import os
import logging
from datetime import date, datetime
import pyodbc
import pandas as pd
from config import DATA_DIR, normalize_fio, ZUP_SQL_CONFIG

logger = logging.getLogger(__name__)


def get_zup_connection_string() -> str:
    """Формирует строку подключения pyodbc к MS SQL Server из config.py."""
    return (
        f"DRIVER={ZUP_SQL_CONFIG['driver']};"
        f"SERVER={ZUP_SQL_CONFIG['server']};"
        f"DATABASE={ZUP_SQL_CONFIG['database']};"
        f"UID={ZUP_SQL_CONFIG['user']};"
        f"PWD={ZUP_SQL_CONFIG['password']};"
        f"TrustServerCertificate={ZUP_SQL_CONFIG.get('trust_server_certificate', 'yes')};"
        f"Encrypt={ZUP_SQL_CONFIG.get('encrypt', 'no')};"
    )


def fetch_zup_absences_from_sql(target_date) -> pd.DataFrame:
    """
    Извлекает оперативные отсутствия и действующие декреты из MS SQL 1С:ЗУП 3.1
    на указанную дату (принимает как datetime.date, так и строку 'DD.MM.YYYY' / 'DD_MM_YYYY').
    """
    if isinstance(target_date, str):
        clean_date_str = target_date.replace('_', '.')
        try:
            target_date = datetime.strptime(clean_date_str, "%d.%m.%Y").date()
        except ValueError:
            logger.error(f"[❌] Неверный формат даты для SQL-запроса: {target_date}. Ожидался DD.MM.YYYY")
            return pd.DataFrame()

    query = """
    DECLARE @TargetDate DATE = ?;

    -- 1. Оперативные отсутствия (Отпуска, Командировки, Больничные, Отгулы)
    SELECT 
        LTRIM(RTRIM(ref_emp._Description)) AS [ФИО],
        CASE state._Fld16925RRef
            WHEN 0x9C10B2452D414FDF4A90E2B2AB81D3F7 THEN N'Отпуск основной'
            WHEN 0xBA63FCF94B4AD0664ED369D2E6505D67 THEN N'Командировка'
            WHEN 0x8C3B61F23954155A40EB0108FC0932DB THEN N'Болезнь'
            WHEN 0x853001C18D0965EE4B2702405C94054A THEN N'Отпуск неоплачиваемый по разрешению работодателя'
            WHEN 0xB7335AEFD8708C3E462861FC59489A38 THEN N'Отпуск по беременности и родам'
            ELSE N'Другое отсутствие'
        END AS [Вид_отсутствия]

    FROM dbo._InfoRg16921 state WITH (NOLOCK)
    INNER JOIN dbo._Reference299 ref_emp WITH (NOLOCK) 
        ON state._Fld16922RRef = ref_emp._IDRRef

    WHERE @TargetDate BETWEEN CAST(CASE WHEN YEAR(state._Fld16926) > 3000 THEN DATEADD(YEAR, -2000, state._Fld16926) ELSE state._Fld16926 END AS DATE)
                          AND CAST(CASE WHEN YEAR(state._Fld16927) > 3000 THEN DATEADD(YEAR, -2000, state._Fld16927) ELSE state._Fld16927 END AS DATE)

    UNION ALL

    -- 2. Динамический выбор ДЕЙСТВУЮЩИХ декретниц по уходу за ребенком
    SELECT 
        active_state.fio AS [ФИО],
        N'Отпуск по уходу за ребенком' AS [Вид_отсутствия]

    FROM (
        SELECT 
            LTRIM(RTRIM(ref_emp._Description)) AS fio,
            all_states._Fld16925RRef AS state_guid,
            CAST(CASE WHEN YEAR(all_states._Fld16926) > 3000 THEN DATEADD(YEAR, -2000, all_states._Fld16926) ELSE all_states._Fld16926 END AS DATE) AS date_start,
            ROW_NUMBER() OVER (
                PARTITION BY all_states._Fld16922RRef 
                ORDER BY all_states._Fld16926 DESC
            ) AS rn
        FROM dbo._InfoRg16921 all_states WITH (NOLOCK)
        INNER JOIN dbo._Reference299 ref_emp WITH (NOLOCK) 
            ON all_states._Fld16922RRef = ref_emp._IDRRef
        WHERE CAST(CASE WHEN YEAR(all_states._Fld16926) > 3000 THEN DATEADD(YEAR, -2000, all_states._Fld16926) ELSE all_states._Fld16926 END AS DATE) <= @TargetDate
    ) active_state

    WHERE active_state.rn = 1 
      AND active_state.state_guid = 0xA4FBA038663B3C2A48DA151C262855E1
      AND active_state.date_start >= DATEADD(YEAR, -3, @TargetDate)

    ORDER BY [ФИО] ASC;
    """
    
    try:
        conn_str = get_zup_connection_string()
        with pyodbc.connect(conn_str, timeout=30) as conn:
            df = pd.read_sql(query, conn, params=[target_date])
            
        if not df.empty:
            df['fio_clean'] = df['ФИО'].apply(normalize_fio)
        return df
    except Exception as e:
        logger.error(f"[❌] Ошибка SQL-выгрузки отсутствий за {target_date}: {e}")
        return pd.DataFrame()


def fetch_zup_staff_from_sql() -> pd.DataFrame:
    """Резервная выгрузка штата из MS SQL."""
    query = """
    SELECT DISTINCT
        LTRIM(RTRIM(ref_emp._Description)) AS [ФИО],
        N'Организация' AS [Подразделение],
        N'Сотрудник' AS [Должность]
    FROM dbo._Reference299 ref_emp WITH (NOLOCK)
    WHERE ref_emp._Description <> '' 
      AND ref_emp._Marked = 0x00
    ORDER BY [ФИО] ASC;
    """
    try:
        conn_str = get_zup_connection_string()
        with pyodbc.connect(conn_str, timeout=5) as conn:
            df = pd.read_sql(query, conn)
            
        if not df.empty:
            df['fio_clean'] = df['ФИО'].apply(normalize_fio)
        return df
    except Exception as e:
        logger.error(f"[❌] Ошибка выгрузки штата из MS SQL: {e}")
        return pd.DataFrame()


def sync_zup_to_excel(target_date) -> bool:
    """Создает дамп в Excel при необходимости."""
    try:
        if isinstance(target_date, str):
            clean_date_str = target_date.replace('_', '.')
            target_date_obj = datetime.strptime(clean_date_str, "%d.%m.%Y").date()
        else:
            target_date_obj = target_date

        date_str_file = target_date_obj.strftime("%d_%m_%Y")
        c_1c_dir = os.path.join(DATA_DIR, "1c")
        os.makedirs(c_1c_dir, exist_ok=True)

        df_staff = fetch_zup_staff_from_sql()
        df_absences = fetch_zup_absences_from_sql(target_date_obj)

        staff_excel_path = os.path.join(c_1c_dir, f"Штат_{date_str_file}.xlsx")
        absences_excel_path = os.path.join(c_1c_dir, f"Отсутствия_{date_str_file}.xlsx")

        with pd.ExcelWriter(staff_excel_path, engine='openpyxl') as writer:
            dummy_headers = pd.DataFrame([[""] * 13] * 8)
            dummy_headers.to_excel(writer, index=False, header=False)
            df_staff[['ФИО', 'Подразделение', 'Должность']].to_excel(writer, startrow=8, index=False)

        with pd.ExcelWriter(absences_excel_path, engine='openpyxl') as writer:
            dummy_headers = pd.DataFrame([[""] * 3] * 3)
            dummy_headers.to_excel(writer, index=False, header=False)
            df_absences[['ФИО', 'Вид_отсутствия']].to_excel(writer, startrow=3, index=False)

        return True

    except Exception as e:
        logger.error(f"[❌] Ошибка прямого импорта из MS SQL 1С: {e}")
        return False