From d23f1f0a3b98d90ff6cd17f52f626f52b97d0fa5 Mon Sep 17 00:00:00 2001
From: Klaas van Schelven <klaas@vanschelven.com>
Date: Thu, 18 Jul 2024 13:17:45 +0200
Subject: [PATCH] Remove load_performance_fixture

in the belief that it was only (mostly?) useful in the context of
the pc-registry performance tests. (We do our other tests end-to-end
using the stress tests)
---
 .../commands/load_performance_fixture.py      | 69 -------------------
 1 file changed, 69 deletions(-)
 delete mode 100644 performance/management/commands/load_performance_fixture.py

diff --git a/performance/management/commands/load_performance_fixture.py b/performance/management/commands/load_performance_fixture.py
deleted file mode 100644
index 7b1c510..0000000
--- a/performance/management/commands/load_performance_fixture.py
+++ /dev/null
@@ -1,69 +0,0 @@
-from django.core.management.base import BaseCommand
-import uuid
-
-import random
-from datetime import datetime, timezone
-
-from django.conf import settings
-
-from performance.bursty_data import generate_bursty_data, buckets_to_points_in_time
-from projects.models import Project
-from issues.models import Issue, Grouping
-from events.models import Event
-
-
-class Command(BaseCommand):
-    help = "..."
-
-    def handle(self, *args, **options):
-        if "performance" not in str(settings.DATABASES["default"]["NAME"]):
-            raise ValueError("This command should only be run on the performance-test database")
-
-        Project.objects.all().delete()
-        Grouping.objects.all().delete()
-        Issue.objects.all().delete()
-        Event.objects.all().delete()
-
-        # as a first approach, let's focus on a 'typical' (whatever that means) local setup (not hosted), for a small
-        # team.  maybe 10 people would work on max 10 projects. let's assume we have 10k per-project limits for events
-        # set up. and let's assume 100 issues per project (far from inbox-zero, approach bug-sewer territory)
-        #
-        projects = [Project.objects.create(name="project %s" % i) for i in range(10)]
-        issues_by_project = {}
-
-        for p in projects:
-            issues_by_project[p.id] = []
-            for i in range(100):
-                issues_by_project[p.id].append(Issue.objects.create(project=p))
-                Grouping.objects.create(
-                    project=p,
-                    grouping_key="grouping key %d" % i,
-                    issue=issues_by_project[p.id][i],
-                )
-
-        # now we have 10 projects, each with 100 issues. let's create 10k events for each project.
-        for p in projects:
-            print("loading 10k events for project", p.name)
-            points = buckets_to_points_in_time(
-                generate_bursty_data(num_buckets=350, expected_nr_of_bursts=10),
-                datetime(2020, 10, 15, tzinfo=timezone.utc),
-                datetime(2021, 10, 15, 10, 5, tzinfo=timezone.utc),
-                10_000,
-            )
-
-            for i, point in enumerate(points):
-                if i % 1_000 == 0:
-                    print("loaded", i, "events")
-
-                # note: because we use such minimal (non-data-containing) events here, the setup in the below may
-                # actually not be representative of real world performance.
-                Event.objects.create(
-                    project=p,
-                    issue=random.choice(issues_by_project[p.id]),
-                    server_side_timestamp=point,
-                    timestamp=point,
-                    event_id=uuid.uuid4().hex,
-                    has_exception=True,
-                    has_logentry=True,
-                    data="{}",
-                )