



import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple

import sentencepiece as spm

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging


lowerCamelCase__			= logging.get_logger(__name__)

lowerCamelCase__			= {"""vocab_file""": """sentencepiece.bpe.model"""}

lowerCamelCase__			= {
    """vocab_file""": {
        """camembert-base""": """https://huggingface.co/camembert-base/resolve/main/sentencepiece.bpe.model""",
    }
}

lowerCamelCase__			= {
    """camembert-base""": 512,
}

lowerCamelCase__			= """▁"""






class    SCREAMING_SNAKE_CASE			(							lowerCamelCase__					):
							__lowerCamelCase	:	str    =VOCAB_FILES_NAMES
							__lowerCamelCase	:	Tuple    =PRETRAINED_VOCAB_FILES_MAP
							__lowerCamelCase	:	Dict    =PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
							__lowerCamelCase	:	Dict    =['input_ids', 'attention_mask']





							def __init__(   self		:		Union[str, Any]      ,				__lowercase		:		List[Any]      ,				__lowercase		:		List[str]="<s>"      ,				__lowercase		:		List[Any]="</s>"      ,				__lowercase		:		str="</s>"      ,				__lowercase		:		Tuple="<s>"      ,				__lowercase		:		str="<unk>"      ,				__lowercase		:		List[str]="<pad>"      ,				__lowercase		:		Optional[Any]="<mask>"      ,				__lowercase		:		Union[str, Any]=["<s>NOTUSED", "</s>NOTUSED"]      ,				__lowercase		:		Optional[Dict[str, Any]] = None      ,				**__lowercase		:		List[str]      ,				):

											'''simple docstring'''
											__a       =		AddedToken(__lowercase      ,				lstrip=__lowercase      ,				rstrip=__lowercase	) if isinstance(__lowercase      ,				__lowercase	) else mask_token

											__a       =		{} if sp_model_kwargs is None else sp_model_kwargs

											super().__init__(
											    bos_token=__lowercase      ,				eos_token=__lowercase      ,				unk_token=__lowercase      ,				sep_token=__lowercase      ,				cls_token=__lowercase      ,				pad_token=__lowercase      ,				mask_token=__lowercase      ,				additional_special_tokens=__lowercase      ,				sp_model_kwargs=self.sp_model_kwargs      ,				**__lowercase      ,				)
											__a       =		spm.SentencePieceProcessor(**self.sp_model_kwargs	)
											self.sp_model.Load(str(__lowercase	)	)
											__a       =		vocab_file
											# HACK: These tokens were added by fairseq but don't seem to be actually used when duplicated in the actual
											# sentencepiece vocabulary (this is the case for <s> and </s>
											__a       =		{"""<s>NOTUSED""": 0, """<pad>""": 1, """</s>NOTUSED""": 2, """<unk>""": 3}
											__a       =		len(self.fairseq_tokens_to_ids	)
											__a       =		len(self.sp_model	) + len(self.fairseq_tokens_to_ids	)
											__a       =		{v: k for k, v in self.fairseq_tokens_to_ids.items()}





							def 						UpperCamelCase_					(   self		:		Dict      ,				__lowercase		:		List[int]      ,				__lowercase		:		Optional[List[int]] = None	):

											'''simple docstring'''

											if token_ids_a is None:
															return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
											__a       =		[self.cls_token_id]
											__a       =		[self.sep_token_id]
											return cls + token_ids_a + sep + sep + token_ids_a + sep





							def 						UpperCamelCase_					(   self		:		Union[str, Any]      ,				__lowercase		:		List[int]      ,				__lowercase		:		Optional[List[int]] = None      ,				__lowercase		:		bool = False	):

											'''simple docstring'''
											if already_has_special_tokens:
															return super().get_special_tokens_mask(
															    token_ids_a=__lowercase      ,				token_ids_a=__lowercase      ,				already_has_special_tokens=__lowercase	)

											if token_ids_a is None:
															return [1] + ([0] * len(__lowercase	)) + [1]
											return [1] + ([0] * len(__lowercase	)) + [1, 1] + ([0] * len(__lowercase	)) + [1]





							def 						UpperCamelCase_					(   self		:		Any      ,				__lowercase		:		List[int]      ,				__lowercase		:		Optional[List[int]] = None	):

											'''simple docstring'''
											__a       =		[self.sep_token_id]
											__a       =		[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 + sep + token_ids_a + sep	) * [0]





							@property
							def 						UpperCamelCase_					(   self		:		Optional[int]	):

											'''simple docstring'''
											return len(self.fairseq_tokens_to_ids	) + len(self.sp_model	)





							def 						UpperCamelCase_					(   self		:		int	):

											'''simple docstring'''
											__a       =		{self.convert_ids_to_tokens(__lowercase	): i for i in range(self.vocab_size	)}
											vocab.update(self.added_tokens_encoder	)
											return vocab





							def 						UpperCamelCase_					(   self		:		Tuple      ,				__lowercase		:		str	):

											'''simple docstring'''
											return self.sp_model.encode(__lowercase      ,				out_type=__lowercase	)





							def 						UpperCamelCase_					(   self		:		Optional[Any]      ,				__lowercase		:		Any	):

											'''simple docstring'''
											if token in self.fairseq_tokens_to_ids:
															return self.fairseq_tokens_to_ids[token]
											elif self.sp_model.PieceToId(__lowercase	) == 0:
															# Convert sentence piece unk token to fairseq unk token index
															return self.unk_token_id
											return self.fairseq_offset + self.sp_model.PieceToId(__lowercase	)





							def 						UpperCamelCase_					(   self		:		Optional[Any]      ,				__lowercase		:		Optional[int]	):

											'''simple docstring'''
											if index in self.fairseq_ids_to_tokens:
															return self.fairseq_ids_to_tokens[index]
											return self.sp_model.IdToPiece(index - self.fairseq_offset	)





							def 						UpperCamelCase_					(   self		:		Tuple      ,				__lowercase		:		List[str]	):

											'''simple docstring'''
											__a       =		[]
											__a       =		""""""
											__a       =		False
											for token in tokens:
															# make sure that special tokens are not decoded using sentencepiece model
															if token in self.all_special_tokens:
																			if not prev_is_special:
																							out_string += " "
																			out_string += self.sp_model.decode(__lowercase	) + token
																			__a       =		True
																			__a       =		[]
															else:
																			current_sub_tokens.append(__lowercase	)
																			__a       =		False
											out_string += self.sp_model.decode(__lowercase	)
											return out_string.strip()





							def __getstate__(   self		:		int	):

											'''simple docstring'''
											__a       =		self.__dict__.copy()
											__a       =		None
											return state





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

											'''simple docstring'''
											__a       =		d

											# for backward compatibility
											if not hasattr(self      ,				"""sp_model_kwargs"""	):
															__a       =		{}

											__a       =		spm.SentencePieceProcessor(**self.sp_model_kwargs	)
											self.sp_model.Load(self.vocab_file	)







							def 						UpperCamelCase_					(   self		:		str      ,				__lowercase		:		str      ,				__lowercase		:		Optional[str] = None	):

											'''simple docstring'''
											if not os.path.isdir(__lowercase	):
															logger.error(F"Vocabulary path ({save_directory}) should be a directory"	)
															return
											__a       =		os.path.join(
											    __lowercase      ,				(filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""]	)

											if os.path.abspath(self.vocab_file	) != os.path.abspath(__lowercase	) and os.path.isfile(self.vocab_file	):
															copyfile(self.vocab_file      ,				__lowercase	)
											elif not os.path.isfile(self.vocab_file	):
															with open(__lowercase      ,				"""wb"""	) as fi:
																			__a       =		self.sp_model.serialized_model_proto()
																			fi.write(__lowercase	)

											return (out_vocab_file,)











from __future__ import annotations

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

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

import requests






class    SCREAMING_SNAKE_CASE			(							lowerCamelCase__					):





							def __init__(   self		:		Any      ,				__lowercase		:		str	):

											'''simple docstring'''
											super().__init__()
											__a       =		[]
											__a       =		domain







							def 						UpperCamelCase_					(   self		:		Union[str, Any]      ,				__lowercase		:		str      ,				__lowercase		:		list[tuple[str, str | None]]	):

											'''simple docstring'''
											# Only parse the 'anchor' tag.
											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      ,				__lowercase	)
																											self.urls.append(__lowercase	)



def   lowerCAmelCase__						(							_SCREAMING_SNAKE_CASE       :			str    ):
				"""simple docstring"""







				return ".".join(get_sub_domain_name(_SCREAMING_SNAKE_CASE    ).split("""."""    )[-2:]    )

def   lowerCAmelCase__						(							_SCREAMING_SNAKE_CASE       :			str    ):
				"""simple docstring"""







				return parse.urlparse(_SCREAMING_SNAKE_CASE    ).netloc

def   lowerCAmelCase__						(							_SCREAMING_SNAKE_CASE       :			str = "https://github.com"    ):
				"""simple docstring"""







				__a       =		get_domain_name(_SCREAMING_SNAKE_CASE    )

				# Initialize the parser
				__a       =		Parser(_SCREAMING_SNAKE_CASE    )

				try:
								# Open URL
								__a       =		requests.get(_SCREAMING_SNAKE_CASE    )

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

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


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