



'''simple docstring'''






import os

import pytest
from attr import dataclass


UpperCamelCase__:     Union[str, Any]										=    "us-east-1"  # defaults region

@dataclass
class        SCREAMING_SNAKE_CASE:







	"""simple docstring"""






	lowerCamelCase__    				= 42
	lowerCamelCase__    				= """arn:aws:iam::558105141721:role/sagemaker_execution_role"""
	lowerCamelCase__    				= {
	    """task_name""": """mnli""",
	    """per_device_train_batch_size""": 16,
	    """per_device_eval_batch_size""": 16,
	    """do_train""": True,
	    """do_eval""": True,
	    """do_predict""": True,
	    """output_dir""": """/opt/ml/model""",
	    """overwrite_output_dir""": True,
	    """max_steps""": 500,
	    """save_steps""": 5_500,
	}
	lowerCamelCase__    				= {**hyperparameters, """max_steps""": 1_000}







	@property
	def   A			(		self    :  List[str]	)    ->	str:
								if self.framework == "pytorch":
															return [
															    {"Name": "train_runtime", "Regex": r"train_runtime.*=\D*(.*?)$"},
															    {"Name": "eval_accuracy", "Regex": r"eval_accuracy.*=\D*(.*?)$"},
															    {"Name": "eval_loss", "Regex": r"eval_loss.*=\D*(.*?)$"},
															]
								else:
															return [
															    {"Name": "train_runtime", "Regex": r"train_runtime.*=\D*(.*?)$"},
															    {"Name": "eval_accuracy", "Regex": r"loss.*=\D*(.*?)]?$"},
															    {"Name": "eval_loss", "Regex": r"sparse_categorical_accuracy.*=\D*(.*?)]?$"},
															]







	@property
	def   A			(		self    :  Optional[int]	)    ->	str:
								return F"""{self.framework}-transfromers-test"""







	@property
	def   A			(		self    :  Any	)    ->	str:
								return F"""./tests/sagemaker/scripts/{self.framework}"""







	@property
	def   A			(		self    :  Optional[int]	)    ->	str:
								if self.framework == "pytorch":
															return "763104351884.dkr.ecr.us-east-1.amazonaws.com/huggingface-pytorch-training:1.7.1-transformers4.6.1-gpu-py36-cu110-ubuntu18.04"
								else:
															return "763104351884.dkr.ecr.us-east-1.amazonaws.com/huggingface-tensorflow-training:2.4.1-transformers4.6.1-gpu-py37-cu110-ubuntu18.04"


@pytest.fixture(scope='''class'''						)
def 				snake_case_  (      _lowerCAmelCase						:		Tuple						)   ->     Tuple:
							UpperCAmelCase				: Optional[Any]											=	SageMakerTestEnvironment(framework=request.cls.framework						)










'''simple docstring'''






from __future__ import annotations

from collections.abc import Generator

import requests
from bsa import BeautifulSoup

UpperCamelCase__:     Union[str, Any]										=    "https://www.indeed.co.in/jobs?q=mobile+app+development&l="


def 				snake_case_  (      _lowerCAmelCase						:		str = "mumbai"						)   ->     Generator[tuple[str, str], None, None]:
							UpperCAmelCase				: Optional[int]											=	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'''}						):
														UpperCAmelCase				: Optional[Any]											=	job.find('''a'''     ,   attrs={'''data-tn-element''': '''jobTitle'''}						).text.strip()
														UpperCAmelCase				: int											=	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]}")





