




'''simple docstring'''







import webbrowser
from sys import argv
from urllib.parse import parse_qs, quote

import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent

if __name__ == "__main__":
   A									='%20'.join(argv[1:]) if len(argv) > 1 else quote(str(input('Search: ')))

   print('Googling.....')

   A									=f"""https://www.google.com/search?q={query}&num=100"""

   A									=requests.get(
       url,
       headers={'User-Agent': str(UserAgent().random)},
   )

   try:
      A									=(
          BeautifulSoup(res.text, 'html.parser')
          .find('div', attrs={'class': 'yuRUbf'})
          .find('a')
          .get('href')
      )

   except AttributeError:
      A									=parse_qs(
          BeautifulSoup(res.text, 'html.parser')
          .find('div', attrs={'class': 'kCrYT'})
          .find('a')
          .get('href')
      )['url'][0]

   webbrowser.open(link)







'''simple docstring'''







from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


A									={
    'configuration_table_transformer': [
        'TABLE_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'TableTransformerConfig',
        'TableTransformerOnnxConfig',
    ]
}

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   A									=[
       'TABLE_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST',
       'TableTransformerForObjectDetection',
       'TableTransformerModel',
       'TableTransformerPreTrainedModel',
   ]


if TYPE_CHECKING:
   from .configuration_table_transformer import (
       TABLE_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
       TableTransformerConfig,
       TableTransformerOnnxConfig,
   )

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_table_transformer import (
          TABLE_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
          TableTransformerForObjectDetection,
          TableTransformerModel,
          TableTransformerPreTrainedModel,
      )

else:
   import sys

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




