import requests
import xml.etree.ElementTree as ET
from base64 import b64encode
from server.backend.schemas.pydantic import settings
from functools import lru_cache
import pandas as pd
from server.backend.api.session import get_session

session = get_session({
    "Accept": "application/xml",
})

def fetch_nomenclature():
    response = session.get(settings.URL_NOMENCLATURE, timeout=10)
    response.raise_for_status()
    return response.text

def parse_nomenclature(xml: str):
    try:
        NS = {
        "atom": "http://www.w3.org/2005/Atom",
        "m": "http://schemas.microsoft.com/ado/2007/08/dataservices/metadata",
        "d": "http://schemas.microsoft.com/ado/2007/08/dataservices",
        }
        rows = []
        # Парсинг XML-ответа
        root = ET.fromstring(xml)
        # Извлечение конкретных данных
        for entry in root.findall('atom:entry', NS):
            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)
            })
        df = pd.DataFrame(rows)
        df = df[df['parent_key'] == 'e0eb911c-03a0-11ef-95bd-fa163e7429d8']
        df['description'] = df['description'].str.extract(r'^([^\s(]+)')
        return df
    except ET.ParseError:
        raise
@lru_cache(maxsize=1)
def nomenclature(flag=False):
    xml_data = fetch_nomenclature()
    root = parse_nomenclature(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