



import re
import string

import numpy as np

import datasets


_lowercase: Tuple      			=		'\nReturns the rate at which the input predicted strings exactly match their references, ignoring any strings input as part of the regexes_to_ignore list.\n'

_lowercase: List[str]      			=		'\nArgs:\n    predictions: List of predicted texts.\n    references: List of reference texts.\n    regexes_to_ignore: List, defaults to None. Regex expressions of characters to\n        ignore when calculating the exact matches. Note: these regexes are removed\n        from the input data before the changes based on the options below (e.g. ignore_case,\n        ignore_punctuation, ignore_numbers) are applied.\n    ignore_case: Boolean, defaults to False. If true, turns everything\n        to lowercase so that capitalization differences are ignored.\n    ignore_punctuation: Boolean, defaults to False. If true, removes all punctuation before\n        comparing predictions and references.\n    ignore_numbers: Boolean, defaults to False. If true, removes all punctuation before\n        comparing predictions and references.\nReturns:\n    exact_match: Dictionary containing exact_match rate. Possible values are between 0.0 and 100.0, inclusive.\nExamples:\n    >>> exact_match = datasets.load_metric("exact_match")\n    >>> refs = ["the cat", "theater", "YELLING", "agent007"]\n    >>> preds = ["cat?", "theater", "yelling", "agent"]\n    >>> results = exact_match.compute(references=refs, predictions=preds)\n    >>> print(round(results["exact_match"], 1))\n    25.0\n\n    >>> exact_match = datasets.load_metric("exact_match")\n    >>> refs = ["the cat", "theater", "YELLING", "agent007"]\n    >>> preds = ["cat?", "theater", "yelling", "agent"]\n    >>> results = exact_match.compute(references=refs, predictions=preds, regexes_to_ignore=["the ", "yell"], ignore_case=True, ignore_punctuation=True)\n    >>> print(round(results["exact_match"], 1))\n    50.0\n\n\n    >>> exact_match = datasets.load_metric("exact_match")\n    >>> refs = ["the cat", "theater", "YELLING", "agent007"]\n    >>> preds = ["cat?", "theater", "yelling", "agent"]\n    >>> results = exact_match.compute(references=refs, predictions=preds, regexes_to_ignore=["the ", "yell", "YELL"], ignore_case=True, ignore_punctuation=True)\n    >>> print(round(results["exact_match"], 1))\n    75.0\n\n    >>> exact_match = datasets.load_metric("exact_match")\n    >>> refs = ["the cat", "theater", "YELLING", "agent007"]\n    >>> preds = ["cat?", "theater", "yelling", "agent"]\n    >>> results = exact_match.compute(references=refs, predictions=preds, regexes_to_ignore=["the ", "yell", "YELL"], ignore_case=True, ignore_punctuation=True, ignore_numbers=True)\n    >>> print(round(results["exact_match"], 1))\n    100.0\n\n    >>> exact_match = datasets.load_metric("exact_match")\n    >>> refs = ["The cat sat on the mat.", "Theaters are great.", "It\'s like comparing oranges and apples."]\n    >>> preds = ["The cat sat on the mat?", "Theaters are great.", "It\'s like comparing apples and oranges."]\n    >>> results = exact_match.compute(references=refs, predictions=preds)\n    >>> print(round(results["exact_match"], 1))\n    33.3\n\n'

_lowercase: Any      			=		'\n'



@datasets.utils.file_utils.add_start_docstrings(_DESCRIPTION,      _KWARGS_DESCRIPTION	)
class 	_lowercase							(   datasets.Metric	):





	"""simple docstring"""




	def      UpperCamelCase_       (self		):
						"""simple docstring"""

						return datasets.MetricInfo(
						    description=_DESCRIPTION		,       citation=_CITATION		,       inputs_description=_KWARGS_DESCRIPTION		,       features=datasets.Features(
						        {
						            "predictions": datasets.Value("string"		,       id="sequence"		),
						            "references": datasets.Value("string"		,       id="sequence"		),
						        }		)		,       reference_urls=[]		,       )




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

						if regexes_to_ignore is not None:
											for s in regexes_to_ignore:
																a					     =   np.array([re.sub(__a		,       ""		,       __a		) for x in predictions]		)
																a					     =   np.array([re.sub(__a		,       ""		,       __a		) for x in references]		)
						else:
											a					     =   np.asarray(__a		)
											a					     =   np.asarray(__a		)

						if ignore_case:
											a					     =   np.char.lower(__a		)
											a					     =   np.char.lower(__a		)

						if ignore_punctuation:
											a					     =   string.punctuation.maketrans(""		,       ""		,       string.punctuation		)
											a					     =   np.char.translate(__a		,       table=__a		)
											a					     =   np.char.translate(__a		,       table=__a		)

						if ignore_numbers:
											a					     =   string.digits.maketrans(""		,       ""		,       string.digits		)
											a					     =   np.char.translate(__a		,       table=__a		)
											a					     =   np.char.translate(__a		,       table=__a		)

						a					     =   predictions == references

						return {"exact_match": np.mean(__a		) * 100}




'''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



