
'''simple docstring'''







import timeit

import numpy as np

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







def        SCREAMING_SNAKE_CASE__			(     __A			) ->			List[str]:
	def wrapper(*__A    ,       **__A			):
		_snake_case     		=	timeit.default_timer()
		_snake_case     		=	func(*lowercase_    ,       **lowercase_			)
		_snake_case     		=	timeit.default_timer() - starttime
		return delta

	_snake_case     		=	func.__name__

	return wrapper







def        SCREAMING_SNAKE_CASE__			(     __A    ,       __A=100    ,       __A=None			) ->			str:
	_snake_case     		=	[]
	_snake_case     		=	seq_shapes or {}
	for i in range(lowercase_			):
		_snake_case     		=	{}
		for col_id, (k, v) in enumerate(features.items()			):
			if isinstance(lowercase_    ,       _ArrayXD			):
				_snake_case     		=	np.random.rand(*v.shape			).astype(v.dtype			)
			elif isinstance(lowercase_    ,       datasets.Value			):
				if v.dtype == "string":
					_snake_case     		=	"""The small grey turtle was surprisingly fast when challenged."""
				else:
					_snake_case     		=	np.random.randint(10    ,       size=1			).astype(v.dtype			).item()
			elif isinstance(lowercase_    ,       datasets.Sequence			):
				while isinstance(lowercase_    ,       datasets.Sequence			):
					_snake_case     		=	v.feature
				_snake_case     		=	seq_shapes[k]
				_snake_case     		=	np.random.rand(*lowercase_			).astype(v.dtype			)
			_snake_case     		=	data

		dummy_data.append((i, example)			)

	return dummy_data







def        SCREAMING_SNAKE_CASE__			(     __A    ,       __A    ,       __A=100    ,       __A=None			) ->			str:
	_snake_case     		=	generate_examples(lowercase_    ,       num_examples=lowercase_    ,       seq_shapes=lowercase_			)

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

		_snake_case     		=	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}.'			)

	_snake_case     		=	datasets.Dataset.from_file(filename=lowercase_    ,       info=datasets.DatasetInfo(features=lowercase_			)			)

	return dataset



'''simple docstring'''







lowercase					:							Tuple   =      {
    "a": "AAAAA",
    "b": "AAAAB",
    "c": "AAABA",
    "d": "AAABB",
    "e": "AABAA",
    "f": "AABAB",
    "g": "AABBA",
    "h": "AABBB",
    "i": "ABAAA",
    "j": "BBBAA",
    "k": "ABAAB",
    "l": "ABABA",
    "m": "ABABB",
    "n": "ABBAA",
    "o": "ABBAB",
    "p": "ABBBA",
    "q": "ABBBB",
    "r": "BAAAA",
    "s": "BAAAB",
    "t": "BAABA",
    "u": "BAABB",
    "v": "BBBAB",
    "w": "BABAA",
    "x": "BABAB",
    "y": "BABBA",
    "z": "BABBB",
    " ": " ",
}


lowercase					:							Union[str, Any]   =      {value: key for key, value in encode_dict.items()}







def        SCREAMING_SNAKE_CASE__			(     __A			) ->			str:
	_snake_case     		=	''
	for letter in word.lower():
		if letter.isalpha() or letter == " ":
			encoded += encode_dict[letter]
		else:
			raise Exception('encode() accepts only letters of the alphabet and spaces'			)
	return encoded







def        SCREAMING_SNAKE_CASE__			(     __A			) ->			str:
	if set(__A			) - {"A", "B", " "} != set():
		raise Exception('decode() accepts only \'A\', \'B\' and spaces'			)
	_snake_case     		=	''
	for word in coded.split():
		while len(__A			) != 0:
			decoded += decode_dict[word[:5]]
			_snake_case     		=	word[5:]
		decoded += " "
	return decoded.strip()


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

					testmod()

