




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 						_A (  _lowerCamelCase				):






  def __init__(  self		:     Tuple				,						**_A		:     int				)		->   List[Any]:






       """simple docstring"""







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






  def  __a      (  self		:     List[Any]				,						_A		:     Optional[int]				)		->   str:






       """simple docstring"""







       lowercase :       Optional[int]       =			[]
       lowercase :       Union[str, Any]       =			[]
       lowercase :       int       =			element if element.name else element.parent
       for parent in child.parents:  # type: bs4.element.Tag
            lowercase :       List[Any]       =			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				)				)
            lowercase :       List[Any]       =			parent
       xpath_tags.reverse()
       xpath_subscripts.reverse()
       return xpath_tags, xpath_subscripts






  def  __a      (  self		:     int				,						_A		:     Optional[Any]				)		->   List[str]:






       """simple docstring"""







       lowercase :       Tuple       =			BeautifulSoup(_A				,						'''html.parser'''				)

       lowercase :       str       =			[]
       lowercase :       Optional[Any]       =			[]
       lowercase :       List[str]       =			[]

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

                 lowercase :       Optional[int]       =			html.unescape(_A				).strip()
                 if not text_in_this_tag:
                      continue

                 all_doc_strings.append(_A				)

                 lowercase :       List[Any]       =			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  __a      (  self		:     Dict				,						_A		:     Union[str, Any]				,						_A		:     Dict				)		->   Any:






       """simple docstring"""







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






  def __call__(  self		:     Any				,						_A		:     Optional[Any]				)		->   BatchFeature:






       """simple docstring"""







       lowercase :       List[str]       =			False

       # Check that strings has a valid type
       if isinstance(_A				,						_A				):
            lowercase :       List[Any]       =			True
       elif isinstance(_A				,						(list, tuple)				):
            if len(_A				) == 0 or isinstance(html_strings[0]				,						_A				):
                 lowercase :       Optional[int]       =			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				)}."""				)

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

       if not is_batched:
            lowercase :       List[str]       =			[html_strings]

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

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

       return encoded_inputs









def  snake_case(    __magic_name__			,		__magic_name__			,		__magic_name__   )			->							int:





     '''simple docstring'''


     if len(__magic_name__   ) != len(__magic_name__   ):
          raise ValueError('''The length of profit and weight must be same.'''   )
     if max_weight <= 0:
          raise ValueError('''max_weight must greater than zero.'''   )
     if any(p < 0 for p in profit   ):
          raise ValueError('''Profit can not be negative.'''   )
     if any(w < 0 for w in weight   ):
          raise ValueError('''Weight can not be negative.'''   )

     # List created to store profit gained for the 1kg in case of each weight
     # respectively.  Calculate and append profit/weight for each element.
     lowercase :       str       =			[p / w for p, w in zip(__magic_name__			,		__magic_name__   )]

     # Creating a copy of the list and sorting profit/weight in ascending order
     lowercase :       str       =			sorted(__magic_name__   )

     # declaring useful variables
     lowercase :       Union[str, Any]       =			len(__magic_name__   )
     lowercase :       Optional[int]       =			0
     lowercase :       Optional[int]       =			0
     lowercase :       int       =			0

     # loop till the total weight do not reach max limit e.g. 15 kg and till i<length
     while limit <= max_weight and i < length:
          # flag value for encountered greatest element in sorted_profit_by_weight
          lowercase :       Optional[int]       =			sorted_profit_by_weight[length - i - 1]
          lowercase :       Union[str, Any]       =			profit_by_weight.index(__magic_name__   )
          lowercase :       Any       =			-1

          # check if the weight encountered is less than the total weight
          # encountered before.
          if max_weight - limit >= weight[index]:
               limit += weight[index]
               # Adding profit gained for the given weight 1 ===
               # weight[index]/weight[index]
               gain += 1 * profit[index]
          else:
               # Since the weight encountered is greater than limit, therefore take the
               # required number of remaining kgs and calculate profit for it.
               # weight remaining / weight[index]
               gain += (max_weight - limit) / weight[index] * profit[index]
               break
          i += 1
     return gain


if __name__ == "__main__":
 print(
     'Input profits, weights, and then max_weight (all positive ints) separated by '
     'spaces.'
 )

 lowerCAmelCase_						=			[int(x) for x in input('Input profits separated by spaces: ').split()]
 lowerCAmelCase_						=			[int(x) for x in input('Input weights separated by spaces: ').split()]
 lowerCAmelCase_						=			int(input('Max weight allowed: '))

 # Function Call
 calc_profit(profit, weight, max_weight)