df3f47c79a
This will be used in a followup PR to order search results instead of the RAC join. Currently, the join with the RAC table in search results in a lookup of ~600K rows, which causes searching to take ~6s. This PR denormalizes the data we need, as well as allowing us to score based on a wider band (6 months vs the current 1 week).
38 lines
1.4 KiB
Python
38 lines
1.4 KiB
Python
from datetime import date, timedelta
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import pytest
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from data.database import RepositoryActionCount, RepositorySearchScore
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from data.model.repository import create_repository
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from data.model.repositoryactioncount import update_repository_score, SEARCH_BUCKETS
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from test.fixtures import database_uri, init_db_path, sqlitedb_file
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@pytest.mark.parametrize('bucket_sums,expected_score', [
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((0, 0, 0, 0), 0),
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((1, 6, 24, 152), 100),
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((2, 6, 24, 152), 101),
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((1, 6, 24, 304), 171),
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((100, 480, 24, 152), 703),
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((1, 6, 24, 15200), 7131),
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((300, 500, 1000, 0), 1733),
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((5000, 0, 0, 0), 5434),
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])
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def test_update_repository_score(bucket_sums, expected_score, database_uri):
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# Create a new repository.
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repo = create_repository('devtable', 'somenewrepo', None, repo_kind='image')
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# Delete the RAC created in create_repository.
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RepositoryActionCount.delete().where(RepositoryActionCount.repository == repo).execute()
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# Add RAC rows for each of the buckets.
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for index, bucket in enumerate(SEARCH_BUCKETS):
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for day in range(0, bucket.days):
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RepositoryActionCount.create(repository=repo,
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count=(bucket_sums[index] / bucket.days * 1.0),
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date=date.today() - bucket.delta + timedelta(days=day))
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assert update_repository_score(repo)
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assert RepositorySearchScore.get(repository=repo).score == expected_score
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