






'''simple docstring'''







import json
from typing import List, Optional, Tuple

from tokenizers import normalizers

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from .tokenization_electra import ElectraTokenizer


_A	:			Optional[int]         ={'''vocab_file''': '''vocab.txt''', '''tokenizer_file''': '''tokenizer.json'''}

_A	:			Optional[Any]         ={
    '''vocab_file''': {
        '''google/electra-small-generator''': (
            '''https://huggingface.co/google/electra-small-generator/resolve/main/vocab.txt'''
        ),
        '''google/electra-base-generator''': '''https://huggingface.co/google/electra-base-generator/resolve/main/vocab.txt''',
        '''google/electra-large-generator''': (
            '''https://huggingface.co/google/electra-large-generator/resolve/main/vocab.txt'''
        ),
        '''google/electra-small-discriminator''': (
            '''https://huggingface.co/google/electra-small-discriminator/resolve/main/vocab.txt'''
        ),
        '''google/electra-base-discriminator''': (
            '''https://huggingface.co/google/electra-base-discriminator/resolve/main/vocab.txt'''
        ),
        '''google/electra-large-discriminator''': (
            '''https://huggingface.co/google/electra-large-discriminator/resolve/main/vocab.txt'''
        ),
    },
    '''tokenizer_file''': {
        '''google/electra-small-generator''': (
            '''https://huggingface.co/google/electra-small-generator/resolve/main/tokenizer.json'''
        ),
        '''google/electra-base-generator''': (
            '''https://huggingface.co/google/electra-base-generator/resolve/main/tokenizer.json'''
        ),
        '''google/electra-large-generator''': (
            '''https://huggingface.co/google/electra-large-generator/resolve/main/tokenizer.json'''
        ),
        '''google/electra-small-discriminator''': (
            '''https://huggingface.co/google/electra-small-discriminator/resolve/main/tokenizer.json'''
        ),
        '''google/electra-base-discriminator''': (
            '''https://huggingface.co/google/electra-base-discriminator/resolve/main/tokenizer.json'''
        ),
        '''google/electra-large-discriminator''': (
            '''https://huggingface.co/google/electra-large-discriminator/resolve/main/tokenizer.json'''
        ),
    },
}

_A	:			Dict         ={
    '''google/electra-small-generator''': 512,
    '''google/electra-base-generator''': 512,
    '''google/electra-large-generator''': 512,
    '''google/electra-small-discriminator''': 512,
    '''google/electra-base-discriminator''': 512,
    '''google/electra-large-discriminator''': 512,
}

_A	:			str         ={
    '''google/electra-small-generator''': {'''do_lower_case''': True},
    '''google/electra-base-generator''': {'''do_lower_case''': True},
    '''google/electra-large-generator''': {'''do_lower_case''': True},
    '''google/electra-small-discriminator''': {'''do_lower_case''': True},
    '''google/electra-base-discriminator''': {'''do_lower_case''': True},
    '''google/electra-large-discriminator''': {'''do_lower_case''': True},
}

class _lowercase	(				_lowercase		):
							a				      =       VOCAB_FILES_NAMES
							a				      =       PRETRAINED_VOCAB_FILES_MAP
							a				      =       PRETRAINED_INIT_CONFIGURATION
							a				      =       PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
							a				      =       ElectraTokenizer




							def __init__(							self:				Dict			,							UpperCamelCase__:				int=None			,							UpperCamelCase__:				str=None			,							UpperCamelCase__:				Optional[int]=True			,							UpperCamelCase__:				str="[UNK]"			,							UpperCamelCase__:				Any="[SEP]"			,							UpperCamelCase__:				str="[PAD]"			,							UpperCamelCase__:				Optional[Any]="[CLS]"			,							UpperCamelCase__:				Union[str, Any]="[MASK]"			,							UpperCamelCase__:				List[str]=True			,							UpperCamelCase__:				Tuple=None			,							**UpperCamelCase__:				Optional[int]			,							):
														super().__init__(
														    __UpperCAmelCase			,							tokenizer_file=__UpperCAmelCase			,							do_lower_case=__UpperCAmelCase			,							unk_token=__UpperCAmelCase			,							sep_token=__UpperCAmelCase			,							pad_token=__UpperCAmelCase			,							cls_token=__UpperCAmelCase			,							mask_token=__UpperCAmelCase			,							tokenize_chinese_chars=__UpperCAmelCase			,							strip_accents=__UpperCAmelCase			,							**__UpperCAmelCase			,							)

														lowerCamelCase__					:	List[str]         =       json.loads(self.backend_tokenizer.normalizer.__getstate__()     )
														if (
														    normalizer_state.get("""lowercase"""			,							__UpperCAmelCase     ) != do_lower_case
														    or normalizer_state.get("""strip_accents"""			,							__UpperCAmelCase     ) != strip_accents
														    or normalizer_state.get("""handle_chinese_chars"""			,							__UpperCAmelCase     ) != tokenize_chinese_chars
														):
																					lowerCamelCase__					:	Union[str, Any]         =       getattr(__UpperCAmelCase			,							normalizer_state.pop("""type"""     )     )
																					lowerCamelCase__					:	Any         =       do_lower_case
																					lowerCamelCase__					:	Tuple         =       strip_accents
																					lowerCamelCase__					:	Dict         =       tokenize_chinese_chars
																					lowerCamelCase__					:	List[Any]         =       normalizer_class(**__UpperCAmelCase     )

														lowerCamelCase__					:	List[Any]         =       do_lower_case




							def 		lowerCamelCase_				(							self:				List[Any]			,							UpperCamelCase__:				Optional[int]			,							UpperCamelCase__:				Tuple=None     ):
														lowerCamelCase__					:	Any         =       [self.cls_token_id] + token_ids_a + [self.sep_token_id]

														if token_ids_a:
																					output += token_ids_a + [self.sep_token_id]

														return output




							def 		lowerCamelCase_				(							self:				Optional[Any]			,							UpperCamelCase__:				List[int]			,							UpperCamelCase__:				Optional[List[int]] = None     ):
														lowerCamelCase__					:	Union[str, Any]         =       [self.sep_token_id]
														lowerCamelCase__					:	Tuple         =       [self.cls_token_id]
														if token_ids_a is None:
																					return len(cls + token_ids_a + sep     ) * [0]
														return len(cls + token_ids_a + sep     ) * [0] + len(token_ids_a + sep     ) * [1]




							def 		lowerCamelCase_				(							self:				List[str]			,							UpperCamelCase__:				str			,							UpperCamelCase__:				Optional[str] = None     ):
														lowerCamelCase__					:	Dict         =       self._tokenizer.model.save(__UpperCAmelCase			,							name=__UpperCAmelCase     )
														return tuple(__UpperCAmelCase     )









from __future__ import annotations

UpperCAmelCase__				   =		"Muhammad Umer Farooq"
UpperCAmelCase__				   =		"MIT"
UpperCAmelCase__				   =		"1.0.0"
UpperCAmelCase__				   =		"Muhammad Umer Farooq"
UpperCAmelCase__				   =		"contact@muhammadumerfarooq.me"
UpperCAmelCase__				   =		"Alpha"

import re
from html.parser import HTMLParser
from urllib import parse

import requests






class 		lowercase_					(	lowercase   ):






      '''simple docstring'''




      def __init__(      self      :						Union[str, Any] ,					__UpperCAmelCase      :						str  )    ->None:




       """simple docstring"""


       super().__init__()
       a		  =      []
       a		  =      domain







      def       __lowerCAmelCase					(      self      :						List[str] ,					__UpperCAmelCase      :						str ,					__UpperCAmelCase      :						list[tuple[str, str | None]]  )    ->None:




       """simple docstring"""


       if tag == "a":
        # Check the list of defined attributes.
        for name, value in attrs:
         # If href is defined, and not empty nor # print it.
         if name == "href" and value != "#" and value != "":
          # If not already in urls.
          if value not in self.urls:
           a		  =      parse.urljoin(self.domain ,					__UpperCAmelCase  )
           self.urls.append(__UpperCAmelCase  )
def 						_a    (      a :str )							->			str:
 return ".".join(get_sub_domain_name(a ).split('''.''' )[-2:] )
def 						_a    (      a :str )							->			str:
 return parse.urlparse(a ).netloc
def 						_a    (      a :str = "https://github.com" )							->			list[str]:
 a		  =      get_domain_name(a )

 # Initialize the parser
 a		  =      Parser(a )

 try:
  # Open URL
  a		  =      requests.get(a )

  # pass the raw HTML to the parser to get links
  parser.feed(r.text )

  # Get links and loop through
  a		  =      set()
  for link in parser.urls:
   # open URL.
   # read = requests.get(link)
   try:
    a		  =      requests.get(a )
    # Get the valid email.
    a		  =      re.findall('''[a-zA-Z0-9]+@''' + domain	,							read.text )
    # If not in list then append it.
    for email in emails:
     valid_emails.add(a )
   except ValueError:
    pass
 except ValueError:
  raise SystemExit(1 )

 # Finally return a sorted list of email addresses with no duplicates.
 return sorted(a )


if __name__ == "__main__":
     UpperCAmelCase__				   =		emails_from_url("https://github.com")
     print(f"""{len(emails)} emails found:""")
     print("\n".join(sorted(emails)))


