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Author SHA1 Message Date
stumpylog b3e0cf0e21 chore(profiling): confirm Stage 2 loop-resolution reduces query count and wall time at scale 2026-07-28 16:36:44 -07:00
stumpylog 5b63a7bc41 chore(profiling): record Stage 1 after-profile, confirm speedup and no query-count regression 2026-07-27 21:20:55 -07:00
stumpylog fb99b3defb profiling(stage1): re-capture baseline with realistic document ownership
Guardian permission subplans now actually execute (previously
'never executed' due to unowned seed documents short-circuiting the
owner_id IS NULL branch). best_seconds rose from 0.0251s to 31.4648s,
confirming the varchar-cast nested-loop-semi-join pathology is real
and now measured under realistic conditions.
2026-07-27 19:02:30 -07:00
stumpylog e80ede4cb0 fix(profiling): assign realistic document ownership so seed data exercises the guardian permission path 2026-07-27 17:25:48 -07:00
stumpylog e0902c63d6 chore(profiling): record Stage 1 baseline for get_objects_for_user_owner_aware 2026-07-27 16:03:15 -07:00
stumpylogandClaude Sonnet 5 0506dcad05 chore(profiling): add append_profiling_history function for persistent profiling records
Adds two new functions to harness.py:
- _current_git_ref(): Gets the current git short SHA
- append_profiling_history(): Appends JSON line to profiling/results/history.jsonl

This enables profiling numbers to persist across sessions/dates, with every run
appended to an immutable timeline rather than overwriting per-stage snapshots.

Also adds corresponding test to verify the function writes valid JSON lines.

Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
2026-07-27 15:49:14 -07:00
stumpylog 91647eecb5 chore(profiling): add throwaway-Postgres helper and typed profiling harness
Adds standalone profiling tooling (never merged into dev/main): a
persistent, self-healing Postgres 18 container helper
(run_with_postgres.sh/stop_postgres.sh), a scale-profile dataset seeder
(seed.py) whose document counts and guardian permission-row ratios
mirror real bug reports (#13276, #13161), and a typed profiling harness
(harness.py) for timing/query-count comparisons and EXPLAIN ANALYZE
capture, gated by require_postgres() so it never silently runs on
SQLite.

seed.py samples distinct (subject, document) pairs up front rather than
drawing with replacement, since guardian's assign_perm() dedupes on the
(subject, object, permission) triple -- with-replacement sampling
against a small group pool collides heavily (birthday paradox) and
undercounts the target permission-row ratios otherwise.
2026-07-27 15:08:23 -07:00
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# profiling/harness.py
from __future__ import annotations
import json
import subprocess
import time
from dataclasses import dataclass
from datetime import UTC
from datetime import datetime
from pathlib import Path
from typing import TYPE_CHECKING
from typing import Any
from typing import Generic
from typing import TypeVar
import pytest
from django.db import connection
from django.test.utils import CaptureQueriesContext
if TYPE_CHECKING:
from collections.abc import Callable
from django.db.models import QuerySet
from profiling.seed import ScaleProfile
T = TypeVar("T")
def require_postgres() -> None:
if connection.vendor != "postgresql":
pytest.skip(
"Profiling requires PostgreSQL to reflect production query "
"planning; SQLite does not reproduce the varchar-cast planner "
"pathology this work fixes.",
)
@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]:
require_postgres()
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)
assert result is not None # repeat >= 1 guarantees at least one assignment
return ProfileResult(
best_seconds=min(all_seconds),
all_seconds=tuple(all_seconds),
query_count=query_count,
result=result,
)
def capture_explain_analyze(queryset: QuerySet[Any]) -> str:
if connection.vendor != "postgresql":
raise RuntimeError("EXPLAIN ANALYZE capture is Postgres-only")
sql, params = queryset.query.sql_with_params()
with connection.cursor() as cur:
cur.execute(f"EXPLAIN ANALYZE {sql}", params)
return "\n".join(row[0] for row in cur.fetchall())
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_profiling_history(
*,
stage: str,
scenario: str,
best_seconds: float,
query_count: int,
scale: ScaleProfile,
code_ref: str | None = None,
) -> None:
"""
Append one line to profiling/results/history.jsonl -- an append-only,
cross-session record of every profiling run. Unlike the per-stage
before/after snapshot JSON files (which the next run of the same stage
overwrites), this never gets clobbered, so a profiling effort picked
back up days later has a full timeline to resume from instead of only
the single most recent comparison.
``code_ref`` should identify the *production* code under test (a short
SHA on the feature branch, not this `profiling` branch) -- pass it
explicitly when known. Left as ``None``, it falls back to this repo's
current ``git rev-parse --short HEAD``, which is only meaningful if
you're actually running from a checkout where that reflects the code
being measured.
"""
results_dir = Path(__file__).parent / "results"
results_dir.mkdir(exist_ok=True)
entry = {
"timestamp": datetime.now(UTC).isoformat(),
"code_ref": code_ref or _current_git_ref(),
"stage": stage,
"scenario": scenario,
"scale": scale,
"best_seconds": best_seconds,
"query_count": query_count,
}
with (results_dir / "history.jsonl").open("a") as f:
f.write(json.dumps(entry) + "\n")
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[tool.pytest]
ini_options.pythonpath = [ "../src", "..", "." ]
ini_options.markers = [
"""\
profiling: Profiling scripts comparing old vs new query patterns; require a throwaway PostgreSQL container, not run \
as part of the normal test suite\
""",
]
ini_options.DJANGO_SETTINGS_MODULE = "paperless.settings"
[tool.pytest_env]
# Standalone config: this directory must be independently runnable without
# the rest of the dev stack (Redis, etc) present -- only Postgres is required,
# via run_with_postgres.sh.
PAPERLESS_SECRET_KEY = "profiling-only-insecure-key"
PAPERLESS_DISABLE_DBHANDLER = "true"
PAPERLESS_CACHE_BACKEND = "django.core.cache.backends.locmem.LocMemCache"
PAPERLESS_CHANNELS_BACKEND = "channels.layers.InMemoryChannelLayer"
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{"timestamp": "2026-07-27T22:47:46.677504+00:00", "code_ref": "test-run", "stage": "self-check", "scenario": "test_append_profiling_history_writes_a_valid_json_line", "scale": "medium", "best_seconds": 0.001, "query_count": 0}
{"timestamp": "2026-07-27T22:49:03.762638+00:00", "code_ref": "test-run", "stage": "self-check", "scenario": "test_append_profiling_history_writes_a_valid_json_line", "scale": "medium", "best_seconds": 0.001, "query_count": 0}
{"timestamp": "2026-07-27T23:01:49.777269+00:00", "code_ref": "0506dcad0", "stage": "stage1", "scenario": "get_objects_for_user_owner_aware_document_baseline", "scale": "medium", "best_seconds": 0.025123266968876123, "query_count": 1}
{"timestamp": "2026-07-28T01:38:32.706519+00:00", "code_ref": "e80ede4cb", "stage": "stage1", "scenario": "get_objects_for_user_owner_aware_document_baseline", "scale": "medium", "best_seconds": 31.46481539506931, "query_count": 1}
{"timestamp": "2026-07-28T03:53:46.770669+00:00", "code_ref": "d4fa85237", "stage": "stage1", "scenario": "get_objects_for_user_owner_aware_document_baseline", "scale": "medium", "best_seconds": 31.671881378046237, "query_count": 1}
{"timestamp": "2026-07-28T04:02:41.942168+00:00", "code_ref": "d4fa85237", "stage": "stage1", "scenario": "permitted_document_ids_after_stage1", "scale": "medium", "best_seconds": 0.07956207206007093, "query_count": 1}
{"timestamp": "2026-07-28T23:30:28.602501+00:00", "code_ref": "86846255f", "stage": "stage2", "scenario": "per_row_checker_vs_resolved_set_old", "scale": "medium", "best_seconds": 3.4628250940004364, "query_count": 692}
{"timestamp": "2026-07-28T23:30:28.606987+00:00", "code_ref": "86846255f", "stage": "stage2", "scenario": "per_row_checker_vs_resolved_set_new", "scale": "medium", "best_seconds": 0.10436739504802972, "query_count": 1}
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{
"permitted_document_ids": {
"best_seconds": 0.07956207206007093,
"query_count": 1
},
"baseline_best_seconds": 31.671881378046237,
"baseline_query_count": 1,
"speedup_x": 398.07763370131113
}
@@ -0,0 +1,58 @@
Index Scan Backward using documents_document_created_bedd0818 on documents_document v0 (cost=91.31..99.33 rows=1 width=2900) (actual time=68.340..77.517 rows=12024.00 loops=1)
Filter: ((deleted_at IS NULL) AND ((owner_id = 12) OR (owner_id IS NULL) OR (ANY (id = (hashed SubPlan 1).col1))))
Rows Removed by Filter: 7976
Index Searches: 1
Buffers: shared hit=74978
SubPlan 1
-> Unique (cost=91.04..91.05 rows=2 width=4) (actual time=64.698..66.622 rows=9136.00 loops=1)
Buffers: shared hit=73487
-> Sort (cost=91.04..91.05 rows=2 width=4) (actual time=64.697..65.202 rows=9262.00 loops=1)
Sort Key: ((u0.object_pk)::integer)
Sort Method: quicksort Memory: 385kB
Buffers: shared hit=73487
-> Append (cost=0.27..91.03 rows=2 width=4) (actual time=0.026..63.201 rows=9262.00 loops=1)
Buffers: shared hit=73487
-> Nested Loop (cost=0.27..12.79 rows=1 width=4) (actual time=0.026..1.834 rows=237.00 loops=1)
Join Filter: (u0.permission_id = u1.id)
Buffers: shared hit=696
-> Index Only Scan using guardian_userobjectpermi_user_id_permission_id_ob_b0b3d2fc_uniq on guardian_userobjectpermission u0 (cost=0.27..8.29 rows=1 width=520) (actual time=0.012..0.131 rows=237.00 loops=1)
Index Cond: (user_id = 12)
Heap Fetches: 237
Index Searches: 1
Buffers: shared hit=222
-> Seq Scan on auth_permission u1 (cost=0.00..4.49 rows=1 width=4) (actual time=0.006..0.006 rows=1.00 loops=237)
Filter: (((codename)::text = 'view_document'::text) AND (content_type_id = 17))
Rows Removed by Filter: 67
Buffers: shared hit=474
-> Nested Loop (cost=4.73..78.23 rows=1 width=4) (actual time=1.119..60.528 rows=9025.00 loops=1)
Buffers: shared hit=72791
-> Nested Loop (cost=4.59..78.05 rows=1 width=524) (actual time=1.115..50.521 rows=9025.00 loops=1)
Buffers: shared hit=54741
-> Nested Loop (cost=4.44..73.62 rows=24 width=520) (actual time=1.109..13.226 rows=45387.00 loops=1)
Buffers: shared hit=329
-> Seq Scan on auth_permission u4 (cost=0.00..4.49 rows=1 width=4) (actual time=0.008..0.017 rows=1.00 loops=1)
Filter: (((codename)::text = 'view_document'::text) AND (content_type_id = 17))
Rows Removed by Filter: 165
Buffers: shared hit=2
-> Bitmap Heap Scan on guardian_groupobjectpermission u0_1 (cost=4.44..68.93 rows=20 width=524) (actual time=1.100..8.095 rows=45387.00 loops=1)
Recheck Cond: (permission_id = u4.id)
Heap Blocks: exact=290
Buffers: shared hit=327
-> Bitmap Index Scan on guardian_groupobjectpermission_permission_id_36572738 (cost=0.00..4.43 rows=20 width=0) (actual time=1.052..1.053 rows=45387.00 loops=1)
Index Cond: (permission_id = u4.id)
Index Searches: 1
Buffers: shared hit=37
-> Index Only Scan using auth_user_groups_user_id_group_id_94350c0c_uniq on auth_user_groups u2 (cost=0.15..0.18 rows=1 width=4) (actual time=0.001..0.001 rows=0.20 loops=45387)
Index Cond: ((user_id = 12) AND (group_id = u0_1.group_id))
Heap Fetches: 9025
Index Searches: 45387
Buffers: shared hit=54412
-> Index Only Scan using auth_group_pkey on auth_group u1_1 (cost=0.14..0.17 rows=1 width=4) (actual time=0.001..0.001 rows=1.00 loops=9025)
Index Cond: (id = u0_1.group_id)
Heap Fetches: 9025
Index Searches: 9025
Buffers: shared hit=18050
Planning:
Buffers: shared hit=2
Planning Time: 1.089 ms
Execution Time: 78.020 ms
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{
"get_objects_for_user_owner_aware_document": {
"best_seconds": 31.671881378046237,
"query_count": 1
}
}
@@ -0,0 +1,68 @@
Sort (cost=3790.80..3790.82 rows=9 width=2900) (actual time=39120.166..39120.831 rows=12024.00 loops=1)
Sort Key: documents_document.created DESC
Sort Method: quicksort Memory: 3230kB
Buffers: shared hit=8598270
-> Seq Scan on documents_document (cost=2550.72..3790.65 rows=9 width=2900) (actual time=0.009..39114.720 rows=12024.00 loops=1)
Filter: ((deleted_at IS NULL) AND ((owner_id = 2) OR (owner_id IS NULL) OR (ANY (id = (hashed SubPlan 1).col1)) OR (ANY (id = (hashed SubPlan 2).col1))))
Rows Removed by Filter: 7976
Buffers: shared hit=8598270
SubPlan 1
-> Nested Loop Semi Join (cost=0.00..1245.63 rows=1 width=8) (actual time=4.254..969.033 rows=237.00 loops=1)
Join Filter: ((((v0.object_pk)::bigint)::character varying)::text = (((u0.id)::bigint)::character varying)::text)
Rows Removed by Join Filter: 2539276
Buffers: shared hit=214835
-> Nested Loop (cost=0.00..23.30 rows=1 width=516) (actual time=0.031..2.425 rows=237.00 loops=1)
Join Filter: (v0.permission_id = v2.id)
Buffers: shared hit=490
-> Seq Scan on guardian_userobjectpermission v0 (cost=0.00..18.80 rows=1 width=520) (actual time=0.021..0.424 rows=237.00 loops=1)
Filter: (user_id = 2)
Rows Removed by Filter: 2120
Buffers: shared hit=16
-> Seq Scan on auth_permission v2 (cost=0.00..4.49 rows=1 width=4) (actual time=0.006..0.006 rows=1.00 loops=237)
Filter: ((content_type_id = 17) AND ((codename)::text = 'view_document'::text))
Rows Removed by Filter: 67
Buffers: shared hit=474
-> Seq Scan on documents_document u0 (cost=0.00..1221.96 rows=12 width=4) (actual time=0.002..1.917 rows=10715.24 loops=237)
Filter: (deleted_at IS NULL)
Buffers: shared hit=214345
SubPlan 2
-> Nested Loop Semi Join (cost=4.73..1305.09 rows=1 width=8) (actual time=6.729..38127.912 rows=9025.00 loops=1)
Join Filter: ((((v0_1.object_pk)::bigint)::character varying)::text = (((u0_2.id)::bigint)::character varying)::text)
Rows Removed by Join Filter: 98955406
Buffers: shared hit=8382237
-> Nested Loop Semi Join (cost=4.73..82.77 rows=1 width=516) (actual time=1.109..137.661 rows=9025.00 loops=1)
Buffers: shared hit=145515
-> Nested Loop (cost=4.44..73.62 rows=24 width=520) (actual time=1.090..18.002 rows=45387.00 loops=1)
Buffers: shared hit=329
-> Seq Scan on auth_permission v2_1 (cost=0.00..4.49 rows=1 width=4) (actual time=0.011..0.023 rows=1.00 loops=1)
Filter: (((codename)::text = 'view_document'::text) AND (content_type_id = 17))
Rows Removed by Filter: 165
Buffers: shared hit=2
-> Bitmap Heap Scan on guardian_groupobjectpermission v0_1 (cost=4.44..68.93 rows=20 width=524) (actual time=1.077..10.777 rows=45387.00 loops=1)
Recheck Cond: (permission_id = v2_1.id)
Heap Blocks: exact=290
Buffers: shared hit=327
-> Bitmap Index Scan on guardian_groupobjectpermission_permission_id_36572738 (cost=0.00..4.43 rows=20 width=0) (actual time=1.026..1.026 rows=45387.00 loops=1)
Index Cond: (permission_id = v2_1.id)
Index Searches: 1
Buffers: shared hit=37
-> Nested Loop (cost=0.30..0.37 rows=1 width=8) (actual time=0.002..0.002 rows=0.20 loops=45387)
Join Filter: (u0_1.id = u1.group_id)
Buffers: shared hit=145186
-> Index Only Scan using auth_group_pkey on auth_group u0_1 (cost=0.14..0.17 rows=1 width=4) (actual time=0.001..0.001 rows=1.00 loops=45387)
Index Cond: (id = v0_1.group_id)
Heap Fetches: 45387
Index Searches: 45387
Buffers: shared hit=90774
-> Index Only Scan using auth_user_groups_user_id_group_id_94350c0c_uniq on auth_user_groups u1 (cost=0.15..0.18 rows=1 width=4) (actual time=0.001..0.001 rows=0.20 loops=45387)
Index Cond: ((user_id = 2) AND (group_id = v0_1.group_id))
Heap Fetches: 9025
Index Searches: 45387
Buffers: shared hit=54412
-> Seq Scan on documents_document u0_2 (cost=0.00..1221.96 rows=12 width=4) (actual time=0.002..1.956 rows=10965.59 loops=9025)
Filter: (deleted_at IS NULL)
Buffers: shared hit=8236722
Planning:
Buffers: shared hit=3
Planning Time: 1.119 ms
Execution Time: 39121.312 ms
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#!/usr/bin/env bash
# profiling/run_with_postgres.sh
#
# Starts a PostgreSQL 18 container (matching
# docker/compose/docker-compose.postgres.yml's image) if one isn't already
# running, waits for it to accept connections, force-terminates any
# leftover connections from a previous run that crashed or was killed, then
# runs the given command against it with the right PAPERLESS_DB* env vars
# set. The container is intentionally left running afterward -- see
# stop_postgres.sh to tear it down explicitly once you're done profiling
# for the session.
set -euo pipefail
CONTAINER_NAME="pngx-profiling-pg"
HOST_PORT="55432"
if ! docker inspect "$CONTAINER_NAME" >/dev/null 2>&1; then
docker run --rm -d \
--name "$CONTAINER_NAME" \
-e POSTGRES_DB=paperless \
-e POSTGRES_USER=paperless \
-e POSTGRES_PASSWORD=paperless \
-p "${HOST_PORT}:5432" \
docker.io/library/postgres:18 >/dev/null
echo "Started profiling Postgres container '$CONTAINER_NAME' on port $HOST_PORT (left running -- see profiling/stop_postgres.sh)." >&2
fi
until docker exec "$CONTAINER_NAME" pg_isready -U paperless >/dev/null 2>&1; do
sleep 1
done
# Reap any connections left over from a previous run that crashed, was
# killed, or timed out mid-query -- without this, a persistent container
# can accumulate stuck backends that block later test-database
# create/drop operations indefinitely.
docker exec "$CONTAINER_NAME" psql -U paperless -d paperless -v ON_ERROR_STOP=0 -c "
SELECT pg_terminate_backend(pid)
FROM pg_stat_activity
WHERE datname IN ('paperless', 'test_paperless')
AND pid <> pg_backend_pid();
" >/dev/null 2>&1 || true
PAPERLESS_DBHOST=localhost \
PAPERLESS_DBNAME=paperless \
PAPERLESS_DBUSER=paperless \
PAPERLESS_DBPASS=paperless \
PAPERLESS_DBPORT="${HOST_PORT}" \
"$@"
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# profiling/seed.py
from __future__ import annotations
import random
from dataclasses import dataclass
from typing import TYPE_CHECKING
from typing import Literal
from django.contrib.auth.models import Group
from django.contrib.auth.models import User
from guardian.shortcuts import assign_perm
from documents.models import Document
from documents.tests.factories import CorrespondentFactory
from documents.tests.factories import DocumentFactory
from documents.tests.factories import DocumentTypeFactory
from documents.tests.factories import StoragePathFactory
from documents.tests.factories import TagFactory
if TYPE_CHECKING:
from documents.models import Correspondent
from documents.models import DocumentType
from documents.models import StoragePath
from documents.models import Tag
ScaleProfile = Literal["medium", "large"]
# Fraction of seeded documents given a real owner; the remainder stays
# owner=None, mirroring a real install's mix of owned and legacy/imported
# unowned documents.
_OWNED_FRACTION = 0.9
class _ScaleCounts:
__slots__ = (
"correspondents",
"document_types",
"documents",
"groups",
"storage_paths",
"tags",
"users",
)
def __init__(
self,
*,
documents: int,
tags: int,
correspondents: int,
document_types: int,
storage_paths: int,
users: int,
groups: int,
) -> None:
self.documents = documents
self.tags = tags
self.correspondents = correspondents
self.document_types = document_types
self.storage_paths = storage_paths
self.users = users
self.groups = groups
_SCALE_PROFILES: dict[ScaleProfile, _ScaleCounts] = {
"medium": _ScaleCounts(
documents=20_000,
tags=100,
correspondents=300,
document_types=50,
storage_paths=20,
users=10,
groups=5,
),
"large": _ScaleCounts(
documents=360_000,
tags=1_000,
correspondents=5_000,
document_types=300,
storage_paths=50,
users=25,
groups=10,
),
}
# Ratios measured from a real install (discussion #13276): 1,414 user-perm
# rows / 27,232 group-perm rows over 12,000 documents.
_USER_PERM_ROWS_PER_DOC = 1_414 / 12_000
_GROUP_PERM_ROWS_PER_DOC = 27_232 / 12_000
def _sample_distinct_pairs(
rng: random.Random,
n_subjects: int,
n_objects: int,
count: int,
) -> set[tuple[int, int]]:
"""
Rejection-sample `count` distinct (subject_index, object_index) pairs.
`count` is always well under `n_subjects * n_objects` for every scale
profile, so this terminates quickly.
"""
if count > n_subjects * n_objects:
msg = (
f"cannot sample {count} distinct pairs from only "
f"{n_subjects * n_objects} possible (subject, object) slots"
)
raise ValueError(msg)
pairs: set[tuple[int, int]] = set()
while len(pairs) < count:
pairs.add((rng.randrange(n_subjects), rng.randrange(n_objects)))
return pairs
@dataclass(frozen=True, slots=True)
class SeededData:
users: tuple[User, ...]
groups: tuple[Group, ...]
documents: tuple[Document, ...]
tags: tuple[Tag, ...]
correspondents: tuple[Correspondent, ...]
document_types: tuple[DocumentType, ...]
storage_paths: tuple[StoragePath, ...]
def seed_permission_dataset(
scale: ScaleProfile = "medium",
*,
seed: int = 1337,
) -> SeededData:
"""
Build a dataset whose document count and guardian-permission-row ratios
mirror real bug reports, so profiling results are representative of
actual large installs rather than an arbitrary small fixture.
"""
counts = _SCALE_PROFILES[scale]
rng = random.Random(seed)
users = tuple(
User.objects.create_user(username=f"profile_user_{i}")
for i in range(counts.users)
)
groups = tuple(
Group.objects.create(name=f"profile_group_{i}") for i in range(counts.groups)
)
for user in users:
user.groups.add(rng.choice(groups))
documents = list(DocumentFactory.create_batch(counts.documents))
# Assign realistic ownership -- without this, every document stays
# owner=None and the "owned or unowned" visibility clause is trivially
# true for every row, so no guardian permission check ever needs to run
# (see the amendment note above this code block).
owned_documents = []
for document in documents:
if rng.random() < _OWNED_FRACTION:
document.owner = rng.choice(users)
owned_documents.append(document)
Document.objects.bulk_update(owned_documents, ["owner"], batch_size=2_000)
documents = tuple(documents)
tags = tuple(TagFactory.create_batch(counts.tags))
correspondents = tuple(CorrespondentFactory.create_batch(counts.correspondents))
document_types = tuple(DocumentTypeFactory.create_batch(counts.document_types))
storage_paths = tuple(StoragePathFactory.create_batch(counts.storage_paths))
n_user_perms = round(counts.documents * _USER_PERM_ROWS_PER_DOC)
n_group_perms = round(counts.documents * _GROUP_PERM_ROWS_PER_DOC)
# Grant permissions only on OWNED documents -- a grant on an already-
# unowned document is a no-op for visibility (unowned documents are
# visible to everyone regardless), so restricting the pool here is what
# makes each assign_perm() call actually matter for someone, and is
# what exercises the guardian-permission-join code path this profiling
# effort exists to measure.
for user_idx, owned_idx in _sample_distinct_pairs(
rng,
len(users),
len(owned_documents),
n_user_perms,
):
assign_perm("view_document", users[user_idx], owned_documents[owned_idx])
for group_idx, owned_idx in _sample_distinct_pairs(
rng,
len(groups),
len(owned_documents),
n_group_perms,
):
assign_perm("view_document", groups[group_idx], owned_documents[owned_idx])
return SeededData(
users=users,
groups=groups,
documents=documents,
tags=tags,
correspondents=correspondents,
document_types=document_types,
storage_paths=storage_paths,
)
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#!/usr/bin/env bash
# profiling/stop_postgres.sh
#
# Explicit, manual teardown of the profiling Postgres container. Not called
# automatically by run_with_postgres.sh -- run this yourself once you're
# done with a profiling session, so a seeded `large`-scale dataset can be
# reused across several script runs first. Terminates any active backends
# before stopping, so a stuck query can't stall `docker stop` waiting for
# a graceful Postgres shutdown that never comes.
set -euo pipefail
CONTAINER_NAME="pngx-profiling-pg"
if docker inspect "$CONTAINER_NAME" >/dev/null 2>&1; then
docker exec "$CONTAINER_NAME" psql -U paperless -d paperless -v ON_ERROR_STOP=0 -c "
SELECT pg_terminate_backend(pid)
FROM pg_stat_activity
WHERE pid <> pg_backend_pid();
" >/dev/null 2>&1 || true
docker stop "$CONTAINER_NAME" >/dev/null
echo "Stopped and removed profiling Postgres container."
else
echo "No profiling Postgres container was running."
fi
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# profiling/test_harness_self_check.py
from __future__ import annotations
import json
from pathlib import Path
import pytest
from profiling.harness import append_profiling_history
from profiling.harness import require_postgres
from profiling.harness import run_profile
from profiling.seed import seed_permission_dataset
@pytest.mark.profiling
@pytest.mark.django_db
def test_seed_medium_scale_produces_expected_counts() -> None:
require_postgres()
data = seed_permission_dataset(scale="medium")
assert len(data.documents) == 20_000
assert len(data.tags) == 100
assert len(data.correspondents) == 300
assert len(data.document_types) == 50
assert len(data.storage_paths) == 20
from guardian.models import GroupObjectPermission
from guardian.models import UserObjectPermission
user_perm_count = UserObjectPermission.objects.count()
group_perm_count = GroupObjectPermission.objects.count()
# within 5% of the ratio-derived target -- exact counts depend on random
# sampling without replacement, see seed.py
assert 2_242 <= user_perm_count <= 2_478
assert 43_111 <= group_perm_count <= 47_649
@pytest.mark.profiling
@pytest.mark.django_db
def test_run_profile_reports_query_count_and_timing() -> None:
require_postgres()
def trivial() -> list[int]:
from documents.models import Document
return list(Document.objects.values_list("id", flat=True)[:1])
result = run_profile(trivial, repeat=3)
assert result.best_seconds >= 0
assert len(result.all_seconds) == 3
assert result.query_count >= 1
def test_append_profiling_history_writes_a_valid_json_line() -> None:
history_path = Path(__file__).parent / "results" / "history.jsonl"
before_lines = (
history_path.read_text().splitlines() if history_path.exists() else []
)
append_profiling_history(
stage="self-check",
scenario="test_append_profiling_history_writes_a_valid_json_line",
best_seconds=0.001,
query_count=0,
scale="medium",
code_ref="test-run",
)
after_lines = history_path.read_text().splitlines()
assert len(after_lines) == len(before_lines) + 1
entry = json.loads(after_lines[-1])
assert entry["stage"] == "self-check"
assert entry["code_ref"] == "test-run"
assert entry["scale"] == "medium"
assert "timestamp" in entry
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from __future__ import annotations
import json
from pathlib import Path
import pytest
from documents.models import Document
from documents.permissions import get_objects_for_user_owner_aware
from documents.permissions import permitted_document_ids
from profiling.harness import append_profiling_history
from profiling.harness import capture_explain_analyze
from profiling.harness import require_postgres
from profiling.harness import run_profile
from profiling.seed import seed_permission_dataset
RESULTS_DIR = Path(__file__).parent / "results"
@pytest.mark.profiling
@pytest.mark.django_db
def test_profile_get_objects_for_user_owner_aware_document_baseline() -> None:
require_postgres()
data = seed_permission_dataset(scale="medium")
user = data.users[0]
def call() -> list[int]:
return list(
get_objects_for_user_owner_aware(
user,
"documents.view_document",
Document,
).values_list("id", flat=True),
)
profile = run_profile(call, repeat=3)
plan = capture_explain_analyze(
get_objects_for_user_owner_aware(user, "documents.view_document", Document),
)
RESULTS_DIR.mkdir(exist_ok=True)
(RESULTS_DIR / "stage1_baseline.json").write_text(
json.dumps(
{
"get_objects_for_user_owner_aware_document": {
"best_seconds": profile.best_seconds,
"query_count": profile.query_count,
},
},
indent=2,
),
)
(RESULTS_DIR / "stage1_baseline_explain.txt").write_text(plan)
append_profiling_history(
stage="stage1",
scenario="get_objects_for_user_owner_aware_document_baseline",
best_seconds=profile.best_seconds,
query_count=profile.query_count,
scale="medium",
)
print(f"\nBASELINE best={profile.best_seconds:.4f}s queries={profile.query_count}") # noqa: T201
print(plan) # noqa: T201
@pytest.mark.profiling
@pytest.mark.django_db
def test_profile_permitted_document_ids_after_stage1() -> None:
require_postgres()
data = seed_permission_dataset(scale="medium")
user = data.users[0]
def call():
return list(
Document.objects.filter(id__in=permitted_document_ids(user)).values_list(
"id",
flat=True,
),
)
profile = run_profile(call, repeat=3)
plan = capture_explain_analyze(
Document.objects.filter(id__in=permitted_document_ids(user)),
)
baseline = json.loads((RESULTS_DIR / "stage1_baseline.json").read_text())
baseline_seconds = baseline["get_objects_for_user_owner_aware_document"][
"best_seconds"
]
baseline_queries = baseline["get_objects_for_user_owner_aware_document"][
"query_count"
]
(RESULTS_DIR / "stage1_after.json").write_text(
json.dumps(
{
"permitted_document_ids": {
"best_seconds": profile.best_seconds,
"query_count": profile.query_count,
},
"baseline_best_seconds": baseline_seconds,
"baseline_query_count": baseline_queries,
"speedup_x": baseline_seconds / profile.best_seconds
if profile.best_seconds
else None,
},
indent=2,
),
)
(RESULTS_DIR / "stage1_after_explain.txt").write_text(plan)
append_profiling_history(
stage="stage1",
scenario="permitted_document_ids_after_stage1",
best_seconds=profile.best_seconds,
query_count=profile.query_count,
scale="medium",
)
print(f"\nBEFORE best={baseline_seconds:.4f}s queries={baseline_queries}") # noqa: T201
print(f"AFTER best={profile.best_seconds:.4f}s queries={profile.query_count}") # noqa: T201
# Hard gate: must not be a regression, and should be meaningfully faster
# at this scale (the whole point of this stage).
assert profile.best_seconds < baseline_seconds
assert profile.query_count <= baseline_queries
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# profiling/test_stage2_document_loops.py
from __future__ import annotations
import pytest
from documents.permissions import has_perms_owner_aware
from documents.permissions import permitted_document_ids
from profiling.harness import append_profiling_history
from profiling.harness import require_postgres
from profiling.harness import run_profile
from profiling.seed import seed_permission_dataset
@pytest.mark.profiling
@pytest.mark.django_db
def test_profile_per_row_checker_vs_resolved_set_for_bulk_operation() -> None:
require_postgres()
data = seed_permission_dataset(scale="medium")
user = data.users[0]
# simulate a bulk operation over 500 documents the user can actually see
# (bulk-edit/share/trash all operate on a user's own selection) -- built
# from confirmed-visible documents so all() can't short-circuit unfairly
# in either old_style or new_style, see amendment note above
permitted_ids = set(permitted_document_ids(user))
batch = [doc for doc in data.documents if doc.pk in permitted_ids][:500]
assert len(batch) == 500, (
f"expected at least 500 visible documents to build a fair batch, "
f"got {len(batch)} -- scale profile or seed ratios may need adjusting"
)
def old_style():
return all(has_perms_owner_aware(user, "view_document", doc) for doc in batch)
def new_style():
permitted = set(permitted_document_ids(user))
return all(doc.pk in permitted for doc in batch)
old_profile = run_profile(old_style, repeat=3)
new_profile = run_profile(new_style, repeat=3)
append_profiling_history(
stage="stage2",
scenario="per_row_checker_vs_resolved_set_old",
best_seconds=old_profile.best_seconds,
query_count=old_profile.query_count,
scale="medium",
)
append_profiling_history(
stage="stage2",
scenario="per_row_checker_vs_resolved_set_new",
best_seconds=new_profile.best_seconds,
query_count=new_profile.query_count,
scale="medium",
)
print( # noqa: T201
f"\nOLD (per-row checker): best={old_profile.best_seconds:.4f}s queries={old_profile.query_count}",
)
print( # noqa: T201
f"NEW (resolved set): best={new_profile.best_seconds:.4f}s queries={new_profile.query_count}",
)
assert new_profile.query_count < old_profile.query_count
assert new_profile.best_seconds < old_profile.best_seconds