





"""simple docstring"""






import argparse
import os

from accelerate.utils import ComputeEnvironment

from .cluster import get_cluster_input
from .config_args import cache_dir, default_config_file, default_yaml_config_file, load_config_from_file  # noqa: F401
from .config_utils import _ask_field, _ask_options, _convert_compute_environment  # noqa: F401
from .sagemaker import get_sagemaker_input


_A   					=    'Launches a series of prompts to create and save a `default_config.yaml` configuration file for your training system. Should always be ran first on your machine'




def 						SCREAMING_SNAKE_CASE					(  )							->   int:
				SCREAMING_SNAKE_CASE__		  =				_ask_options(
				    "In which compute environment are you running?"  ,					["This machine", "AWS (Amazon SageMaker)"]  ,					_convert_compute_environment  ,					)
				if compute_environment == ComputeEnvironment.AMAZON_SAGEMAKER:
								SCREAMING_SNAKE_CASE__		  =				get_sagemaker_input()
				else:
								SCREAMING_SNAKE_CASE__		  =				get_cluster_input()
				return config




def 						SCREAMING_SNAKE_CASE					(  __UpperCAmelCase=None       )							->   List[Any]:
				if subparsers is not None:
								SCREAMING_SNAKE_CASE__		  =				subparsers.add_parser("config"  ,					description=__UpperCAmelCase       )
				else:
								SCREAMING_SNAKE_CASE__		  =				argparse.ArgumentParser("Accelerate config command"  ,					description=__UpperCAmelCase       )

				parser.add_argument(
				    "--config_file"  ,					default=__UpperCAmelCase  ,					help=(
				        "The path to use to store the config file. Will default to a file named default_config.yaml in the cache "
				        "location, which is the content of the environment `HF_HOME` suffixed with 'accelerate', or if you don't have "
				        "such an environment variable, your cache directory ('~/.cache' or the content of `XDG_CACHE_HOME`) suffixed "
				        "with 'huggingface'."
				    )  ,					)

				if subparsers is not None:
								parser.set_defaults(func=__UpperCAmelCase       )
				return parser




def 						SCREAMING_SNAKE_CASE					(  __UpperCAmelCase       )							->   List[str]:
				SCREAMING_SNAKE_CASE__		  =				get_user_input()
				if args.config_file is not None:
								SCREAMING_SNAKE_CASE__		  =				args.config_file
				else:
								if not os.path.isdir(__UpperCAmelCase       ):
												os.makedirs(__UpperCAmelCase       )
								SCREAMING_SNAKE_CASE__		  =				default_yaml_config_file

				if config_file.endswith(".json"       ):
								config.to_json_file(__UpperCAmelCase       )
				else:
								config.to_yaml_file(__UpperCAmelCase       )
				print(F"""accelerate configuration saved at {config_file}"""       )




def 						SCREAMING_SNAKE_CASE					(  )							->   Optional[int]:
				SCREAMING_SNAKE_CASE__		  =				config_command_parser()
				SCREAMING_SNAKE_CASE__		  =				parser.parse_args()
				config_command(__UpperCAmelCase       )


if __name__ == "__main__":
						main()





"""simple docstring"""






from __future__ import annotations

from collections.abc import Generator

import requests
from bsa import BeautifulSoup

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




def 						SCREAMING_SNAKE_CASE					(  __UpperCAmelCase = "mumbai"       )							->   Generator[tuple[str, str], None, None]:
				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]}')




