




"""simple docstring"""



from __future__ import annotations

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

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

import requests




class      UpperCAmelCase_  (						A_							):




    def __init__(   self						:	int     ,			snake_case_						:	str				)				->							None:




     '''simple docstring'''

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




    def 							__magic_name__							(   self						:	Union[str, Any]     ,			snake_case_						:	str     ,			snake_case_						:	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     ,			snake_case_				)
         self.urls.append(snake_case_				)







def   _SCREAMING_SNAKE_CASE       (							lowercase_						)						->		str:
 return ".".join(get_sub_domain_name(lowercase_						).split("."						)[-2:]						)







def   _SCREAMING_SNAKE_CASE       (							lowercase_						)						->		str:
 return parse.urlparse(lowercase_						).netloc







def   _SCREAMING_SNAKE_CASE       (							lowercase_ = "https://github.com"						)						->		list[str]:
 A__	=    get_domain_name(lowercase_						)

 # Initialize the parser
 A__	=    Parser(lowercase_						)

 try:
  # Open URL
  A__	=    requests.get(lowercase_						)

  # 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(lowercase_						)
    # 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(lowercase_						)
   except ValueError:
    pass
 except ValueError:
  raise SystemExit(1						)

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


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











"""simple docstring"""



from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding




class      UpperCAmelCase_  (						A_							):
    lowercase__						 =				['''image_processor''', '''tokenizer''']
    lowercase__						 =				'''AutoImageProcessor'''
    lowercase__						 =				'''AutoTokenizer'''




    def __init__(   self						:	str     ,			snake_case_						:	Dict     ,			snake_case_						:	List[str]				)				->							str:




     '''simple docstring'''

     super().__init__(snake_case_     ,			snake_case_				)
     A__	=    self.image_processor




    def __call__(   self						:	int     ,			snake_case_						:	Any=None     ,			snake_case_						:	Any=None     ,			snake_case_						:	Union[str, Any]=None     ,			**snake_case_						:	Optional[int]				)				->							Optional[int]:




     '''simple docstring'''

     if text is None and images is None:
      raise ValueError("You have to specify either text or images. Both cannot be none."				)

     if text is not None:
      A__	=    self.tokenizer(snake_case_     ,			return_tensors=snake_case_     ,			**snake_case_				)

     if images is not None:
      A__	=    self.image_processor(snake_case_     ,			return_tensors=snake_case_     ,			**snake_case_				)

     if text is not None and images is not None:
      A__	=    image_features.pixel_values
      return encoding
     elif text is not None:
      return encoding
     else:
      return BatchEncoding(data=dict(**snake_case_				)     ,			tensor_type=snake_case_				)




    def 							__magic_name__							(   self						:	Optional[int]     ,			*snake_case_						:	Union[str, Any]     ,			**snake_case_						:	List[Any]				)				->							int:




     '''simple docstring'''

     return self.tokenizer.batch_decode(*snake_case_     ,			**snake_case_				)




    def 							__magic_name__							(   self						:	List[str]     ,			*snake_case_						:	List[str]     ,			**snake_case_						:	Optional[int]				)				->							Tuple:




     '''simple docstring'''

     return self.tokenizer.decode(*snake_case_     ,			**snake_case_				)




    @property
    def 							__magic_name__							(   self						:	List[Any]				)				->							List[Any]:




     '''simple docstring'''

     return ["input_ids", "attention_mask", "pixel_values"]





