"""simple docstring"""






from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


_A   					=    {
    'configuration_mvp': ['MVP_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MvpConfig', 'MvpOnnxConfig'],
    'tokenization_mvp': ['MvpTokenizer'],
}

try:
						if not is_tokenizers_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						_A   					=    ['MvpTokenizerFast']

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						_A   					=    [
						    'MVP_PRETRAINED_MODEL_ARCHIVE_LIST',
						    'MvpForCausalLM',
						    'MvpForConditionalGeneration',
						    'MvpForQuestionAnswering',
						    'MvpForSequenceClassification',
						    'MvpModel',
						    'MvpPreTrainedModel',
						]

if TYPE_CHECKING:
						from .configuration_mvp import MVP_PRETRAINED_CONFIG_ARCHIVE_MAP, MvpConfig, MvpOnnxConfig
						from .tokenization_mvp import MvpTokenizer

						try:
												if not is_tokenizers_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .tokenization_mvp_fast import MvpTokenizerFast

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_mvp import (
												    MVP_PRETRAINED_MODEL_ARCHIVE_LIST,
												    MvpForCausalLM,
												    MvpForConditionalGeneration,
												    MvpForQuestionAnswering,
												    MvpForSequenceClassification,
												    MvpModel,
												    MvpPreTrainedModel,
												)

else:
						import sys

						_A   					=    _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)





"""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]}')




