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* pydantic v2 * pydanticv2 * fix parser * fix annotated * fix model dumping * mysql ingestion * clean root models * clean root models * bump airflow * bump airflow * bump airflow * optionals * optionals * optionals * jdk * airflow migrate * fab provider * fab provider * fab provider * some more fixes * fixing tests and imports * model_dump and model_validate * model_dump and model_validate * model_dump and model_validate * union * pylint * pylint * integration tests * fix CostAnalysisReportData * integration tests * tests * missing defaults * missing defaults
56 lines
1.8 KiB
Python
56 lines
1.8 KiB
Python
# Copyright 2021 Collate
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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# http://www.apache.org/licenses/LICENSE-2.0
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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"""
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Validator for column value missing count to be equal test case
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"""
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from typing import Optional
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from sqlalchemy import Column, inspect
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from metadata.data_quality.validations.column.base.columnValuesMissingCount import (
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BaseColumnValuesMissingCountValidator,
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)
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from metadata.data_quality.validations.mixins.sqa_validator_mixin import (
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SQAValidatorMixin,
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)
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from metadata.profiler.metrics.registry import Metrics
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from metadata.utils.logger import test_suite_logger
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logger = test_suite_logger()
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class ColumnValuesMissingCountValidator(
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BaseColumnValuesMissingCountValidator, SQAValidatorMixin
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):
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"""Validator for column value missing count to be equal test case"""
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def _get_column_name(self) -> Column:
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"""Get column name from the test case entity link
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Returns:
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SQALikeColumn: column
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"""
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return self.get_column_name(
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self.test_case.entityLink.root,
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inspect(self.runner.table).c,
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)
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def _run_results(self, metric: Metrics, column: Column, **kwargs) -> Optional[int]:
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"""compute result of the test case
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Args:
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metric: metric
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column: column
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"""
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return self.run_query_results(self.runner, metric, column, **kwargs)
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