




import numpy as np
from cva import COLOR_BGR2GRAY, cvtColor, imread
from numpy import array, uinta
from PIL import Image

from digital_image_processing import change_contrast as cc
from digital_image_processing import convert_to_negative as cn
from digital_image_processing import sepia as sp
from digital_image_processing.dithering import burkes as bs
from digital_image_processing.edge_detection import canny
from digital_image_processing.filters import convolve as conv
from digital_image_processing.filters import gaussian_filter as gg
from digital_image_processing.filters import local_binary_pattern as lbp
from digital_image_processing.filters import median_filter as med
from digital_image_processing.filters import sobel_filter as sob
from digital_image_processing.resize import resize as rs

UpperCAmelCase_									=	imread(r'digital_image_processing/image_data/lena_small.jpg')
UpperCAmelCase_									=	cvtColor(img, COLOR_BGR2GRAY)




def 					lowerCamelCase__       (						):





       '''simple docstring'''



       __lowerCamelCase   =						cn.convert_to_negative(A__	)
       # assert negative_img array for at least one True
       assert negative_img.any()




def 					lowerCamelCase__       (						):





       '''simple docstring'''



       with Image.open("""digital_image_processing/image_data/lena_small.jpg"""	) as img:
              # Work around assertion for response
              assert str(cc.change_contrast(A__  ,			110	)	).startswith(
                  """<PIL.Image.Image image mode=RGB size=100x100 at"""	)




def 					lowerCamelCase__       (						):





       '''simple docstring'''



       __lowerCamelCase   =						canny.gen_gaussian_kernel(9  ,			sigma=1.4	)
       # Assert ambiguous array
       assert resp.all()




def 					lowerCamelCase__       (						):





       '''simple docstring'''



       __lowerCamelCase   =						imread("""digital_image_processing/image_data/lena_small.jpg"""  ,			0	)
       # assert ambiguous array for all == True
       assert canny_img.all()
       __lowerCamelCase   =						canny.canny(A__	)
       # assert canny array for at least one True
       assert canny_array.any()




def 					lowerCamelCase__       (						):





       '''simple docstring'''



       assert gg.gaussian_filter(A__  ,			5  ,			sigma=0.9	).all()




def 					lowerCamelCase__       (						):





       '''simple docstring'''



       __lowerCamelCase   =						array([[0.25, 0.5, 0.25], [0.5, -3, 0.5], [0.25, 0.5, 0.25]]	)
       __lowerCamelCase   =						conv.img_convolve(A__  ,			A__	).astype(A__	)
       assert res.any()




def 					lowerCamelCase__       (						):





       '''simple docstring'''



       assert med.median_filter(A__  ,			3	).any()




def 					lowerCamelCase__       (						):





       '''simple docstring'''



       __lowerCamelCase,   __lowerCamelCase   =						sob.sobel_filter(A__	)
       assert grad.any() and theta.any()




def 					lowerCamelCase__       (						):





       '''simple docstring'''



       __lowerCamelCase   =						sp.make_sepia(A__  ,			20	)
       assert sepia.all()




def 					lowerCamelCase__       (						A__       :					str = "digital_image_processing/image_data/lena_small.jpg"	):





       '''simple docstring'''



       __lowerCamelCase   =						bs.Burkes(imread(A__  ,			1	)  ,			120	)
       burkes.process()
       assert burkes.output_img.any()




def 					lowerCamelCase__       (						A__       :					str = "digital_image_processing/image_data/lena_small.jpg"  ,			):





       '''simple docstring'''



       __lowerCamelCase   =						rs.NearestNeighbour(imread(A__  ,			1	)  ,			400  ,			200	)
       nn.process()
       assert nn.output.any()




def 					lowerCamelCase__       (						):





       '''simple docstring'''



       __lowerCamelCase   =						"""digital_image_processing/image_data/lena.jpg"""

       # Reading the image and converting it to grayscale.
       __lowerCamelCase   =						imread(A__  ,			0	)

       # Test for get_neighbors_pixel function() return not None
       __lowerCamelCase   =						0
       __lowerCamelCase   =						0
       __lowerCamelCase   =						image[x_coordinate][y_coordinate]

       __lowerCamelCase   =						lbp.get_neighbors_pixel(
           A__  ,			A__  ,			A__  ,			A__	)

       assert neighbors_pixels is not None

       # Test for local_binary_pattern function()
       # Create a numpy array as the same height and width of read image
       __lowerCamelCase   =						np.zeros((image.shape[0], image.shape[1])	)

       # Iterating through the image and calculating the local binary pattern value
       # for each pixel.
       for i in range(0  ,			image.shape[0]	):
              for j in range(0  ,			image.shape[1]	):
                     __lowerCamelCase   =						lbp.local_binary_value(A__  ,			A__  ,			A__	)

       assert lbp_image.any()









"""simple docstring"""



import requests
from bsa import BeautifulSoup
def 						_SCREAMING_SNAKE_CASE (    __snake_case			:  str = "AAPL"    ):





  '''simple docstring'''





  lowercase							    =       f'https://in.finance.yahoo.com/quote/{symbol}?s={symbol}'
  lowercase							    =       BeautifulSoup(requests.get(__snake_case    ).text		,					'html.parser'    )
  lowercase							    =       'My(6px) Pos(r) smartphone_Mt(6px)'
  return soup.find('div'		,					class_=class_    ).find('span'    ).text


if __name__ == "__main__":
    for symbol in "AAPL AMZN IBM GOOG MSFT ORCL".split():
        print(F'''Current {symbol:<4} stock price is {stock_price(symbol):>8}''')


