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

import fsspec

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




class 				A__ (			_lowerCamelCase):

		def __init__(   self ,	_SCREAMING_SNAKE_CASE ,	_SCREAMING_SNAKE_CASE = None ,	_SCREAMING_SNAKE_CASE = None ,	_SCREAMING_SNAKE_CASE = None ,	_SCREAMING_SNAKE_CASE = False ,	_SCREAMING_SNAKE_CASE = False ,	_SCREAMING_SNAKE_CASE = None ,	_SCREAMING_SNAKE_CASE = None ,	**_SCREAMING_SNAKE_CASE ,	):
			super().__init__(
			    A__ ,	split=A__ ,	features=A__ ,	cache_dir=A__ ,	keep_in_memory=A__ ,	streaming=A__ ,	num_proc=A__ ,	**A__ ,	)
			__lowerCAmelCase    :		Tuple		    =   field
			__lowerCAmelCase    :		Optional[int]		    =   path_or_paths if isinstance(A__ ,	A__				) else {self.split: path_or_paths}
			__lowerCAmelCase    :		List[Any]		    =   Json(
			    cache_dir=A__ ,	data_files=A__ ,	features=A__ ,	field=A__ ,	**A__ ,	)







		def 							__lowerCamelCase							(   self				):
			# Build iterable dataset
			if self.streaming:
				__lowerCAmelCase    :		Dict		    =   self.builder.as_streaming_dataset(split=self.split				)
			# Build regular (map-style) dataset
			else:
				__lowerCAmelCase    :		str		    =   None
				__lowerCAmelCase    :		str		    =   None
				__lowerCAmelCase    :		Union[str, Any]		    =   None
				__lowerCAmelCase    :		Any		    =   None

				self.builder.download_and_prepare(
				    download_config=A__ ,	download_mode=A__ ,	verification_mode=A__ ,	base_path=A__ ,	num_proc=self.num_proc ,	)
				__lowerCAmelCase    :		Union[str, Any]		    =   self.builder.as_dataset(
				    split=self.split ,	verification_mode=A__ ,	in_memory=self.keep_in_memory				)
			return dataset




class 				A__ :

		def __init__(   self ,	_SCREAMING_SNAKE_CASE ,	_SCREAMING_SNAKE_CASE ,	_SCREAMING_SNAKE_CASE = None ,	_SCREAMING_SNAKE_CASE = None ,	**_SCREAMING_SNAKE_CASE ,	):
			if num_proc is not None and num_proc <= 0:
				raise ValueError(f"num_proc {num_proc} must be an integer > 0."				)

			__lowerCAmelCase    :		int		    =   dataset
			__lowerCAmelCase    :		Any		    =   path_or_buf
			__lowerCAmelCase    :		Union[str, Any]		    =   batch_size if batch_size else config.DEFAULT_MAX_BATCH_SIZE
			__lowerCAmelCase    :		str		    =   num_proc
			__lowerCAmelCase    :		Union[str, Any]		    =   """utf-8"""
			__lowerCAmelCase    :		List[Any]		    =   to_json_kwargs

		def 							__lowerCamelCase							(   self				):
			__lowerCAmelCase    :		List[Any]		    =   self.to_json_kwargs.pop('path_or_buf' ,	A__				)
			__lowerCAmelCase    :		List[Any]		    =   self.to_json_kwargs.pop('orient' ,	'records'				)
			__lowerCAmelCase    :		Optional[Any]		    =   self.to_json_kwargs.pop('lines' ,	True if orient == 'records' else False				)
			__lowerCAmelCase    :		Optional[int]		    =   self.to_json_kwargs.pop('index' ,	False if orient in ['split', 'table'] else True				)
			__lowerCAmelCase    :		int		    =   self.to_json_kwargs.pop('compression' ,	A__				)

			if compression not in [None, "infer", "gzip", "bz2", "xz"]:
				raise NotImplementedError(f"`datasets` currently does not support {compression} compression"				)

			if isinstance(self.path_or_buf ,	(str, bytes, os.PathLike)				):
				with fsspec.open(self.path_or_buf ,	'wb' ,	compression=A__				) as buffer:
					__lowerCAmelCase    :		Optional[Any]		    =   self._write(file_obj=A__ ,	orient=A__ ,	lines=A__ ,	index=A__ ,	**self.to_json_kwargs				)
			else:
				if compression:
					raise NotImplementedError(
					    f"The compression parameter is not supported when writing to a buffer, but compression={compression}"
					    ' was passed. Please provide a local path instead.'				)
				__lowerCAmelCase    :		int		    =   self._write(
				    file_obj=self.path_or_buf ,	orient=A__ ,	lines=A__ ,	index=A__ ,	**self.to_json_kwargs				)
			return written

		def 							__lowerCamelCase							(   self ,	_SCREAMING_SNAKE_CASE				):
			__lowerCAmelCase    :		int		    =   args

			__lowerCAmelCase    :		Union[str, Any]		    =   query_table(
			    table=self.dataset.data ,	key=slice(A__ ,	offset + self.batch_size				) ,	indices=self.dataset._indices ,	)
			__lowerCAmelCase    :		List[Any]		    =   batch.to_pandas().to_json(
			    path_or_buf=A__ ,	orient=A__ ,	lines=A__ ,	index=A__ ,	**A__				)
			if not json_str.endswith('\n'				):
				json_str += "\n"
			return json_str.encode(self.encoding				)







		def 							__lowerCamelCase							(   self ,	_SCREAMING_SNAKE_CASE ,	_SCREAMING_SNAKE_CASE ,	_SCREAMING_SNAKE_CASE ,	_SCREAMING_SNAKE_CASE ,	**_SCREAMING_SNAKE_CASE ,	):
			__lowerCAmelCase    :		List[str]		    =   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 json from Arrow format' ,	):
					__lowerCAmelCase    :		Optional[int]		    =   self._batch_json((offset, orient, lines, index, to_json_kwargs)				)
					written += file_obj.write(A__				)
			else:
				__lowerCAmelCase    :		Optional[int]		    =   len(self.dataset				), self.batch_size
				with multiprocessing.Pool(self.num_proc				) as pool:
					for json_str in logging.tqdm(
					    pool.imap(
					        self._batch_json ,	[(offset, orient, lines, index, to_json_kwargs) for offset in range(0 ,	A__ ,	A__				)] ,	) ,	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 json from Arrow format' ,	):
						written += file_obj.write(A__				)

			return written

"""simple docstring"""







def 					__lowerCAmelCase       (_UpperCamelCase ,						_UpperCamelCase ,						_UpperCamelCase	):
	__lowerCAmelCase    :		List[str]		    =   len(_UpperCamelCase	)
	__lowerCAmelCase    :		Tuple		    =   [[0] * n for i in range(_UpperCamelCase	)]
	for i in range(_UpperCamelCase	):
		__lowerCAmelCase    :		Any		    =   y_points[i]

	for i in range(2 ,						_UpperCamelCase	):
		for j in range(_UpperCamelCase ,						_UpperCamelCase	):
			__lowerCAmelCase    :		int		    =   (
			    (xa - x_points[j - i + 1]) * q[j][i - 1]
			    - (xa - x_points[j]) * q[j - 1][i - 1]
			) / (x_points[j] - x_points[j - i + 1])

	return [q[n - 1][n - 1], q]


if __name__ == "__main__":
							import doctest

							doctest.testmod()