


'''simple docstring'''


from typing import TYPE_CHECKING

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


__magic_name__			=      {
    'configuration_tapas': ['TAPAS_PRETRAINED_CONFIG_ARCHIVE_MAP', 'TapasConfig'],
    'tokenization_tapas': ['TapasTokenizer'],
}

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 __magic_name__			=      [
     'TAPAS_PRETRAINED_MODEL_ARCHIVE_LIST',
     'TapasForMaskedLM',
     'TapasForQuestionAnswering',
     'TapasForSequenceClassification',
     'TapasModel',
     'TapasPreTrainedModel',
     'load_tf_weights_in_tapas',
 ]
try:
 if not is_tf_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 __magic_name__			=      [
     'TF_TAPAS_PRETRAINED_MODEL_ARCHIVE_LIST',
     'TFTapasForMaskedLM',
     'TFTapasForQuestionAnswering',
     'TFTapasForSequenceClassification',
     'TFTapasModel',
     'TFTapasPreTrainedModel',
 ]


if TYPE_CHECKING:
 from .configuration_tapas import TAPAS_PRETRAINED_CONFIG_ARCHIVE_MAP, TapasConfig
 from .tokenization_tapas import TapasTokenizer

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_tapas import (
      TAPAS_PRETRAINED_MODEL_ARCHIVE_LIST,
      TapasForMaskedLM,
      TapasForQuestionAnswering,
      TapasForSequenceClassification,
      TapasModel,
      TapasPreTrainedModel,
      load_tf_weights_in_tapas,
  )

 try:
  if not is_tf_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_tf_tapas import (
      TF_TAPAS_PRETRAINED_MODEL_ARCHIVE_LIST,
      TFTapasForMaskedLM,
      TFTapasForQuestionAnswering,
      TFTapasForSequenceClassification,
      TFTapasModel,
      TFTapasPreTrainedModel,
  )


else:
 import sys

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




'''simple docstring'''


import sys
import webbrowser

import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent

if __name__ == "__main__":
     print('Googling.....')
     __magic_name__			=      'https://www.google.com/search?q=' + ' '.join(sys.argv[1:])
     __magic_name__			=      requests.get(url, headers={'UserAgent': UserAgent().random})
     # res.raise_for_status()
     with open('project1a.html', 'wb') as out_file:  # only for knowing the class
          for data in res.iter_content(10_000):
               out_file.write(data)
     __magic_name__			=      BeautifulSoup(res.text, 'html.parser')
     __magic_name__			=      list(soup.select('.eZt8xd'))[:5]

     print(len(links))
     for link in links:
          if link.text == "Maps":
               webbrowser.open(link.get('href'))
          else:
               webbrowser.open(f"""https://google.com{link.get('href')}""")
