



"""simple docstring"""






from __future__ import annotations






def 	snake_case_  (				A_ :		list[int]						):


       '''simple docstring'''





       if len(A_						) == 0:
              return array

       _lowerCamelCase      ,   _lowerCamelCase						:    Dict         =			min(A_						), max(A_						)

       # Compute the variables
       _lowerCamelCase						:    List[str]         =			_max - _min + 1
       _lowerCamelCase      ,   _lowerCamelCase						:    List[Any]         =			[0] * holes_range, [0] * holes_range

       # Make the sorting.
       for i in array:
              _lowerCamelCase						:    List[Any]         =			i - _min
              _lowerCamelCase						:    Optional[int]         =			i
              holes_repeat[index] += 1

       # Makes the array back by replacing the numbers.
       _lowerCamelCase						:    Any         =			0
       for i in range(A_						):
              while holes_repeat[i] > 0:
                     _lowerCamelCase						:    List[str]         =			holes[i]
                     index += 1
                     holes_repeat[i] -= 1

    # Returns the sorted array.
       return array


if __name__ == "__main__":
   import doctest

   doctest.testmod()
   lowerCAmelCase__      =    input('''Enter numbers separated by comma:\n''')
   lowerCAmelCase__      =    [int(x) for x in user_input.split(''',''')]
   print(pigeon_sort(unsorted))







"""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_  (				A_ :		Optional[int]						):


       '''simple docstring'''





       def wrapper(*A_ :		int,    **A_ :		List[str]						):
              _lowerCamelCase						:    Tuple         =			timeit.default_timer()
              _lowerCamelCase						:    Optional[Any]         =			func(*A_,    **A_						)
              _lowerCamelCase						:    Tuple         =			timeit.default_timer() - starttime
              return delta

       _lowerCamelCase						:    Optional[Any]         =			func.__name__

       return wrapper






def 	snake_case_  (				A_ :		dict,    A_ :		List[str]=1_00,    A_ :		Optional[Any]=None						):


       '''simple docstring'''





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

              dummy_data.append((i, example)						)

       return dummy_data







def 	snake_case_  (				A_ :		List[str],    A_ :		Optional[int],    A_ :		Optional[int]=1_00,    A_ :		Optional[Any]=None						):


       '''simple docstring'''





       _lowerCamelCase						:    Optional[int]         =			generate_examples(A_,    num_examples=A_,    seq_shapes=A_						)

       with ArrowWriter(features=A_,    path=A_						) as writer:
              for key, record in dummy_data:
                     _lowerCamelCase						:    Optional[Any]         =			features.encode_example(A_						)
                     writer.write(A_						)

              _lowerCamelCase      ,   _lowerCamelCase						:    Dict         =			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						:    List[Any]         =			datasets.Dataset.from_file(filename=A_,    info=datasets.DatasetInfo(features=A_						)						)

       return dataset


