


"""simple docstring"""


import timeit

import numpy as np

import datasets
from datasets.arrow_writer import ArrowWriter
from datasets.features.features import _ArrayXD







def 			__snake_case							( UpperCamelCase__						)   ->		Dict:







		"""simple docstring"""





		def wrapper(*UpperCamelCase__			,      **UpperCamelCase__						):
				A       							=			timeit.default_timer()
				A       							=			func(*_lowercase			,      **_lowercase						)
				A       							=			timeit.default_timer() - starttime
				return delta

		A       							=			func.__name__

		return wrapper







def 			__snake_case							( UpperCamelCase__			,      UpperCamelCase__=100			,      UpperCamelCase__=None						)   ->		Optional[int]:







		"""simple docstring"""





		A       							=			[]
		A       							=			seq_shapes or {}
		for i in range(_lowercase						):
				A       							=			{}
				for col_id, (k, v) in enumerate(features.items()						):
						if isinstance(_lowercase			,      _ArrayXD						):
								A       							=			np.random.rand(*v.shape						).astype(v.dtype						)
						elif isinstance(_lowercase			,      datasets.Value						):
								if v.dtype == "string":
										A       							=			"The small grey turtle was surprisingly fast when challenged."
								else:
										A       							=			np.random.randint(10			,      size=1						).astype(v.dtype						).item()
						elif isinstance(_lowercase			,      datasets.Sequence						):
								while isinstance(_lowercase			,      datasets.Sequence						):
										A       							=			v.feature
								A       							=			seq_shapes[k]
								A       							=			np.random.rand(*_lowercase						).astype(v.dtype						)
						A       							=			data

				dummy_data.append((i, example)						)

		return dummy_data







def 			__snake_case							( UpperCamelCase__			,      UpperCamelCase__			,      UpperCamelCase__=100			,      UpperCamelCase__=None						)   ->		Optional[Any]:







		"""simple docstring"""





		A       							=			generate_examples(_lowercase			,      num_examples=_lowercase			,      seq_shapes=_lowercase						)

		with ArrowWriter(features=_lowercase			,      path=_lowercase						) as writer:
				for key, record in dummy_data:
						A       							=			features.encode_example(_lowercase						)
						writer.write(_lowercase						)

				A       							=			writer.finalize()

		if not num_final_examples == num_examples:
				raise ValueError(
				    f'Error writing the dataset, wrote {num_final_examples} examples but should have written {num_examples}.'						)

		A       							=			datasets.Dataset.from_file(filename=_lowercase			,      info=datasets.DatasetInfo(features=_lowercase						)						)

		return dataset












"""simple docstring"""




def  _SCREAMING_SNAKE_CASE						(      _lowercase		:       Tuple   )					->Optional[Any]:






	'''simple docstring'''






	a :						Any      =							[]
	a :						List[str]      =							set({"(", "[", "{"}   )
	a :						int      =							set({")", "]", "}"}   )
	a :						int      =							{"{": "}", "[": "]", "(": ")"}

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

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

	return len(_lowercase   ) == 0






def  _SCREAMING_SNAKE_CASE						(      )					->Tuple:






	'''simple docstring'''






	a :						Any      =							input("Enter sequence of brackets: "   )
	if is_balanced(_lowercase   ):
		print(_lowercase       ,			"is balanced"   )
	else:
		print(_lowercase       ,			"is not balanced"   )


if __name__ == "__main__":
		main()


