


from collections.abc import Callable




def       a_ (       SCREAMING_SNAKE_CASE__   : Callable[[float], float]						,     SCREAMING_SNAKE_CASE__   : float						,     SCREAMING_SNAKE_CASE__   : float	):
       '''simple docstring'''





       _lowerCamelCase			:						float            =a
       _lowerCamelCase			:						float            =b
       if function(SCREAMING_SNAKE_CASE__	) == 0:  # one of the a or b is a root for the function
              return a
       elif function(SCREAMING_SNAKE_CASE__	) == 0:
              return b
       elif (
           function(SCREAMING_SNAKE_CASE__	) * function(SCREAMING_SNAKE_CASE__	) > 0
       ):  # if none of these are root and they are both positive or negative,
              # then this algorithm can't find the root
              raise ValueError('could not find root in given interval.'	)
       else:
              _lowerCamelCase			:						float            =start + (end - start) / 2.0
              while abs(start - mid	) > 10**-7:  # until precisely equals to 10^-7
                     if function(SCREAMING_SNAKE_CASE__	) == 0:
                            return mid
                     elif function(SCREAMING_SNAKE_CASE__	) * function(SCREAMING_SNAKE_CASE__	) < 0:
                            _lowerCamelCase			:						Any            =mid
                     else:
                            _lowerCamelCase			:						Optional[int]            =mid
                     _lowerCamelCase			:						Union[str, Any]            =start + (end - start) / 2.0
              return mid




def       a_ (       SCREAMING_SNAKE_CASE__   : float	):
       '''simple docstring'''





       return x**3 - 2 * x - 5


if __name__ == "__main__":
 print(bisection(f, 1, 10_00))

 import doctest

 doctest.testmod()






from typing import Optional

from .. import Features, NamedSplit
from ..packaged_modules.text.text import Text
from ..utils.typing import NestedDataStructureLike, PathLike
from .abc import AbstractDatasetReader




class A    (  UpperCamelCase_	):






      def __init__(   self		:	Union[str, Any]     ,  lowercase_		:	NestedDataStructureLike[PathLike]     ,  lowercase_		:	Optional[NamedSplit] = None     ,  lowercase_		:	Optional[Features] = None     ,  lowercase_		:	str = None     ,  lowercase_		:	bool = False     ,  lowercase_		:	bool = False     ,  lowercase_		:	Optional[int] = None     ,  **lowercase_		:	Optional[int]     ,  )   ->		Union[str, Any]:
             """simple docstring"""




             super().__init__(
                 lowercase_     ,  split=lowercase_     ,  features=lowercase_     ,  cache_dir=lowercase_     ,  keep_in_memory=lowercase_     ,  streaming=lowercase_     ,  num_proc=lowercase_     ,  **lowercase_     ,  )
             _lowerCamelCase			:						Optional[int]            =path_or_paths if isinstance(lowercase_     ,  lowercase_					) else {self.split: path_or_paths}
             _lowerCamelCase			:						int            =Text(
                 cache_dir=lowercase_     ,  data_files=lowercase_     ,  features=lowercase_     ,  **lowercase_     ,  )






      def 			lowerCamelCase			(   self		:	Optional[Any]					)   ->		Dict:
             """simple docstring"""




             if self.streaming:
                    _lowerCamelCase			:						Optional[Any]            =self.builder.as_streaming_dataset(split=self.split					)
             # Build regular (map-style) dataset
             else:
                    _lowerCamelCase			:						List[str]            =None
                    _lowerCamelCase			:						int            =None
                    _lowerCamelCase			:						Optional[Any]            =None
                    _lowerCamelCase			:						Any            =None

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


