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# or more contributor license agreements.  See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership.  The ASF licenses this file
# to you 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.
from typing import Any, Dict, TYPE_CHECKING

import pytest

if TYPE_CHECKING:
    from superset.connectors.sqla.models import SqlMetric, TableColumn


@pytest.fixture
def columns_default() -> Dict[str, Any]:
    """Default props for new columns"""
    return {
        "changed_by": 1,
        "created_by": 1,
        "datasets": [],
        "tables": [],
        "is_additive": False,
        "is_aggregation": False,
        "is_dimensional": False,
        "is_filterable": True,
        "is_increase_desired": True,
        "is_partition": False,
        "is_physical": True,
        "is_spatial": False,
        "is_temporal": False,
        "description": None,
        "extra_json": "{}",
        "unit": None,
        "warning_text": None,
        "is_managed_externally": False,
        "external_url": None,
    }


@pytest.fixture
def sample_columns() -> Dict["TableColumn", Dict[str, Any]]:
    from superset.connectors.sqla.models import TableColumn

    return {
        TableColumn(column_name="ds", is_dttm=1, type="TIMESTAMP"): {
            "name": "ds",
            "expression": "ds",
            "type": "TIMESTAMP",
            "advanced_data_type": None,
            "is_temporal": True,
            "is_physical": True,
        },
        TableColumn(column_name="num_boys", type="INTEGER", groupby=True): {
            "name": "num_boys",
            "expression": "num_boys",
            "type": "INTEGER",
            "advanced_data_type": None,
            "is_dimensional": True,
            "is_physical": True,
        },
        TableColumn(column_name="region", type="VARCHAR", groupby=True): {
            "name": "region",
            "expression": "region",
            "type": "VARCHAR",
            "advanced_data_type": None,
            "is_dimensional": True,
            "is_physical": True,
        },
        TableColumn(
            column_name="profit",
            type="INTEGER",
            groupby=False,
            expression="revenue-expenses",
        ): {
            "name": "profit",
            "expression": "revenue-expenses",
            "type": "INTEGER",
            "advanced_data_type": None,
            "is_physical": False,
        },
    }


@pytest.fixture
def sample_metrics() -> Dict["SqlMetric", Dict[str, Any]]:
    from superset.connectors.sqla.models import SqlMetric

    return {
        SqlMetric(metric_name="cnt", expression="COUNT(*)", metric_type="COUNT"): {
            "name": "cnt",
            "expression": "COUNT(*)",
            "extra_json": '{"metric_type": "COUNT"}',
            "type": "UNKNOWN",
            "advanced_data_type": None,
            "is_additive": True,
            "is_aggregation": True,
            "is_filterable": False,
            "is_physical": False,
        },
        SqlMetric(
            metric_name="avg revenue", expression="AVG(revenue)", metric_type="AVG"
        ): {
            "name": "avg revenue",
            "expression": "AVG(revenue)",
            "extra_json": '{"metric_type": "AVG"}',
            "type": "UNKNOWN",
            "advanced_data_type": None,
            "is_additive": False,
            "is_aggregation": True,
            "is_filterable": False,
            "is_physical": False,
        },
    }