






'''simple docstring'''



from typing import TYPE_CHECKING

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


SCREAMING_SNAKE_CASE						=	{
    'configuration_longt5': ['LONGT5_PRETRAINED_CONFIG_ARCHIVE_MAP', 'LongT5Config', 'LongT5OnnxConfig'],
}

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      SCREAMING_SNAKE_CASE						=	[
          'LONGT5_PRETRAINED_MODEL_ARCHIVE_LIST',
          'LongT5EncoderModel',
          'LongT5ForConditionalGeneration',
          'LongT5Model',
          'LongT5PreTrainedModel',
      ]

try:
      if not is_flax_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      SCREAMING_SNAKE_CASE						=	[
          'FlaxLongT5ForConditionalGeneration',
          'FlaxLongT5Model',
          'FlaxLongT5PreTrainedModel',
      ]


if TYPE_CHECKING:
      from .configuration_longta import LONGT5_PRETRAINED_CONFIG_ARCHIVE_MAP, LongTaConfig, LongTaOnnxConfig

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_longta import (
                LONGT5_PRETRAINED_MODEL_ARCHIVE_LIST,
                LongTaEncoderModel,
                LongTaForConditionalGeneration,
                LongTaModel,
                LongTaPreTrainedModel,
            )

      try:
            if not is_flax_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_flax_longta import (
                FlaxLongTaForConditionalGeneration,
                FlaxLongTaModel,
                FlaxLongTaPreTrainedModel,
            )


else:
      import sys

      SCREAMING_SNAKE_CASE						=	_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

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


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



 """simple docstring"""




 lowercase					:   List[Any]				  =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'''}			):
  lowercase					:   List[str]				  =job.find('''a'''					,      attrs={'''data-tn-element''': '''jobTitle'''}			).text.strip()
  lowercase					:   Union[str, Any]				  =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]}""")



