



import timeit

import numpy as np

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







def     UpperCAmelCase_		(					snake_case__					)	->     List[str]:



				"""simple docstring"""





				def wrapper(*snake_case__    ,			**snake_case__					):
								lowerCAmelCase__		  =  timeit.default_timer()
								lowerCAmelCase__		  =  func(*snake_case__    ,			**snake_case__					)
								lowerCAmelCase__		  =  timeit.default_timer() - starttime
								return delta

				lowerCAmelCase__		  =  func.__name__

				return wrapper







def     UpperCAmelCase_		(					snake_case__    ,			snake_case__=100    ,			snake_case__=None					)	->     str:



				"""simple docstring"""





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

								dummy_data.append((i, example)					)

				return dummy_data







def     UpperCAmelCase_		(					snake_case__    ,			snake_case__    ,			snake_case__=100    ,			snake_case__=None					)	->     Union[str, Any]:



				"""simple docstring"""





				lowerCAmelCase__		  =  generate_examples(snake_case__    ,			num_examples=snake_case__    ,			seq_shapes=snake_case__					)

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

								lowerCAmelCase__  ,   lowerCAmelCase__		  =  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}.'					)

				lowerCAmelCase__		  =  datasets.Dataset.from_file(filename=snake_case__    ,			info=datasets.DatasetInfo(features=snake_case__					)					)

				return dataset





import random
from typing import Any







def     UpperCAmelCase_		(					snake_case__					)	->     list[Any]:



				"""simple docstring"""





				for _ in range(len(snake_case__					)					):
								lowerCAmelCase__		  =  random.randint(0    ,			len(snake_case__					) - 1					)
								lowerCAmelCase__		  =  random.randint(0    ,			len(snake_case__					) - 1					)
								lowerCAmelCase__  ,   lowerCAmelCase__		  =  data[b], data[a]
				return data


if __name__ == "__main__":
	_lowerCAmelCase	:   int    =   [0, 1, 2, 3, 4, 5, 6, 7]
	_lowerCAmelCase	:   Optional[Any]    =   ["python", "says", "hello", "!"]
	print("Fisher-Yates Shuffle:")
	print("List", integers, strings)
	print("FY Shuffle", fisher_yates_shuffle(integers), fisher_yates_shuffle(strings))
