






from collections import defaultdict





def 		__UpperCAmelCase     (	a_				,	a_):
							snake_case_           =				first_str.lower().strip()
							snake_case_           =				second_str.lower().strip()

							# Remove whitespace
							snake_case_           =				first_str.replace(' '				,	'')
							snake_case_           =				second_str.replace(' '				,	'')

							# Strings of different lengths are not anagrams
							if len(a_) != len(a_):
														return False

							# Default values for count should be 0
							snake_case_           =				defaultdict(a_)

							# For each character in input strings,
							# increment count in the corresponding
							for i in range(len(a_)):
														count[first_str[i]] += 1
														count[second_str[i]] -= 1

							return all(_count == 0 for _count in count.values())


if __name__ == "__main__":
	from doctest import testmod

	testmod()
	lowercase    				=   input("Enter the first string ").strip()
	lowercase    				=   input("Enter the second string ").strip()

	lowercase    				=   check_anagrams(input_a, input_b)
	print(f'{input_a} and {input_b} are {"" if status else "not "}anagrams.')













from dataclasses import dataclass, field
from typing import ClassVar, Dict

from ..features import Features, Value
from .base import TaskTemplate




@dataclass(frozen=snake_case_							)
class 					UpperCamelCase_ (     snake_case_							):



	'''simple docstring'''




	lowerCAmelCase						=					field(default='''language-modeling'''			,   metadata={'''include_in_asdict_even_if_is_default''': True}							)

	lowerCAmelCase						=					Features({'''text''': Value('''string'''							)}							)
	lowerCAmelCase						=					Features({}							)
	lowerCAmelCase						=					"text"




	@property
	def 				_UpperCamelCase     (			self   )			->       Dict[str, str]:
								return {self.text_column: "text"}





