Этот код является частью моего проекта Django, моя задача - найти название компании из парсинга описания вакансии, но я не могу получить название компании?

from .CleanJdTextData import Cleaned_Text, ReadModule from resume_app.Config_Reader import Config_Dict from jd_app.Designation_Extract import Designation_Extract

nlp_Company_Module = ReadModule(Config_Dict['company_aliases_resume_parsing']) nlp_designation_module = ReadModule(Config_Dict['designation_saveLoc'])

добавлено

class CompanyExtract():

def __init__(self, cleaned_data, nlp_cn):
    self.cleaned_data = cleaned_data
    self.nlp_cn = nlp_cn


def company_extract(self):
    company_designation_dict = dict()    
    if all([self.cleaned_data, isinstance(self.cleaned_data, tuple)]):
        try:
            area_to_search = self.cleaned_data[:10]
        except:
            area_to_search = self.cleaned_data
        area_to_search = self.cleaned_data

        for index, data in enumerate(area_to_search):
            
        # for data in area_to_search:
            company_data = self.apply_Nlp_On_Data(data)
            
            if any([company_data]):
                company_designation_dict.update({'company_name':company_data})
                designation = Designation_Extract(self.cleaned_data, nlp_designation_module()).extract_designation(index)
                if any([designation]):
                    company_designation_dict.update({'designation':designation})

    return company_designation_dict



def lemma_Add_In_data(self, str_data):
    lemma_add = ' '.join([x.lemma_ if x.text != "limited" else x.text for x in self.nlp_cn(str_data)])
    data = [str_data, lemma_add] if lemma_add != str_data else [str_data]
    if any([data]):
        return data

def replace_Pvt_Ltd(self, str_data):
    if all([str_data, isinstance(str_data, str)]):
        replace_dict = {"pvt": "private", "ltd": "limited", "co":"company", "inc":"incorporated", "corp": "corporation"}
        data = ' '.join([replace_dict[x] if x in replace_dict.keys() else x for x in str_data.split()])

        if any([data]):
            return self.lemma_Add_In_data(data)



    
def apply_Nlp_On_Data(self, str_data):
    if all([str_data, isinstance(str_data, str)]):
        replace_pvt_ltd_ = self.replace_Pvt_Ltd(str_data)
        if any([replace_pvt_ltd_]):
            for company_name in replace_pvt_ltd_:
                doc = self.nlp_cn(company_name)
                company_name_s = [x.text.title() for x in doc]
                if any([company_name_s]):
                    return company_name_s[0]



        

class ExtractCompanyName: def init(self, text_data): self.text_data = text_data

def extract_company_name(self):
     if all([self.text_data, isinstance(self.text_data, tuple)]):
        company_designation_dict = dict()
        global obj_Of_clean_Data
        obj_Of_clean_Data = Cleaned_Text(self.text_data, ['+', '&'])
        company_designation_dict = CompanyExtract(obj_Of_clean_Data(), nlp_Company_Module()).company_extract()
        if any([company_designation_dict]):
            return company_designation_dict

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