





'''simple docstring'''






from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_sentencepiece_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


A_		:  str		 =						{"configuration_xlnet": ["XLNET_PRETRAINED_CONFIG_ARCHIVE_MAP", "XLNetConfig"]}

try:
    if not is_sentencepiece_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    A_		:  List[str]		 =						["XLNetTokenizer"]

try:
    if not is_tokenizers_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    A_		:  Any		 =						["XLNetTokenizerFast"]

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    A_		:  Tuple		 =						[
        "XLNET_PRETRAINED_MODEL_ARCHIVE_LIST",
        "XLNetForMultipleChoice",
        "XLNetForQuestionAnswering",
        "XLNetForQuestionAnsweringSimple",
        "XLNetForSequenceClassification",
        "XLNetForTokenClassification",
        "XLNetLMHeadModel",
        "XLNetModel",
        "XLNetPreTrainedModel",
        "load_tf_weights_in_xlnet",
    ]

try:
    if not is_tf_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    A_		:  Union[str, Any]		 =						[
        "TF_XLNET_PRETRAINED_MODEL_ARCHIVE_LIST",
        "TFXLNetForMultipleChoice",
        "TFXLNetForQuestionAnsweringSimple",
        "TFXLNetForSequenceClassification",
        "TFXLNetForTokenClassification",
        "TFXLNetLMHeadModel",
        "TFXLNetMainLayer",
        "TFXLNetModel",
        "TFXLNetPreTrainedModel",
    ]


if TYPE_CHECKING:
    from .configuration_xlnet import XLNET_PRETRAINED_CONFIG_ARCHIVE_MAP, XLNetConfig

    try:
        if not is_sentencepiece_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .tokenization_xlnet import XLNetTokenizer

    try:
        if not is_tokenizers_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .tokenization_xlnet_fast import XLNetTokenizerFast

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_xlnet import (
            XLNET_PRETRAINED_MODEL_ARCHIVE_LIST,
            XLNetForMultipleChoice,
            XLNetForQuestionAnswering,
            XLNetForQuestionAnsweringSimple,
            XLNetForSequenceClassification,
            XLNetForTokenClassification,
            XLNetLMHeadModel,
            XLNetModel,
            XLNetPreTrainedModel,
            load_tf_weights_in_xlnet,
        )

    try:
        if not is_tf_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_tf_xlnet import (
            TF_XLNET_PRETRAINED_MODEL_ARCHIVE_LIST,
            TFXLNetForMultipleChoice,
            TFXLNetForQuestionAnsweringSimple,
            TFXLNetForSequenceClassification,
            TFXLNetForTokenClassification,
            TFXLNetLMHeadModel,
            TFXLNetMainLayer,
            TFXLNetModel,
            TFXLNetPreTrainedModel,
        )

else:
    import sys

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






'''simple docstring'''
import requests

lowercase__											=''  # <-- Put your OpenWeatherMap appid here!
lowercase__											='https://api.openweathermap.org/data/2.5/'






def      UpperCamelCase_				(      A__ = "Chicago"  ,      A__ = APPID						):
	return requests.get(URL_BASE + """weather"""  ,      params=locals()						).json()






def      UpperCamelCase_				(      A__ = "Kolkata, India"  ,      A__ = APPID						):
	return requests.get(URL_BASE + """forecast"""  ,      params=locals()						).json()






def      UpperCamelCase_				(      A__ = 55.68  ,      A__ = 12.57  ,      A__ = APPID						):
	return requests.get(URL_BASE + """onecall"""  ,      params=locals()						).json()


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

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