code: 
  
  
  
  
  
  
  import csv
  import os
  
  import pytest
  
  from datasets import Dataset, DatasetDict, Features, NamedSplit, Value
  from datasets.io.csv import CsvDatasetReader, CsvDatasetWriter
  
  from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases
  
  
  
  
  
  
  
  def 			lowercase__  (				A_:	Optional[Any]     ,			A_:	str		)  ->							Dict:
  
  
  
  
  
  
  
         """simple docstring"""
  
  
  
  
  
  
         assert isinstance(A_     ,			A_		)
         assert dataset.num_rows == 4
         assert dataset.num_columns == 3
         assert dataset.column_names == ["col_1", "col_2", "col_3"]
         for feature, expected_dtype in expected_features.items():
                assert dataset.features[feature].dtype == expected_dtype
  
  
  
  
  
  
  
  @pytest.mark.parametrize("""keep_in_memory"""     ,			[False, True]		)
  def 			lowercase__  (				A_:	int     ,			A_:	str     ,			A_:	str		)  ->							List[Any]:
  
  
  
  
  
  
  
         """simple docstring"""
  
  
  
  
  
  
         __UpperCAmelCase    							=tmp_path / """cache"""
         __UpperCAmelCase    							={"""col_1""": """int64""", """col_2""": """int64""", """col_3""": """float64"""}
         with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
                __UpperCAmelCase    							=CsvDatasetReader(A_     ,			cache_dir=A_     ,			keep_in_memory=A_		).read()
         _check_csv_dataset(A_     ,			A_		)
  
  
  
  
  
  
  
  @pytest.mark.parametrize(
      """features"""     ,			[
          None,
          {"""col_1""": """string""", """col_2""": """int64""", """col_3""": """float64"""},
          {"""col_1""": """string""", """col_2""": """string""", """col_3""": """string"""},
          {"""col_1""": """int32""", """col_2""": """int32""", """col_3""": """int32"""},
          {"""col_1""": """float32""", """col_2""": """float32""", """col_3""": """float32"""},
      ]     ,			)
  def 			lowercase__  (				A_:	Tuple     ,			A_:	Optional[int]     ,			A_:	Union[str, Any]		)  ->							int:
  
  
  
  
  
  
  
         """simple docstring"""
  
  
  
  
  
  
         __UpperCAmelCase    							=tmp_path / """cache"""
         # CSV file loses col_1 string dtype information: default now is "int64" instead of "string"
         __UpperCAmelCase    							={"""col_1""": """int64""", """col_2""": """int64""", """col_3""": """float64"""}
         __UpperCAmelCase    							=features.copy() if features else default_expected_features
         __UpperCAmelCase    							=(
             Features({feature: Value(A_		) for feature, dtype in features.items()}		) if features is not None else None
         )
         __UpperCAmelCase    							=CsvDatasetReader(A_     ,			features=A_     ,			cache_dir=A_		).read()
         _check_csv_dataset(A_     ,			A_		)
  
  
  
  
  
  
  
  @pytest.mark.parametrize("""split"""     ,			[None, NamedSplit("""train"""		), """train""", """test"""]		)
  def 			lowercase__  (				A_:	Optional[int]     ,			A_:	Tuple     ,			A_:	Optional[int]		)  ->							Dict:
  
  
  
  
  
  
  
         """simple docstring"""
  
  
  
  
  
  
         __UpperCAmelCase    							=tmp_path / """cache"""
         __UpperCAmelCase    							={"""col_1""": """int64""", """col_2""": """int64""", """col_3""": """float64"""}
         __UpperCAmelCase    							=CsvDatasetReader(A_     ,			cache_dir=A_     ,			split=A_		).read()
         _check_csv_dataset(A_     ,			A_		)
         assert dataset.split == split if split else "train"
  
  
  
  
  
  
  
  @pytest.mark.parametrize("""path_type"""     ,			[str, list]		)
  def 			lowercase__  (				A_:	Tuple     ,			A_:	List[Any]     ,			A_:	Optional[Any]		)  ->							Any:
  
  
  
  
  
  
  
         """simple docstring"""
  
  
  
  
  
  
         if issubclass(A_     ,			A_		):
                __UpperCAmelCase    							=csv_path
         elif issubclass(A_     ,			A_		):
                __UpperCAmelCase    							=[csv_path]
         __UpperCAmelCase    							=tmp_path / """cache"""
         __UpperCAmelCase    							={"""col_1""": """int64""", """col_2""": """int64""", """col_3""": """float64"""}
         __UpperCAmelCase    							=CsvDatasetReader(A_     ,			cache_dir=A_		).read()
         _check_csv_dataset(A_     ,			A_		)
  
  
  
  
  
  
  
  def 			lowercase__  (				A_:	List[Any]     ,			A_:	str     ,			A_:	Optional[int]=("train",)		)  ->							Union[str, Any]:
  
  
  
  
  
  
  
         """simple docstring"""
  
  
  
  
  
  
         assert isinstance(A_     ,			A_		)
         for split in splits:
                __UpperCAmelCase    							=dataset_dict[split]
                assert dataset.num_rows == 4
                assert dataset.num_columns == 3
                assert dataset.column_names == ["col_1", "col_2", "col_3"]
                for feature, expected_dtype in expected_features.items():
                       assert dataset.features[feature].dtype == expected_dtype
  
  
  
  
  
  
  
  @pytest.mark.parametrize("""keep_in_memory"""     ,			[False, True]		)
  def 			lowercase__  (				A_:	List[str]     ,			A_:	List[str]     ,			A_:	str		)  ->							Any:
  
  
  
  
  
  
  
         """simple docstring"""
  
  
  
  
  
  
         __UpperCAmelCase    							=tmp_path / """cache"""
         __UpperCAmelCase    							={"""col_1""": """int64""", """col_2""": """int64""", """col_3""": """float64"""}
         with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
                __UpperCAmelCase    							=CsvDatasetReader({"""train""": csv_path}     ,			cache_dir=A_     ,			keep_in_memory=A_		).read()
         _check_csv_datasetdict(A_     ,			A_		)
  
  
  
  
  
  
  
  @pytest.mark.parametrize(
      """features"""     ,			[
          None,
          {"""col_1""": """string""", """col_2""": """int64""", """col_3""": """float64"""},
          {"""col_1""": """string""", """col_2""": """string""", """col_3""": """string"""},
          {"""col_1""": """int32""", """col_2""": """int32""", """col_3""": """int32"""},
          {"""col_1""": """float32""", """col_2""": """float32""", """col_3""": """float32"""},
      ]     ,			)
  def 			lowercase__  (				A_:	str     ,			A_:	Dict     ,			A_:	Tuple		)  ->							Optional[Any]:
  
  
  
  
  
  
  
         """simple docstring"""
  
  
  
  
  
  
         __UpperCAmelCase    							=tmp_path / """cache"""
         # CSV file loses col_1 string dtype information: default now is "int64" instead of "string"
         __UpperCAmelCase    							={"""col_1""": """int64""", """col_2""": """int64""", """col_3""": """float64"""}
         __UpperCAmelCase    							=features.copy() if features else default_expected_features
         __UpperCAmelCase    							=(
             Features({feature: Value(A_		) for feature, dtype in features.items()}		) if features is not None else None
         )
         __UpperCAmelCase    							=CsvDatasetReader({"""train""": csv_path}     ,			features=A_     ,			cache_dir=A_		).read()
         _check_csv_datasetdict(A_     ,			A_		)
  
  
  
  
  
  
  
  @pytest.mark.parametrize("""split"""     ,			[None, NamedSplit("""train"""		), """train""", """test"""]		)
  def 			lowercase__  (				A_:	List[Any]     ,			A_:	Any     ,			A_:	Tuple		)  ->							Optional[int]:
  
  
  
  
  
  
  
         """simple docstring"""
  
  
  
  
  
  
         if split:
                __UpperCAmelCase    							={split: csv_path}
         else:
                __UpperCAmelCase    							={"""train""": csv_path, """test""": csv_path}
         __UpperCAmelCase    							=tmp_path / """cache"""
         __UpperCAmelCase    							={"""col_1""": """int64""", """col_2""": """int64""", """col_3""": """float64"""}
         __UpperCAmelCase    							=CsvDatasetReader(A_     ,			cache_dir=A_		).read()
         _check_csv_datasetdict(A_     ,			A_     ,			splits=list(path.keys()		)		)
         assert all(dataset[split].split == split for split in path.keys()		)
  
  
  
  
  
  
  
  def 			lowercase__  (				A_:	Tuple		)  ->							Tuple:
  
  
  
  
  
  
  
         """simple docstring"""
  
  
  
  
  
  
         with open(A_     ,			encoding="""utf-8"""		) as csvfile:
                yield from csv.reader(A_		)
  
  
  
  
  
  
  
  def 			lowercase__  (				A_:	Dict     ,			A_:	Tuple		)  ->							List[str]:
  
  
  
  
  
  
  
         """simple docstring"""
  
  
  
  
  
  
         __UpperCAmelCase    							=tmp_path / """cache"""
         __UpperCAmelCase    							=os.path.join(A_     ,			"""tmp.csv"""		)
         __UpperCAmelCase    							=CsvDatasetReader({"""train""": csv_path}     ,			cache_dir=A_		).read()
         CsvDatasetWriter(dataset["""train"""]     ,			A_     ,			num_proc=1		).write()
  
         __UpperCAmelCase    							=iter_csv_file(A_		)
         __UpperCAmelCase    							=iter_csv_file(A_		)
  
         for rowa, rowa in zip(A_     ,			A_		):
                assert rowa == rowa
  
  
  
  
  
  
  
  def 			lowercase__  (				A_:	str     ,			A_:	List[Any]		)  ->							Optional[int]:
  
  
  
  
  
  
  
         """simple docstring"""
  
  
  
  
  
  
         __UpperCAmelCase    							=tmp_path / """cache"""
         __UpperCAmelCase    							=os.path.join(A_     ,			"""tmp.csv"""		)
         __UpperCAmelCase    							=CsvDatasetReader({"""train""": csv_path}     ,			cache_dir=A_		).read()
         CsvDatasetWriter(dataset["""train"""]     ,			A_     ,			num_proc=2		).write()
  
         __UpperCAmelCase    							=iter_csv_file(A_		)
         __UpperCAmelCase    							=iter_csv_file(A_		)
  
         for rowa, rowa in zip(A_     ,			A_		):
                assert rowa == rowa
  
  
  
  
  
  
  
  def 			lowercase__  (				A_:	str     ,			A_:	Any		)  ->							Any:
  
  
  
  
  
  
  
         """simple docstring"""
  
  
  
  
  
  
         __UpperCAmelCase    							=tmp_path / """cache"""
         __UpperCAmelCase    							=os.path.join(A_     ,			"""tmp.csv"""		)
         __UpperCAmelCase    							=CsvDatasetReader({"""train""": csv_path}     ,			cache_dir=A_		).read()
         with pytest.raises(A_		):
                CsvDatasetWriter(dataset["""train"""]     ,			A_     ,			num_proc=0		)
  
  
  
  
  
style_context: 
  
  
  
  
  
  
  from __future__ import annotations
  
  __A  							=  [2, 1, 4, 5, 6, 0, 8, 9, 1, 2, 0, 6, 4, 2, 0, 6, 5, 3, 2, 7]
  
  
  
  class 							_A :
      """simple docstring"""
  
      def __init__(							self			:    List[str]   ,    __SCREAMING_SNAKE_CASE			:    int			)			->       None:
             __UpperCAmelCase    							=-1
             __UpperCAmelCase    							=-1
             __UpperCAmelCase    							=[-1] * length
             __UpperCAmelCase    							=None
             __UpperCAmelCase    							=None
  
  
  
      def __repr__(							self			:    Optional[int]			)			->       str:
             return f'''Node(min_value={self.minn} max_value={self.maxx})'''
  
  
  
  
  
  
  
  def 			lowercase__  (				A_:	list[int]		)  ->							Node | None:
  
  
  
  
  
  
  
         """simple docstring"""
  
  
  
  
  
  
         __UpperCAmelCase    							=Node(len(A_		)		)
         __UpperCAmelCase							,   __UpperCAmelCase    							=min(A_		), max(A_		)
         # Leaf node case where the node contains only one unique value
         if root.minn == root.maxx:
                return root
         __UpperCAmelCase    							=(root.minn + root.maxx) // 2
  
         __UpperCAmelCase    							=[]
         __UpperCAmelCase    							=[]
  
         for index, num in enumerate(A_		):
                if num <= pivot:
                       left_arr.append(A_		)
                else:
                       right_arr.append(A_		)
                __UpperCAmelCase    							=len(A_		)
         __UpperCAmelCase    							=build_tree(A_		)
         __UpperCAmelCase    							=build_tree(A_		)
         return root
  
  
  
  
  
  
  
  def 			lowercase__  (				A_:	Node | None     ,			A_:	int     ,			A_:	int		)  ->							int:
  
  
  
  
  
  
  
         """simple docstring"""
  
  
  
  
  
  
         if index < 0 or node is None:
                return 0
         # Leaf node cases
         if node.minn == node.maxx:
                return index + 1 if node.minn == num else 0
         __UpperCAmelCase    							=(node.minn + node.maxx) // 2
         if num <= pivot:
                # go the left subtree and map index to the left subtree
                return rank_till_index(node.left     ,			A_     ,			node.map_left[index] - 1		)
         else:
                # go to the right subtree and map index to the right subtree
                return rank_till_index(node.right     ,			A_     ,			index - node.map_left[index]		)
  
  
  
  
  
  
  
  def 			lowercase__  (				A_:	Node | None     ,			A_:	int     ,			A_:	int     ,			A_:	int		)  ->							int:
  
  
  
  
  
  
  
         """simple docstring"""
  
  
  
  
  
  
         if start > end:
                return 0
         __UpperCAmelCase    							=rank_till_index(A_     ,			A_     ,			A_		)
         __UpperCAmelCase    							=rank_till_index(A_     ,			A_     ,			start - 1		)
         return rank_till_end - rank_before_start
  
  
  
  
  
  
  
  def 			lowercase__  (				A_:	Node | None     ,			A_:	int     ,			A_:	int     ,			A_:	int		)  ->							int:
  
  
  
  
  
  
  
         """simple docstring"""
  
  
  
  
  
  
         if index > (end - start) or start > end or node is None:
                return -1
         # Leaf node case
         if node.minn == node.maxx:
                return node.minn
         # Number of elements in the left subtree in interval [start, end]
         __UpperCAmelCase    							=node.map_left[end] - (
             node.map_left[start - 1] if start else 0
         )
         if num_elements_in_left_tree > index:
                return quantile(
                    node.left     ,			A_     ,			(node.map_left[start - 1] if start else 0)     ,			node.map_left[end] - 1     ,			)
         else:
                return quantile(
                    node.right     ,			index - num_elements_in_left_tree     ,			start - (node.map_left[start - 1] if start else 0)     ,			end - node.map_left[end]     ,			)
  
  
  
  
  
  
  
  def 			lowercase__  (				A_:	Node | None     ,			A_:	int     ,			A_:	int     ,			A_:	int     ,			A_:	int		)  ->							int:
  
  
  
  
  
  
  
         """simple docstring"""
  
  
  
  
  
  
         if (
             start > end
             or node is None
             or start_num > end_num
             or node.minn > end_num
             or node.maxx < start_num
         ):
                return 0
         if start_num <= node.minn and node.maxx <= end_num:
                return end - start + 1
         __UpperCAmelCase    							=range_counting(
             node.left     ,			(node.map_left[start - 1] if start else 0)     ,			node.map_left[end] - 1     ,			A_     ,			A_     ,			)
         __UpperCAmelCase    							=range_counting(
             node.right     ,			start - (node.map_left[start - 1] if start else 0)     ,			end - node.map_left[end]     ,			A_     ,			A_     ,			)
         return left + right
  
  
  if __name__ == "__main__":
     import doctest
  
     doctest.testmod()
  
  
  
  
  