# Copyright 2021 Collate # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # http://www.apache.org/licenses/LICENSE-2.0 # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. """ Test Metrics behavior """ import os import sys from unittest import TestCase, mock from unittest.mock import Mock, patch from uuid import uuid4 import pandas as pd import pytest from metadata.generated.schema.entity.data.table import Column as EntityColumn from metadata.generated.schema.entity.data.table import ColumnName, DataType, Table from metadata.generated.schema.entity.services.connections.database.datalake.s3Config import ( S3Config, ) from metadata.generated.schema.entity.services.connections.database.datalakeConnection import ( DatalakeConnection, ) from metadata.generated.schema.security.credentials.awsCredentials import AWSCredentials from metadata.generated.schema.tests.customMetric import CustomMetric from metadata.generated.schema.type.entityReference import EntityReference from metadata.profiler.interface.pandas.profiler_interface import ( PandasProfilerInterface, ) from metadata.profiler.processor.core import Profiler from metadata.sampler.pandas.sampler import DatalakeSampler BUCKET_NAME = "MyBucket" REGION = "us-west-1" if sys.version_info < (3, 9): pytest.skip( "requires python 3.9+ due to incompatibility with object patch", allow_module_level=True, ) class FakeClient: def __init__(self): self._client = None class FakeConnection: def __init__(self): self.client = FakeClient() class MetricsTest(TestCase): """ Run checks on different metrics """ current_dir = os.path.dirname(__file__) resources_dir = os.path.join(current_dir, "resources") datalake_conn = DatalakeConnection( configSource=S3Config( securityConfig=AWSCredentials( awsAccessKeyId="fake_access_key", awsSecretAccessKey="fake_secret_key", awsRegion=REGION, ) ) ) dfs = [ pd.read_csv(os.path.join(resources_dir, "profiler_test_.csv"), parse_dates=[5]) ] table_entity = Table( id=uuid4(), name="user", databaseSchema=EntityReference(id=uuid4(), type="databaseSchema", name="name"), columns=[ EntityColumn( name=ColumnName("id"), dataType=DataType.INT, ), EntityColumn( name=ColumnName("first_name"), dataType=DataType.STRING, ), EntityColumn( name=ColumnName("last_name"), dataType=DataType.STRING, ), EntityColumn( name=ColumnName("city"), dataType=DataType.STRING, ), EntityColumn( name=ColumnName("country"), dataType=DataType.STRING, ), EntityColumn( name=ColumnName("birthdate"), dataType=DataType.DATE, ), EntityColumn( name=ColumnName("age"), dataType=DataType.INT, ), ], ) @mock.patch( "metadata.profiler.interface.profiler_interface.get_ssl_connection", return_value=FakeConnection(), ) @mock.patch( "metadata.sampler.sampler_interface.get_ssl_connection", return_value=FakeConnection(), ) def setUp(self, *_): with ( patch.object(DatalakeSampler, "table", new_callable=lambda: self.dfs), patch.object(DatalakeSampler, "get_client", return_value=Mock()), ): self.sampler = DatalakeSampler( service_connection_config=DatalakeConnection(configSource={}), ometa_client=None, entity=self.table_entity, ) self.datalake_profiler_interface = PandasProfilerInterface( service_connection_config=DatalakeConnection(configSource={}), ometa_client=None, entity=self.table_entity, source_config=None, sampler=self.sampler, thread_count=1, ) @mock.patch( "metadata.profiler.interface.profiler_interface.get_ssl_connection", return_value=FakeConnection(), ) @mock.patch( "metadata.sampler.sampler_interface.get_ssl_connection", return_value=FakeConnection(), ) def test_table_custom_metric(self, *_): table_entity = Table( id=uuid4(), name="user", databaseSchema=EntityReference( id=uuid4(), type="databaseSchema", name="name" ), columns=[ EntityColumn( name=ColumnName("id"), dataType=DataType.INT, ), EntityColumn( name=ColumnName("first_name"), dataType=DataType.STRING, ), EntityColumn( name=ColumnName("last_name"), dataType=DataType.STRING, ), EntityColumn( name=ColumnName("city"), dataType=DataType.STRING, ), EntityColumn( name=ColumnName("country"), dataType=DataType.STRING, ), EntityColumn( name=ColumnName("birthdate"), dataType=DataType.DATE, ), EntityColumn( name=ColumnName("age"), dataType=DataType.INT, ), ], customMetrics=[ CustomMetric( name="LastNameFilter", expression="'last_name' != Doe", ), CustomMetric( name="notUS", expression="'country == US'", ), ], ) with ( patch.object(DatalakeSampler, "table", new_callable=lambda: self.dfs), patch.object(DatalakeSampler, "get_client", return_value=Mock()), ): sampler = DatalakeSampler( service_connection_config=DatalakeConnection(configSource={}), ometa_client=None, entity=table_entity, ) datalake_profiler_interface = PandasProfilerInterface( service_connection_config=DatalakeConnection(configSource={}), ometa_client=None, entity=table_entity, source_config=None, sampler=sampler, thread_count=1, ) profiler = Profiler( profiler_interface=datalake_profiler_interface, ) metrics = profiler.compute_metrics() for k, v in metrics._table_results.items(): for metric in v: if metric.name == "LastNameFilter": assert metric.value == 1 if metric.name == "notUS": assert metric.value == 2 @mock.patch( "metadata.profiler.interface.profiler_interface.get_ssl_connection", return_value=FakeConnection(), ) @mock.patch( "metadata.sampler.sampler_interface.get_ssl_connection", return_value=FakeConnection(), ) def test_column_custom_metric(self, *_): table_entity = Table( id=uuid4(), name="user", databaseSchema=EntityReference( id=uuid4(), type="databaseSchema", name="name" ), columns=[ EntityColumn( name=ColumnName("id"), dataType=DataType.INT, customMetrics=[ CustomMetric( name="LastNameFilter", columnName="id", expression="'last_name' != Doe", ), CustomMetric( name="notUS", columnName="id", expression="'country == US'", ), ], ) ], ) with ( patch.object(DatalakeSampler, "table", new_callable=lambda: self.dfs), patch.object(DatalakeSampler, "get_client", return_value=Mock()), ): sampler = DatalakeSampler( service_connection_config=DatalakeConnection(configSource={}), ometa_client=None, entity=table_entity, ) datalake_profiler_interface = PandasProfilerInterface( service_connection_config=DatalakeConnection(configSource={}), ometa_client=None, entity=table_entity, source_config=None, sampler=sampler, thread_count=1, ) profiler = Profiler( profiler_interface=datalake_profiler_interface, ) metrics = profiler.compute_metrics() for k, v in metrics._column_results.items(): for metric in v.get("customMetrics", []): if metric.name == "CustomerBornAfter1991": assert metric.value == 1 if metric.name == "AverageAge": assert metric.value == 2