





from collections.abc import Iterable
from typing import Any

class   lowerCAmelCase				:
 def __init__( self    : Optional[int]     ,	UpperCAmelCase    : int | None = None      )     ->      Union[str, Any]:
     lowerCamelCase__       : int   					=						value
     lowerCamelCase__       : Node | None   					=						None  # Added in order to delete a node easier
     lowerCamelCase__       : Node | None   					=						None
     lowerCamelCase__       : Node | None   					=						None







 def __repr__( self    : List[Any]      )     ->      str:
     from pprint import pformat

     if self.left is None and self.right is None:
         return str(self.value      )
     return pformat({F"""{self.value}""": (self.left, self.right)}     ,	indent=1      )


class   lowerCAmelCase				:
 def __init__( self    : List[Any]     ,	UpperCAmelCase    : Node | None = None      )     ->      List[str]:
     lowerCamelCase__       : Dict   					=						root
 def __str__( self    : List[Any]      )     ->      str:
     return str(self.root      )
 def 	A_      ( self    : Dict     ,	UpperCAmelCase    : Node     ,	UpperCAmelCase    : Node | None      )     ->      None:
     if new_children is not None:  # reset its kids
         lowerCamelCase__       : List[Any]   					=						node.parent
     if node.parent is not None:  # reset its parent
         if self.is_right(UpperCAmelCase      ):  # If it is the right children
             lowerCamelCase__       : Optional[Any]   					=						new_children
         else:
             lowerCamelCase__       : Union[str, Any]   					=						new_children
     else:
         lowerCamelCase__       : int   					=						new_children
 def 	A_      ( self    : Dict     ,	UpperCAmelCase    : Node      )     ->      bool:
     if node.parent and node.parent.right:
         return node == node.parent.right
     return False
 def 	A_      ( self    : Dict      )     ->      bool:
     return self.root is None
 def 	A_      ( self    : List[Any]     ,	UpperCAmelCase    : Optional[Any]      )     ->      None:
     lowerCamelCase__       : List[Any]   					=						Node(UpperCAmelCase      )  # create a new Node
     if self.empty():  # if Tree is empty
         lowerCamelCase__       : List[str]   					=						new_node  # set its root
     else:  # Tree is not empty
         lowerCamelCase__       : Any   					=						self.root  # from root
         if parent_node is None:
             return
         while True:  # While we don't get to a leaf
             if value < parent_node.value:  # We go left
                 if parent_node.left is None:
                     lowerCamelCase__       : Optional[Any]   					=						new_node  # We insert the new node in a leaf
                     break
                 else:
                     lowerCamelCase__       : Union[str, Any]   					=						parent_node.left
             else:
                 if parent_node.right is None:
                     lowerCamelCase__       : str   					=						new_node
                     break
                 else:
                     lowerCamelCase__       : Union[str, Any]   					=						parent_node.right
         lowerCamelCase__       : List[Any]   					=						parent_node
 def 	A_      ( self    : List[Any]     ,	*UpperCAmelCase    : int      )     ->      None:
     for value in values:
         self.__insert(UpperCAmelCase      )
 def 	A_      ( self    : int     ,	UpperCAmelCase    : Optional[Any]      )     ->      Node | None:
     if self.empty():
         raise IndexError('Warning: Tree is empty! please use another.'      )
     else:
         lowerCamelCase__       : Optional[Any]   					=						self.root
         # use lazy evaluation here to avoid NoneType Attribute error
         while node is not None and node.value is not value:
             lowerCamelCase__       : str   					=						node.left if value < node.value else node.right
         return node
 def 	A_      ( self    : Optional[Any]     ,	UpperCAmelCase    : Node | None = None      )     ->      Node | None:
     if node is None:
         if self.root is None:
             return None
         lowerCamelCase__       : Any   					=						self.root

     if not self.empty():
         while node.right is not None:
             lowerCamelCase__       : Optional[Any]   					=						node.right
     return node
 def 	A_      ( self    : Optional[Any]     ,	UpperCAmelCase    : Node | None = None      )     ->      Node | None:
     if node is None:
         lowerCamelCase__       : Tuple   					=						self.root
     if self.root is None:
         return None
     if not self.empty():
         lowerCamelCase__       : Tuple   					=						self.root
         while node.left is not None:
             lowerCamelCase__       : Optional[int]   					=						node.left
     return node
 def 	A_      ( self    : int     ,	UpperCAmelCase    : int      )     ->      None:
     lowerCamelCase__       : Tuple   					=						self.search(UpperCAmelCase      )  # Look for the node with that label
     if node is not None:
         if node.left is None and node.right is None:  # If it has no children
             self.__reassign_nodes(UpperCAmelCase     ,	UpperCAmelCase      )
         elif node.left is None:  # Has only right children
             self.__reassign_nodes(UpperCAmelCase     ,	node.right      )
         elif node.right is None:  # Has only left children
             self.__reassign_nodes(UpperCAmelCase     ,	node.left      )
         else:
             lowerCamelCase__       : Union[str, Any]   					=						self.get_max(
                 node.left      )  # Gets the max value of the left branch
             self.remove(tmp_node.value      )  # type: ignore
             lowerCamelCase__       : Union[str, Any]   					=						(
                 tmp_node.value  # type: ignore
             )  # Assigns the value to the node to delete and keep tree structure
 def 	A_      ( self    : Dict     ,	UpperCAmelCase    : Node | None      )     ->      Iterable:
     if node is not None:
         yield node  # Preorder Traversal
         yield from self.preorder_traverse(node.left      )
         yield from self.preorder_traverse(node.right      )
 def 	A_      ( self    : Union[str, Any]     ,	UpperCAmelCase    : List[str]=None      )     ->      Any:
     if traversal_function is None:
         return self.preorder_traverse(self.root      )
     else:
         return traversal_function(self.root      )
 def 	A_      ( self    : Optional[Any]     ,	UpperCAmelCase    : list     ,	UpperCAmelCase    : Node | None      )     ->      None:
     if node:
         self.inorder(UpperCAmelCase     ,	node.left      )
         arr.append(node.value      )
         self.inorder(UpperCAmelCase     ,	node.right      )







 def 	A_      ( self    : Optional[Any]     ,	UpperCAmelCase    : int     ,	UpperCAmelCase    : Node      )     ->      int:
     lowerCamelCase__       : list[int]   					=						[]
     self.inorder(UpperCAmelCase     ,	UpperCAmelCase      )  # append all values to list using inorder traversal
     return arr[k - 1]


def 			SCREAMING_SNAKE_CASE (			_UpperCAmelCase					)     ->	list[Node]:
    lowerCamelCase__       : Dict   					=						[]
    if curr_node is not None:
        lowerCamelCase__       : List[str]   					=						postorder(curr_node.left					) + postorder(curr_node.right					) + [curr_node]
    return node_list


def 			SCREAMING_SNAKE_CASE (			)     ->	None:
    lowerCamelCase__       : Optional[Any]   					=						(8, 3, 6, 1, 10, 14, 13, 4, 7)
    lowerCamelCase__       : Tuple   					=						BinarySearchTree()
    for i in testlist:
        t.insert(_UpperCAmelCase					)

    # Prints all the elements of the list in order traversal
    print(_UpperCAmelCase					)

    if t.search(6					) is not None:
        print('The value 6 exists'					)
    else:
        print('The value 6 doesn\'t exist'					)

    if t.search(-1					) is not None:
        print('The value -1 exists'					)
    else:
        print('The value -1 doesn\'t exist'					)

    if not t.empty():
        print('Max Value: '		,      t.get_max().value					)  # type: ignore
        print('Min Value: '		,      t.get_min().value					)  # type: ignore

    for i in testlist:
        t.remove(_UpperCAmelCase					)
        print(_UpperCAmelCase					)


if __name__ == "__main__":
    import doctest

    doctest.testmod(verbose=True)












import itertools
from dataclasses import dataclass
from typing import List, Optional

import pyarrow as pa
import pyarrow.parquet as pq

import datasets
from datasets.table import table_cast


_UpperCAmelCase							:			Optional[Any]        =							datasets.utils.logging.get_logger(__name__)

@dataclass
class   lowerCAmelCase				(   datasets.BuilderConfig     ):
 UpperCAmelCase__						=						1_00_00
 UpperCAmelCase__						=						None
 UpperCAmelCase__						=						None


class   lowerCAmelCase				(   datasets.ArrowBasedBuilder     ):
 UpperCAmelCase__						=						ParquetConfig
 def 	A_      ( self    : int      )     ->      Optional[int]:
     return datasets.DatasetInfo(features=self.config.features      )
 def 	A_      ( self    : int     ,	UpperCAmelCase    : str      )     ->      Any:
     if not self.config.data_files:
         raise ValueError(F"""At least one data file must be specified, but got data_files={self.config.data_files}"""      )
     lowerCamelCase__       : List[Any]   					=						dl_manager.download_and_extract(self.config.data_files      )
     if isinstance(UpperCAmelCase     ,	(str, list, tuple)      ):
         lowerCamelCase__       : int   					=						data_files
         if isinstance(UpperCAmelCase     ,	UpperCAmelCase      ):
             lowerCamelCase__       : int   					=						[files]
         # Use `dl_manager.iter_files` to skip hidden files in an extracted archive
         lowerCamelCase__       : str   					=						[dl_manager.iter_files(UpperCAmelCase      ) for file in files]
         return [datasets.SplitGenerator(name=datasets.Split.TRAIN     ,	gen_kwargs={'files': files}      )]
     lowerCamelCase__       : Optional[Any]   					=						[]
     for split_name, files in data_files.items():
         if isinstance(UpperCAmelCase     ,	UpperCAmelCase      ):
             lowerCamelCase__       : Optional[Any]   					=						[files]
         # Use `dl_manager.iter_files` to skip hidden files in an extracted archive
         lowerCamelCase__       : Dict   					=						[dl_manager.iter_files(UpperCAmelCase      ) for file in files]
         # Infer features is they are stoed in the arrow schema
         if self.info.features is None:
             for file in itertools.chain.from_iterable(UpperCAmelCase      ):
                 with open(UpperCAmelCase     ,	'rb'      ) as f:
                     lowerCamelCase__       : Optional[Any]   					=						datasets.Features.from_arrow_schema(pq.read_schema(UpperCAmelCase      )      )
                 break
         splits.append(datasets.SplitGenerator(name=UpperCAmelCase     ,	gen_kwargs={'files': files}      )      )
     return splits
 def 	A_      ( self    : Optional[int]     ,	UpperCAmelCase    : pa.Table      )     ->      pa.Table:
     if self.info.features is not None:
         # more expensive cast to support nested features with keys in a different order
         # allows str <-> int/float or str to Audio for example
         lowerCamelCase__       : Any   					=						table_cast(UpperCAmelCase     ,	self.info.features.arrow_schema      )
     return pa_table







 def 	A_      ( self    : Any     ,	UpperCAmelCase    : Tuple      )     ->      List[str]:
     lowerCamelCase__       : Optional[Any]   					=						self.info.features.arrow_schema if self.info.features is not None else None
     if self.info.features is not None and self.config.columns is not None:
         if sorted(field.name for field in schema      ) != sorted(self.config.columns      ):
             raise ValueError(
                 F"""Tried to load parquet data with columns '{self.config.columns}' with mismatching features '{self.info.features}'"""      )
     for file_idx, file in enumerate(itertools.chain.from_iterable(UpperCAmelCase      )      ):
         with open(UpperCAmelCase     ,	'rb'      ) as f:
             lowerCamelCase__       : List[Any]   					=						pq.ParquetFile(UpperCAmelCase      )
             try:
                 for batch_idx, record_batch in enumerate(
                     parquet_file.iter_batches(batch_size=self.config.batch_size     ,	columns=self.config.columns      )      ):
                     lowerCamelCase__       : Tuple   					=						pa.Table.from_batches([record_batch]      )
                     # Uncomment for debugging (will print the Arrow table size and elements)
                     # logger.warning(f"pa_table: {pa_table} num rows: {pa_table.num_rows}")
                     # logger.warning('\n'.join(str(pa_table.slice(i, 1).to_pydict()) for i in range(pa_table.num_rows)))
                     yield F"""{file_idx}_{batch_idx}""", self._cast_table(UpperCAmelCase      )
             except ValueError as e:
                 logger.error(F"""Failed to read file '{file}' with error {type(UpperCAmelCase      )}: {e}"""      )
                 raise





