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chore: remove temporary profiling infrastructure
Profiling tests and helper served their purpose during the search performance optimization work. Baseline and post-implementation data captured in docs/superpowers/plans/. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
This commit is contained in:
Trenton Holmes
@@ -1,71 +0,0 @@
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"""
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Temporary profiling utilities for comparing implementations.
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Usage in a management command or shell::
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from documents.profiling import profile_block
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with profile_block("new check_sanity"):
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messages = check_sanity()
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with profile_block("old check_sanity"):
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messages = check_sanity_old()
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Drop this file when done.
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"""
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from __future__ import annotations
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import tracemalloc
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from contextlib import contextmanager
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from time import perf_counter
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from typing import TYPE_CHECKING
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if TYPE_CHECKING:
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from collections.abc import Generator
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from django.db import connection
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from django.db import reset_queries
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from django.test.utils import override_settings
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@contextmanager
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def profile_block(label: str = "block") -> Generator[None, None, None]:
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"""Profile memory, wall time, and DB queries for a code block.
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Prints a summary to stdout on exit. Requires no external packages.
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Enables DEBUG temporarily to capture Django's query log.
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"""
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tracemalloc.start()
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snapshot_before = tracemalloc.take_snapshot()
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with override_settings(DEBUG=True):
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reset_queries()
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start = perf_counter()
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yield
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elapsed = perf_counter() - start
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queries = list(connection.queries)
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snapshot_after = tracemalloc.take_snapshot()
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_, peak = tracemalloc.get_traced_memory()
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tracemalloc.stop()
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# Compare snapshots for top allocations
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stats = snapshot_after.compare_to(snapshot_before, "lineno")
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query_time = sum(float(q["time"]) for q in queries)
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mem_diff = sum(s.size_diff for s in stats)
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print(f"\n{'=' * 60}") # noqa: T201
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print(f" Profile: {label}") # noqa: T201
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print(f"{'=' * 60}") # noqa: T201
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print(f" Wall time: {elapsed:.4f}s") # noqa: T201
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print(f" Queries: {len(queries)} ({query_time:.4f}s)") # noqa: T201
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print(f" Memory delta: {mem_diff / 1024:.1f} KiB") # noqa: T201
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print(f" Peak memory: {peak / 1024:.1f} KiB") # noqa: T201
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print("\n Top 5 allocations:") # noqa: T201
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for stat in stats[:5]:
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print(f" {stat}") # noqa: T201
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print(f"{'=' * 60}\n") # noqa: T201
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@@ -1,111 +0,0 @@
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"""
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Temporary profiling tests for search performance.
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Run with: uv run pytest src/documents/tests/test_search_profiling.py -v -s -p no:xdist
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The -s flag is required to see profile_block() output on stdout.
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The -p no:xdist flag disables parallel execution so profiling data is accurate.
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Delete this file when profiling is complete.
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"""
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import pytest
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from django.contrib.auth.models import User
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from rest_framework.test import APIClient
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from documents.models import Document
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from documents.profiling import profile_block
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from documents.search import get_backend
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from documents.search import reset_backend
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from documents.tests.utils import DirectoriesMixin
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pytestmark = [pytest.mark.search, pytest.mark.django_db]
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DOC_COUNT = 200 # Enough to exercise pagination and overfetch behavior
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class TestSearchProfilingBaseline(DirectoriesMixin):
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"""Baseline profiling of the CURRENT search implementation.
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Run BEFORE making changes, record the output, then compare with Task 6.
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"""
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@pytest.fixture(autouse=True)
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def _setup(self):
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reset_backend()
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self.user = User.objects.create_superuser(username="profiler")
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self.client = APIClient()
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self.client.force_authenticate(user=self.user)
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backend = get_backend()
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for i in range(DOC_COUNT):
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doc = Document.objects.create(
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title=f"Profiling document number {i}",
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content=f"This is searchable content for document {i} with keyword profiling",
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checksum=f"PROF{i:04d}",
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archive_serial_number=i + 1,
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)
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backend.add_or_update(doc)
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yield
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reset_backend()
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def test_profile_relevance_search(self):
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"""Profile: relevance-ranked search, no ordering, page 1 default page_size."""
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with profile_block("BEFORE — relevance search (no ordering)"):
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response = self.client.get("/api/documents/?query=profiling")
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assert response.status_code == 200
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assert response.data["count"] == DOC_COUNT
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def test_profile_sorted_search(self):
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"""Profile: search with ORM-based ordering (created field)."""
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with profile_block("BEFORE — sorted search (ordering=created)"):
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response = self.client.get(
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"/api/documents/?query=profiling&ordering=created",
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)
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assert response.status_code == 200
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assert response.data["count"] == DOC_COUNT
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def test_profile_paginated_search(self):
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"""Profile: search requesting page 2 with explicit page_size."""
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with profile_block("BEFORE — paginated search (page=2, page_size=25)"):
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response = self.client.get(
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"/api/documents/?query=profiling&page=2&page_size=25",
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)
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assert response.status_code == 200
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assert len(response.data["results"]) == 25
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def test_profile_search_with_selection_data(self):
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"""Profile: search with include_selection_data=true."""
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with profile_block("BEFORE — search with selection_data"):
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response = self.client.get(
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"/api/documents/?query=profiling&include_selection_data=true",
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)
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assert response.status_code == 200
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assert "selection_data" in response.data
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def test_profile_backend_search_only(self):
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"""Profile: raw backend.search() call to isolate Tantivy cost from DRF."""
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backend = get_backend()
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with profile_block("BEFORE — backend.search(page_size=10000, all highlights)"):
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results = backend.search(
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"profiling",
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user=None,
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page=1,
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page_size=10000,
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sort_field=None,
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sort_reverse=False,
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)
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assert results.total == DOC_COUNT
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def test_profile_backend_search_single_page(self):
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"""Profile: raw backend.search() with real page size to compare."""
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backend = get_backend()
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with profile_block("BEFORE — backend.search(page_size=25)"):
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results = backend.search(
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"profiling",
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user=None,
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page=1,
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page_size=25,
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sort_field=None,
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sort_reverse=False,
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)
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assert len(results.hits) == 25
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