


"""simple docstring"""




import numpy as np
import PIL
import torch
import torchvision.transforms as T
import torchvision.transforms.functional as TF
from PIL import Image

def 				lowercase_		(		_A      :   str   , _A      :   str=256						):

      """simple docstring"""




      lowerCamelCase__		:    Optional[int]   =  min(img.size						)

      if s < target_image_size:
            raise ValueError(F"min dim for image {s} < {target_image_size}"						)

      lowerCamelCase__		:    List[Any]   =  target_image_size / s
      lowerCamelCase__		:    List[str]   =  (round(r * img.size[1]						), round(r * img.size[0]						))
      lowerCamelCase__		:    int   =  TF.resize(_A   , _A   , interpolation=PIL.Image.LANCZOS						)
      lowerCamelCase__		:    int   =  TF.center_crop(_A   , output_size=2 * [target_image_size]						)
      lowerCamelCase__		:    Optional[int]   =  torch.unsqueeze(T.ToTensor()(_A						)   , 0						)
      return img

def 				lowercase_		(		_A      :   List[str]						):

      """simple docstring"""




      lowerCamelCase__		:    Tuple   =  2.0 * x - 1.0
      return x

def 				lowercase_		(		_A      :   Any   , _A      :   int=True   , _A      :   Optional[int]="RGB"						):

      """simple docstring"""




      lowerCamelCase__		:    Dict   =  x.detach().cpu()
      if process:
            lowerCamelCase__		:    Union[str, Any]   =  post_process_tensor(_A						)
      lowerCamelCase__		:    Any   =  x.numpy()
      if process:
            lowerCamelCase__		:    Optional[Any]   =  (255 * x).astype(np.uinta						)
      lowerCamelCase__		:    Dict   =  Image.fromarray(_A						)
      if not x.mode == mode:
            lowerCamelCase__		:    Union[str, Any]   =  x.convert(_A						)
      return x

def 				lowercase_		(		_A      :   Union[str, Any]						):

      """simple docstring"""




      lowerCamelCase__		:    List[str]   =  torch.clamp(_A   , -1.0   , 1.0						)
      lowerCamelCase__		:    Dict   =  (x + 1.0) / 2.0
      lowerCamelCase__		:    Union[str, Any]   =  x.permute(1   , 2   , 0						)
      return x


def 				lowercase_		(		_A      :   str						):

      """simple docstring"""




      lowerCamelCase__		:    int   =  post_process_tensor(x.squeeze()						)
      return x.permute(2   , 0   , 1						).unsqueeze(0						)






from urllib.error import HTTPError

from bsa import BeautifulSoup
from requests import exceptions, get

A				:   List[str]		= "https://www.wellrx.com/prescriptions/{0}/{1}/?freshSearch=true"

def 				lowercase_		(		_A      :   str   , _A      :   str						):

      """simple docstring"""




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

            lowerCamelCase__		:    List[str]   =  BASE_URL.format(_A   , _A						)
            lowerCamelCase__		:    int   =  get(_A						)

            # Is the response ok?
            response.raise_for_status()

            # Scrape the data using bs4
            lowerCamelCase__		:    Dict   =  BeautifulSoup(response.text   , "html.parser"						)

            # This list will store the name and price.
            lowerCamelCase__		:    int   =  []

            # Fetch all the grids that contains the items.
            lowerCamelCase__		:    List[str]   =  soup.find_all("div"   , {"class": "grid-x pharmCard"}						)
            if grid_list and len(_A						) > 0:
                  for grid in grid_list:
                        # Get the pharmacy price.
                        lowerCamelCase__		:    Optional[int]   =  grid.find("p"   , {"class": "list-title"}						).text

                        # Get price of the drug.
                        lowerCamelCase__		:    Union[str, Any]   =  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
    A				:   Any		= input("Enter drug name: ").strip()
    A				:   Union[str, Any]		= input("Enter zip code: ").strip()

    A				:   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:
            A				:   Dict		= pharmacy_price["pharmacy_name"]
            A				:   Optional[int]		= pharmacy_price["price"]

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


