





'''simple docstring'''




import os
from typing import BinaryIO, Optional, Union

import numpy as np
import pyarrow.parquet as pq

from .. import Audio, Dataset, Features, Image, NamedSplit, Value, config
from ..features.features import FeatureType, _visit
from ..formatting import query_table
from ..packaged_modules import _PACKAGED_DATASETS_MODULES
from ..packaged_modules.parquet.parquet import Parquet
from ..utils import logging
from ..utils.typing import NestedDataStructureLike, PathLike
from .abc import AbstractDatasetReader
def       UpperCAmelCase_				(   __lowercase				: Tuple			)						->			List[str]:


     '''simple docstring'''



     _UpperCAmelCase					=  np.inf

     def set_batch_size(__lowercase				: Tuple			) -> None:
          nonlocal batch_size
          if isinstance(_a     ,	_a			):
               _UpperCAmelCase					=  min(_a     ,	config.PARQUET_ROW_GROUP_SIZE_FOR_IMAGE_DATASETS			)
          elif isinstance(_a     ,	_a			):
               _UpperCAmelCase					=  min(_a     ,	config.PARQUET_ROW_GROUP_SIZE_FOR_AUDIO_DATASETS			)
          elif isinstance(_a     ,	_a			) and feature.dtype == "binary":
               _UpperCAmelCase					=  min(_a     ,	config.PARQUET_ROW_GROUP_SIZE_FOR_BINARY_DATASETS			)

     _visit(_a     ,	_a			)

     return None if batch_size is np.inf else batch_size







class     A_      (    __A     ):




 def __init__(   self			:       Union[str, Any]      ,     snake_case_			:       NestedDataStructureLike[PathLike]      ,     snake_case_			:       Optional[NamedSplit] = None      ,     snake_case_			:       Optional[Features] = None      ,     snake_case_			:       str = None      ,     snake_case_			:       bool = False      ,     snake_case_			:       bool = False      ,     snake_case_			:       Optional[int] = None      ,     **snake_case_			:       str      ,     ):
      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_      ,     )
      _UpperCAmelCase					=  path_or_paths if isinstance(snake_case_      ,     snake_case_       ) else {self.split: path_or_paths}
      _UpperCAmelCase					=  _PACKAGED_DATASETS_MODULES["parquet"][1]
      _UpperCAmelCase					=  Parquet(
          cache_dir=snake_case_      ,     data_files=snake_case_      ,     features=snake_case_      ,     hash=snake_case_      ,     **snake_case_      ,     )




 def 	lowercase      (   self			:       int       ):

      if self.streaming:
           _UpperCAmelCase					=  self.builder.as_streaming_dataset(split=self.split       )
      # Build regular (map-style) dataset
      else:
           _UpperCAmelCase					=  None
           _UpperCAmelCase					=  None
           _UpperCAmelCase					=  None
           _UpperCAmelCase					=  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      ,     )
           _UpperCAmelCase					=  self.builder.as_dataset(
               split=self.split      ,     verification_mode=snake_case_      ,     in_memory=self.keep_in_memory       )
      return dataset







class     A_      :




 def __init__(   self			:       Union[str, Any]      ,     snake_case_			:       Dataset      ,     snake_case_			:       Union[PathLike, BinaryIO]      ,     snake_case_			:       Optional[int] = None      ,     **snake_case_			:       Optional[Any]      ,     ):
      _UpperCAmelCase					=  dataset
      _UpperCAmelCase					=  path_or_buf
      _UpperCAmelCase					=  batch_size or get_writer_batch_size(dataset.features       )
      _UpperCAmelCase					=  parquet_writer_kwargs




 def 	lowercase      (   self			:       Optional[int]       ):
      _UpperCAmelCase					=  self.batch_size if self.batch_size else config.DEFAULT_MAX_BATCH_SIZE

      if isinstance(self.path_or_buf      ,     (str, bytes, os.PathLike)       ):
           with open(self.path_or_buf      ,     "wb+"       ) as buffer:
                _UpperCAmelCase					=  self._write(file_obj=snake_case_      ,     batch_size=snake_case_      ,     **self.parquet_writer_kwargs       )
      else:
           _UpperCAmelCase					=  self._write(file_obj=self.path_or_buf      ,     batch_size=snake_case_      ,     **self.parquet_writer_kwargs       )
      return written




 def 	lowercase      (   self			:       Optional[Any]      ,     snake_case_			:       BinaryIO      ,     snake_case_			:       int      ,     **snake_case_			:       str       ):
      _UpperCAmelCase					=  0
      _UpperCAmelCase					=  parquet_writer_kwargs.pop("path_or_buf"      ,     snake_case_       )
      _UpperCAmelCase					=  self.dataset.features.arrow_schema

      _UpperCAmelCase					=  pq.ParquetWriter(snake_case_      ,     schema=snake_case_      ,     **snake_case_       )

      for offset in logging.tqdm(
          range(0      ,     len(self.dataset       )      ,     snake_case_       )      ,     unit="ba"      ,     disable=not logging.is_progress_bar_enabled()      ,     desc="Creating parquet from Arrow format"      ,     ):
           _UpperCAmelCase					=  query_table(
               table=self.dataset._data      ,     key=slice(snake_case_      ,     offset + batch_size       )      ,     indices=self.dataset._indices if self.dataset._indices is not None else None      ,     )
           writer.write_table(snake_case_       )
           written += batch.nbytes
      writer.close()
      return written







from __future__ import annotations

import math






class _UpperCamelCase				:
			'''simple docstring'''







			def __init__(      self				:			Dict   ,   a				:			int						)				->							None:

				"""simple docstring"""

				SCREAMING_SNAKE_CASE :   Dict					  =							size
				# approximate the overall size of segment tree with given value
				SCREAMING_SNAKE_CASE :   Any					  =							[0 for i in range(0   ,   4 * size						)]
				# create array to store lazy update
				SCREAMING_SNAKE_CASE :   Union[str, Any]					  =							[0 for i in range(0   ,   4 * size						)]
				SCREAMING_SNAKE_CASE :   Any					  =							[0 for i in range(0   ,   4 * size						)]  # flag for lazy update
			def 				__UpperCamelCase			(      self				:			Tuple   ,   a				:			int						)				->							int:

				"""simple docstring"""

				return idx * 2
			def 				__UpperCamelCase			(      self				:			str   ,   a				:			int						)				->							int:

				"""simple docstring"""

				return idx * 2 + 1
			def 				__UpperCamelCase			(      self				:			int   ,   a				:			int   ,   a				:			int   ,   a				:			int   ,   a				:			list[int]						)				->							None:

				"""simple docstring"""

				if left_element == right_element:
					SCREAMING_SNAKE_CASE :   int					  =							a[left_element - 1]
				else:
					SCREAMING_SNAKE_CASE :   Optional[int]					  =							(left_element + right_element) // 2
					self.build(self.left(a						)   ,   a   ,   a   ,   a						)
					self.build(self.right(a						)   ,   mid + 1   ,   a   ,   a						)
					SCREAMING_SNAKE_CASE :   List[Any]					  =							max(
					    self.segment_tree[self.left(a						)]   ,   self.segment_tree[self.right(a						)]						)
			def 				__UpperCamelCase			(      self				:			Optional[Any]   ,   a				:			int   ,   a				:			int   ,   a				:			int   ,   a				:			int   ,   a				:			int   ,   a				:			int						)				->							bool:

				"""simple docstring"""

				if self.flag[idx] is True:
					SCREAMING_SNAKE_CASE :   Any					  =							self.lazy[idx]
					SCREAMING_SNAKE_CASE :   List[str]					  =							False
					if left_element != right_element:
						SCREAMING_SNAKE_CASE :   Optional[Any]					  =							self.lazy[idx]
						SCREAMING_SNAKE_CASE :   int					  =							self.lazy[idx]
						SCREAMING_SNAKE_CASE :   Any					  =							True
						SCREAMING_SNAKE_CASE :   List[Any]					  =							True

				if right_element < a or left_element > b:
					return True
				if left_element >= a and right_element <= b:
					SCREAMING_SNAKE_CASE :   Optional[Any]					  =							val
					if left_element != right_element:
						SCREAMING_SNAKE_CASE :   str					  =							val
						SCREAMING_SNAKE_CASE :   str					  =							val
						SCREAMING_SNAKE_CASE :   Tuple					  =							True
						SCREAMING_SNAKE_CASE :   Optional[Any]					  =							True
					return True
				SCREAMING_SNAKE_CASE :   int					  =							(left_element + right_element) // 2
				self.update(self.left(a						)   ,   a   ,   a   ,   a   ,   a   ,   a						)
				self.update(self.right(a						)   ,   mid + 1   ,   a   ,   a   ,   a   ,   a						)
				SCREAMING_SNAKE_CASE :   Optional[int]					  =							max(
				    self.segment_tree[self.left(a						)]   ,   self.segment_tree[self.right(a						)]						)
				return True
			def 				__UpperCamelCase			(      self				:			Dict   ,   a				:			int   ,   a				:			int   ,   a				:			int   ,   a				:			int   ,   a				:			int						)				->							int | float:

				"""simple docstring"""

				if self.flag[idx] is True:
					SCREAMING_SNAKE_CASE :   int					  =							self.lazy[idx]
					SCREAMING_SNAKE_CASE :   List[Any]					  =							False
					if left_element != right_element:
						SCREAMING_SNAKE_CASE :   Optional[Any]					  =							self.lazy[idx]
						SCREAMING_SNAKE_CASE :   Optional[Any]					  =							self.lazy[idx]
						SCREAMING_SNAKE_CASE :   Optional[Any]					  =							True
						SCREAMING_SNAKE_CASE :   Union[str, Any]					  =							True
				if right_element < a or left_element > b:
					return -math.inf
				if left_element >= a and right_element <= b:
					return self.segment_tree[idx]
				SCREAMING_SNAKE_CASE :   Dict					  =							(left_element + right_element) // 2
				SCREAMING_SNAKE_CASE :   Tuple					  =							self.query(self.left(a						)   ,   a   ,   a   ,   a   ,   a						)
				SCREAMING_SNAKE_CASE :   Tuple					  =							self.query(self.right(a						)   ,   mid + 1   ,   a   ,   a   ,   a						)
				return max(a   ,   a						)






			def __str__(      self				:			str						)				->							str:

				"""simple docstring"""

				return str([self.query(1   ,   1   ,   self.size   ,   a   ,   a						) for i in range(1   ,   self.size + 1						)]						)


if __name__ == "__main__":
			a_      =     [1, 2, -4, 7, 3, -5, 6, 11, -20, 9, 14, 15, 5, 2, -8]
			a_      =     15
			a_      =     SegmentTree(size)
			segt.build(1, 1, size, A)
			print(segt.query(1, 1, size, 4, 6))
			print(segt.query(1, 1, size, 7, 11))
			print(segt.query(1, 1, size, 7, 12))
			segt.update(1, 1, size, 1, 3, 111)
			print(segt.query(1, 1, size, 1, 15))
			segt.update(1, 1, size, 7, 8, 235)
			print(segt)