
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


lowercase__	:str										=					logging.get_logger(__name__)







class        lowercase	(      SCREAMING_SNAKE_CASE__	):




							def __init__(       self     ,**A__):
												requires_backends(self     ,['''bs4'''])
												super().__init__(**A__)




							def 				A__   (       self     ,A__):
												lowercase					=		[]
												lowercase					=		[]
												lowercase					=		element if element.name else element.parent
												for parent in child.parents:  # type: bs4.element.Tag
																	lowercase					=		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					=		parent
												xpath_tags.reverse()
												xpath_subscripts.reverse()
												return xpath_tags, xpath_subscripts




							def 				A__   (       self     ,A__):
												lowercase					=		BeautifulSoup(A__     ,'''html.parser''')

												lowercase					=		[]
												lowercase					=		[]
												lowercase					=		[]

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

																						lowercase					=		html.unescape(A__).strip()
																						if not text_in_this_tag:
																											continue

																						all_doc_strings.append(A__)

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





							def __call__(       self     ,A__):
												lowercase					=		False

												# Check that strings has a valid type
												if isinstance(A__     ,A__):
																	lowercase					=		True
												elif isinstance(A__     ,(list, tuple)):
																	if len(A__) == 0 or isinstance(html_strings[0]     ,A__):
																						lowercase					=		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					=		bool(isinstance(A__     ,(list, tuple)) and (isinstance(html_strings[0]     ,A__)))

												if not is_batched:
																	lowercase					=		[html_strings]

												# Get nodes + xpaths
												lowercase					=		[]
												lowercase					=		[]
												for html_string in html_strings:
																	lowercase			,		lowercase			,		lowercase					=		self.get_three_from_single(A__)
																	nodes.append(A__)
																	lowercase					=		[]
																	for node, tag_list, sub_list in zip(A__     ,A__     ,A__):
																						lowercase					=		self.construct_xpath(A__     ,A__)
																						xpath_strings.append(A__)
																	xpaths.append(A__)

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

												return encoded_inputs






def  UpperCamelCase					(							lowerCAmelCase__ = 1000	):
					'''simple docstring'''
					lowercase					=		-1
					lowercase					=		0
					for a in range(1				,    n // 3	):
										# Solving the two equations a**2+b**2=c**2 and a+b+c=N eliminating c
										lowercase					=		(n * n - 2 * a * n) // (2 * n - 2 * a)
										lowercase					=		n - a - b
										if c * c == (a * a + b * b):
															lowercase					=		a * b * c
															if candidate >= product:
																				lowercase					=		candidate
					return product


if __name__ == "__main__":
							print(F'{solution() = }')




