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# 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 __future__ import annotations

import logging
import re
from datetime import datetime
from re import Pattern
from typing import Any, Optional

from flask_babel import gettext as __
from sqlalchemy import types
from sqlalchemy.dialects.mssql.base import SMALLDATETIME

from superset.constants import TimeGrain
from superset.db_engine_specs.base import BaseEngineSpec
from superset.errors import SupersetErrorType
from superset.models.sql_types.mssql_sql_types import GUID
from superset.utils.core import GenericDataType

logger = logging.getLogger(__name__)


# Regular expressions to catch custom errors
CONNECTION_ACCESS_DENIED_REGEX = re.compile("Adaptive Server connection failed")
CONNECTION_INVALID_HOSTNAME_REGEX = re.compile(
    r"Adaptive Server is unavailable or does not exist \((?P<hostname>.*?)\)"
    "(?!.*Net-Lib error).*$"
)
CONNECTION_PORT_CLOSED_REGEX = re.compile(
    r"Net-Lib error during Connection refused \(61\)"
)
CONNECTION_HOST_DOWN_REGEX = re.compile(
    r"Net-Lib error during Operation timed out \(60\)"
)


class MssqlEngineSpec(BaseEngineSpec):
    engine = "mssql"
    engine_name = "Microsoft SQL Server"
    max_column_name_length = 128
    allows_cte_in_subquery = False
    supports_multivalues_insert = True

    _time_grain_expressions = {
        None: "{col}",
        TimeGrain.SECOND: "DATEADD(SECOND, \
            DATEDIFF(SECOND, '2000-01-01', {col}), '2000-01-01')",
        TimeGrain.MINUTE: "DATEADD(MINUTE, DATEDIFF(MINUTE, 0, {col}), 0)",
        TimeGrain.FIVE_MINUTES: "DATEADD(MINUTE, \
            DATEDIFF(MINUTE, 0, {col}) / 5 * 5, 0)",
        TimeGrain.TEN_MINUTES: "DATEADD(MINUTE, \
            DATEDIFF(MINUTE, 0, {col}) / 10 * 10, 0)",
        TimeGrain.FIFTEEN_MINUTES: "DATEADD(MINUTE, \
            DATEDIFF(MINUTE, 0, {col}) / 15 * 15, 0)",
        TimeGrain.THIRTY_MINUTES: "DATEADD(MINUTE, \
            DATEDIFF(MINUTE, 0, {col}) / 30 * 30, 0)",
        TimeGrain.HOUR: "DATEADD(HOUR, DATEDIFF(HOUR, 0, {col}), 0)",
        TimeGrain.DAY: "DATEADD(DAY, DATEDIFF(DAY, 0, {col}), 0)",
        TimeGrain.WEEK: "DATEADD(DAY, 1 - DATEPART(WEEKDAY, {col}),"
        " DATEADD(DAY, DATEDIFF(DAY, 0, {col}), 0))",
        TimeGrain.MONTH: "DATEADD(MONTH, DATEDIFF(MONTH, 0, {col}), 0)",
        TimeGrain.QUARTER: "DATEADD(QUARTER, DATEDIFF(QUARTER, 0, {col}), 0)",
        TimeGrain.YEAR: "DATEADD(YEAR, DATEDIFF(YEAR, 0, {col}), 0)",
        TimeGrain.WEEK_STARTING_SUNDAY: "DATEADD(DAY, -1,"
        " DATEADD(WEEK, DATEDIFF(WEEK, 0, {col}), 0))",
        TimeGrain.WEEK_STARTING_MONDAY: "DATEADD(WEEK,"
        " DATEDIFF(WEEK, 0, DATEADD(DAY, -1, {col})), 0)",
    }

    column_type_mappings = (
        (
            re.compile(r"^smalldatetime.*", re.IGNORECASE),
            SMALLDATETIME(),
            GenericDataType.TEMPORAL,
        ),
        (
            re.compile(r"^uniqueidentifier.*", re.IGNORECASE),
            GUID(),
            GenericDataType.STRING,
        ),
    )

    custom_errors: dict[Pattern[str], tuple[str, SupersetErrorType, dict[str, Any]]] = {
        CONNECTION_ACCESS_DENIED_REGEX: (
            __(
                'Either the username "%(username)s", password, '
                'or database name "%(database)s" is incorrect.'
            ),
            SupersetErrorType.CONNECTION_ACCESS_DENIED_ERROR,
            {},
        ),
        CONNECTION_INVALID_HOSTNAME_REGEX: (
            __('The hostname "%(hostname)s" cannot be resolved.'),
            SupersetErrorType.CONNECTION_INVALID_HOSTNAME_ERROR,
            {},
        ),
        CONNECTION_PORT_CLOSED_REGEX: (
            __('Port %(port)s on hostname "%(hostname)s" refused the connection.'),
            SupersetErrorType.CONNECTION_PORT_CLOSED_ERROR,
            {},
        ),
        CONNECTION_HOST_DOWN_REGEX: (
            __(
                'The host "%(hostname)s" might be down, and can\'t be '
                "reached on port %(port)s."
            ),
            SupersetErrorType.CONNECTION_HOST_DOWN_ERROR,
            {},
        ),
    }

    @classmethod
    def epoch_to_dttm(cls) -> str:
        return "dateadd(S, {col}, '1970-01-01')"

    @classmethod
    def convert_dttm(
        cls, target_type: str, dttm: datetime, db_extra: Optional[dict[str, Any]] = None
    ) -> Optional[str]:
        sqla_type = cls.get_sqla_column_type(target_type)

        if isinstance(sqla_type, types.Date):
            return f"CONVERT(DATE, '{dttm.date().isoformat()}', 23)"
        if isinstance(sqla_type, SMALLDATETIME):
            datetime_formatted = dttm.isoformat(sep=" ", timespec="seconds")
            return f"""CONVERT(SMALLDATETIME, '{datetime_formatted}', 20)"""
        if isinstance(sqla_type, types.DateTime):
            datetime_formatted = dttm.isoformat(timespec="milliseconds")
            return f"""CONVERT(DATETIME, '{datetime_formatted}', 126)"""
        return None

    @classmethod
    def fetch_data(
        cls, cursor: Any, limit: Optional[int] = None
    ) -> list[tuple[Any, ...]]:
        if not cursor.description:
            return []
        data = super().fetch_data(cursor, limit)
        # Lists of `pyodbc.Row` need to be unpacked further
        return cls.pyodbc_rows_to_tuples(data)

    @classmethod
    def extract_error_message(cls, ex: Exception) -> str:
        if str(ex).startswith("(8155,"):
            return (
                f"{cls.engine} error: All your SQL functions need to "  # noqa: S608
                "have an alias on MSSQL. For example: SELECT COUNT(*) AS C1 FROM TABLE1"
            )
        return f"{cls.engine} error: {cls._extract_error_message(ex)}"


class AzureSynapseSpec(MssqlEngineSpec):
    engine = "mssql"
    engine_name = "Azure Synapse"
    default_driver = "pyodbc"