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api 1.4

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This commit is contained in:
Dmitrii Seliakov
2026-01-02 14:43:50 +03:00
parent d0f462dfee
commit 5d15ff9f5e
10 changed files with 73 additions and 36 deletions
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3
run.py
View File

@@ -1,6 +1,6 @@
import server.backend.services.excel as excel
from server.backend.services.validating_files import validating
from server.backend.api import companies,contractors,storages
from server.backend.api import companies,contractors,storages, nomenclature
#_______________
from pathlib import Path
path = Path("./excel_files")
@@ -21,6 +21,7 @@ match args.mode:
companies.companies()
contractors.contractor()
storages.storages()
nomenclature.nomenclature(flag=True)
case "orgs":
print("Режим:", args.mode)
companies.companies()

30
server/backend/api/nomenclature.py
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@@ -2,6 +2,8 @@ import requests
import xml.etree.ElementTree as ET
from base64 import b64encode
from server.backend.schemas.pydantic import settings
import re
from functools import lru_cache
import pandas as pd
auth_str = f"{settings.USERNAME}:{settings.PASSWORD}"
b64_auth_str = b64encode(auth_str.encode("utf-8")).decode("utf-8")
@@ -32,16 +34,32 @@ def parse_contragents(xml: str):
properties = entry.find('atom:content',NS).find(
'm:properties', NS)
rows.append({
'Ref_Key': properties.findtext('d:Ref_Key', default=None, namespaces=NS),
'Description': properties.findtext('d:Description', default=None, namespaces=NS),
'Parent_Key': properties.findtext('d:Parent_Key', default=None, namespaces=NS)
'ref_key': properties.findtext('d:Ref_Key', default=None, namespaces=NS),
'description': properties.findtext('d:Description', default=None, namespaces=NS),
'parent_key': properties.findtext('d:Parent_Key', default=None, namespaces=NS)
})
df = pd.DataFrame(rows)
df = df[df['Parent_Key'] == 'e0eb911c-03a0-11ef-95bd-fa163e7429d8']
df['Description'] = df['Description'].str.extract(r'^([^\s(]+)')
df = df[df['parent_key'] == 'e0eb911c-03a0-11ef-95bd-fa163e7429d8']
df['description'] = df['description'].str.extract(r'^([^\s(]+)')
return df
except ET.ParseError:
raise
def nomenclature():
@lru_cache(maxsize=1)
def nomenclature(flag=False):
xml_data = fetch_contragents()
root = parse_contragents(xml_data)
if flag:
root.to_excel("./excel_files/nomenclature.xlsx")
return root
def processing(df):
df2=nomenclature()
result = df.merge(
df2[['description', 'ref_key']], #берутся столбцы из df2
left_on='arti', #столбец для сравнения в df
right_on='description', #столбец для сравнения в df2
how='left' #left join для df
).drop(columns='description') #удаление временного стобца
not_matched = result.loc[result['ref_key'].isna(), 'arti'].unique()
if len(not_matched) > 0:
raise ValueError(f'Не найдены значения: {not_matched}')
return result

10
server/backend/handlers/ozon_handler.py
View File

@@ -1,6 +1,6 @@
from pydantic import ValidationError
from server.backend.schemas.pydantic import ExcelInfo,settings
from server.backend.api.nomenclature import nomenclature
from server.backend.schemas.pydantic import ExcelInfo,settings,Translit
from server.backend.api.nomenclature import processing
import re
def process_sheet(df, real_arti:str, real_quantity:str, real_sum_1:str, real_sum_2:str):
@@ -9,11 +9,12 @@ def process_sheet(df, real_arti:str, real_quantity:str, real_sum_1:str, real_sum
df[real_sum_1]+=df[real_sum_2]
df = df[[real_arti, real_quantity, real_sum_1]].copy()
df.rename(columns={real_arti: 'arti', real_quantity: 'counts', real_sum_1: 'price'}, inplace=True) #переименовываем для pydantic
df['arti'] = df['arti'].astype(str).str.extract(f'({settings.PATTERN})', flags=re.IGNORECASE) #arti под regex
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
df['price'] = df['price'].astype(float) #Float to Int, if exists
df['counts'] = df['counts'].astype(int) #Float to Int, if exists
df = df.groupby('arti', as_index=False).agg({'counts': 'sum', 'price': 'sum'}) #groupping
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:
@@ -22,7 +23,6 @@ def process_sheet(df, real_arti:str, real_quantity:str, real_sum_1:str, real_sum
errors.append((i, e.errors())) #выводит ошибку и пишет номер строки
if errors:
raise Exception(f"There are some errors with validation in Отчет о реализации, check it ", 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

10
server/backend/handlers/ozon_purchases_handler.py
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@@ -1,18 +1,18 @@
from pydantic import ValidationError
from server.backend.schemas.pydantic import ExcelInfo, settings
from server.backend.schemas.pydantic import ExcelInfo, settings,Translit
from server.backend.api.nomenclature import processing
import re
def process_sheet(df, real_arti:int, real_quantity:int, real_sum_1:int):
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]].copy()
df.rename(columns={real_arti: 'arti', real_quantity: 'counts', real_sum_1: 'price'}, inplace=True) #переименовываем для pydantic
df['arti'] = df['arti'].astype(str).str.extract(f'({settings.PATTERN})', flags=re.IGNORECASE) #arti под regex
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
df['price'] = df['price'].astype(float) #Float to Int, if exists
df['counts'] = df['counts'].astype(int) #Float to Int, if exists
df = df.groupby('arti', as_index=False).agg({'counts': 'sum', 'price': 'sum'}) #groupping
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:

10
server/backend/handlers/ozon_wb_yandex_com_handler.py
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@@ -1,19 +1,19 @@
from pydantic import ValidationError
from server.backend.schemas.pydantic import ExcelInfo,settings
from server.backend.schemas.pydantic import ExcelInfo,settings,Translit
from server.backend.api.nomenclature import processing
import re
def process_sheet(df, real_arti:str, real_quantity:str, real_sum_1:str):
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]].copy()
df.rename(columns={real_arti: 'arti', real_quantity: 'counts', real_sum_1: 'price'}, inplace=True) #переименовываем для pydantic
df['arti'] = df['arti'].astype(str).str.extract(f'({settings.PATTERN})', flags=re.IGNORECASE) #arti под regex
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
df['price'] = df['price'].astype(float) #переделка к норм виду и преобразование в float
df['counts'] = df['counts'].astype(int) #Float to Int, if exists
df = df.groupby('arti', as_index=False).agg({'counts': 'sum', 'price': 'sum'}) #groupping
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:

10
server/backend/handlers/wb_handler.py
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@@ -1,19 +1,19 @@
from pydantic import ValidationError
from server.backend.schemas.pydantic import ExcelInfo, settings
from server.backend.schemas.pydantic import ExcelInfo, settings,Translit
from server.backend.api.nomenclature import processing
import re
def process_sheet(df, document_type:str):
df = df[['Артикул поставщика', 'Тип документа', 'Кол-во', 'Вайлдберриз реализовал Товар (Пр)']].copy().dropna() #copy and drop all NA values
df = df[(df != 0).all(axis=1)] #drop all 0 values
df = df[df['Тип документа'] == document_type] #фильтруем по типу документа
df = df[['Артикул поставщика', 'Кол-во', 'Вайлдберриз реализовал Товар (Пр)']].copy()
df.rename(columns={'Артикул поставщика': 'arti', 'Кол-во': 'counts', 'Вайлдберриз реализовал Товар (Пр)': 'price'}, inplace=True) #переименовываем для pydantic
df['arti'] = df['arti'].astype(str).str.extract(f'({settings.PATTERN})', flags=re.IGNORECASE) #arti под regex
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
df['price'] = df['price'].astype(float) #Float to Int, if exists
df['counts'] = df['counts'].astype(int) #Float to Int, if exists
df = df.groupby('arti', as_index=False).agg({'counts': 'sum', 'price': 'sum'})
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:

9
server/backend/handlers/wb_purchases_handler.py
View File

@@ -1,5 +1,6 @@
from pydantic import ValidationError
from server.backend.schemas.pydantic import ExcelInfo, settings
from server.backend.schemas.pydantic import ExcelInfo, settings,Translit
from server.backend.api.nomenclature import processing
import re
def process_sheet(df, real_arti:str, real_quantity:str, real_sum_1:str):
@@ -7,12 +8,12 @@ def process_sheet(df, real_arti:str, real_quantity:str, real_sum_1:str):
df = df[(df != 0).all(axis=1)] #drop all 0 values
df = df[[real_arti, real_quantity, real_sum_1]].copy()
df.rename(columns={real_arti: 'arti', real_quantity: 'counts', real_sum_1: 'price'}, inplace=True) #переименовываем для pydantic
df['arti'] = df['arti'].astype(str).str.extract(f'({settings.PATTERN})', flags=re.IGNORECASE) #arti под regex
df['arti'] = df['arti'].astype(str).str.upper().str.extract(f'({settings.PATTERN})') #arti под regex
df['arti'] = df['arti'].replace(Translit.TRANSLIT, regex=True)
df['price'] = df['price'].str.replace(' ', '', regex=False).str.replace(',', '.', regex=False).astype(float) #переделка к норм виду и преобразование в float
df['counts'] = df['counts'].astype(int) #Float to Int, if exists
df = df.groupby('arti', as_index=False).agg({'counts': 'sum', 'price': 'sum'}) #groupping
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:

9
server/backend/handlers/yandex_handler.py
View File

@@ -1,5 +1,6 @@
from pydantic import ValidationError
from server.backend.schemas.pydantic import ExcelInfo, settings
from server.backend.schemas.pydantic import ExcelInfo, settings,Translit
from server.backend.api.nomenclature import processing
import re
def process_sheet(df, multiply_price=1, sheet_name=''):
@@ -7,12 +8,12 @@ def process_sheet(df, multiply_price=1, sheet_name=''):
df = df[(df != 0).all(axis=1)] #drop all 0 values
df['Сумма транзакции, ₽'] *= multiply_price #умножаем на -1 для возвратов
df.rename(columns={'Ваш SKU': 'arti', 'Количество, шт.': 'counts', 'Сумма транзакции, ₽': 'price'}, inplace=True) #переименовываем для pydantic
df['arti'] = df['arti'].astype(str).str.extract(f'({settings.PATTERN})', flags=re.IGNORECASE) #regex implemented
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
df['price'] = df['price'].astype(float) #To float, if exists
df['counts'] = df['counts'].astype(int) #To float, if exists
df = df.groupby('arti', as_index=False).agg({'counts': 'sum', 'price': 'sum'}) #groupping
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:

16
server/backend/schemas/pydantic.py
View File

@@ -4,6 +4,7 @@ class ExcelInfo(BaseModel):
arti:str = Field(..., min_length=5, max_length=12, description="arti of the clothes")
counts:int = Field(..., gt=0, description="the quantity of the clothes")
price:float = Field(..., gt=0, description="the price of the clothes")
ref_key:str = Field(..., description="reffering key from db")
class ExcelRealization(BaseModel):
pass
class ExcelReturning(BaseModel):
@@ -44,4 +45,19 @@ class Settings(BaseSettings):
env_file=".env",
env_file_encoding="utf-8"
)
class Translit():
TRANSLIT = {
'А': 'A',
'В': 'B',
'Е': 'E',
'К': 'K',
'М': 'M',
'Н': 'H',
'О': 'O',
'Р': 'P',
'С': 'C',
'Т': 'T',
'Х': 'X',
}
settings = Settings()

2
server/backend/services/excel.py
View File

@@ -64,7 +64,7 @@ class WBPurchasesHandler(BaseHandler):
if "Sheet1" not in dfs:
raise Exception(f"В файле {self.file_path.name} отсутствуют необходимые листы")
validated_data = wb_purchases_handler.evaluating(dfs)
print("Выкупы WB завершены, валидированных строк:", len(validated_data), "Реализация")
print("Выкупы WB завершены, валидированных строк:", len(validated_data), "Реализация", validated_data)
class OZONComHandler(BaseHandler):
def process(self):