





"""simple docstring"""





def       a__					(					_SCREAMING_SNAKE_CASE    ):




		"""simple docstring"""


		UpperCamelCase   =	[]
		UpperCamelCase   =	set({"(", "[", "{"}    )
		UpperCamelCase   =	set({")", "]", "}"}    )
		UpperCamelCase   =	{"{": "}", "[": "]", "(": ")"}

		for i in range(len(_SCREAMING_SNAKE_CASE    )    ):
				if s[i] in open_brackets:
						stack.append(s[i]    )

				elif s[i] in closed_brackets and (
				    len(_SCREAMING_SNAKE_CASE    ) == 0 or (len(_SCREAMING_SNAKE_CASE    ) > 0 and open_to_closed[stack.pop()] != s[i])
				):
						return False

		return len(_SCREAMING_SNAKE_CASE    ) == 0


def       a__					(					):




		"""simple docstring"""


		UpperCamelCase   =	input("Enter sequence of brackets: "    )
		if is_balanced(_SCREAMING_SNAKE_CASE    ):
				print(_SCREAMING_SNAKE_CASE  ,	"is balanced"    )
		else:
				print(_SCREAMING_SNAKE_CASE  ,	"is not balanced"    )


if __name__ == "__main__":
						main()













"""simple docstring"""





lowerCAmelCase__     			=			'''
# Transformers installation
! pip install transformers datasets
# To install from source instead of the last release, comment the command above and uncomment the following one.
# ! pip install git+https://github.com/huggingface/transformers.git
'''

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






