
"""simple docstring"""






import math




class      _SCREAMING_SNAKE_CASE   :






			def __init__(   self			,  __A			)     ->	Any:
						lowerCAmelCase_       :Dict     	=    len(snake_case_			)
						lowerCAmelCase_       :Any     	=    [0] * (
						    4 * self.N
						)  # approximate the overall size of segment tree with array N
						self.build(1			,  0			,  self.N - 1			)






			def 					__lowerCAmelCase					(   self			,  __A			)     ->	int:
						return idx * 2






			def 					__lowerCAmelCase					(   self			,  __A			)     ->	Union[str, Any]:
						return idx * 2 + 1






			def 					__lowerCAmelCase					(   self			,  __A			,  __A			,  __A			)     ->	Tuple:  # noqa: E741

						if l == r:
									lowerCAmelCase_       :Any     	=    A[l]
						else:
									lowerCAmelCase_       :str     	=    (l + r) // 2
									self.build(self.left(snake_case_			)			,  snake_case_			,  snake_case_			)
									self.build(self.right(snake_case_			)			,  mid + 1			,  snake_case_			)
									lowerCAmelCase_       :Dict     	=    max(self.st[self.left(snake_case_			)]			,  self.st[self.right(snake_case_			)]			)






			def 					__lowerCAmelCase					(   self			,  __A			,  __A			,  __A			)     ->	List[str]:
						return self.update_recursive(1			,  0			,  self.N - 1			,  a - 1			,  b - 1			,  snake_case_			)






			def 					__lowerCAmelCase					(   self			,  __A			,  __A			,  __A			,  __A			,  __A			,  __A			)     ->	List[str]:  # noqa: E741

						if r < a or l > b:
									return True
						if l == r:
									lowerCAmelCase_       :int     	=    val
									return True
						lowerCAmelCase_       :Tuple     	=    (l + r) // 2
						self.update_recursive(self.left(snake_case_			)			,  snake_case_			,  snake_case_			,  snake_case_			,  snake_case_			,  snake_case_			)
						self.update_recursive(self.right(snake_case_			)			,  mid + 1			,  snake_case_			,  snake_case_			,  snake_case_			,  snake_case_			)
						lowerCAmelCase_       :Tuple     	=    max(self.st[self.left(snake_case_			)]			,  self.st[self.right(snake_case_			)]			)
						return True






			def 					__lowerCAmelCase					(   self			,  __A			,  __A			)     ->	Tuple:
						return self.query_recursive(1			,  0			,  self.N - 1			,  a - 1			,  b - 1			)






			def 					__lowerCAmelCase					(   self			,  __A			,  __A			,  __A			,  __A			,  __A			)     ->	Optional[Any]:  # noqa: E741

						if r < a or l > b:
									return -math.inf
						if l >= a and r <= b:
									return self.st[idx]
						lowerCAmelCase_       :Any     	=    (l + r) // 2
						lowerCAmelCase_       :Optional[Any]     	=    self.query_recursive(self.left(snake_case_			)			,  snake_case_			,  snake_case_			,  snake_case_			,  snake_case_			)
						lowerCAmelCase_       :List[Any]     	=    self.query_recursive(self.right(snake_case_			)			,  mid + 1			,  snake_case_			,  snake_case_			,  snake_case_			)
						return max(snake_case_			,  snake_case_			)






			def 					__lowerCAmelCase					(   self			)     ->	Any:
						lowerCAmelCase_       :int     	=    []
						for i in range(1			,  N + 1			):
									show_list += [self.query(snake_case_			,  snake_case_			)]
						print(snake_case_			)


if __name__ == "__main__":
				__UpperCAmelCase 					=    [1, 2, -4, 7, 3, -5, 6, 11, -20, 9, 14, 15, 5, 2, -8]
				__UpperCAmelCase 					=    15
				__UpperCAmelCase 					=    SegmentTree(A)
				print(segt.query(4, 6))
				print(segt.query(7, 11))
				print(segt.query(7, 12))
				segt.update(1, 3, 1_11)
				print(segt.query(1, 15))
				segt.update(7, 8, 2_35)
				segt.show_data()













"""simple docstring"""




import multiprocessing
import os
from typing import BinaryIO, Optional, Union

from .. import Dataset, Features, NamedSplit, config
from ..formatting import query_table
from ..packaged_modules.csv.csv import Csv
from ..utils import logging
from ..utils.typing import NestedDataStructureLike, PathLike
from .abc import AbstractDatasetReader

class 					_UpperCAmelCase    (  UpperCAmelCase__						):



      '''simple docstring'''

      def __init__(	self   , snake_case_   , snake_case_ = None   , snake_case_ = None   , snake_case_ = None   , snake_case_ = False   , snake_case_ = False   , snake_case_ = None   , **snake_case_   , ):

        """simple docstring"""

        super().__init__(
            snake_case_   , split=snake_case_   , features=snake_case_   , cache_dir=snake_case_   , keep_in_memory=snake_case_   , streaming=snake_case_   , num_proc=snake_case_   , **snake_case_   , )
        A_    :			int									=    path_or_paths if isinstance(snake_case_   , snake_case_    ) else {self.split: path_or_paths}
        A_    :			List[str]									=    Csv(
            cache_dir=snake_case_   , data_files=snake_case_   , features=snake_case_   , **snake_case_   , )

      def    lowerCamelCase_     (	self    ):

        """simple docstring"""

        if self.streaming:
          A_    :			List[str]									=    self.builder.as_streaming_dataset(split=self.split    )
        # Build regular (map-style) dataset
        else:
          A_    :			List[Any]									=    None
          A_    :			Optional[int]									=    None
          A_    :			Optional[int]									=    None
          A_    :			List[str]									=    None

          self.builder.download_and_prepare(
              download_config=snake_case_   , download_mode=snake_case_   , verification_mode=snake_case_   , base_path=snake_case_   , num_proc=self.num_proc   , )
          A_    :			List[Any]									=    self.builder.as_dataset(
              split=self.split   , verification_mode=snake_case_   , in_memory=self.keep_in_memory    )
        return dataset


class 					_UpperCAmelCase    :



      '''simple docstring'''

      def __init__(	self   , snake_case_   , snake_case_   , snake_case_ = None   , snake_case_ = None   , **snake_case_   , ):

        """simple docstring"""

        if num_proc is not None and num_proc <= 0:
          raise ValueError(F"""num_proc {num_proc} must be an integer > 0."""    )

        A_    :			Optional[int]									=    dataset
        A_    :			List[str]									=    path_or_buf
        A_    :			Optional[int]									=    batch_size if batch_size else config.DEFAULT_MAX_BATCH_SIZE
        A_    :			Optional[int]									=    num_proc
        A_    :			Optional[int]									=    'utf-8'
        A_    :			int									=    to_csv_kwargs

      def    lowerCamelCase_     (	self    ):

        """simple docstring"""

        A_    :			Union[str, Any]									=    self.to_csv_kwargs.pop('path_or_buf'   , snake_case_    )
        A_    :			str									=    self.to_csv_kwargs.pop('header'   , snake_case_    )
        A_    :			Optional[Any]									=    self.to_csv_kwargs.pop('index'   , snake_case_    )

        if isinstance(self.path_or_buf   , (str, bytes, os.PathLike)    ):
          with open(self.path_or_buf   , 'wb+'    ) as buffer:
            A_    :			Optional[Any]									=    self._write(file_obj=snake_case_   , header=snake_case_   , index=snake_case_   , **self.to_csv_kwargs    )
        else:
          A_    :			int									=    self._write(file_obj=self.path_or_buf   , header=snake_case_   , index=snake_case_   , **self.to_csv_kwargs    )
        return written

      def    lowerCamelCase_     (	self   , snake_case_    ):

        """simple docstring"""

        A_		,			A_		,			A_		,			A_    :			Union[str, Any]									=    args

        A_    :			Dict									=    query_table(
            table=self.dataset.data   , key=slice(snake_case_   , offset + self.batch_size    )   , indices=self.dataset._indices   , )
        A_    :			List[str]									=    batch.to_pandas().to_csv(
            path_or_buf=snake_case_   , header=header if (offset == 0) else False   , index=snake_case_   , **snake_case_    )
        return csv_str.encode(self.encoding    )

      def    lowerCamelCase_     (	self   , snake_case_   , snake_case_   , snake_case_   , **snake_case_    ):

        """simple docstring"""

        A_    :			Any									=    0

        if self.num_proc is None or self.num_proc == 1:
          for offset in logging.tqdm(
              range(0   , len(self.dataset    )   , self.batch_size    )   , unit='ba'   , disable=not logging.is_progress_bar_enabled()   , desc='Creating CSV from Arrow format'   , ):
            A_    :			Optional[int]									=    self._batch_csv((offset, header, index, to_csv_kwargs)    )
            written += file_obj.write(snake_case_    )

        else:
          A_		,			A_    :			Optional[int]									=    len(self.dataset    ), self.batch_size
          with multiprocessing.Pool(self.num_proc    ) as pool:
            for csv_str in logging.tqdm(
                pool.imap(
                    self._batch_csv   , [(offset, header, index, to_csv_kwargs) for offset in range(0   , snake_case_   , snake_case_    )]   , )   , total=(num_rows // batch_size) + 1 if num_rows % batch_size else num_rows // batch_size   , unit='ba'   , disable=not logging.is_progress_bar_enabled()   , desc='Creating CSV from Arrow format'   , ):
              written += file_obj.write(snake_case_    )

        return written