


from __future__ import annotations

from collections.abc import Generator

import requests
from bsa import BeautifulSoup

A				:       int      =  'https://www.indeed.co.in/jobs?q=mobile+app+development&l='





def 						_lowerCAmelCase							(     _lowerCAmelCase = "mumbai"			)    ->						Generator[tuple[str, str], None, None]:


						'''simple docstring'''






						__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"}			):
												__snake_case				=		job.find("a"   ,						attrs={"data-tn-element": "jobTitle"}			).text.strip()
												__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]}''')









A				:       Any      =  '\n# Transformers installation\n! pip install transformers datasets\n# To install from source instead of the last release, comment the command above and uncomment the following one.\n# ! pip install git+https://github.com/huggingface/transformers.git\n'

A				:       Optional[int]      =  [{'type': 'code', 'content': INSTALL_CONTENT}]
A				:       Optional[int]      =  {
    '{processor_class}': 'FakeProcessorClass',
    '{model_class}': 'FakeModelClass',
    '{object_class}': 'FakeObjectClass',
}





