
'''simple docstring'''







import html

from ...feature_extraction_utils import BatchFeature, FeatureExtractionMixin
from ...utils import is_bsa_available, logging, requires_backends


if is_bsa_available():
  import bsa
  from bsa import BeautifulSoup


__lowerCAmelCase         =    logging.get_logger(__name__)







class UpperCAmelCase__	( __UpperCAmelCase	):





  """simple docstring"""

  def __init__(		self      :     int							,**_a      :     Tuple       ):


     '''simple docstring'''






     requires_backends(self							,['bs4']       )
     super().__init__(**_a       )


  def   __lowercase		(		self      :     Union[str, Any]							,_a      :     List[Any]       ):


     '''simple docstring'''






     _a				:	int			=   []
     _a				:	Dict			=   []
     _a				:	Optional[Any]			=   element if element.name else element.parent
     for parent in child.parents:  # type: bs4.element.Tag
        _a				:	str			=   parent.find_all(child.name							,recursive=_a       )
        xpath_tags.append(child.name       )
        xpath_subscripts.append(
            0 if 1 == len(_a       ) else next(i for i, s in enumerate(_a							,1       ) if s is child       )       )
        _a				:	Optional[Any]			=   parent
     xpath_tags.reverse()
     xpath_subscripts.reverse()
     return xpath_tags, xpath_subscripts


  def   __lowercase		(		self      :     str							,_a      :     str       ):


     '''simple docstring'''






     _a				:	int			=   BeautifulSoup(_a							,'html.parser'       )

     _a				:	List[str]			=   []
     _a				:	str			=   []
     _a				:	List[Any]			=   []

     for element in html_code.descendants:
        if type(_a       ) == bsa.element.NavigableString:
           if type(element.parent       ) != bsa.element.Tag:
              continue

           _a				:	Union[str, Any]			=   html.unescape(_a       ).strip()
           if not text_in_this_tag:
              continue

           all_doc_strings.append(_a       )

           _a				:	List[str]			=   self.xpath_soup(_a       )
           stringaxtag_seq.append(_a       )
           stringaxsubs_seq.append(_a       )

     if len(_a       ) != len(_a       ):
        raise ValueError('Number of doc strings and xtags does not correspond'       )
     if len(_a       ) != len(_a       ):
        raise ValueError('Number of doc strings and xsubs does not correspond'       )

     return all_doc_strings, stringaxtag_seq, stringaxsubs_seq


  def   __lowercase		(		self      :     Tuple							,_a      :     int							,_a      :     Any       ):


     '''simple docstring'''






     _a				:	int			=   ''
     for tagname, subs in zip(_a							,_a       ):
        xpath += F"""/{tagname}"""
        if subs != 0:
           xpath += F"""[{subs}]"""
     return xpath


  def __call__(		self      :     Tuple							,_a      :     int       ):


     '''simple docstring'''






     _a				:	List[str]			=   False

     # Check that strings has a valid type
     if isinstance(_a							,_a       ):
        _a				:	Optional[int]			=   True
     elif isinstance(_a							,(list, tuple)       ):
        if len(_a       ) == 0 or isinstance(html_strings[0]							,_a       ):
           _a				:	Dict			=   True

     if not valid_strings:
        raise ValueError(
            'HTML strings must of type `str`, `List[str]` (batch of examples), '
            F"""but is of type {type(_a       )}."""       )

     _a				:	Dict			=   bool(isinstance(_a							,(list, tuple)       ) and (isinstance(html_strings[0]							,_a       ))       )

     if not is_batched:
        _a				:	Tuple			=   [html_strings]

     # Get nodes + xpaths
     _a				:	Optional[int]			=   []
     _a				:	int			=   []
     for html_string in html_strings:
        _a				:	int			=   self.get_three_from_single(_a       )
        nodes.append(_a       )
        _a				:	Optional[Any]			=   []
        for node, tag_list, sub_list in zip(_a							,_a							,_a       ):
           _a				:	List[Any]			=   self.construct_xpath(_a							,_a       )
           xpath_strings.append(_a       )
        xpaths.append(_a       )

     # return as Dict
     _a				:	Dict			=   {'nodes': nodes, 'xpaths': xpaths}
     _a				:	int			=   BatchFeature(data=_a							,tensor_type=_a       )

     return encoded_inputs










from math import loga



def A_	(		A__				)  ->		int:
       if a < 0:
              raise ValueError('Input value must be a positive integer'				)
       elif isinstance(A__		,      A__				):
              raise TypeError('Input value must be a \'int\' type'				)
       return 0 if (a == 0) else int(loga(a & -a				)				)


if __name__ == "__main__":
    import doctest

    doctest.testmod()


