OpenMetadata/ingestion/tests/unit/profiler/pandas/test_custom_metrics.py

#  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 datetime
import os
from unittest import TestCase
from unittest.mock import patch
from uuid import uuid4

import pandas as pd

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

BUCKET_NAME = "MyBucket"
REGION = "us-west-1"


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,
            ),
        ],
    )

    def setUp(self):
        with patch(
            "metadata.mixins.pandas.pandas_mixin.fetch_dataframe",
            return_value=self.dfs,
        ):
            self.sqa_profiler_interface = PandasProfilerInterface(
                self.datalake_conn,
                None,
                self.table_entity,
                None,
                None,
                None,
                None,
                None,
                thread_count=1,
            )

    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(
            "metadata.mixins.pandas.pandas_mixin.fetch_dataframe",
            return_value=self.dfs,
        ):
            self.sqa_profiler_interface = PandasProfilerInterface(
                self.datalake_conn,
                None,
                table_entity,
                None,
                None,
                None,
                None,
                None,
                thread_count=1,
            )

        profiler = Profiler(
            profiler_interface=self.sqa_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

    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(
            "metadata.mixins.pandas.pandas_mixin.fetch_dataframe",
            return_value=self.dfs,
        ):
            self.sqa_profiler_interface = PandasProfilerInterface(
                self.datalake_conn,
                None,
                table_entity,
                None,
                None,
                None,
                None,
                None,
                thread_count=1,
            )

        profiler = Profiler(
            profiler_interface=self.sqa_profiler_interface,
        )
        metrics = profiler.compute_metrics()
        for k, v in metrics._column_results.items():
            for metric in v.get("customMetrics", []):
                if metric.name == "CustomerBornedAfter1991":
                    assert metric.value == 1
                if metric.name == "AverageAge":
                    assert metric.value == 2