from pydantic import ValidationError
from server.backend.schemas.pydantic import ExcelInfo,settings,Translit
from server.backend.api.nomenclature import processing
import datetime
import re
def report_date(df, format: str):
    cell = str(df.iloc[0, 4])
    match = re.search(r"\d{2}\.\d{2}\.\d{4}", cell)
    if not match:
        return None
    dt = datetime.datetime.strptime(match.group(0), "%d.%m.%Y")
    return dt.strftime(format)
def process_sheet(df,real_arti: int,real_quantity: int,real_sum_1: int,real_sum_2: int):
    # пропускаем служебные строки
    df = df.iloc[2:].reset_index(drop=True)

    # выбираем нужные колонки по индексам
    df = df.iloc[:, [real_arti, real_quantity, real_sum_1, real_sum_2]].copy()
    df.dropna(inplace=True)
    df = df[(df != 0).all(axis=1)]

    # складываем суммы
    df.iloc[:, 2] += df.iloc[:, 3]
    df = df.iloc[:, [0, 1, 2]]
    df.columns = ['arti', 'counts', 'price']

    # нормализация
    df['arti'] = df['arti'].replace(Translit.TRANSLIT, regex=True)
    df['arti'] = df['arti'].astype(str).str.upper().str.extract(f'({settings.PATTERN})')
    df['price'] = df['price'].astype(float)
    df['counts'] = df['counts'].astype(int)

    # группировка
    df = df.groupby('arti', as_index=False).agg({'counts': 'sum', 'price': 'sum'})
    df = processing(df)
    validated_rows, errors = [], []
    for i, row in df.iterrows():
        try:
            validated_rows.append(ExcelInfo(**row.to_dict()))
        except ValidationError as e:
            errors.append((i, e.errors()))
    if errors:
        raise Exception("There are some errors with validation in Отчет о реализации", errors)
    return validated_rows
def evaluating(dfs):
    validated_rows_1 = process_sheet(dfs["Отчет о реализации"], real_arti=2,real_quantity=8, real_sum_1=5,real_sum_2=6)   # номера столбцов от озона
    validated_rows_2 = process_sheet(dfs["Отчет о реализации"], real_arti=2,real_quantity=16, real_sum_1=13,real_sum_2=14)#
    date=report_date(dfs["Отчет о реализации"], format=settings.TIMEFORMAT)
    return validated_rows_1, validated_rows_2, date