date 1.3

server/backend/handlers/ozon_purchases_handler.py

@@ -5,13 +5,13 @@ import re
 import datetime
 import re
 import datetime
-def report_date(df, format: str):
+def report_date(df, date_format: str):
     row_text = " ".join(df.iloc[0].astype(str))
     match = re.search(r"по\s+(\d{2}\.\d{2}\.\d{4})", row_text)
     if not match:
-        return None
+        raise ValueError("There is no date in ozon_purchase_handler")
     dt = datetime.datetime.strptime(match.group(1), "%d.%m.%Y")
-    return dt.strftime(format)
+    return dt.strftime(date_format)
 def process_sheet(df, real_arti:int, real_quantity:int, real_sum_1:int):
     df = df.iloc[2:].reset_index(drop=True)
 
@@ -44,5 +44,5 @@ def process_sheet(df, real_arti:int, real_quantity:int, real_sum_1:int):
     return validated_rows
 def evaluating(dfs):
     validated_rows_1 = process_sheet(dfs["Отчет о выкупленных товарах"], real_arti=3,real_quantity=10, real_sum_1=11)   # номера столбцов от озона
-    date=report_date(dfs["Отчет о выкупленных товарах"], format=settings.TIMEFORMAT)
+    date=report_date(dfs["Отчет о выкупленных товарах"], date_format=settings.TIMEFORMAT)
     return validated_rows_1, date

server/backend/handlers/ozon_wb_yandex_com_handler.py

@@ -8,12 +8,13 @@ def last_day_of_month(format: str):
     last_day = next_month - datetime.timedelta(days=next_month.day)
     return last_day.strftime(format)
 def process_sheet(df, real_arti:str, real_quantity:str, real_sum_1:str):
+    df= df.iloc[2:].reset_index(drop=True)
     #Выборка
-    df = df[[real_arti, real_quantity, real_sum_1]].copy().dropna() #copy and drop all NA values
+    df = df.iloc[:, [real_arti, real_quantity, real_sum_1]].copy().dropna()
+    #df = df[[real_arti, real_quantity, real_sum_1]].copy().dropna() #copy and drop all NA values
     df = df[(df != 0).all(axis=1)] #drop all 0 values
-    df = df[[real_arti, real_quantity, real_sum_1]]
-    df.rename(columns={real_arti: 'arti', real_quantity: 'counts', real_sum_1: 'price'}, inplace=True) #переименовываем для pydantic
-
+    #df = df[[real_arti, real_quantity, real_sum_1]]
+    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})') #arti под regex
@@ -22,7 +23,7 @@ def process_sheet(df, real_arti:str, real_quantity:str, real_sum_1:str):
 
     #Группировка
     df = df.groupby('arti', as_index=False).agg({'counts': 'sum', 'price': 'sum'}) #groupping
-    df = processing(df) #vlookup for ref_keys
+    #df = processing(df) #vlookup for ref_keys
     validated_rows, errors = [], []
     for i, row in df.iterrows(): #проходит построчно по df, где i - индекс строки, row - данные строки
         try:
@@ -33,6 +34,7 @@ def process_sheet(df, real_arti:str, real_quantity:str, real_sum_1:str):
         raise Exception(f"There are some errors with validation in Лист_1, check it ", errors)
     return validated_rows
 def evaluating(dfs):
-    validated_rows_1 = process_sheet(dfs["Лист_1"], real_arti="Артикул",real_quantity=dfs["Лист_1"].columns[4], real_sum_1=dfs["Лист_1"].columns[8])   # номера столбцов
+    #validated_rows_1 = process_sheet(dfs["Лист_1"], real_arti="Артикул",real_quantity=dfs["Лист_1"].columns[4], real_sum_1=dfs["Лист_1"].columns[8])   # номера столбцов
+    validated_rows_1 = process_sheet(dfs["Лист_1"], real_arti=0,real_quantity=4, real_sum_1=8) 
     date = last_day_of_month(settings.TIMEFORMAT)
     return validated_rows_1, date

server/backend/handlers/wb_handler.py

@@ -3,10 +3,10 @@ from server.backend.schemas.pydantic import ExcelInfo, settings,Translit
 from server.backend.api.nomenclature import processing
 import datetime
 
-def last_day_of_month(format: str):
+def last_day_of_month(date_format: str):
     next_month = datetime.datetime.now().replace(day=28) + datetime.timedelta(days=4)
     last_day = next_month - datetime.timedelta(days=next_month.day)
-    return last_day.strftime(format)
+    return last_day.strftime(date_format)
 def process_sheet(df, document_type:str):
     #Выборка
     df = df[['Артикул поставщика', 'Тип документа', 'Кол-во', 'Вайлдберриз реализовал Товар (Пр)']].copy().dropna() #copy and drop all NA values

server/backend/handlers/wb_purchases_handler.py

@@ -3,13 +3,13 @@ from server.backend.schemas.pydantic import ExcelInfo, settings,Translit
 from server.backend.api.nomenclature import processing
 import re
 import datetime
-def report_date(df, format: str):
+def report_date(df, date_format: str):
     row_text = " ".join(df.iloc[0].astype(str))
     match = re.search(r"\d{4}-\d{2}-\d{2}", row_text)
     if not match:
-        return None
+        raise ValueError("There is no date in ozon_purchase_handler")
     dt = datetime.datetime.strptime(match.group(0), "%Y-%m-%d")
-    return dt.strftime(format)
+    return dt.strftime(date_format)
 def process_sheet(df, real_arti:str, real_quantity:str, real_sum_1:str):
     df = df.iloc[2:].reset_index(drop=True)
     #Выборка
@@ -38,5 +38,5 @@ def evaluating(dfs):
 #     validated_rows_1 = process_sheet(dfs["Sheet1"], real_arti='Артикул',real_quantity="Количество", real_sum_1='''Сумма выкупа, руб., 
 # (вкл. НДС)''')   # номера столбцов от озона
     validated_rows_1 = process_sheet(dfs["Sheet1"], real_arti=1,real_quantity=3, real_sum_1=4)   # номера столбцов от озона
-    date=report_date(dfs["Sheet1"], format=settings.TIMEFORMAT)
+    date=report_date(dfs["Sheet1"], date_format=settings.TIMEFORMAT)
     return validated_rows_1, date