
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 					lowercase__(							UpperCAmelCase				):



	"""simple docstring"""




	def __init__(			self    :     List[str]			,				SCREAMING_SNAKE_CASE_    :     NestedDataStructureLike[PathLike]			,				SCREAMING_SNAKE_CASE_    :     Optional[NamedSplit] = None			,				SCREAMING_SNAKE_CASE_    :     Optional[Features] = None			,				SCREAMING_SNAKE_CASE_    :     str = None			,				SCREAMING_SNAKE_CASE_    :     bool = False			,				SCREAMING_SNAKE_CASE_    :     bool = False			,				SCREAMING_SNAKE_CASE_    :     Optional[str] = None			,				SCREAMING_SNAKE_CASE_    :     Optional[int] = None			,				**SCREAMING_SNAKE_CASE_    :     int			,				)			->	Dict:
					super().__init__(
					    SCREAMING_SNAKE_CASE_			,				split=SCREAMING_SNAKE_CASE_			,				features=SCREAMING_SNAKE_CASE_			,				cache_dir=SCREAMING_SNAKE_CASE_			,				keep_in_memory=SCREAMING_SNAKE_CASE_			,				streaming=SCREAMING_SNAKE_CASE_			,				num_proc=SCREAMING_SNAKE_CASE_			,				**SCREAMING_SNAKE_CASE_			,				)
					lowercase_	    =   field
					lowercase_	    =   path_or_paths if isinstance(SCREAMING_SNAKE_CASE_			,				SCREAMING_SNAKE_CASE_			) else {self.split: path_or_paths}
					lowercase_	    =   Json(
					    cache_dir=SCREAMING_SNAKE_CASE_			,				data_files=SCREAMING_SNAKE_CASE_			,				features=SCREAMING_SNAKE_CASE_			,				field=SCREAMING_SNAKE_CASE_			,				**SCREAMING_SNAKE_CASE_			,				)




	def 		_lowercase    (			self    :     Dict			)			->	Optional[int]:
					# Build iterable dataset
					if self.streaming:
									lowercase_	    =   self.builder.as_streaming_dataset(split=self.split			)
					# Build regular (map-style) dataset
					else:
									lowercase_	    =   None
									lowercase_	    =   None
									lowercase_	    =   None
									lowercase_	    =   None

									self.builder.download_and_prepare(
									    download_config=SCREAMING_SNAKE_CASE_			,				download_mode=SCREAMING_SNAKE_CASE_			,				verification_mode=SCREAMING_SNAKE_CASE_			,				base_path=SCREAMING_SNAKE_CASE_			,				num_proc=self.num_proc			,				)
									lowercase_	    =   self.builder.as_dataset(
									    split=self.split			,				verification_mode=SCREAMING_SNAKE_CASE_			,				in_memory=self.keep_in_memory			)
					return dataset

class 					lowercase__:



	"""simple docstring"""




	def __init__(			self    :     Union[str, Any]			,				SCREAMING_SNAKE_CASE_    :     Dataset			,				SCREAMING_SNAKE_CASE_    :     Union[PathLike, BinaryIO]			,				SCREAMING_SNAKE_CASE_    :     Optional[int] = None			,				SCREAMING_SNAKE_CASE_    :     Optional[int] = None			,				**SCREAMING_SNAKE_CASE_    :     List[str]			,				)			->	int:
					if num_proc is not None and num_proc <= 0:
									raise ValueError(f'''num_proc {num_proc} must be an integer > 0.'''			)

					lowercase_	    =   dataset
					lowercase_	    =   path_or_buf
					lowercase_	    =   batch_size if batch_size else config.DEFAULT_MAX_BATCH_SIZE
					lowercase_	    =   num_proc
					lowercase_	    =   '''utf-8'''
					lowercase_	    =   to_json_kwargs
	def 		_lowercase    (			self    :     List[Any]			)			->	int:
					lowercase_	    =   self.to_json_kwargs.pop('''path_or_buf'''			,				SCREAMING_SNAKE_CASE_			)
					lowercase_	    =   self.to_json_kwargs.pop('''orient'''			,				'''records'''			)
					lowercase_	    =   self.to_json_kwargs.pop('''lines'''			,				True if orient == '''records''' else False			)
					lowercase_	    =   self.to_json_kwargs.pop('''index'''			,				False if orient in ['''split''', '''table'''] else True			)
					lowercase_	    =   self.to_json_kwargs.pop('''compression'''			,				SCREAMING_SNAKE_CASE_			)

					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=SCREAMING_SNAKE_CASE_			) as buffer:
													lowercase_	    =   self._write(file_obj=SCREAMING_SNAKE_CASE_			,				orient=SCREAMING_SNAKE_CASE_			,				lines=SCREAMING_SNAKE_CASE_			,				index=SCREAMING_SNAKE_CASE_			,				**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.'''			)
									lowercase_	    =   self._write(
									    file_obj=self.path_or_buf			,				orient=SCREAMING_SNAKE_CASE_			,				lines=SCREAMING_SNAKE_CASE_			,				index=SCREAMING_SNAKE_CASE_			,				**self.to_json_kwargs			)
					return written
	def 		_lowercase    (			self    :     Dict			,				SCREAMING_SNAKE_CASE_    :     Optional[Any]			)			->	List[Any]:
					lowercase_    ,      lowercase_    ,      lowercase_    ,      lowercase_    ,      lowercase_	    =   args

					lowercase_	    =   query_table(
					    table=self.dataset.data			,				key=slice(SCREAMING_SNAKE_CASE_			,				offset + self.batch_size			)			,				indices=self.dataset._indices			,				)
					lowercase_	    =   batch.to_pandas().to_json(
					    path_or_buf=SCREAMING_SNAKE_CASE_			,				orient=SCREAMING_SNAKE_CASE_			,				lines=SCREAMING_SNAKE_CASE_			,				index=SCREAMING_SNAKE_CASE_			,				**SCREAMING_SNAKE_CASE_			)
					if not json_str.endswith('''\n'''			):
									json_str += "\n"
					return json_str.encode(self.encoding			)




	def 		_lowercase    (			self    :     List[Any]			,				SCREAMING_SNAKE_CASE_    :     BinaryIO			,				SCREAMING_SNAKE_CASE_    :     List[str]			,				SCREAMING_SNAKE_CASE_    :     List[Any]			,				SCREAMING_SNAKE_CASE_    :     str			,				**SCREAMING_SNAKE_CASE_    :     str			,				)			->	int:
					lowercase_	    =   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'''			,				):
													lowercase_	    =   self._batch_json((offset, orient, lines, index, to_json_kwargs)			)
													written += file_obj.write(SCREAMING_SNAKE_CASE_			)
					else:
									lowercase_    ,      lowercase_	    =   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			,				SCREAMING_SNAKE_CASE_			,				SCREAMING_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 json from Arrow format'''			,				):
																	written += file_obj.write(SCREAMING_SNAKE_CASE_			)

					return written






import os

# Precomputes a list of the 100 first triangular numbers
__a         =   [int(0.5 * n * (n + 1)) for n in range(1, 1_0_1)]




def 							a		(				):


				'''simple docstring'''
				lowercase_	    =   os.path.dirname(os.path.realpath(snake_case__   )   )
				lowercase_	    =   os.path.join(snake_case__		,  '''words.txt'''   )

				lowercase_	    =   ''''''
				with open(snake_case__   ) as f:
								lowercase_	    =   f.readline()

				lowercase_	    =   [word.strip('''"'''   ) for word in words.strip('''\r\n'''   ).split(''','''   )]
				lowercase_	    =   [
				    word
				    for word in [sum(ord(snake_case__   ) - 64 for x in word   ) for word in words]
				    if word in TRIANGULAR_NUMBERS
				]
				return len(snake_case__   )


if __name__ == "__main__":
						print(solution())




