storage_path.pk
@@ -235,12 +233,12 @@ class TestBuildTaxonomyCandidates:
- Only 5 storage_paths are returned
"""
storage_paths = StoragePathFactory.create_batch(7)
similar_documents = [
make_similar(DocumentFactory.create(storage_path=sp).pk, 0.5)
nodes = [
make_node(DocumentFactory.create(storage_path=sp).pk, 0.5)
for sp in storage_paths
]
result = build_taxonomy_candidates(similar_documents, user=None)
result = build_taxonomy_candidates(nodes, user=None)
assert len(result["storage_paths"]) == 5
@@ -260,14 +258,14 @@ class TestBuildTaxonomyCandidates:
tag = TagFactory.create(name="Restricted")
document = DocumentFactory.create()
document.tags.add(tag)
similar_documents = [make_similar(document.pk, 0.5)]
nodes = [make_node(document.pk, 0.5)]
user = UserFactory.create()
mocker.patch(
"documents.permissions.permitted_object_ids",
return_value=[], # user cannot see this tag
)
result = build_taxonomy_candidates(similar_documents, user=user)
result = build_taxonomy_candidates(nodes, user=user)
assert result["tags"] == []
@@ -297,10 +295,10 @@ class TestBuildTaxonomyCandidates:
tag.save()
document = DocumentFactory.create()
document.tags.add(tag)
similar_documents = [make_similar(document.pk, 0.5)]
nodes = [make_node(document.pk, 0.5)]
spy = mocker.patch("documents.permissions.permitted_object_ids")
result = build_taxonomy_candidates(similar_documents, user=None)
result = build_taxonomy_candidates(nodes, user=None)
assert result["tags"][0]["name"] == "Owned"
spy.assert_not_called()
+8
View File
@@ -0,0 +1,8 @@
from django.apps import AppConfig
from django.utils.translation import gettext_lazy as _
class PaperlessBenchmarkConfig(AppConfig):
name = "paperless_benchmark"
verbose_name = _("Paperless benchmark")
+136
View File
@@ -0,0 +1,136 @@
from __future__ import annotations
from typing import TYPE_CHECKING
from django.db import connection
if TYPE_CHECKING:
from django.db.models import QuerySet
def _reset_table_names() -> list[str]:
from guardian.models import GroupObjectPermission
from guardian.models import UserObjectPermission
from documents.models import Correspondent
from documents.models import Document
from documents.models import DocumentType
from documents.models import StoragePath
from documents.models import Tag
return [
Document.tags.through._meta.db_table,
Document._meta.db_table,
Tag._meta.db_table,
Correspondent._meta.db_table,
DocumentType._meta.db_table,
StoragePath._meta.db_table,
UserObjectPermission._meta.db_table,
GroupObjectPermission._meta.db_table,
]
def _delete_all_users_and_groups() -> None:
# ASSUMPTION: this tool assumes a disposable benchmark database, never
# point it at a real install. This deletes EVERY user and group in the
# database (not just benchmark-created ones) -- there is no way to
# distinguish "real" users from seeded ones, so this is only safe against
# a database that exists solely to run this benchmarking tool. The
# `benchmark seed --reset` CLI path requires an explicit
# `--yes-i-know-this-wipes-the-database` flag before reaching here; do
# not remove that guard.
from django.contrib.auth import get_user_model
from django.contrib.auth.models import Group
get_user_model().objects.all().delete()
Group.objects.all().delete()
def _reset_postgresql() -> None:
tables = _reset_table_names()
with connection.cursor() as cursor:
cursor.execute(f"TRUNCATE TABLE {', '.join(tables)} RESTART IDENTITY CASCADE;")
_delete_all_users_and_groups()
def _reset_mariadb() -> None:
# MariaDB's TRUNCATE has no CASCADE clause and refuses to truncate a
# table referenced by a foreign key while checks are enabled, so
# checks are disabled for the duration of the reset.
tables = _reset_table_names()
with connection.cursor() as cursor:
cursor.execute("SET FOREIGN_KEY_CHECKS = 0;")
try:
for table in tables:
cursor.execute(f"TRUNCATE TABLE {table};")
finally:
cursor.execute("SET FOREIGN_KEY_CHECKS = 1;")
_delete_all_users_and_groups()
def _reset_sqlite() -> None:
from documents.models import Correspondent
from documents.models import Document
from documents.models import DocumentType
from documents.models import StoragePath
from documents.models import Tag
Document.global_objects.all().delete()
Tag.objects.all().delete()
Correspondent.objects.all().delete()
DocumentType.objects.all().delete()
StoragePath.objects.all().delete()
_delete_all_users_and_groups()
def reset_benchmark_data() -> None:
"""
Remove all previously-seeded benchmark data (documents, tags,
correspondents, document types, storage paths, guardian permission
rows, users, and groups) so a fresh `benchmark seed` run starts
from an empty slate. Dispatches per-backend because TRUNCATE syntax
and cascade behavior differ across the 3 supported databases.
"""
if connection.vendor == "postgresql":
_reset_postgresql()
elif connection.vendor == "mysql":
# MariaDB also reports vendor == "mysql" under Django's mysql backend.
_reset_mariadb()
else:
_reset_sqlite()
def capture_explain(queryset: QuerySet) -> str:
"""
Return the query plan for `queryset` using the current backend's
explain facility. PostgreSQL supports `EXPLAIN ANALYZE {sql}` (real
execution stats). MariaDB does NOT accept that syntax -- verified
against a real MariaDB 12.3 container: `EXPLAIN ANALYZE {sql}` raises a
1064 syntax error, while MariaDB's own `ANALYZE {sql}` form (no
`EXPLAIN` keyword) works and returns real per-row execution stats
(`r_rows`, `r_filtered`, etc. columns) -- this is MariaDB's
EXPLAIN-ANALYZE-equivalent, distinct from MySQL 8.0.18+'s
`EXPLAIN ANALYZE` syntax, which MariaDB does not implement. SQLite only
supports EXPLAIN QUERY PLAN (the chosen plan, not real timing/row
counts) -- that output is clearly labeled rather than silently looking
equivalent to the other two backends' output.
"""
sql, params = queryset.query.sql_with_params()
with connection.cursor() as cursor:
if connection.vendor == "postgresql":
cursor.execute(f"EXPLAIN ANALYZE {sql}", params)
return "\n".join(str(row[0]) for row in cursor.fetchall())
if connection.vendor == "mysql":
# MariaDB also reports vendor == "mysql" under Django's mysql
# backend. Unlike MySQL 8.0.18+, MariaDB has no `EXPLAIN
# ANALYZE` syntax -- its equivalent is `ANALYZE <statement>`.
cursor.execute(f"ANALYZE {sql}", params)
columns = [c[0] for c in cursor.description]
header = " | ".join(columns)
rows = "\n".join(
" | ".join(str(c) for c in row) for row in cursor.fetchall()
)
return f"{header}\n{rows}"
cursor.execute(f"EXPLAIN QUERY PLAN {sql}", params)
rows = "\n".join(" | ".join(str(c) for c in row) for row in cursor.fetchall())
return f"(plan only -- no execution stats on SQLite)\n{rows}"
+81
View File
@@ -0,0 +1,81 @@
# src/paperless_benchmark/endpoints.py
from __future__ import annotations
import statistics
import time
from dataclasses import dataclass
from typing import TYPE_CHECKING
if TYPE_CHECKING:
from django.contrib.auth.models import User
from rest_framework.test import APIClient
ENDPOINTS: tuple[tuple[str, str], ...] = (
("documents_default", "/api/documents/"),
("documents_page50", "/api/documents/?page_size=50"),
("tags_all", "/api/tags/?page_size=100000"),
)
@dataclass(frozen=True, slots=True)
class EndpointTiming:
user_label: str
endpoint_name: str
query_count: int
min_ms: float
median_ms: float
max_ms: float
def _timed_requests(client: APIClient, url: str, n: int) -> list[float]:
times = []
for _ in range(n):
t0 = time.perf_counter()
resp = client.get(url)
t1 = time.perf_counter()
if resp.status_code != 200:
raise RuntimeError(
f"GET {url} -> {resp.status_code}: {resp.content[:300]!r}",
)
times.append(t1 - t0)
return times
def _query_count(client: APIClient, url: str) -> int:
from django.db import connection
from django.test.utils import CaptureQueriesContext
with CaptureQueriesContext(connection) as ctx:
resp = client.get(url)
if resp.status_code != 200:
raise RuntimeError(f"GET {url} -> {resp.status_code}: {resp.content[:300]!r}")
return len(ctx.captured_queries)
def run_endpoint_benchmarks(
*,
perf_target: User,
perf_admin: User,
repeat: int,
) -> list[EndpointTiming]:
from rest_framework.test import APIClient
results: list[EndpointTiming] = []
for user_label, user in (("target", perf_target), ("admin", perf_admin)):
client = APIClient()
client.force_authenticate(user=user)
for name, url in ENDPOINTS:
client.get(url) # warm-up request, not counted
qcount = _query_count(client, url)
times_ms = [t * 1000 for t in _timed_requests(client, url, repeat)]
results.append(
EndpointTiming(
user_label=user_label,
endpoint_name=name,
query_count=qcount,
min_ms=min(times_ms),
median_ms=statistics.median(times_ms),
max_ms=max(times_ms),
),
)
return results
+56
View File
@@ -0,0 +1,56 @@
# src/paperless_benchmark/harness.py
from __future__ import annotations
import time
from dataclasses import dataclass
from typing import TYPE_CHECKING
from typing import Generic
from typing import TypeVar
from django.db import connection
from django.test.utils import CaptureQueriesContext
if TYPE_CHECKING:
from collections.abc import Callable
T = TypeVar("T")
@dataclass(frozen=True, slots=True)
class ProfileResult(Generic[T]):
best_seconds: float
all_seconds: tuple[float, ...]
query_count: int
result: T
def run_profile(fn: Callable[[], T], *, repeat: int = 5) -> ProfileResult[T]:
"""
Call `fn` `repeat` times, capturing wall-clock time for every call and
the SQL query count for the final call. Returns the best (minimum)
time across all repeats, since the first call(s) can be skewed by
connection warm-up or cold caches.
"""
if repeat < 1:
raise ValueError("repeat must be >= 1")
all_seconds: list[float] = []
result: T | None = None
query_count = 0
for i in range(repeat):
with CaptureQueriesContext(connection) as ctx:
start = time.perf_counter()
result = fn()
all_seconds.append(time.perf_counter() - start)
if i == repeat - 1:
query_count = len(ctx.captured_queries)
# Purely a type-narrowing aid for the type checker: the `repeat < 1`
# guard above already turns the one case that could leave `result`
# unset into a clear ValueError, so this is unreachable in practice.
assert result is not None
return ProfileResult(
best_seconds=min(all_seconds),
all_seconds=tuple(all_seconds),
query_count=query_count,
result=result,
)
@@ -0,0 +1,222 @@
# src/paperless_benchmark/management/commands/benchmark.py
from __future__ import annotations
from typing import Any
from django.core.management.base import BaseCommand
from django.core.management.base import CommandError
from django.core.management.base import CommandParser
class Command(BaseCommand):
help = "Seed, run, and profile paperless-ngx performance benchmarks."
def add_arguments(self, parser: CommandParser) -> None:
parser.add_argument(
"action",
choices=["seed", "run", "profile", "list-scenarios"],
help="Which benchmark action to perform.",
)
parser.add_argument(
"scenario",
nargs="?",
default=None,
help="Scenario name (required for `profile`; see `list-scenarios`).",
)
parser.add_argument(
"--tier",
choices=["home", "medium", "large"],
default="medium",
help="Dataset scale tier for `seed` (default: medium).",
)
parser.add_argument(
"--reset",
action="store_true",
default=False,
help="For `seed`: truncate existing benchmark data first.",
)
parser.add_argument(
"--yes-i-know-this-wipes-the-database",
action="store_true",
default=False,
help=(
"Required alongside --reset: confirms you understand `seed "
"--reset` deletes ALL users, ALL groups, and ALL documents/"
"tags/correspondents/document types/storage paths in this "
"database, not just benchmark-created ones."
),
)
parser.add_argument(
"--seed",
type=int,
default=42,
help="RNG seed for reproducible datasets (default: 42).",
)
parser.add_argument(
"--repeat",
type=int,
default=5,
help="Number of timed repetitions for `run`/`profile` (default: 5).",
)
parser.add_argument(
"--label",
default="baseline",
help="Free-text tag for a `run`, printed and recorded in history only.",
)
parser.add_argument(
"--explain",
action="store_true",
default=False,
help="For `profile`: also capture and print the query plan.",
)
def handle(self, *args: Any, **options: Any) -> None:
action = options["action"]
if action == "seed":
self._handle_seed(options)
elif action == "run":
self._handle_run(options)
elif action == "profile":
self._handle_profile(options)
else:
self._handle_list_scenarios()
def _handle_seed(self, options: dict[str, Any]) -> None:
from paperless_benchmark.db import reset_benchmark_data
from paperless_benchmark.seeding import seed_benchmark_dataset
if options["reset"]:
if not options["yes_i_know_this_wipes_the_database"]:
raise CommandError(
"--reset requires --yes-i-know-this-wipes-the-database. "
"This deletes ALL users, ALL groups, and ALL documents, "
"tags, correspondents, document types, and storage paths "
"in this database -- not just benchmark-created ones. "
"Only run this against a disposable benchmark database, "
"never a real install. Re-run with "
"--reset --yes-i-know-this-wipes-the-database to proceed.",
)
self.stdout.write("Resetting existing benchmark data...")
reset_benchmark_data()
data = seed_benchmark_dataset(options["tier"], seed=options["seed"])
self.stdout.write(
self.style.SUCCESS(
f"Seeded tier={options['tier']!r}: {data.documents} documents, "
f"{len(data.users)} users, {len(data.groups)} groups.",
),
)
def _handle_run(self, options: dict[str, Any]) -> None:
from django.contrib.auth import get_user_model
from django.db import connection
from documents.models import Document
from paperless_benchmark.endpoints import run_endpoint_benchmarks
from paperless_benchmark.results import append_history
user_model = get_user_model()
try:
perf_target = user_model.objects.get(username="perf_target")
perf_admin = user_model.objects.get(username="perf_admin")
except user_model.DoesNotExist as e:
raise CommandError(
"No benchmark dataset found. Run `manage.py benchmark seed` first.",
) from e
db_vendor = connection.vendor
document_count = Document.objects.count()
results = run_endpoint_benchmarks(
perf_target=perf_target,
perf_admin=perf_admin,
repeat=options["repeat"],
)
self.stdout.write(f"# label={options['label']} repeat={options['repeat']}")
self.stdout.write(
f"{'user':7s} {'endpoint':20s} {'queries':>8s} "
f"{'min_ms':>9s} {'median_ms':>10s} {'max_ms':>9s}",
)
for r in results:
self.stdout.write(
f"{r.user_label:7s} {r.endpoint_name:20s} {r.query_count:8d} "
f"{r.min_ms:9.1f} {r.median_ms:10.1f} {r.max_ms:9.1f}",
)
append_history(
{
"mode": "run",
"label": options["label"],
"user": r.user_label,
"endpoint": r.endpoint_name,
"query_count": r.query_count,
"min_ms": r.min_ms,
"median_ms": r.median_ms,
"max_ms": r.max_ms,
"db_vendor": db_vendor,
"document_count": document_count,
},
)
def _handle_profile(self, options: dict[str, Any]) -> None:
from django.contrib.auth import get_user_model
from django.db import connection
from documents.models import Document
from paperless_benchmark.db import capture_explain
from paperless_benchmark.harness import run_profile
from paperless_benchmark.results import append_history
from paperless_benchmark.scenarios import get as get_scenario
if not options["scenario"]:
raise CommandError(
"`profile` requires a scenario name; see `list-scenarios`.",
)
scenario = get_scenario(options["scenario"])
user_model = get_user_model()
try:
perf_target = user_model.objects.get(username="perf_target")
except user_model.DoesNotExist as e:
raise CommandError(
"No benchmark dataset found. Run `manage.py benchmark seed` first.",
) from e
profile = run_profile(
lambda: scenario.run(perf_target),
repeat=options["repeat"],
)
self.stdout.write(
f"{scenario.name}: best={profile.best_seconds:.4f}s "
f"queries={profile.query_count}",
)
if options["explain"]:
if scenario.queryset_for_explain is not None:
plan = capture_explain(scenario.queryset_for_explain(perf_target))
self.stdout.write(plan)
else:
self.stdout.write(
self.style.WARNING(
f"--explain was requested but scenario {scenario.name!r} "
"does not support it (no queryset_for_explain); skipping.",
),
)
append_history(
{
"mode": "profile",
"scenario": scenario.name,
"best_seconds": profile.best_seconds,
"query_count": profile.query_count,
"db_vendor": connection.vendor,
"document_count": Document.objects.count(),
},
)
def _handle_list_scenarios(self) -> None:
from paperless_benchmark.scenarios import all_scenarios
for scenario in all_scenarios():
self.stdout.write(f"{scenario.name}: {scenario.describe}")
+39
View File
@@ -0,0 +1,39 @@
# src/paperless_benchmark/results.py
from __future__ import annotations
import json
import subprocess
from datetime import UTC
from datetime import datetime
from pathlib import Path
from typing import Any
RESULTS_DIR = Path(__file__).resolve().parent.parent.parent / "benchmark_results"
def _current_git_ref() -> str:
result = subprocess.run(
["git", "rev-parse", "--short", "HEAD"],
capture_output=True,
text=True,
check=False,
)
return result.stdout.strip() or "unknown"
def append_history(entry: dict[str, Any], *, code_ref: str | None = None) -> None:
"""
Append one line to benchmark_results/history.jsonl -- a local-only,
append-only, cross-session record of every `benchmark run`/`profile`
invocation. Unlike a single overwritten snapshot file, this survives
across sessions so a benchmarking effort picked back up days later has
a full timeline instead of only the most recent result.
"""
RESULTS_DIR.mkdir(exist_ok=True)
record = {
"timestamp": datetime.now(UTC).isoformat(),
"code_ref": code_ref or _current_git_ref(),
**entry,
}
with (RESULTS_DIR / "history.jsonl").open("a") as f:
f.write(json.dumps(record) + "\n")
+110
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@@ -0,0 +1,110 @@
# src/paperless_benchmark/scenarios.py
from __future__ import annotations
from dataclasses import dataclass
from typing import TYPE_CHECKING
from typing import Any
if TYPE_CHECKING:
from collections.abc import Callable
from django.contrib.auth.models import User
from django.db.models import QuerySet
@dataclass(frozen=True, slots=True)
class Scenario:
name: str
describe: str
run: Callable[[User], Any]
queryset_for_explain: Callable[[User], QuerySet] | None = None
_SCENARIOS: dict[str, Scenario] = {}
def register(scenario: Scenario) -> None:
_SCENARIOS[scenario.name] = scenario
def get(name: str) -> Scenario:
from django.core.management.base import CommandError
try:
return _SCENARIOS[name]
except KeyError:
available = ", ".join(sorted(_SCENARIOS)) or "(none registered)"
raise CommandError(
f"Unknown benchmark scenario {name!r}. Available: {available}",
) from None
def all_scenarios() -> tuple[Scenario, ...]:
return tuple(_SCENARIOS.values())
def _guardian_visibility_query_run(user: User) -> list[int]:
from documents.models import Document
from documents.permissions import get_objects_for_user_owner_aware
return list(
get_objects_for_user_owner_aware(
user,
"documents.view_document",
Document,
).values_list("id", flat=True),
)
def _guardian_visibility_query_queryset(user: User) -> QuerySet:
from documents.models import Document
from documents.permissions import get_objects_for_user_owner_aware
return get_objects_for_user_owner_aware(user, "documents.view_document", Document)
register(
Scenario(
name="guardian_visibility_query",
describe=(
"Document-visibility queryset for a user with mixed owned/shared "
"documents -- exercises documents.permissions."
"get_objects_for_user_owner_aware's guardian permission join."
),
run=_guardian_visibility_query_run,
queryset_for_explain=_guardian_visibility_query_queryset,
),
)
def _permitted_document_ids_run(user: User) -> list[int]:
from documents.models import Document
from documents.permissions import permitted_document_ids
return list(
Document.objects.filter(id__in=permitted_document_ids(user)).values_list(
"id",
flat=True,
),
)
def _permitted_document_ids_queryset(user: User) -> QuerySet:
from documents.models import Document
from documents.permissions import permitted_document_ids
return Document.objects.filter(id__in=permitted_document_ids(user))
register(
Scenario(
name="permitted_document_ids",
describe=(
"Document-visibility query built from documents.permissions."
"permitted_document_ids -- the resolved-ID-set alternative to "
"guardian_visibility_query, for side-by-side comparison."
),
run=_permitted_document_ids_run,
queryset_for_explain=_permitted_document_ids_queryset,
),
)
+445
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@@ -0,0 +1,445 @@
# src/paperless_benchmark/seeding.py
from __future__ import annotations
import datetime
import random
import time
from dataclasses import dataclass
from typing import TYPE_CHECKING
from typing import Literal
if TYPE_CHECKING:
from django.contrib.auth.models import Group
from django.contrib.auth.models import User
Tier = Literal["home", "medium", "large"]
CHUNK_SIZE = 5_000
MIME_TYPES = (
"application/pdf",
"image/png",
"image/jpeg",
"text/plain",
)
# Ownership split for documents, mirroring the shape used in the #11950
# perf-benchmark dataset (owned-by-target / owned-by-other / unowned).
OWNED_BY_TARGET_FRACTION = 0.60
OWNED_BY_OTHER_FRACTION = 0.30
# remainder (0.10) is unowned
# Of documents owned by "other" users, the fraction explicitly shared
# (view, or view+change) with perf_target via guardian permissions --
# this is what exercises the get_user_can_change() per-row N+1 that the
# `run` endpoint benchmarks measure.
SHARED_WITH_TARGET_FRACTION = 0.5
SHARED_WITH_CHANGE_FRACTION = 0.5
# Guardian permission-row ratios measured from a real install (discussion
# #13276): 1,414 user-perm rows / 27,232 group-perm rows over 12,000
# documents. Layered across ALL owned documents for the general user/group
# pool (not just perf_target's shares), so `profile` scenarios exercise a
# realistic permission-join shape for arbitrary users, not only perf_target.
USER_PERM_ROWS_PER_DOC = 1_414 / 12_000
GROUP_PERM_ROWS_PER_DOC = 27_232 / 12_000
@dataclass(frozen=True, slots=True)
class _TierCounts:
documents: int
tags: int
correspondents: int
document_types: int
storage_paths: int
other_users: int
groups: int
tags_per_doc: tuple[int, int]
TIERS: dict[Tier, _TierCounts] = {
"home": _TierCounts(
documents=500,
tags=20,
correspondents=10,
document_types=8,
storage_paths=5,
other_users=3,
groups=2,
tags_per_doc=(1, 3),
),
"medium": _TierCounts(
documents=20_000,
tags=100,
correspondents=300,
document_types=50,
storage_paths=20,
other_users=10,
groups=5,
tags_per_doc=(2, 6),
),
"large": _TierCounts(
documents=360_000,
tags=1_000,
correspondents=5_000,
document_types=300,
storage_paths=50,
other_users=25,
groups=10,
tags_per_doc=(3, 7),
),
}
def log(msg: str) -> None:
print(f"[{time.strftime('%H:%M:%S')}] {msg}", flush=True) # noqa: T201
@dataclass(frozen=True, slots=True)
class SeededData:
"""
Summary of a completed seed run. `documents`/`tags`/`correspondents`/
`document_types`/`storage_paths` are counts, not the seeded ORM
instances: at the `large` tier (360,000 documents) holding every
instance in memory simultaneously is a real risk for zero benefit, since
no caller consumes anything but the counts. `perf_target`/`perf_admin`/
`users`/`groups` stay as real objects -- at most ~26 users/12 groups even
at `large` tier, and small enough to be useful to a future caller.
"""
perf_target: User
perf_admin: User
users: tuple[User, ...]
groups: tuple[Group, ...]
documents: int
tags: int
correspondents: int
document_types: int
storage_paths: int
def _grant_model_level_permissions(user: User) -> None:
"""
Grant perf_target Django model-level view/add/change permissions on
Document and Tag, on top of the per-object guardian grants seeding
creates elsewhere. DRF's PaperlessObjectPermissions checks model-level
permissions before guardian's object-level ones are ever consulted, so
without this perf_target gets a blanket 403 on /api/documents/ and
/api/tags/ regardless of which documents guardian says it can see.
"""
from django.contrib.auth.models import Permission
from django.contrib.contenttypes.models import ContentType
from documents.models import Document
from documents.models import Tag
for model in (Document, Tag):
content_type = ContentType.objects.get_for_model(model)
codenames = [
f"{action}_{model._meta.model_name}" for action in ("view", "add", "change")
]
perms = Permission.objects.filter(
content_type=content_type,
codename__in=codenames,
)
user.user_permissions.add(*perms)
def _create_users_and_groups(
counts: _TierCounts,
) -> tuple[User, User, tuple[User, ...], tuple[Group, ...]]:
from django.contrib.auth.models import Group
from documents.tests.factories import UserFactory
perf_target = UserFactory.create(username="perf_target")
_grant_model_level_permissions(perf_target)
perf_admin = UserFactory.create(username="perf_admin", superuser=True)
other_users = tuple(UserFactory.create_batch(counts.other_users))
groups = tuple(
Group.objects.create(name=f"benchmark_group_{i}") for i in range(counts.groups)
)
log(
f"Created users: 1 target, 1 superuser, {len(other_users)} other, "
f"{len(groups)} groups.",
)
return perf_target, perf_admin, other_users, groups
def _create_lookup_tables(counts: _TierCounts):
from documents.models import Correspondent
from documents.models import DocumentType
from documents.models import StoragePath
from documents.models import Tag
from documents.tests.factories import CorrespondentFactory
from documents.tests.factories import DocumentTypeFactory
from documents.tests.factories import StoragePathFactory
from documents.tests.factories import TagFactory
tags = tuple(Tag.objects.bulk_create(TagFactory.build_batch(counts.tags)))
correspondents = tuple(
Correspondent.objects.bulk_create(
CorrespondentFactory.build_batch(counts.correspondents),
),
)
document_types = tuple(
DocumentType.objects.bulk_create(
DocumentTypeFactory.build_batch(counts.document_types),
),
)
storage_paths = tuple(
StoragePath.objects.bulk_create(
StoragePathFactory.build_batch(counts.storage_paths),
),
)
log(
f"Created {len(tags)} tags, {len(correspondents)} correspondents, "
f"{len(document_types)} document types, {len(storage_paths)} storage paths.",
)
return tags, correspondents, document_types, storage_paths
def _assign_owner(rng: random.Random, perf_target: User, other_users: tuple[User, ...]):
roll = rng.random()
if roll < OWNED_BY_TARGET_FRACTION:
return perf_target, "target"
if roll < OWNED_BY_TARGET_FRACTION + OWNED_BY_OTHER_FRACTION:
return rng.choice(other_users), "other"
return None, "unowned"
def _seed_documents(
rng: random.Random,
counts: _TierCounts,
tags,
correspondents,
document_types,
storage_paths,
perf_target,
other_users,
) -> tuple[int, list[int]]:
"""
Bulk-create `counts.documents` documents in chunks. Returns the total
document count plus a lightweight list of pks for documents that ended
up with an owner (target or other) -- that's all
`_grant_general_permissions` needs to sample from, so full `Document`
instances aren't accumulated across chunks (a real memory concern at the
`large` tier's 360,000 documents).
"""
from django.contrib.auth.models import Permission
from django.contrib.contenttypes.models import ContentType
from guardian.models import UserObjectPermission
from documents.models import Document
from documents.tests.factories import DocumentFactory
tag_ids = [t.pk for t in tags]
correspondent_ids = [c.pk for c in correspondents]
document_type_ids = [d.pk for d in document_types]
storage_path_ids = [s.pk for s in storage_paths]
doc_content_type = ContentType.objects.get_for_model(Document)
view_perm = Permission.objects.get(
codename="view_document",
content_type=doc_content_type,
)
change_perm = Permission.objects.get(
codename="change_document",
content_type=doc_content_type,
)
through_model = Document.tags.through
document_count = 0
owned_document_pks: list[int] = []
remaining = counts.documents
while remaining > 0:
chunk_n = min(CHUNK_SIZE, remaining)
remaining -= chunk_n
batch = []
owner_buckets = []
for _ in range(chunk_n):
doc = DocumentFactory.build(
mime_type=rng.choice(MIME_TYPES),
page_count=rng.randint(1, 30),
correspondent_id=(
rng.choice(correspondent_ids)
if correspondent_ids and rng.random() < 0.8
else None
),
document_type_id=(
rng.choice(document_type_ids)
if document_type_ids and rng.random() < 0.6
else None
),
storage_path_id=(
rng.choice(storage_path_ids)
if storage_path_ids and rng.random() < 0.8
else None
),
# Document.created is a plain DateField (default: today).
# Leaving it unset would give every seeded document the same
# date, collapsing Document's ("-created",) ordering index
# into a single-valued sort key -- spread it over a
# realistic multi-year window instead.
created=datetime.date.today()
- datetime.timedelta(days=rng.randint(0, 365 * 3)),
)
owner, bucket = _assign_owner(rng, perf_target, other_users)
doc.owner_id = owner.pk if owner else None
batch.append(doc)
owner_buckets.append(bucket)
created = Document.objects.bulk_create(batch, batch_size=CHUNK_SIZE)
through_rows = []
for doc in created:
k = rng.randint(*counts.tags_per_doc)
for tag_id in rng.sample(tag_ids, min(k, len(tag_ids))):
through_rows.append(through_model(document_id=doc.pk, tag_id=tag_id))
if through_rows:
through_model.objects.bulk_create(through_rows, batch_size=CHUNK_SIZE)
perm_rows = []
for doc, bucket in zip(created, owner_buckets, strict=True):
if bucket == "unowned":
continue
owned_document_pks.append(doc.pk)
if bucket != "other":
continue
if rng.random() >= SHARED_WITH_TARGET_FRACTION:
continue
perm_rows.append(
UserObjectPermission(
permission=view_perm,
content_type=doc_content_type,
object_pk=str(doc.pk),
user=perf_target,
),
)
if rng.random() < SHARED_WITH_CHANGE_FRACTION:
perm_rows.append(
UserObjectPermission(
permission=change_perm,
content_type=doc_content_type,
object_pk=str(doc.pk),
user=perf_target,
),
)
if perm_rows:
UserObjectPermission.objects.bulk_create(perm_rows, batch_size=CHUNK_SIZE)
document_count += len(created)
log(f" {document_count}/{counts.documents} documents seeded")
return document_count, owned_document_pks
def _grant_general_permissions(
rng: random.Random,
owned_document_pks: list[int],
users,
groups,
) -> None:
"""
Layer realistic (issue #13276-derived) guardian permission-row ratios
across owned documents for the general user/group pool, so `profile`
scenarios exercise the same permission-join shape regardless of which
user they check visibility for (not just perf_target).
"""
from django.contrib.auth.models import Permission
from django.contrib.contenttypes.models import ContentType
from guardian.models import GroupObjectPermission
from guardian.models import UserObjectPermission
from documents.models import Document
if not owned_document_pks or not users:
return
doc_content_type = ContentType.objects.get_for_model(Document)
view_perm = Permission.objects.get(
codename="view_document",
content_type=doc_content_type,
)
n_user_perms = round(len(owned_document_pks) * USER_PERM_ROWS_PER_DOC)
n_group_perms = (
round(len(owned_document_pks) * GROUP_PERM_ROWS_PER_DOC) if groups else 0
)
user_rows = [
UserObjectPermission(
permission=view_perm,
content_type=doc_content_type,
object_pk=str(rng.choice(owned_document_pks)),
user=rng.choice(users),
)
for _ in range(n_user_perms)
]
if user_rows:
UserObjectPermission.objects.bulk_create(
user_rows,
batch_size=CHUNK_SIZE,
ignore_conflicts=True,
)
group_rows = [
GroupObjectPermission(
permission=view_perm,
content_type=doc_content_type,
object_pk=str(rng.choice(owned_document_pks)),
group=rng.choice(groups),
)
for _ in range(n_group_perms)
]
if group_rows:
GroupObjectPermission.objects.bulk_create(
group_rows,
batch_size=CHUNK_SIZE,
ignore_conflicts=True,
)
log(f" Granted {len(user_rows)} user perms, {len(group_rows)} group perms.")
def seed_benchmark_dataset(tier: Tier, *, seed: int = 42) -> SeededData:
"""
Build a benchmark dataset at the given scale tier: a named perf_target
(mixed owned/shared documents) and perf_admin (superuser) for endpoint
benchmarking, plus a general user/group pool with realistic guardian
permission-row ratios for profile scenarios.
"""
counts = TIERS[tier]
rng = random.Random(seed)
log(f"Seeding tier={tier!r}")
perf_target, perf_admin, other_users, groups = _create_users_and_groups(counts)
tags, correspondents, document_types, storage_paths = _create_lookup_tables(counts)
document_count, owned_document_pks = _seed_documents(
rng,
counts,
tags,
correspondents,
document_types,
storage_paths,
perf_target,
other_users,
)
all_users = (perf_target, *other_users)
_grant_general_permissions(rng, owned_document_pks, all_users, groups)
log(f"Done. {document_count} documents seeded for tier={tier!r}.")
return SeededData(
perf_target=perf_target,
perf_admin=perf_admin,
users=all_users,
groups=groups,
documents=document_count,
tags=len(tags),
correspondents=len(correspondents),
document_types=len(document_types),
storage_paths=len(storage_paths),
)
+2 -22
View File
@@ -1,9 +1,7 @@
import logging
from celery import Task
from celery import shared_task
from documents.models import PaperlessTask
from paperless_mail.mail import MailAccountHandler
from paperless_mail.mail import MailError
from paperless_mail.models import MailAccount
@@ -12,26 +10,8 @@ from paperless_mail.models import MailRule
logger = logging.getLogger("paperless.mail.tasks")
@shared_task(bind=True)
def process_mail_accounts(self: Task, account_ids: list[int] | None = None) -> str:
# A scheduled check can still be running (or queued) when the next one
# ProcessedMail dedup only records a message once its
# handling has finished, so an overlapping run can still pick up the same
# not-yet-recorded message. Skip outright rather than race it.
other_mail_fetch_running = (
PaperlessTask.objects.filter(
task_type=PaperlessTask.TaskType.MAIL_FETCH,
status__in=[PaperlessTask.Status.PENDING, PaperlessTask.Status.STARTED],
)
.exclude(task_id=self.request.id)
.exists()
)
if other_mail_fetch_running:
logger.info(
"Mail account processing is already running; skipping this run.",
)
return "Skipped: mail account processing already in progress."
@shared_task
def process_mail_accounts(account_ids: list[int] | None = None) -> str:
total_new_documents = 0
accounts = (
MailAccount.objects.filter(pk__in=account_ids)
@@ -1,134 +0,0 @@
from typing import Final
import pytest
import pytest_mock
from documents.models import PaperlessTask
from documents.tests.factories import PaperlessTaskFactory
from paperless_mail import tasks
from paperless_mail.tests.factories import MailAccountFactory
from paperless_mail.tests.factories import MailRuleFactory
NO_DOCUMENTS_ADDED: Final = "No new documents were added."
SKIPPED: Final = "Skipped: mail account processing already in progress."
@pytest.mark.django_db
@pytest.mark.usefixtures("account_with_rule")
class TestProcessMailAccountsOverlap:
@pytest.fixture
def account_with_rule(self) -> None:
"""An enabled mail account with a single enabled rule."""
account = MailAccountFactory.create()
MailRuleFactory.create(account=account, enabled=True)
@pytest.mark.parametrize(
("status", "expected_result", "expected_call_count"),
[
pytest.param(
PaperlessTask.Status.PENDING,
SKIPPED,
0,
id="pending-task-blocks",
),
pytest.param(
PaperlessTask.Status.STARTED,
SKIPPED,
0,
id="started-task-blocks",
),
pytest.param(
PaperlessTask.Status.SUCCESS,
NO_DOCUMENTS_ADDED,
1,
id="finished-task-does-not-block",
),
],
)
def test_skips_only_while_another_mail_fetch_task_runs(
self,
mocker: pytest_mock.MockerFixture,
status: PaperlessTask.Status,
expected_result: str,
expected_call_count: int,
) -> None:
"""
GIVEN:
- An enabled mail account with a rule
- Another mail fetch task row in the given status
WHEN:
- Mail accounts are processed
THEN:
- Processing is skipped only if that other task is pending or running
"""
PaperlessTaskFactory.create(
task_type=PaperlessTask.TaskType.MAIL_FETCH,
trigger_source=PaperlessTask.TriggerSource.SCHEDULED,
status=status,
)
mocked_handle = mocker.patch.object(
tasks.MailAccountHandler,
"handle_mail_account",
return_value=0,
)
result = tasks.process_mail_accounts()
assert mocked_handle.call_count == expected_call_count
assert result == expected_result
def test_runs_when_no_other_mail_fetch_task_exists(
self,
mocker: pytest_mock.MockerFixture,
) -> None:
"""
GIVEN:
- An enabled mail account with a rule
- No other mail fetch task rows
WHEN:
- Mail accounts are processed
THEN:
- The account is handled
"""
mocked_handle = mocker.patch.object(
tasks.MailAccountHandler,
"handle_mail_account",
return_value=0,
)
result = tasks.process_mail_accounts()
mocked_handle.assert_called_once()
assert result == NO_DOCUMENTS_ADDED
def test_does_not_skip_due_to_its_own_task_row(
self,
mocker: pytest_mock.MockerFixture,
) -> None:
"""
GIVEN:
- An enabled mail account with a rule
- A running mail fetch task row belonging to this very task
WHEN:
- Mail accounts are processed under that task id
THEN:
- The task does not skip itself and handles the account
"""
PaperlessTaskFactory.create(
task_id="self-task-id",
task_type=PaperlessTask.TaskType.MAIL_FETCH,
trigger_source=PaperlessTask.TriggerSource.SCHEDULED,
status=PaperlessTask.Status.STARTED,
)
mocked_handle = mocker.patch.object(
tasks.MailAccountHandler,
"handle_mail_account",
return_value=0,
)
result = tasks.process_mail_accounts.apply(task_id="self-task-id").result
mocked_handle.assert_called_once()
assert result == NO_DOCUMENTS_ADDED