


from __future__ import annotations

SCREAMING_SNAKE_CASE	:Optional[int]  		=     [2, 1, 4, 5, 6, 0, 8, 9, 1, 2, 0, 6, 4, 2, 0, 6, 5, 3, 2, 7]


class     __lowerCAmelCase     :






  """simple docstring"""





  def __init__(     self       :       str    ,				_lowerCAmelCase       :       int  )   -> None:




     """simple docstring"""
     snake_case_					    =					-1
     snake_case_					    =					-1
     snake_case_					    =					[-1] * length
     snake_case_					    =					None
     snake_case_					    =					None



  def __repr__(     self       :       Dict  )   -> str:




     """simple docstring"""
     return F'''Node(min_value={self.minn} max_value={self.maxx})'''






def 			_lowerCAmelCase						(							lowerCAmelCase_							:list[int]							)->Node | None:
   '''simple docstring'''






   snake_case_					    =					Node(len(lowerCAmelCase_							)							)
   snake_case_    ,    snake_case_					    =					min(lowerCAmelCase_							), max(lowerCAmelCase_							)
   # Leaf node case where the node contains only one unique value
   if root.minn == root.maxx:
      return root
   snake_case_					    =					(root.minn + root.maxx) // 2

   snake_case_					    =					[]
   snake_case_					    =					[]

   for index, num in enumerate(lowerCAmelCase_							):
      if num <= pivot:
         left_arr.append(lowerCAmelCase_							)
      else:
         right_arr.append(lowerCAmelCase_							)
      snake_case_					    =					len(lowerCAmelCase_							)
   snake_case_					    =					build_tree(lowerCAmelCase_							)
   snake_case_					    =					build_tree(lowerCAmelCase_							)
   return root



def 			_lowerCAmelCase						(							lowerCAmelCase_							:Node | None		,						lowerCAmelCase_							:int		,						lowerCAmelCase_							: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
   snake_case_					    =					(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		,						lowerCAmelCase_		,						node.map_left[index] - 1							)
   else:
      # go to the right subtree and map index to the right subtree
      return rank_till_index(node.right		,						lowerCAmelCase_		,						index - node.map_left[index]							)



def 			_lowerCAmelCase						(							lowerCAmelCase_							:Node | None		,						lowerCAmelCase_							:int		,						lowerCAmelCase_							:int		,						lowerCAmelCase_							:int							)->int:
   '''simple docstring'''






   if start > end:
      return 0
   snake_case_					    =					rank_till_index(lowerCAmelCase_		,						lowerCAmelCase_		,						lowerCAmelCase_							)
   snake_case_					    =					rank_till_index(lowerCAmelCase_		,						lowerCAmelCase_		,						start - 1							)
   return rank_till_end - rank_before_start



def 			_lowerCAmelCase						(							lowerCAmelCase_							:Node | None		,						lowerCAmelCase_							:int		,						lowerCAmelCase_							:int		,						lowerCAmelCase_							: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]
   snake_case_					    =					node.map_left[end] - (
       node.map_left[start - 1] if start else 0
   )
   if num_elements_in_left_tree > index:
      return quantile(
          node.left		,						lowerCAmelCase_		,						(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 			_lowerCAmelCase						(							lowerCAmelCase_							:Node | None		,						lowerCAmelCase_							:int		,						lowerCAmelCase_							:int		,						lowerCAmelCase_							:int		,						lowerCAmelCase_							: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
   snake_case_					    =					range_counting(
       node.left		,						(node.map_left[start - 1] if start else 0)		,						node.map_left[end] - 1		,						lowerCAmelCase_		,						lowerCAmelCase_		,						)
   snake_case_					    =					range_counting(
       node.right		,						start - (node.map_left[start - 1] if start else 0)		,						end - node.map_left[end]		,						lowerCAmelCase_		,						lowerCAmelCase_		,						)
   return left + right


if __name__ == "__main__":
    import doctest

    doctest.testmod()








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 			_lowerCAmelCase						(							lowerCAmelCase_							:Optional[Any]		,						lowerCAmelCase_							:List[str]							)->Dict:
   '''simple docstring'''






   assert isinstance(lowerCAmelCase_		,						lowerCAmelCase_							)
   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 			_lowerCAmelCase						(							lowerCAmelCase_							:Dict		,						lowerCAmelCase_							:List[Any]		,						lowerCAmelCase_							:List[str]							)->int:
   '''simple docstring'''






   snake_case_					    =					tmp_path / "cache"
   snake_case_					    =					{"col_1": "int64", "col_2": "int64", "col_3": "float64"}
   with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
      snake_case_					    =					CsvDatasetReader(lowerCAmelCase_		,						cache_dir=lowerCAmelCase_		,						keep_in_memory=lowerCAmelCase_							).read()
   _check_csv_dataset(lowerCAmelCase_		,						lowerCAmelCase_							)



@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 			_lowerCAmelCase						(							lowerCAmelCase_							:List[str]		,						lowerCAmelCase_							:Optional[Any]		,						lowerCAmelCase_							:Optional[Any]							)->Optional[int]:
   '''simple docstring'''






   snake_case_					    =					tmp_path / "cache"
   # CSV file loses col_1 string dtype information: default now is "int64" instead of "string"
   snake_case_					    =					{"col_1": "int64", "col_2": "int64", "col_3": "float64"}
   snake_case_					    =					features.copy() if features else default_expected_features
   snake_case_					    =					(
       Features({feature: Value(lowerCAmelCase_							) for feature, dtype in features.items()}							) if features is not None else None
   )
   snake_case_					    =					CsvDatasetReader(lowerCAmelCase_		,						features=lowerCAmelCase_		,						cache_dir=lowerCAmelCase_							).read()
   _check_csv_dataset(lowerCAmelCase_		,						lowerCAmelCase_							)



@pytest.mark.parametrize("split"		,						[None, NamedSplit("train"							), "train", "test"]							)
def 			_lowerCAmelCase						(							lowerCAmelCase_							:Optional[int]		,						lowerCAmelCase_							:Tuple		,						lowerCAmelCase_							:List[Any]							)->Optional[int]:
   '''simple docstring'''






   snake_case_					    =					tmp_path / "cache"
   snake_case_					    =					{"col_1": "int64", "col_2": "int64", "col_3": "float64"}
   snake_case_					    =					CsvDatasetReader(lowerCAmelCase_		,						cache_dir=lowerCAmelCase_		,						split=lowerCAmelCase_							).read()
   _check_csv_dataset(lowerCAmelCase_		,						lowerCAmelCase_							)
   assert dataset.split == split if split else "train"



@pytest.mark.parametrize("path_type"		,						[str, list]							)
def 			_lowerCAmelCase						(							lowerCAmelCase_							:Any		,						lowerCAmelCase_							:Dict		,						lowerCAmelCase_							:List[Any]							)->List[Any]:
   '''simple docstring'''






   if issubclass(lowerCAmelCase_		,						lowerCAmelCase_							):
      snake_case_					    =					csv_path
   elif issubclass(lowerCAmelCase_		,						lowerCAmelCase_							):
      snake_case_					    =					[csv_path]
   snake_case_					    =					tmp_path / "cache"
   snake_case_					    =					{"col_1": "int64", "col_2": "int64", "col_3": "float64"}
   snake_case_					    =					CsvDatasetReader(lowerCAmelCase_		,						cache_dir=lowerCAmelCase_							).read()
   _check_csv_dataset(lowerCAmelCase_		,						lowerCAmelCase_							)



def 			_lowerCAmelCase						(							lowerCAmelCase_							:List[str]		,						lowerCAmelCase_							:Dict		,						lowerCAmelCase_							:List[str]=("train",)							)->Optional[Any]:
   '''simple docstring'''






   assert isinstance(lowerCAmelCase_		,						lowerCAmelCase_							)
   for split in splits:
      snake_case_					    =					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 			_lowerCAmelCase						(							lowerCAmelCase_							:Union[str, Any]		,						lowerCAmelCase_							:Dict		,						lowerCAmelCase_							:List[Any]							)->Any:
   '''simple docstring'''






   snake_case_					    =					tmp_path / "cache"
   snake_case_					    =					{"col_1": "int64", "col_2": "int64", "col_3": "float64"}
   with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
      snake_case_					    =					CsvDatasetReader({"train": csv_path}		,						cache_dir=lowerCAmelCase_		,						keep_in_memory=lowerCAmelCase_							).read()
   _check_csv_datasetdict(lowerCAmelCase_		,						lowerCAmelCase_							)



@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 			_lowerCAmelCase						(							lowerCAmelCase_							:List[Any]		,						lowerCAmelCase_							:Optional[Any]		,						lowerCAmelCase_							:Any							)->str:
   '''simple docstring'''






   snake_case_					    =					tmp_path / "cache"
   # CSV file loses col_1 string dtype information: default now is "int64" instead of "string"
   snake_case_					    =					{"col_1": "int64", "col_2": "int64", "col_3": "float64"}
   snake_case_					    =					features.copy() if features else default_expected_features
   snake_case_					    =					(
       Features({feature: Value(lowerCAmelCase_							) for feature, dtype in features.items()}							) if features is not None else None
   )
   snake_case_					    =					CsvDatasetReader({"train": csv_path}		,						features=lowerCAmelCase_		,						cache_dir=lowerCAmelCase_							).read()
   _check_csv_datasetdict(lowerCAmelCase_		,						lowerCAmelCase_							)



@pytest.mark.parametrize("split"		,						[None, NamedSplit("train"							), "train", "test"]							)
def 			_lowerCAmelCase						(							lowerCAmelCase_							:str		,						lowerCAmelCase_							:Tuple		,						lowerCAmelCase_							:Any							)->str:
   '''simple docstring'''






   if split:
      snake_case_					    =					{split: csv_path}
   else:
      snake_case_					    =					{"train": csv_path, "test": csv_path}
   snake_case_					    =					tmp_path / "cache"
   snake_case_					    =					{"col_1": "int64", "col_2": "int64", "col_3": "float64"}
   snake_case_					    =					CsvDatasetReader(lowerCAmelCase_		,						cache_dir=lowerCAmelCase_							).read()
   _check_csv_datasetdict(lowerCAmelCase_		,						lowerCAmelCase_		,						splits=list(path.keys()							)							)
   assert all(dataset[split].split == split for split in path.keys()							)



def 			_lowerCAmelCase						(							lowerCAmelCase_							:Tuple							)->str:
   '''simple docstring'''






   with open(lowerCAmelCase_		,						encoding="utf-8"							) as csvfile:
      yield from csv.reader(lowerCAmelCase_							)



def 			_lowerCAmelCase						(							lowerCAmelCase_							:Tuple		,						lowerCAmelCase_							:Dict							)->Any:
   '''simple docstring'''






   snake_case_					    =					tmp_path / "cache"
   snake_case_					    =					os.path.join(lowerCAmelCase_		,						"tmp.csv"							)
   snake_case_					    =					CsvDatasetReader({"train": csv_path}		,						cache_dir=lowerCAmelCase_							).read()
   CsvDatasetWriter(dataset["train"]		,						lowerCAmelCase_		,						num_proc=1							).write()

   snake_case_					    =					iter_csv_file(lowerCAmelCase_							)
   snake_case_					    =					iter_csv_file(lowerCAmelCase_							)

   for rowa, rowa in zip(lowerCAmelCase_		,						lowerCAmelCase_							):
      assert rowa == rowa



def 			_lowerCAmelCase						(							lowerCAmelCase_							:str		,						lowerCAmelCase_							:Any							)->Union[str, Any]:
   '''simple docstring'''






   snake_case_					    =					tmp_path / "cache"
   snake_case_					    =					os.path.join(lowerCAmelCase_		,						"tmp.csv"							)
   snake_case_					    =					CsvDatasetReader({"train": csv_path}		,						cache_dir=lowerCAmelCase_							).read()
   CsvDatasetWriter(dataset["train"]		,						lowerCAmelCase_		,						num_proc=2							).write()

   snake_case_					    =					iter_csv_file(lowerCAmelCase_							)
   snake_case_					    =					iter_csv_file(lowerCAmelCase_							)

   for rowa, rowa in zip(lowerCAmelCase_		,						lowerCAmelCase_							):
      assert rowa == rowa



def 			_lowerCAmelCase						(							lowerCAmelCase_							:Any		,						lowerCAmelCase_							:Optional[int]							)->int:
   '''simple docstring'''






   snake_case_					    =					tmp_path / "cache"
   snake_case_					    =					os.path.join(lowerCAmelCase_		,						"tmp.csv"							)
   snake_case_					    =					CsvDatasetReader({"train": csv_path}		,						cache_dir=lowerCAmelCase_							).read()
   with pytest.raises(lowerCAmelCase_							):
      CsvDatasetWriter(dataset["train"]		,						lowerCAmelCase_		,						num_proc=0							)




