




import requests
from bsa import BeautifulSoup
def 		a_							( __lowerCAmelCase = "https://www.worldometers.info/coronavirus"				):
  lowerCAmelCase__										=      BeautifulSoup(requests.get(__lowerCAmelCase				).text   , '''html.parser'''				)
  lowerCAmelCase__										=      soup.findAll('''h1'''				)
  lowerCAmelCase__										=      soup.findAll('''div'''   , {'''class''': '''maincounter-number'''}				)
  keys += soup.findAll('''span'''   , {'''class''': '''panel-title'''}				)
  values += soup.findAll('''div'''   , {'''class''': '''number-table-main'''}				)
  return {key.text.strip(): value.text.strip() for key, value in zip(__lowerCAmelCase   , __lowerCAmelCase				)}


if __name__ == "__main__":
      print("""\033[1m""" + """COVID-19 Status of the World""" + """\033[0m\n""")
      for key, value in world_covidaa_stats().items():
            print(F"{key}\n{value}\n")







from typing import TYPE_CHECKING

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


__magic_name__  :  Optional[int]					=       {
    """configuration_biogpt""": ["""BIOGPT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """BioGptConfig"""],
    """tokenization_biogpt""": ["""BioGptTokenizer"""],
}

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      __magic_name__  :  int					=       [
          """BIOGPT_PRETRAINED_MODEL_ARCHIVE_LIST""",
          """BioGptForCausalLM""",
          """BioGptForTokenClassification""",
          """BioGptForSequenceClassification""",
          """BioGptModel""",
          """BioGptPreTrainedModel""",
      ]


if TYPE_CHECKING:
      from .configuration_biogpt import BIOGPT_PRETRAINED_CONFIG_ARCHIVE_MAP, BioGptConfig
      from .tokenization_biogpt import BioGptTokenizer

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_biogpt import (
                BIOGPT_PRETRAINED_MODEL_ARCHIVE_LIST,
                BioGptForCausalLM,
                BioGptForSequenceClassification,
                BioGptForTokenClassification,
                BioGptModel,
                BioGptPreTrainedModel,
            )


else:
      import sys

      __magic_name__  :  int					=       _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)

