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feat(profiling): add workflow trigger matching profiling
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
This commit is contained in:
Trenton H
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test_workflow_profile.py
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231
test_workflow_profile.py
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"""
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Workflow trigger matching profiling.
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Run with:
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uv run pytest ../test_workflow_profile.py \
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-m profiling --override-ini="addopts=" -s -v
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Corpus: 500 documents + correspondents + tags + sets of WorkflowTrigger
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objects at 5 and 20 count to allow scaling comparisons.
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Scenarios
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---------
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TestWorkflowMatchingProfile
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- test_existing_document_5_workflows existing_document_matches_workflow x 5 triggers
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- test_existing_document_20_workflows same x 20 triggers
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- test_workflow_prefilter prefilter_documents_by_workflowtrigger on 500 docs
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- test_trigger_type_comparison compare DOCUMENT_ADDED vs DOCUMENT_UPDATED overhead
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"""
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from __future__ import annotations
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import random
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import time
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import pytest
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from faker import Faker
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from profiling import profile_block
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from documents.matching import existing_document_matches_workflow
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from documents.matching import prefilter_documents_by_workflowtrigger
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from documents.models import Correspondent
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from documents.models import Document
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from documents.models import Tag
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from documents.models import Workflow
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from documents.models import WorkflowAction
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from documents.models import WorkflowTrigger
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pytestmark = [pytest.mark.profiling, pytest.mark.django_db]
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NUM_DOCS = 500
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NUM_CORRESPONDENTS = 10
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NUM_TAGS = 20
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SEED = 42
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# ---------------------------------------------------------------------------
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# Module-scoped fixture
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# ---------------------------------------------------------------------------
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@pytest.fixture(scope="module")
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def module_db(django_db_setup, django_db_blocker):
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"""Unlock the DB for the whole module (module-scoped)."""
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with django_db_blocker.unblock():
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yield
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@pytest.fixture(scope="module")
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def workflow_corpus(module_db):
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"""
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500 documents + correspondents + tags + sets of workflow triggers
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at 5 and 20 count to allow scaling comparisons.
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"""
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fake = Faker()
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Faker.seed(SEED)
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rng = random.Random(SEED)
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# ---- lookup objects ---------------------------------------------------
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print("\n[setup] Creating lookup objects...") # noqa: T201
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correspondents = [
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Correspondent.objects.create(name=f"wfcorp-{i}-{fake.company()}"[:128])
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for i in range(NUM_CORRESPONDENTS)
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]
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tags = [
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Tag.objects.create(name=f"wftag-{i}-{fake.word()}"[:100])
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for i in range(NUM_TAGS)
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]
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# ---- documents --------------------------------------------------------
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print(f"[setup] Building {NUM_DOCS} documents...") # noqa: T201
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raw_docs = []
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for i in range(NUM_DOCS):
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raw_docs.append(
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Document(
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title=fake.sentence(nb_words=4).rstrip("."),
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content=fake.paragraph(nb_sentences=3),
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checksum=f"WF{i:07d}",
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correspondent=rng.choice(correspondents + [None] * 3),
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),
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)
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documents = Document.objects.bulk_create(raw_docs, batch_size=500)
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for doc in documents:
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k = rng.randint(0, 3)
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if k:
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doc.tags.add(*rng.sample(tags, k))
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sample_doc = documents[0]
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print(f"[setup] Sample doc pk={sample_doc.pk}") # noqa: T201
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# ---- build triggers at scale 5 and 20 --------------------------------
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_wf_counter = [0]
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def _make_triggers(n: int, trigger_type: int) -> list[WorkflowTrigger]:
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triggers = []
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for i in range(n):
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# Alternate between no filter and a correspondent filter
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corr = correspondents[i % NUM_CORRESPONDENTS] if i % 3 == 0 else None
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trigger = WorkflowTrigger.objects.create(
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type=trigger_type,
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filter_has_correspondent=corr,
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)
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action = WorkflowAction.objects.create(
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type=WorkflowAction.WorkflowActionType.ASSIGNMENT,
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)
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idx = _wf_counter[0]
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_wf_counter[0] += 1
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wf = Workflow.objects.create(name=f"wf-profile-{idx}")
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wf.triggers.add(trigger)
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wf.actions.add(action)
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triggers.append(trigger)
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return triggers
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print("[setup] Creating workflow triggers...") # noqa: T201
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triggers_5 = _make_triggers(5, WorkflowTrigger.WorkflowTriggerType.DOCUMENT_UPDATED)
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triggers_20 = _make_triggers(
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20,
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WorkflowTrigger.WorkflowTriggerType.DOCUMENT_UPDATED,
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)
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triggers_added = _make_triggers(
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5,
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WorkflowTrigger.WorkflowTriggerType.DOCUMENT_ADDED,
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)
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yield {
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"doc": sample_doc,
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"triggers_5": triggers_5,
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"triggers_20": triggers_20,
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"triggers_added": triggers_added,
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}
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# Teardown
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print("\n[teardown] Removing workflow corpus...") # noqa: T201
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Workflow.objects.all().delete()
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WorkflowTrigger.objects.all().delete()
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WorkflowAction.objects.all().delete()
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Document.objects.all().delete()
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Correspondent.objects.all().delete()
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Tag.objects.all().delete()
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# ---------------------------------------------------------------------------
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# TestWorkflowMatchingProfile
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# ---------------------------------------------------------------------------
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class TestWorkflowMatchingProfile:
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"""Profile workflow trigger evaluation per document save."""
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@pytest.fixture(autouse=True)
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def _setup(self, workflow_corpus):
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self.doc = workflow_corpus["doc"]
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self.triggers_5 = workflow_corpus["triggers_5"]
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self.triggers_20 = workflow_corpus["triggers_20"]
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self.triggers_added = workflow_corpus["triggers_added"]
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def test_existing_document_5_workflows(self):
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"""existing_document_matches_workflow x 5 DOCUMENT_UPDATED triggers."""
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doc = self.doc
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triggers = self.triggers_5
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with profile_block(
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f"existing_document_matches_workflow [{len(triggers)} triggers]",
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):
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for trigger in triggers:
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existing_document_matches_workflow(doc, trigger)
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def test_existing_document_20_workflows(self):
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"""existing_document_matches_workflow x 20 triggers -- shows linear scaling."""
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doc = self.doc
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triggers = self.triggers_20
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with profile_block(
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f"existing_document_matches_workflow [{len(triggers)} triggers]",
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):
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for trigger in triggers:
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existing_document_matches_workflow(doc, trigger)
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# Also time each call individually to show per-trigger overhead
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timings = []
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for trigger in triggers:
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t0 = time.perf_counter()
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existing_document_matches_workflow(doc, trigger)
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timings.append((time.perf_counter() - t0) * 1_000_000)
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avg_us = sum(timings) / len(timings)
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print(f"\n Per-trigger avg: {avg_us:.1f} us (n={len(timings)})") # noqa: T201
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def test_workflow_prefilter(self):
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"""prefilter_documents_by_workflowtrigger on 500 docs -- tag + correspondent filters."""
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qs = Document.objects.all()
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print(f"\n Corpus: {qs.count()} documents") # noqa: T201
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for trigger in self.triggers_20[:3]:
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label = (
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f"prefilter_documents_by_workflowtrigger "
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f"[corr={trigger.filter_has_correspondent_id}]"
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)
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with profile_block(label):
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result = prefilter_documents_by_workflowtrigger(qs, trigger)
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# Evaluate the queryset
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count = result.count()
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print(f" -> {count} docs passed filter") # noqa: T201
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def test_trigger_type_comparison(self):
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"""Compare per-call overhead of DOCUMENT_UPDATED vs DOCUMENT_ADDED."""
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doc = self.doc
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runs = 200
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for label, triggers in [
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("DOCUMENT_UPDATED", self.triggers_5),
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("DOCUMENT_ADDED", self.triggers_added),
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]:
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t0 = time.perf_counter()
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for _ in range(runs):
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for trigger in triggers:
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existing_document_matches_workflow(doc, trigger)
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total_calls = runs * len(triggers)
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us_per_call = (time.perf_counter() - t0) / total_calls * 1_000_000
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print( # noqa: T201
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f" {label:<22s} {us_per_call:.2f} us/call "
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f"({total_calls} calls, {len(triggers)} triggers)",
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)
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