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44c158b8c2
The new module/class helps us constructing queries and count records to expose various statistics on the homepage. We also utilize for some new prometheus metrics (package and user gauges). Record counts are being cached with Redis. Signed-off-by: moson <moson@archlinux.org>
39 lines
970 B
Python
39 lines
970 B
Python
import pytest
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from prometheus_client import REGISTRY, generate_latest
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from aurweb import db
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from aurweb.cache import db_query_cache
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from aurweb.models.account_type import USER_ID
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from aurweb.models.user import User
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@pytest.fixture(autouse=True)
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def setup(db_test):
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return
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@pytest.fixture
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def user() -> User:
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with db.begin():
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user = db.create(
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User,
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Username="test",
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Email="test@example.org",
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RealName="Test User",
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Passwd="testPassword",
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AccountTypeID=USER_ID,
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)
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yield user
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def test_search_cache_metrics(user: User):
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# Fire off 3 identical queries for caching
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for _ in range(3):
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db_query_cache("key", db.query(User))
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# Get metrics
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metrics = str(generate_latest(REGISTRY))
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# We should have 1 miss and 2 hits
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assert 'search_requests_total{cache="miss"} 1.0' in metrics
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assert 'search_requests_total{cache="hit"} 2.0' in metrics
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