



import pprint

import requests

SCREAMING_SNAKE_CASE_:str					=						"""https://zenquotes.io/api"""




def      __UpperCamelCase     (  )	->  Tuple:



    """simple docstring"""






    return requests.get(API_ENDPOINT_URL + """/today"""		).json()




def      __UpperCamelCase     (  )	->  List[str]:



    """simple docstring"""






    return requests.get(API_ENDPOINT_URL + """/random"""		).json()


if __name__ == "__main__":
     SCREAMING_SNAKE_CASE_:Any					=						random_quotes()
     pprint.pprint(response)







from typing import TYPE_CHECKING

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


SCREAMING_SNAKE_CASE_:Optional[int]					=						{
    """configuration_tapas""": ["""TAPAS_PRETRAINED_CONFIG_ARCHIVE_MAP""", """TapasConfig"""],
    """tokenization_tapas""": ["""TapasTokenizer"""],
}

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     SCREAMING_SNAKE_CASE_:Optional[int]					=						[
         """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:
     SCREAMING_SNAKE_CASE_:Optional[Any]					=						[
         """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

     SCREAMING_SNAKE_CASE_:str					=						_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)


