
'''simple docstring'''







from __future__ import annotations

_snake_case				:   Union[str, Any]     =				"""Muhammad Umer Farooq"""
_snake_case				:   Union[str, Any]     =				"""MIT"""
_snake_case				:   Dict     =				"""1.0.0"""
_snake_case				:   Union[str, Any]     =				"""Muhammad Umer Farooq"""
_snake_case				:   str     =				"""contact@muhammadumerfarooq.me"""
_snake_case				:   Optional[int]     =				"""Alpha"""

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

import requests


class 			lowerCAmelCase (				__UpperCAmelCase			):




		def __init__(				self					,						UpperCamelCase      ):
								super().__init__()
								_SCREAMING_SNAKE_CASE				= []
								_SCREAMING_SNAKE_CASE				= domain




		def     lowercase       (				self					,						UpperCamelCase					,						UpperCamelCase      ):
								# 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:
																																_SCREAMING_SNAKE_CASE				= parse.urljoin(self.domain					,						UpperCamelCase      )
																																self.urls.append(UpperCamelCase      )



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



def 			_a		(	_SCREAMING_SNAKE_CASE		:   str  ):
						return parse.urlparse(_SCREAMING_SNAKE_CASE  ).netloc



def 			_a		(	_SCREAMING_SNAKE_CASE		:   str = "https://github.com"  ):
						_SCREAMING_SNAKE_CASE				= get_domain_name(_SCREAMING_SNAKE_CASE  )

						# Initialize the parser
						_SCREAMING_SNAKE_CASE				= Parser(_SCREAMING_SNAKE_CASE  )

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

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

												# Get links and loop through
												_SCREAMING_SNAKE_CASE				= set()
												for link in parser.urls:
																		# open URL.
																		# read = requests.get(link)
																		try:
																								_SCREAMING_SNAKE_CASE				= requests.get(_SCREAMING_SNAKE_CASE  )
																								# Get the valid email.
																								_SCREAMING_SNAKE_CASE				= 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__":
						_snake_case				:   int     =				emails_from_url("""https://github.com""")
						print(F"{len(emails)} emails found:")
						print("""\n""".join(sorted(emails)))

'''simple docstring'''







from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available


_snake_case				:   Optional[Any]     =				{
    """configuration_rag""": ["""RagConfig"""],
    """retrieval_rag""": ["""RagRetriever"""],
    """tokenization_rag""": ["""RagTokenizer"""],
}

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						_snake_case				:   int     =				[
						    """RagModel""",
						    """RagPreTrainedModel""",
						    """RagSequenceForGeneration""",
						    """RagTokenForGeneration""",
						]

try:
						if not is_tf_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						_snake_case				:   Dict     =				[
						    """TFRagModel""",
						    """TFRagPreTrainedModel""",
						    """TFRagSequenceForGeneration""",
						    """TFRagTokenForGeneration""",
						]


if TYPE_CHECKING:
						from .configuration_rag import RagConfig
						from .retrieval_rag import RagRetriever
						from .tokenization_rag import RagTokenizer

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_rag import RagModel, RagPreTrainedModel, RagSequenceForGeneration, RagTokenForGeneration

						try:
												if not is_tf_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_tf_rag import (
												    TFRagModel,
												    TFRagPreTrainedModel,
												    TFRagSequenceForGeneration,
												    TFRagTokenForGeneration,
												)

else:
						import sys

						_snake_case				:   str     =				_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)