

'''simple docstring'''







from typing import TYPE_CHECKING

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


__lowerCamelCase						    =      {
    'configuration_transfo_xl': ['TRANSFO_XL_PRETRAINED_CONFIG_ARCHIVE_MAP', 'TransfoXLConfig'],
    'tokenization_transfo_xl': ['TransfoXLCorpus', 'TransfoXLTokenizer'],
}

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      __lowerCamelCase						    =      [
          'TRANSFO_XL_PRETRAINED_MODEL_ARCHIVE_LIST',
          'AdaptiveEmbedding',
          'TransfoXLForSequenceClassification',
          'TransfoXLLMHeadModel',
          'TransfoXLModel',
          'TransfoXLPreTrainedModel',
          'load_tf_weights_in_transfo_xl',
      ]

try:
      if not is_tf_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      __lowerCamelCase						    =      [
          'TF_TRANSFO_XL_PRETRAINED_MODEL_ARCHIVE_LIST',
          'TFAdaptiveEmbedding',
          'TFTransfoXLForSequenceClassification',
          'TFTransfoXLLMHeadModel',
          'TFTransfoXLMainLayer',
          'TFTransfoXLModel',
          'TFTransfoXLPreTrainedModel',
      ]


if TYPE_CHECKING:
      from .configuration_transfo_xl import TRANSFO_XL_PRETRAINED_CONFIG_ARCHIVE_MAP, TransfoXLConfig
      from .tokenization_transfo_xl import TransfoXLCorpus, TransfoXLTokenizer

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_transfo_xl import (
                TRANSFO_XL_PRETRAINED_MODEL_ARCHIVE_LIST,
                AdaptiveEmbedding,
                TransfoXLForSequenceClassification,
                TransfoXLLMHeadModel,
                TransfoXLModel,
                TransfoXLPreTrainedModel,
                load_tf_weights_in_transfo_xl,
            )

      try:
            if not is_tf_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_tf_transfo_xl import (
                TF_TRANSFO_XL_PRETRAINED_MODEL_ARCHIVE_LIST,
                TFAdaptiveEmbedding,
                TFTransfoXLForSequenceClassification,
                TFTransfoXLLMHeadModel,
                TFTransfoXLMainLayer,
                TFTransfoXLModel,
                TFTransfoXLPreTrainedModel,
            )

else:
      import sys

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



'''simple docstring'''







import requests

__lowerCamelCase						    =      ''''''  # <-- Put your OpenWeatherMap appid here!
__lowerCamelCase						    =      '''https://api.openweathermap.org/data/2.5/'''
def  UpperCAmelCase__      ( UpperCAmelCase__ = "Chicago",    UpperCAmelCase__ = APPID			)     ->     dict:
       return requests.get(URL_BASE + """weather""",    params=locals()			).json()
def  UpperCAmelCase__      ( UpperCAmelCase__ = "Kolkata, India",    UpperCAmelCase__ = APPID			)     ->     dict:
       return requests.get(URL_BASE + """forecast""",    params=locals()			).json()
def  UpperCAmelCase__      ( UpperCAmelCase__ = 55.68,    UpperCAmelCase__ = 12.57,    UpperCAmelCase__ = APPID			)     ->     dict:
       return requests.get(URL_BASE + """onecall""",    params=locals()			).json()


if __name__ == "__main__":
      from pprint import pprint

      while True:
            __lowerCamelCase						    =      input('''Enter a location:''').strip()
            if location:
                  pprint(current_weather(location))
            else:
                  break
