
'''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 				lowerCAmelCase__     (						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       ,							):


											"""simple docstring"""





											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_			:  int									= path_or_paths if isinstance(__SCREAMING_SNAKE_CASE       ,							__SCREAMING_SNAKE_CASE	) else {self.split: path_or_paths}
											lowercase_			:  List[Any]									= Csv(
											    cache_dir=__SCREAMING_SNAKE_CASE       ,							data_files=__SCREAMING_SNAKE_CASE       ,							features=__SCREAMING_SNAKE_CASE       ,							**__SCREAMING_SNAKE_CASE       ,							)






					def 			_snake_case					(     self	):


											"""simple docstring"""





											if self.streaming:
																	lowercase_			:  List[str]									= self.builder.as_streaming_dataset(split=self.split	)
											# Build regular (map-style) dataset
											else:
																	lowercase_			:  Any									= None
																	lowercase_			:  Optional[Any]									= None
																	lowercase_			:  str									= None
																	lowercase_			:  Optional[int]									= 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_			:  Tuple									= self.builder.as_dataset(
																	    split=self.split       ,							verification_mode=__SCREAMING_SNAKE_CASE       ,							in_memory=self.keep_in_memory	)
											return dataset







class 				lowerCAmelCase__     :






					def __init__(     self       ,							__SCREAMING_SNAKE_CASE       ,							__SCREAMING_SNAKE_CASE       ,							__SCREAMING_SNAKE_CASE = None       ,							__SCREAMING_SNAKE_CASE = None       ,							**__SCREAMING_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.'''	)

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






					def 			_snake_case					(     self	):


											"""simple docstring"""





											lowercase_			:  List[str]									= self.to_csv_kwargs.pop('''path_or_buf'''       ,							__SCREAMING_SNAKE_CASE	)
											lowercase_			:  Optional[Any]									= self.to_csv_kwargs.pop('''header'''       ,							__SCREAMING_SNAKE_CASE	)
											lowercase_			:  Dict									= self.to_csv_kwargs.pop('''index'''       ,							__SCREAMING_SNAKE_CASE	)

											if isinstance(self.path_or_buf       ,							(str, bytes, os.PathLike)	):
																	with open(self.path_or_buf       ,							'''wb+'''	) as buffer:
																							lowercase_			:  Any									= self._write(file_obj=__SCREAMING_SNAKE_CASE       ,							header=__SCREAMING_SNAKE_CASE       ,							index=__SCREAMING_SNAKE_CASE       ,							**self.to_csv_kwargs	)
											else:
																	lowercase_			:  str									= self._write(file_obj=self.path_or_buf       ,							header=__SCREAMING_SNAKE_CASE       ,							index=__SCREAMING_SNAKE_CASE       ,							**self.to_csv_kwargs	)
											return written






					def 			_snake_case					(     self       ,							__SCREAMING_SNAKE_CASE	):


											"""simple docstring"""





											lowercase_			:  int									= args

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






					def 			_snake_case					(     self       ,							__SCREAMING_SNAKE_CASE       ,							__SCREAMING_SNAKE_CASE       ,							__SCREAMING_SNAKE_CASE       ,							**__SCREAMING_SNAKE_CASE	):


											"""simple docstring"""





											lowercase_			:  Dict									= 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'''       ,							):
																							lowercase_			:  Any									= self._batch_csv((offset, header, index, to_csv_kwargs)	)
																							written += file_obj.write(__SCREAMING_SNAKE_CASE	)

											else:
																	lowercase_			:  Union[str, Any]									= 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       ,							__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 CSV from Arrow format'''       ,							):
																													written += file_obj.write(__SCREAMING_SNAKE_CASE	)

											return written





'''simple docstring'''







import math
def       snake_case_	(       __SCREAMING_SNAKE_CASE      :				int							):



						"""simple docstring"""





						if 1 < number < 4:
												# 2 and 3 are primes
												return True
						elif number < 2 or number % 2 == 0 or number % 3 == 0:
												# Negatives, 0, 1, all even numbers, all multiples of 3 are not primes
												return False

						# All primes number are in format of 6k +/- 1
						for i in range(5   ,   int(math.sqrt(__SCREAMING_SNAKE_CASE							) + 1							)   ,   6							):
												if number % i == 0 or number % (i + 2) == 0:
																		return False
						return True
def       snake_case_	(       __SCREAMING_SNAKE_CASE      :				int = 2000000							):



						"""simple docstring"""





						return sum(num for num in range(3   ,   __SCREAMING_SNAKE_CASE   ,   2							) if is_prime(__SCREAMING_SNAKE_CASE							)							) + 2 if n > 2 else 0


if __name__ == "__main__":
							print(f"""{solution() = }""")



