


'''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'''







from __future__ import annotations

# Define the Gravitational Constant G and the function
a__    :   Optional[int]								=			6.67_43E-11  # unit of G : m^3 * kg^-1 * s^-2







def _UpperCamelCase			(	__A ,     __A ,     __A ,     __A       )				->						dict[str, float]:


      '''simple docstring'''



      UpperCamelCase__      =							mass_a * mass_a

      if (force, mass_a, mass_a, distance).count(0       ) != 1:
            raise ValueError("One and only one argument must be 0"       )
      if force < 0:
            raise ValueError("Gravitational force can not be negative"       )
      if distance < 0:
            raise ValueError("Distance can not be negative"       )
      if mass_a < 0 or mass_a < 0:
            raise ValueError("Mass can not be negative"       )
      if force == 0:
            UpperCamelCase__      =							GRAVITATIONAL_CONSTANT * product_of_mass / (distance**2)
            return {"force": force}
      elif mass_a == 0:
            UpperCamelCase__      =							(force) * (distance**2) / (GRAVITATIONAL_CONSTANT * mass_a)
            return {"mass_1": mass_a}
      elif mass_a == 0:
            UpperCamelCase__      =							(force) * (distance**2) / (GRAVITATIONAL_CONSTANT * mass_a)
            return {"mass_2": mass_a}
      elif distance == 0:
            UpperCamelCase__      =							(GRAVITATIONAL_CONSTANT * product_of_mass / (force)) ** 0.5
            return {"distance": distance}
      raise ValueError("One and only one argument must be 0"       )


# Run doctest
if __name__ == "__main__":
  import doctest

  doctest.testmod()





