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# to you under the Apache License, Version 2.0 (the
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#
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#
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# under the License.o

from datetime import datetime
from typing import Any, Dict, Optional

from superset.db_engine_specs.base import BaseEngineSpec
from superset.db_engine_specs.hive import HiveEngineSpec

time_grain_expressions = {
    None: "{col}",
    "PT1S": "date_trunc('second', {col})",
    "PT1M": "date_trunc('minute', {col})",
    "PT1H": "date_trunc('hour', {col})",
    "P1D": "date_trunc('day', {col})",
    "P1W": "date_trunc('week', {col})",
    "P1M": "date_trunc('month', {col})",
    "P3M": "date_trunc('quarter', {col})",
    "P1Y": "date_trunc('year', {col})",
    "P1W/1970-01-03T00:00:00Z": (
        "date_trunc('week', {col} + interval '1 day') + interval '5 days'"
    ),
    "1969-12-28T00:00:00Z/P1W": (
        "date_trunc('week', {col} + interval '1 day') - interval '1 day'"
    ),
}


class DatabricksHiveEngineSpec(HiveEngineSpec):
    engine = "databricks"
    engine_name = "Databricks Interactive Cluster"
    driver = "pyhive"
    _show_functions_column = "function"

    _time_grain_expressions = time_grain_expressions


class DatabricksODBCEngineSpec(BaseEngineSpec):
    engine = "databricks"
    engine_name = "Databricks SQL Endpoint"
    driver = "pyodbc"

    _time_grain_expressions = time_grain_expressions

    @classmethod
    def convert_dttm(
        cls, target_type: str, dttm: datetime, db_extra: Optional[Dict[str, Any]] = None
    ) -> Optional[str]:
        return HiveEngineSpec.convert_dttm(target_type, dttm, db_extra=db_extra)

    @classmethod
    def epoch_to_dttm(cls) -> str:
        return HiveEngineSpec.epoch_to_dttm()


class DatabricksNativeEngineSpec(DatabricksODBCEngineSpec):
    engine = "databricks"
    engine_name = "Databricks Native Connector"
    driver = "connector"