


'''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  lowercase_					(   a__       ):


    def __init__(					self  , a  , a = None  , a = None  , a = None  , a = False  , a = False  , a = None  , **a  , ):
          super().__init__(
              a  , split=a  , features=a  , cache_dir=a  , keep_in_memory=a  , streaming=a  , num_proc=a  , **a  , )
          UpperCamelCase__  =    path_or_paths if isinstance(a  , a   ) else {self.split: path_or_paths}
          UpperCamelCase__  =    Csv(
              cache_dir=a  , data_files=a  , features=a  , **a  , )


    def        __a							(					self   ):
          # Build iterable dataset
          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=a  , download_mode=a  , verification_mode=a  , base_path=a  , num_proc=self.num_proc  , )
                UpperCamelCase__  =    self.builder.as_dataset(
                    split=self.split  , verification_mode=a  , in_memory=self.keep_in_memory   )
          return dataset

class  lowercase_					:


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

          UpperCamelCase__  =    dataset
          UpperCamelCase__  =    path_or_buf
          UpperCamelCase__  =    batch_size if batch_size else config.DEFAULT_MAX_BATCH_SIZE
          UpperCamelCase__  =    num_proc
          UpperCamelCase__  =    "utf-8"
          UpperCamelCase__  =    to_csv_kwargs


    def        __a							(					self   ):
          UpperCamelCase__  =    self.to_csv_kwargs.pop("path_or_buf"  , a   )
          UpperCamelCase__  =    self.to_csv_kwargs.pop("header"  , a   )
          UpperCamelCase__  =    self.to_csv_kwargs.pop("index"  , a   )

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


    def        __a							(					self  , a   ):
          UpperCamelCase__ ,     UpperCamelCase__ ,     UpperCamelCase__ ,     UpperCamelCase__  =    args

          UpperCamelCase__  =    query_table(
              table=self.dataset.data  , key=slice(a  , offset + self.batch_size   )  , indices=self.dataset._indices  , )
          UpperCamelCase__  =    batch.to_pandas().to_csv(
              path_or_buf=a  , header=header if (offset == 0) else False  , index=a  , **a   )
          return csv_str.encode(self.encoding   )


    def        __a							(					self  , a  , a  , a  , **a   ):
          UpperCamelCase__  =    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"  , ):
                      UpperCamelCase__  =    self._batch_csv((offset, header, index, to_csv_kwargs)   )
                      written += file_obj.write(a   )

          else:
                UpperCamelCase__ ,     UpperCamelCase__  =    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  , 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 CSV from Arrow format"  , ):
                            written += file_obj.write(a   )

          return written









'''simple docstring'''







import math







def _UpperCamelCase	(					__A   )							->		bool:


      '''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(__A   ) + 1   )				,      6   ):
            if number % i == 0 or number % (i + 2) == 0:
                  return False
      return True







def _UpperCamelCase	(					__A = 1000				,      __A = 1000   )							->		int:


      '''simple docstring'''



      UpperCamelCase__  =    [0, 0, 0]  # length, a, b
      for a in range((a_limit * -1) + 1				,      __A   ):
            for b in range(2				,      __A   ):
                  if is_prime(__A   ):
                        UpperCamelCase__  =    0
                        UpperCamelCase__  =    0
                        while is_prime((n**2) + (a * n) + b   ):
                              count += 1
                              n += 1
                        if count > longest[0]:
                              UpperCamelCase__  =    [count, a, b]
      UpperCamelCase__  =    longest[1] * longest[2]
      return ans


if __name__ == "__main__":
  print(solution(1_0_0_0, 1_0_0_0))





