code: 
  
  
  
  
  
  import random
  def   _A (	SCREAMING_SNAKE_CASE  :     List[str]		):
  
  
  
  
  
    """simple docstring"""
  
  
  
    def is_sorted(SCREAMING_SNAKE_CASE  :     List[str]		):
      for i in range(len(SCREAMING_SNAKE_CASE		) - 1		):
        if collection[i] > collection[i + 1]:
          return False
      return True
  
    while not is_sorted(SCREAMING_SNAKE_CASE		):
      random.shuffle(SCREAMING_SNAKE_CASE		)
    return collection
  
  
  if __name__ == "__main__":
       UpperCAmelCase			:			Optional[int]	  = input("""Enter numbers separated by a comma:\n""").strip()
       UpperCAmelCase			:			Any	  = [int(item) for item in user_input.split(""",""")]
       print(bogo_sort(unsorted))
  
  
  
  
  
  
  
style_context: 
  
  
  
  
  
  import os
  import tempfile
  from pathlib import Path
  from unittest import TestCase
  
  import pyarrow as pa
  import pytest
  
  from datasets.arrow_dataset import Dataset
  from datasets.arrow_reader import ArrowReader, BaseReader, FileInstructions, ReadInstruction, make_file_instructions
  from datasets.info import DatasetInfo
  from datasets.splits import NamedSplit, Split, SplitDict, SplitInfo
  
  from .utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases
  
  
  
  
  
  
  
  class        __lowerCAmelCase (					UpperCamelCase__):
  
  
  
  
  
  
  
        def      _lowercase						(					self	,   lowerCAmelCase__	,   lowerCAmelCase__=False							)     ->		List[Any]:
  
  
  
          '''simple docstring'''
  
  
  
  
          a__      ,							a__      ,							a__			:      Optional[int]            =(
              filename_skip_take["filename"],
              filename_skip_take["skip"] if "skip" in filename_skip_take else None,
              filename_skip_take["take"] if "take" in filename_skip_take else None,
          )
          open(os.path.join(lowerCAmelCase__							)	,   "wb"							).close()
          a__			:      Optional[int]            =pa.Table.from_pydict({"filename": [Path(lowerCAmelCase__							).name] * 1_0_0}							)
          if take == -1:
            a__			:      int            =len(lowerCAmelCase__							) - skip
          if skip is not None and take is not None:
            a__			:      Optional[Any]            =pa_table.slice(lowerCAmelCase__	,   lowerCAmelCase__							)
          return pa_table
  
  
  
  
  
  
  
  class        __lowerCAmelCase (					UpperCamelCase__):
  
  
  
  
  
  
  
        def      _lowercase						(					self							)     ->		str:
  
  
  
          '''simple docstring'''
  
  
  
  
          a__			:      List[str]            ="my_name"
          a__			:      List[Any]            =SplitInfo(name="train"	,   num_examples=1_0_0							)
          a__			:      List[str]            =SplitInfo(name="test"	,   num_examples=1_0_0							)
          a__			:      List[Any]            =[train_info, test_info]
          a__			:      Union[str, Any]            =SplitDict()
          split_dict.add(lowerCAmelCase__							)
          split_dict.add(lowerCAmelCase__							)
          a__			:      Dict            =DatasetInfo(splits=lowerCAmelCase__							)
  
          with tempfile.TemporaryDirectory() as tmp_dir:
            a__			:      Optional[Any]            =ReaderTest(lowerCAmelCase__	,   lowerCAmelCase__							)
  
            a__			:      Any            ="test[:33%]"
            a__			:      int            =Dataset(**reader.read(lowerCAmelCase__	,   lowerCAmelCase__	,   lowerCAmelCase__							)							)
            self.assertEqual(dset["filename"][0]	,   F'''{name}-test'''							)
            self.assertEqual(dset.num_rows	,   3_3							)
            self.assertEqual(dset.num_columns	,   1							)
  
            a__			:      Tuple            =["train", "test[:33%]"]
            a__			:      str            =[Split.TRAIN, ReadInstruction.from_spec("test[:33%]"							)]
            for instructions in [instructionsa, instructionsa]:
              a__			:      Optional[int]            =[reader.read(lowerCAmelCase__	,   lowerCAmelCase__	,   lowerCAmelCase__							) for instr in instructions]
              a__      ,							a__			:      Optional[int]            =(Dataset(**lowerCAmelCase__							) for dataset_kwargs in datasets_kwargs)
              self.assertEqual(train_dset["filename"][0]	,   F'''{name}-train'''							)
              self.assertEqual(train_dset.num_rows	,   1_0_0							)
              self.assertEqual(train_dset.num_columns	,   1							)
              self.assertIsInstance(train_dset.split	,   lowerCAmelCase__							)
              self.assertEqual(str(train_dset.split							)	,   "train"							)
              self.assertEqual(test_dset["filename"][0]	,   F'''{name}-test'''							)
              self.assertEqual(test_dset.num_rows	,   3_3							)
              self.assertEqual(test_dset.num_columns	,   1							)
              self.assertIsInstance(test_dset.split	,   lowerCAmelCase__							)
              self.assertEqual(str(test_dset.split							)	,   "test[:33%]"							)
              del train_dset, test_dset
  
  
  
  
  
  
  
        def      _lowercase						(					self							)     ->		Optional[Any]:
  
  
  
          '''simple docstring'''
  
  
  
  
          a__			:      Any            ="my_name"
          a__			:      List[Any]            =SplitInfo(name="train"	,   num_examples=1_0_0_0	,   shard_lengths=[1_0_0] * 1_0							)
          a__			:      Optional[Any]            =[train_info]
          a__			:      Any            =SplitDict()
          split_dict.add(lowerCAmelCase__							)
          a__			:      Any            =DatasetInfo(splits=lowerCAmelCase__							)
  
          with tempfile.TemporaryDirectory() as tmp_dir:
            a__			:      Optional[int]            =ReaderTest(lowerCAmelCase__	,   lowerCAmelCase__							)
  
            a__			:      Union[str, Any]            ="train[:33%]"
            a__			:      Union[str, Any]            =Dataset(**reader.read(lowerCAmelCase__	,   lowerCAmelCase__	,   lowerCAmelCase__							)							)
            self.assertEqual(dset["filename"][0]	,   F'''{name}-train-00000-of-00010'''							)
            self.assertEqual(dset["filename"][-1]	,   F'''{name}-train-00003-of-00010'''							)
            self.assertEqual(dset.num_rows	,   3_3_0							)
            self.assertEqual(dset.num_columns	,   1							)
  
  
  
  
  
  
  
        def      _lowercase						(					self							)     ->		List[str]:
  
  
  
          '''simple docstring'''
  
  
  
  
          a__			:      Dict            =SplitInfo(name="train"	,   num_examples=1_0_0							)
          a__			:      str            =SplitInfo(name="test"	,   num_examples=1_0_0							)
          a__			:      int            =SplitDict()
          split_dict.add(lowerCAmelCase__							)
          split_dict.add(lowerCAmelCase__							)
          a__			:      int            =DatasetInfo(splits=lowerCAmelCase__							)
  
          with tempfile.TemporaryDirectory() as tmp_dir:
            a__			:      Tuple            =ReaderTest(lowerCAmelCase__	,   lowerCAmelCase__							)
  
            a__			:      Tuple            =[
                {"filename": os.path.join(lowerCAmelCase__	,   "train"							)},
                {"filename": os.path.join(lowerCAmelCase__	,   "test"							), "skip": 1_0, "take": 1_0},
            ]
            a__			:      Optional[Any]            =Dataset(**reader.read_files(lowerCAmelCase__	,   original_instructions="train+test[10:20]"							)							)
            self.assertEqual(dset.num_rows	,   1_1_0							)
            self.assertEqual(dset.num_columns	,   1							)
            del dset
  @pytest.mark.parametrize("in_memory" , [False, True]		)
  def   _A (	SCREAMING_SNAKE_CASE  :     Optional[Any] , SCREAMING_SNAKE_CASE  :     Optional[Any] , SCREAMING_SNAKE_CASE  :     Optional[Any]		):
  
  
  
  
  
    """simple docstring"""
  
  
  
    a__			:      int            =arrow_file
    with assert_arrow_memory_increases() if in_memory else assert_arrow_memory_doesnt_increase():
      a__			:      str            =ArrowReader.read_table(SCREAMING_SNAKE_CASE , in_memory=SCREAMING_SNAKE_CASE		)
    assert table.shape == dataset.data.shape
    assert set(table.column_names		) == set(dataset.data.column_names		)
    assert dict(table.to_pydict()		) == dict(dataset.data.to_pydict()		)  # to_pydict returns OrderedDict
  @pytest.mark.parametrize("in_memory" , [False, True]		)
  def   _A (	SCREAMING_SNAKE_CASE  :     Tuple , SCREAMING_SNAKE_CASE  :     List[Any] , SCREAMING_SNAKE_CASE  :     str		):
  
  
  
  
  
    """simple docstring"""
  
  
  
    a__			:      Optional[int]            =arrow_file
    a__			:      Tuple            =ArrowReader("" , SCREAMING_SNAKE_CASE		)
    with assert_arrow_memory_increases() if in_memory else assert_arrow_memory_doesnt_increase():
      a__			:      Union[str, Any]            =reader.read_files([{"filename": filename}] , in_memory=SCREAMING_SNAKE_CASE		)
    assert dataset_kwargs.keys() == {"arrow_table", "info", "split"}
    a__			:      Dict            =dataset_kwargs["arrow_table"]
    assert table.shape == dataset.data.shape
    assert set(table.column_names		) == set(dataset.data.column_names		)
    assert dict(table.to_pydict()		) == dict(dataset.data.to_pydict()		)  # to_pydict returns OrderedDict
  def   _A (	):
  
  
  
  
  
    """simple docstring"""
  
  
  
    assert ReadInstruction("train" , to=10 , unit="abs"		).to_spec() == "train[:10]"
    assert ReadInstruction("train" , from_=-80 , to=10 , unit="%"		).to_spec() == "train[-80%:10%]"
  
    a__			:      List[Any]            ="train+test"
    assert ReadInstruction.from_spec(SCREAMING_SNAKE_CASE		).to_spec() == spec_train_test
  
    a__			:      Union[str, Any]            ="train[2:10]"
    assert ReadInstruction.from_spec(SCREAMING_SNAKE_CASE		).to_spec() == spec_train_abs
  
    a__			:      List[Any]            ="train[15%:-20%]"
    assert ReadInstruction.from_spec(SCREAMING_SNAKE_CASE		).to_spec() == spec_train_pct
  
    a__			:      Dict            ="train[:10%](closest)"
    assert ReadInstruction.from_spec(SCREAMING_SNAKE_CASE		).to_spec() == "train[:10%]"
  
    a__			:      Tuple            ="train[:10%](pct1_dropremainder)"
    assert ReadInstruction.from_spec(SCREAMING_SNAKE_CASE		).to_spec() == spec_train_pct_rounding
  
    a__			:      List[Any]            ="train[:10%](pct1_dropremainder)+test[-10%:](pct1_dropremainder)"
    assert ReadInstruction.from_spec(SCREAMING_SNAKE_CASE		).to_spec() == spec_train_test_pct_rounding
  def   _A (	):
  
  
  
  
  
    """simple docstring"""
  
  
  
    a__			:      Optional[Any]            ="dummy"
    a__			:      Dict            =[SplitInfo(name="train" , num_examples=100		)]
    a__			:      Optional[Any]            ="train[:33%]"
    a__			:      int            ="arrow"
    a__			:      Any            ="prefix"
  
    a__			:      Tuple            =make_file_instructions(SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE		)
    assert isinstance(SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE		)
    assert file_instructions.num_examples == 33
    assert file_instructions.file_instructions == [
        {"filename": os.path.join(SCREAMING_SNAKE_CASE , f'''{name}-train.arrow'''		), "skip": 0, "take": 33}
    ]
  
    a__			:      List[str]            =[SplitInfo(name="train" , num_examples=100 , shard_lengths=[10] * 10		)]
    a__			:      Union[str, Any]            =make_file_instructions(SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE		)
    assert isinstance(SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE		)
    assert file_instructions.num_examples == 33
    assert file_instructions.file_instructions == [
        {"filename": os.path.join(SCREAMING_SNAKE_CASE , f'''{name}-train-00000-of-00010.arrow'''		), "skip": 0, "take": -1},
        {"filename": os.path.join(SCREAMING_SNAKE_CASE , f'''{name}-train-00001-of-00010.arrow'''		), "skip": 0, "take": -1},
        {"filename": os.path.join(SCREAMING_SNAKE_CASE , f'''{name}-train-00002-of-00010.arrow'''		), "skip": 0, "take": -1},
        {"filename": os.path.join(SCREAMING_SNAKE_CASE , f'''{name}-train-00003-of-00010.arrow'''		), "skip": 0, "take": 3},
    ]
  
  
  
  
  
  @pytest.mark.parametrize("name, expected_exception" , [(None, TypeError), ("", ValueError)]		)
  def   _A (	SCREAMING_SNAKE_CASE  :     Tuple , SCREAMING_SNAKE_CASE  :     Tuple		):
  
  
  
  
  
    """simple docstring"""
  
  
  
    a__			:      Dict            =[SplitInfo(name="train" , num_examples=100		)]
    a__			:      Any            ="train"
    a__			:      Optional[Any]            ="arrow"
    a__			:      List[Any]            ="prefix_path"
    with pytest.raises(SCREAMING_SNAKE_CASE		):
      a__			:      Optional[Any]            =make_file_instructions(SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE		)
  
  
  
  
  
  
  