



from typing import Dict, List, Optional, Union

import numpy as np

from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import convert_to_rgb, normalize, rescale, resize, to_channel_dimension_format
from ...image_utils import (
    OPENAI_CLIP_MEAN,
    OPENAI_CLIP_STD,
    ChannelDimension,
    ImageInput,
    PILImageResampling,
    make_list_of_images,
    to_numpy_array,
    valid_images,
)
from ...utils import TensorType, is_vision_available, logging


if is_vision_available():
				import PIL


_lowercase: List[Any]      			=		logging.get_logger(__name__)



class 	_lowercase							(   lowerCAmelCase_	):





	"""simple docstring"""
	__A							=							["pixel_values"]




	def __init__(self		,       lowerCamelCase_ = True		,       lowerCamelCase_ = None		,       lowerCamelCase_ = PILImageResampling.BICUBIC		,       lowerCamelCase_ = True		,       lowerCamelCase_ = 1 / 255		,       lowerCamelCase_ = True		,       lowerCamelCase_ = None		,       lowerCamelCase_ = None		,       lowerCamelCase_ = True		,       **lowerCamelCase_		,       ):
						"""simple docstring"""

						super().__init__(**__a		)
						a					     =   size if size is not None else {'height': 384, 'width': 384}
						a					     =   get_size_dict(__a		,       default_to_square=__a		)

						a					     =   do_resize
						a					     =   size
						a					     =   resample
						a					     =   do_rescale
						a					     =   rescale_factor
						a					     =   do_normalize
						a					     =   image_mean if image_mean is not None else OPENAI_CLIP_MEAN
						a					     =   image_std if image_std is not None else OPENAI_CLIP_STD
						a					     =   do_convert_rgb




	def      UpperCamelCase_       (self		,       lowerCamelCase_		,       lowerCamelCase_		,       lowerCamelCase_ = PILImageResampling.BICUBIC		,       lowerCamelCase_ = None		,       **lowerCamelCase_		,       ):
						"""simple docstring"""

						a					     =   get_size_dict(__a		,       default_to_square=__a		)
						if "height" not in size or "width" not in size:
											raise ValueError(F'''The `size` dictionary must contain the keys `height` and `width`. Got {size.keys()}'''		)
						a					     =   (size['height'], size['width'])
						return resize(__a		,       size=__a		,       resample=__a		,       data_format=__a		,       **__a		)




	def      UpperCamelCase_       (self		,       lowerCamelCase_		,       lowerCamelCase_		,       lowerCamelCase_ = None		,       **lowerCamelCase_		,       ):
						"""simple docstring"""

						return rescale(__a		,       scale=__a		,       data_format=__a		,       **__a		)




	def      UpperCamelCase_       (self		,       lowerCamelCase_		,       lowerCamelCase_		,       lowerCamelCase_		,       lowerCamelCase_ = None		,       **lowerCamelCase_		,       ):
						"""simple docstring"""

						return normalize(__a		,       mean=__a		,       std=__a		,       data_format=__a		,       **__a		)




	def      UpperCamelCase_       (self		,       lowerCamelCase_		,       lowerCamelCase_ = None		,       lowerCamelCase_ = None		,       lowerCamelCase_ = None		,       lowerCamelCase_ = None		,       lowerCamelCase_ = None		,       lowerCamelCase_ = None		,       lowerCamelCase_ = None		,       lowerCamelCase_ = None		,       lowerCamelCase_ = None		,       lowerCamelCase_ = None		,       lowerCamelCase_ = ChannelDimension.FIRST		,       **lowerCamelCase_		,       ):
						"""simple docstring"""

						a					     =   do_resize if do_resize is not None else self.do_resize
						a					     =   resample if resample is not None else self.resample
						a					     =   do_rescale if do_rescale is not None else self.do_rescale
						a					     =   rescale_factor if rescale_factor is not None else self.rescale_factor
						a					     =   do_normalize if do_normalize is not None else self.do_normalize
						a					     =   image_mean if image_mean is not None else self.image_mean
						a					     =   image_std if image_std is not None else self.image_std
						a					     =   do_convert_rgb if do_convert_rgb is not None else self.do_convert_rgb

						a					     =   size if size is not None else self.size
						a					     =   get_size_dict(__a		,       default_to_square=__a		)

						a					     =   make_list_of_images(__a		)

						if not valid_images(__a		):
											raise ValueError(
											    "Invalid image type. Must be of type PIL.Image.Image, numpy.ndarray, "
											    "torch.Tensor, tf.Tensor or jax.ndarray."		)

						if do_resize and size is None or resample is None:
											raise ValueError("Size and resample must be specified if do_resize is True."		)

						if do_rescale and rescale_factor is None:
											raise ValueError("Rescale factor must be specified if do_rescale is True."		)

						if do_normalize and (image_mean is None or image_std is None):
											raise ValueError("Image mean and std must be specified if do_normalize is True."		)

						# PIL RGBA images are converted to RGB
						if do_convert_rgb:
											a					     =   [convert_to_rgb(__a		) for image in images]

						# All transformations expect numpy arrays.
						a					     =   [to_numpy_array(__a		) for image in images]

						if do_resize:
											a					     =   [self.resize(image=__a		,       size=__a		,       resample=__a		) for image in images]

						if do_rescale:
											a					     =   [self.rescale(image=__a		,       scale=__a		) for image in images]

						if do_normalize:
											a					     =   [self.normalize(image=__a		,       mean=__a		,       std=__a		) for image in images]

						a					     =   [to_channel_dimension_format(__a		,       __a		) for image in images]

						a					     =   BatchFeature(data={"pixel_values": images}		,       tensor_type=__a		)

						return encoded_outputs




'''simple docstring'''



import requests

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






def   lowerCamelCase							(_SCREAMING_SNAKE_CASE      :   str = "Chicago"						,      _SCREAMING_SNAKE_CASE      :   str = APPID   ):
					return requests.get(URL_BASE + 'weather'						,      params=locals()   ).json()






def   lowerCamelCase							(_SCREAMING_SNAKE_CASE      :   str = "Kolkata, India"						,      _SCREAMING_SNAKE_CASE      :   str = APPID   ):
					return requests.get(URL_BASE + 'forecast'						,      params=locals()   ).json()






def   lowerCamelCase							(_SCREAMING_SNAKE_CASE      :   float = 5_5.6_8						,      _SCREAMING_SNAKE_CASE      :   float = 1_2.5_7						,      _SCREAMING_SNAKE_CASE      :   str = APPID   ):
					return requests.get(URL_BASE + 'onecall'						,      params=locals()   ).json()


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

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



