






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 		SCREAMING_SNAKE_CASE__	(  SCREAMING_SNAKE_CASE_     ):

  '''simple docstring'''







  def __init__(      self		:			Union[str, Any]       ,				lowerCamelCase		:			List[str]       ,				lowerCamelCase		:			str = None       ,				lowerCamelCase		:			Optional[Any] = None       ,				lowerCamelCase		:			Optional[Any] = None       ,				lowerCamelCase		:			Dict = False       ,				lowerCamelCase		:			Optional[int] = False       ,				lowerCamelCase		:			Any = None       ,				lowerCamelCase		:			List[str] = None       ,				**lowerCamelCase		:			str       ,				)						->	List[Any]:


         """simple docstring"""
         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							=    field
         _UpperCAmelCase							=    path_or_paths if isinstance(snake_case__       ,				snake_case__							) else {self.split: path_or_paths}
         _UpperCAmelCase							=    Json(
             cache_dir=snake_case__       ,				data_files=snake_case__       ,				features=snake_case__       ,				field=snake_case__       ,				**snake_case__       ,				)





  def  lowerCamelCase       (      self		:			Optional[int]							)						->	Optional[int]:


         """simple docstring"""

         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 		SCREAMING_SNAKE_CASE__	:

  '''simple docstring'''







  def __init__(      self		:			str       ,				lowerCamelCase		:			List[Any]       ,				lowerCamelCase		:			Optional[int]       ,				lowerCamelCase		:			str = None       ,				lowerCamelCase		:			List[Any] = None       ,				**lowerCamelCase		:			Dict       ,				)						->	Union[str, Any]:


         """simple docstring"""

         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_json_kwargs


  def  lowerCamelCase       (      self		:			Optional[int]							)						->	Optional[int]:


         """simple docstring"""
         _UpperCAmelCase							=    self.to_json_kwargs.pop("""path_or_buf"""       ,				snake_case__							)
         _UpperCAmelCase							=    self.to_json_kwargs.pop("""orient"""       ,				"""records"""							)
         _UpperCAmelCase							=    self.to_json_kwargs.pop("""lines"""       ,				True if orient == """records""" else False							)
         _UpperCAmelCase							=    self.to_json_kwargs.pop("""index"""       ,				False if orient in ["""split""", """table"""] else True							)
         _UpperCAmelCase							=    self.to_json_kwargs.pop("""compression"""       ,				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=snake_case__							) as buffer:
                       _UpperCAmelCase							=    self._write(file_obj=snake_case__       ,				orient=snake_case__       ,				lines=snake_case__       ,				index=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."""							)
                _UpperCAmelCase							=    self._write(
                    file_obj=self.path_or_buf       ,				orient=snake_case__       ,				lines=snake_case__       ,				index=snake_case__       ,				**self.to_json_kwargs							)
         return written


  def  lowerCamelCase       (      self		:			str       ,				lowerCamelCase		:			List[str]							)						->	Tuple:


         """simple docstring"""
         _UpperCAmelCase							=    args

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





  def  lowerCamelCase       (      self		:			str       ,				lowerCamelCase		:			Optional[Any]       ,				lowerCamelCase		:			Optional[int]       ,				lowerCamelCase		:			Dict       ,				lowerCamelCase		:			Dict       ,				**lowerCamelCase		:			List[Any]       ,				)						->	Optional[int]:


         """simple docstring"""
         _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 json from Arrow format"""       ,				):
                       _UpperCAmelCase							=    self._batch_json((offset, orient, lines, index, to_json_kwargs)							)
                       written += file_obj.write(snake_case__							)
         else:
                _UpperCAmelCase							=    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       ,				snake_case__       ,				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(snake_case__							)

         return written



'''simple docstring'''







from __future__ import annotations

from math import gcd






def       lowercase					(_A ,    _A = 2 ,    _A = 1 ,    _A = 3 ,    ):







       """simple docstring"""







       if num < 2:
              raise ValueError('The input value cannot be less than 2'       )

       # Because of the relationship between ``f(f(x))`` and ``f(x)``, this
       # algorithm struggles to find factors that are divisible by two.
       # As a workaround, we specifically check for two and even inputs.
       #   See: https://math.stackexchange.com/a/2856214/165820
       if num > 2 and num % 2 == 0:
              return 2

       # Pollard's Rho algorithm requires a function that returns pseudorandom
       # values between 0 <= X < ``num``.  It doesn't need to be random in the
       # sense that the output value is cryptographically secure or difficult
       # to calculate, it only needs to be random in the sense that all output
       # values should be equally likely to appear.
       # For this reason, Pollard suggested using ``f(x) = (x**2 - 1) % num``
       # However, the success of Pollard's algorithm isn't guaranteed and is
       # determined in part by the initial seed and the chosen random function.
       # To make retries easier, we will instead use ``f(x) = (x**2 + C) % num``
       # where ``C`` is a value that we can modify between each attempt.
       def rand_fn(_A ,    _A ,    _A       ) -> int:
              return (pow(_A ,    2       ) + step) % modulus

       for _ in range(_A       ):
              # These track the position within the cycle detection logic.
              _lowerCAmelCase     :				Dict       =							seed
              _lowerCAmelCase     :				int       =							seed

              while True:
                     # At each iteration, the tortoise moves one step and the hare moves two.
                     _lowerCAmelCase     :				str       =							rand_fn(_A ,    _A ,    _A       )
                     _lowerCAmelCase     :				Optional[int]       =							rand_fn(_A ,    _A ,    _A       )
                     _lowerCAmelCase     :				Union[str, Any]       =							rand_fn(_A ,    _A ,    _A       )

                     # At some point both the tortoise and the hare will enter a cycle whose
                     # length ``p`` is a divisor of ``num``.  Once in that cycle, at some point
                     # the tortoise and hare will end up on the same value modulo ``p``.
                     # We can detect when this happens because the position difference between
                     # the tortoise and the hare will share a common divisor with ``num``.
                     _lowerCAmelCase     :				Optional[int]       =							gcd(hare - tortoise ,    _A       )

                     if divisor == 1:
                            # No common divisor yet, just keep searching.
                            continue
                     else:
                            # We found a common divisor!
                            if divisor == num:
                                   # Unfortunately, the divisor is ``num`` itself and is useless.
                                   break
                            else:
                                   # The divisor is a nontrivial factor of ``num``!
                                   return divisor

        # If we made it here, then this attempt failed.
        # We need to pick a new starting seed for the tortoise and hare
        # in addition to a new step value for the random function.
        # To keep this example implementation deterministic, the
        # new values will be generated based on currently available
        # values instead of using something like ``random.randint``.

        # We can use the hare's position as the new seed.
        # This is actually what Richard Brent's the "optimized" variant does.
              _lowerCAmelCase     :				Tuple       =							hare

              # The new step value for the random function can just be incremented.
              # At first the results will be similar to what the old function would
              # have produced, but the value will quickly diverge after a bit.
              step += 1

       # We haven't found a divisor within the requested number of attempts.
       # We were unlucky or ``num`` itself is actually prime.
       return None


if __name__ == "__main__":
       import argparse

       lowerCAmelCase     :  Tuple											=    argparse.ArgumentParser()
       parser.add_argument(
           """num""",
           type=int,
           help="""The value to find a divisor of""",
       )
       parser.add_argument(
           """--attempts""",
           type=int,
           default=3,
           help="""The number of attempts before giving up""",
       )
       lowerCAmelCase     :  List[str]											=    parser.parse_args()

       lowerCAmelCase     :  List[str]											=    pollard_rho(args.num, attempts=args.attempts)
       if divisor is None:
              print(F'''{args.num} is probably prime''')
       else:
              lowerCAmelCase     :  Union[str, Any]											=    args.num // divisor
              print(F'''{args.num} = {divisor} * {quotient}''')

