




'''simple docstring'''






from urllib.error import HTTPError

from bsa import BeautifulSoup
from requests import exceptions, get

lowercase	:      Union[str, Any]				=       """https://www.wellrx.com/prescriptions/{0}/{1}/?freshSearch=true"""




def 		a_( lowerCamelCase   ,				lowerCamelCase      )				->Optional[int]:






       '''simple docstring'''




       try:
              # Has user provided both inputs?
              if not drug_name or not zip_code:
                     return None

              lowercase  :		Optional[Any]						=      BASE_URL.format(lowerCamelCase   ,				lowerCamelCase      )
              lowercase  :		str						=      get(lowerCamelCase      )

              # Is the response ok?
              response.raise_for_status()

              # Scrape the data using bs4
              lowercase  :		int						=      BeautifulSoup(response.text   ,				'''html.parser'''      )

              # This list will store the name and price.
              lowercase  :		Optional[Any]						=      []

              # Fetch all the grids that contains the items.
              lowercase  :		Tuple						=      soup.find_all('''div'''   ,				{'''class''': '''grid-x pharmCard'''}      )
              if grid_list and len(lowerCamelCase      ) > 0:
                     for grid in grid_list:
                            # Get the pharmacy price.
                            lowercase  :		int						=      grid.find('''p'''   ,				{'''class''': '''list-title'''}      ).text

                            # Get price of the drug.
                            lowercase  :		Dict						=      grid.find('''span'''   ,				{'''p''', '''price price-large'''}      ).text

                            pharmacy_price_list.append(
                                {
                                    '''pharmacy_name''': pharmacy_name,
                                    '''price''': price,
                                }      )

              return pharmacy_price_list

       except (HTTPError, exceptions.RequestException, ValueError):
              return None


if __name__ == "__main__":
      # Enter a drug name and a zip code
      lowercase	:      Optional[int]				=       input('''Enter drug name: ''').strip()
      lowercase	:      List[Any]				=       input('''Enter zip code: ''').strip()

      lowercase	:      list | None				=       fetch_pharmacy_and_price_list(
          drug_name, zip_code
      )

      if pharmacy_price_list:
            print(f'\nSearch results for {drug_name} at location {zip_code}:')
            for pharmacy_price in pharmacy_price_list:
                  lowercase	:      Tuple				=       pharmacy_price["""pharmacy_name"""]
                  lowercase	:      str				=       pharmacy_price["""price"""]

                  print(f'Pharmacy: {name} Price: {price}')
      else:
            print(f'No results found for {drug_name}')











'''simple docstring'''






import numpy as np
from PIL import Image




def 		a_( lowerCamelCase      )				->np.array:






       '''simple docstring'''




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




def 		a_( lowerCamelCase      )				->np.array:






       '''simple docstring'''




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




def 		a_( lowerCamelCase   ,				lowerCamelCase      )				->np.array:






       '''simple docstring'''




       lowercase  :		Optional[Any]						=      np.zeros_like(lowerCamelCase      )
       lowercase  :		Any						=      np.zeros(
           (image.shape[0] + kernel.shape[0] - 1, image.shape[1] + kernel.shape[1] - 1)      )

       # Copy image to padded image
       lowercase  :		List[str]						=      image

       # Iterate over image & apply kernel
       for x in range(image.shape[1]      ):
              for y in range(image.shape[0]      ):
                     lowercase  :		Union[str, Any]						=      (
                         kernel * image_padded[y : y + kernel.shape[0], x : x + kernel.shape[1]]
                     ).sum()
                     lowercase  :		Any						=      int(summation == 5      )
       return output


# kernel to be applied
lowercase	:      List[Any]				=       np.array([[0, 1, 0], [1, 1, 1], [0, 1, 0]])

if __name__ == "__main__":
      # read original image
      lowercase	:      Dict				=       np.array(Image.open(r'''..\image_data\lena.jpg'''))
      # Apply erosion operation to a binary image
      lowercase	:      List[str]				=       erosion(grayabinary(rgbagray(image)), structuring_element)
      # Save the output image
      lowercase	:      Optional[Any]				=       Image.fromarray(output).convert('''RGB''')
      pil_img.save('''result_erosion.png''')




