





'''simple docstring'''





import timeit

import numpy as np

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


def     lowerCamelCase_	(      lowerCAmelCase:	Optional[int]				)->		List[Any]:
  def wrapper(*lowerCAmelCase:	Tuple    ,							**lowerCAmelCase:	int				):
    _snake_case   :				Any														=	timeit.default_timer()
    _snake_case   :				Dict														=	func(*lowerCAmelCase    ,							**lowerCAmelCase				)
    _snake_case   :				Optional[int]														=	timeit.default_timer() - starttime
    return delta

  _snake_case   :				List[str]														=	func.__name__

  return wrapper


def     lowerCamelCase_	(      lowerCAmelCase:	dict    ,							lowerCAmelCase:	Dict=1_00    ,							lowerCAmelCase:	Optional[Any]=None				)->		List[Any]:
  _snake_case   :				Optional[int]														=	[]
  _snake_case   :				List[str]														=	seq_shapes or {}
  for i in range(lowerCAmelCase				):
    _snake_case   :				Optional[Any]														=	{}
    for col_id, (k, v) in enumerate(features.items()				):
      if isinstance(lowerCAmelCase    ,							_ArrayXD				):
        _snake_case   :				Union[str, Any]														=	np.random.rand(*v.shape				).astype(v.dtype				)
      elif isinstance(lowerCAmelCase    ,							datasets.Value				):
        if v.dtype == "string":
          _snake_case   :				Optional[Any]														=	'The small grey turtle was surprisingly fast when challenged.'
        else:
          _snake_case   :				List[Any]														=	np.random.randint(10    ,							size=1				).astype(v.dtype				).item()
      elif isinstance(lowerCAmelCase    ,							datasets.Sequence				):
        while isinstance(lowerCAmelCase    ,							datasets.Sequence				):
          _snake_case   :				Optional[Any]														=	v.feature
        _snake_case   :				Optional[int]														=	seq_shapes[k]
        _snake_case   :				Tuple														=	np.random.rand(*lowerCAmelCase				).astype(v.dtype				)
      _snake_case   :				Optional[int]														=	data

    dummy_data.append((i, example)				)

  return dummy_data







def     lowerCamelCase_	(      lowerCAmelCase:	Any    ,							lowerCAmelCase:	List[str]    ,							lowerCAmelCase:	Dict=1_00    ,							lowerCAmelCase:	Optional[Any]=None				)->		Dict:
  _snake_case   :				List[Any]														=	generate_examples(lowerCAmelCase    ,							num_examples=lowerCAmelCase    ,							seq_shapes=lowerCAmelCase				)

  with ArrowWriter(features=lowerCAmelCase    ,							path=lowerCAmelCase				) as writer:
    for key, record in dummy_data:
      _snake_case   :				Union[str, Any]														=	features.encode_example(lowerCAmelCase				)
      writer.write(lowerCAmelCase				)

    _snake_case   :				List[Any]														=	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   :				Optional[Any]														=	datasets.Dataset.from_file(filename=lowerCAmelCase    ,							info=datasets.DatasetInfo(features=lowerCAmelCase				)				)

  return dataset











def     lowerCamelCase_	(      lowerCAmelCase:	int				)->		int:

  if not isinstance(lowerCAmelCase    ,							lowerCAmelCase				):
    _snake_case   :				Union[str, Any]														=	F"""Input value of [number={number}] must be an integer"""
    raise TypeError(lowerCAmelCase				)

  if number < 1:
    _snake_case   :				int														=	F"""Input value of [number={number}] must be > 0"""
    raise ValueError(lowerCAmelCase				)

  _snake_case   :				int														=	1

  for i in range(1    ,							lowerCAmelCase				):
    current_number *= 4 * i - 2
    current_number //= i + 1

  return current_number


if __name__ == "__main__":
      import doctest

      doctest.testmod()




