

from __future__ import annotations

from collections.abc import Generator

import requests
from bsa import BeautifulSoup

_SCREAMING_SNAKE_CASE  :						Optional[int]         =    '''https://www.indeed.co.in/jobs?q=mobile+app+development&l='''
def        UpperCAmelCase_     (		_A = "mumbai"       ):





     '''simple docstring'''




     SCREAMING_SNAKE_CASE__					=					BeautifulSoup(requests.get(url + location       ).content   ,	'''html.parser'''       )
     # This attribute finds out all the specifics listed in a job
     for job in soup.find_all('''div'''   ,	attrs={'''data-tn-component''': '''organicJob'''}       ):
          SCREAMING_SNAKE_CASE__					=					job.find('''a'''   ,	attrs={'''data-tn-element''': '''jobTitle'''}       ).text.strip()
          SCREAMING_SNAKE_CASE__					=					job.find('''span'''   ,	{'''class''': '''company'''}       ).text.strip()
          yield job_title, company_name


if __name__ == "__main__":
       for i, job in enumerate(fetch_jobs('''Bangalore'''), 1):
              print(F"Job {i:>2} is {job[0]} at {job[1]}")





def        UpperCAmelCase_     (		_A       ):





     '''simple docstring'''




     SCREAMING_SNAKE_CASE__					=					[]
     for data in source_data:
          for i, el in enumerate(_A       ):
               if len(_A       ) < i + 1:
                    data_lists.append([]       )
               data_lists[i].append(float(_A       )       )
     return data_lists
def        UpperCAmelCase_     (		_A   ,	_A       ):





     '''simple docstring'''




     SCREAMING_SNAKE_CASE__					=					[]
     for dlist, weight in zip(_A   ,	_A       ):
          SCREAMING_SNAKE_CASE__					=					min(_A       )
          SCREAMING_SNAKE_CASE__					=					max(_A       )

          SCREAMING_SNAKE_CASE__					=					[]
          # for weight 0 score is 1 - actual score
          if weight == 0:
               for item in dlist:
                    try:
                         score.append(1 - ((item - mind) / (maxd - mind))       )
                    except ZeroDivisionError:
                         score.append(1       )

          elif weight == 1:
               for item in dlist:
                    try:
                         score.append((item - mind) / (maxd - mind)       )
                    except ZeroDivisionError:
                         score.append(0       )

        # weight not 0 or 1
          else:
               SCREAMING_SNAKE_CASE__					=					F'''Invalid weight of {weight:f} provided'''
               raise ValueError(_A       )

          score_lists.append(_A       )

     return score_lists
def        UpperCAmelCase_     (		_A       ):





     '''simple docstring'''




     SCREAMING_SNAKE_CASE__					=					[0 for i in range(len(score_lists[0]       )       )]

     for slist in score_lists:
          for j, ele in enumerate(_A       ):
               SCREAMING_SNAKE_CASE__					=					final_scores[j] + ele

     return final_scores







def        UpperCAmelCase_     (		_A   ,	_A       ):





     '''simple docstring'''




     SCREAMING_SNAKE_CASE__					=					get_data(_A       )
     SCREAMING_SNAKE_CASE__					=					calculate_each_score(_A   ,	_A       )
     SCREAMING_SNAKE_CASE__					=					generate_final_scores(_A       )

     # append scores to source data
     for i, ele in enumerate(_A       ):
          source_data[i].append(_A       )

     return source_data


