
"""simple docstring"""



from __future__ import annotations

_snake_case          =						'''Muhammad Umer Farooq'''
_snake_case          =						'''MIT'''
_snake_case          =						'''1.0.0'''
_snake_case          =						'''Muhammad Umer Farooq'''
_snake_case          =						'''contact@muhammadumerfarooq.me'''
_snake_case          =						'''Alpha'''

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

import requests
class        _SCREAMING_SNAKE_CASE  (  UpperCAmelCase							):






				'''simple docstring'''



				def __init__(					self	:			List[Any]				,     UpperCAmelCase_	:			str  )		->  None:







											"""simple docstring"""




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







				def 				__lowerCamelCase	(					self	:			List[Any]				,     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:
																																							_lowerCAmelCase  	=			parse.urljoin(self.domain				,     UpperCAmelCase_  )
																																							self.urls.append(UpperCAmelCase_  )






def 	__snake_case  (    SCREAMING_SNAKE_CASE:					str						):






							"""simple docstring"""



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






def 	__snake_case  (    SCREAMING_SNAKE_CASE:					str						):






							"""simple docstring"""



							return parse.urlparse(SCREAMING_SNAKE_CASE						).netloc






def 	__snake_case  (    SCREAMING_SNAKE_CASE:					str = "https://github.com"						):






							"""simple docstring"""



							_lowerCAmelCase  	=			get_domain_name(SCREAMING_SNAKE_CASE						)

							# Initialize the parser
							_lowerCAmelCase  	=			Parser(SCREAMING_SNAKE_CASE						)

							try:
														# Open URL
														_lowerCAmelCase  	=			requests.get(SCREAMING_SNAKE_CASE						)

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

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








"""simple docstring"""



from pathlib import Path

import numpy as np
from PIL import Image






def 	__snake_case  (    SCREAMING_SNAKE_CASE:					np.ndarray						):






							"""simple docstring"""



							_lowerCAmelCase	,		_lowerCAmelCase	,		_lowerCAmelCase  	=			rgb[:, :, 0], rgb[:, :, 1], rgb[:, :, 2]
							return 0.29_89 * r + 0.58_70 * g + 0.11_40 * b






def 	__snake_case  (    SCREAMING_SNAKE_CASE:					np.ndarray						):






							"""simple docstring"""



							return (gray > 127) & (gray <= 255)






def 	__snake_case  (    SCREAMING_SNAKE_CASE:					np.ndarray     ,  SCREAMING_SNAKE_CASE:					np.ndarray						):






							"""simple docstring"""



							_lowerCAmelCase  	=			np.zeros_like(SCREAMING_SNAKE_CASE						)
							_lowerCAmelCase  	=			np.zeros(
							    (image.shape[0] + kernel.shape[0] - 1, image.shape[1] + kernel.shape[1] - 1)						)

							# Copy image to padded image
							_lowerCAmelCase  	=			image

							# Iterate over image & apply kernel
							for x in range(image.shape[1]						):
														for y in range(image.shape[0]						):
																					_lowerCAmelCase  	=			(
																					    kernel * image_padded[y : y + kernel.shape[0], x : x + kernel.shape[1]]
																					).sum()
																					_lowerCAmelCase  	=			int(summation > 0						)
							return output


if __name__ == "__main__":
	# read original image
	_snake_case          =						Path(__file__).resolve().parent / '''image_data''' / '''lena.jpg'''
	_snake_case          =						np.array(Image.open(lena_path))
	# kernel to be applied
	_snake_case          =						np.array([[0, 1, 0], [1, 1, 1], [0, 1, 0]])
	_snake_case          =						dilation(gray_to_binary(rgb_to_gray(lena)), structuring_element)
	# Save the output image
	_snake_case          =						Image.fromarray(output).convert('''RGB''')
	pil_img.save('''result_dilation.png''')






