


'''simple docstring'''



def     lowerCamelCase				(_SCREAMING_SNAKE_CASE :  Dict  ):
					# if the collection is empty, returns empty
					if collection == []:
										return []

					# get some information about the collection
					__a     :			str          =    len(A__  )
					__a     :			Union[str, Any]          =    max(A__  )
					__a     :			Union[str, Any]          =    min(A__  )

					# create the counting array
					__a     :			Dict          =    coll_max + 1 - coll_min
					__a     :			Dict          =    [0] * counting_arr_length

					# count how much a number appears in the collection
					for number in collection:
										counting_arr[number - coll_min] += 1

					# sum each position with it's predecessors. now, counting_arr[i] tells
					# us how many elements <= i has in the collection
					for i in range(1		, A__  ):
										__a     :			Dict          =    counting_arr[i] + counting_arr[i - 1]

					# create the output collection
					__a     :			Optional[Any]          =    [0] * coll_len

					# place the elements in the output, respecting the original order (stable
					# sort) from end to begin, updating counting_arr
					for i in reversed(range(0		, A__  )  ):
										__a     :			List[str]          =    collection[i]
										counting_arr[collection[i] - coll_min] -= 1

					return ordered






def     lowerCamelCase				(_SCREAMING_SNAKE_CASE :  Any  ):
					return "".join([chr(A__  ) for i in counting_sort([ord(A__  ) for c in string]  )]  )


if __name__ == "__main__":
	# Test string sort
	assert counting_sort_string('thisisthestring') == "eghhiiinrsssttt"

	__lowercase      :		Union[str, Any]			=      input('Enter numbers separated by a comma:\n').strip()
	__lowercase      :		Union[str, Any]			=      [int(item) for item in user_input.split(',')]
	print(counting_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__		):
			def wrapper(*A__      ,**A__		):
						UpperCAmelCase_	:					Union[str, Any]     	=   timeit.default_timer()
						UpperCAmelCase_	:					Union[str, Any]     	=   func(*A__      ,**A__		)
						UpperCAmelCase_	:					Dict     	=   timeit.default_timer() - starttime
						return delta

			UpperCAmelCase_	:					Optional[Any]     	=   func.__name__

			return wrapper

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

						dummy_data.append((i, example)		)

			return dummy_data




def 							snake_case (  A__      ,A__      ,A__=1_00      ,A__=None		):
			UpperCAmelCase_	:					Optional[Any]     	=   generate_examples(A__      ,num_examples=A__      ,seq_shapes=A__		)

			with ArrowWriter(features=A__      ,path=A__		) as writer:
						for key, record in dummy_data:
									UpperCAmelCase_	:					Any     	=   features.encode_example(A__		)
									writer.write(A__		)

						UpperCAmelCase_	,      UpperCAmelCase_	:					Optional[int]     	=   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}."""		)

			UpperCAmelCase_	:					List[Any]     	=   datasets.Dataset.from_file(filename=A__      ,info=datasets.DatasetInfo(features=A__		)		)

			return dataset



