

from collections import defaultdict

def 						UpperCamelCase					(lowercase_: Optional[Any]    ,      lowercase_: Union[str, Any]					)     ->      List[Any]:
	A__							:    str        =		first_str.lower().strip()
	A__							:    Dict        =		second_str.lower().strip()

	# Remove whitespace
	A__							:    List[str]        =		first_str.replace(""" """    ,      """"""					)
	A__							:    int        =		second_str.replace(""" """    ,      """"""					)

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

	# Default values for count should be 0
	A__							:    defaultdict[str, int]        =		defaultdict(SCREAMING_SNAKE_CASE__					)

	# For each character in input strings,
	# increment count in the corresponding
	for i in range(len(SCREAMING_SNAKE_CASE__					)					):
		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()
	A_       : List[Any]         =			input('Enter the first string ').strip()
	A_       : int         =			input('Enter the second string ').strip()

	A_       : List[Any]         =			check_anagrams(input_a, input_b)
	print(f'''{input_a} and {input_b} are {"" if status else "not "}anagrams.''')







'''simple docstring'''


UpperCAmelCase_		:   Union[str, Any]							   =		'\n# Transformers installation\n! pip install transformers datasets\n# To install from source instead of the last release, comment the command above and uncomment the following one.\n# ! pip install git+https://github.com/huggingface/transformers.git\n'

UpperCAmelCase_		:   Dict							   =		[{'type': 'code', 'content': INSTALL_CONTENT}]
UpperCAmelCase_		:   Any							   =		{
    '{processor_class}': 'FakeProcessorClass',
    '{model_class}': 'FakeModelClass',
    '{object_class}': 'FakeObjectClass',
}




