"""simple docstring"""


from urllib.error import HTTPError

from bsa import BeautifulSoup
from requests import exceptions, get

__UpperCamelCase										=     '''https://www.wellrx.com/prescriptions/{0}/{1}/?freshSearch=true'''







def    UpperCAmelCase       (						UpperCAmelCase		,   UpperCAmelCase   )							-> list | None:

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

          snake_case_   			=   BASE_URL.format(UpperCAmelCase		,   UpperCAmelCase   )
          snake_case_   			=   get(UpperCAmelCase   )

          # Is the response ok?
          response.raise_for_status()

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

          # This list will store the name and price.
          snake_case_   			=   []

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

                    # Get price of the drug.
                    snake_case_   			=   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
    __UpperCamelCase										=     input('''Enter drug name: ''').strip()
    __UpperCamelCase										=     input('''Enter zip code: ''').strip()

    __UpperCamelCase										=     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:
            __UpperCamelCase										=     pharmacy_price['''pharmacy_name''']
            __UpperCamelCase										=     pharmacy_price['''price''']

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


"""simple docstring"""


from ...configuration_utils import PretrainedConfig
from ...utils import logging


__UpperCamelCase										=     logging.get_logger(__name__)

__UpperCamelCase										=     {
    '''uw-madison/nystromformer-512''': '''https://huggingface.co/uw-madison/nystromformer-512/resolve/main/config.json''',
    # See all Nystromformer models at https://huggingface.co/models?filter=nystromformer
}




class 					UpperCamelCase   (							lowerCAmelCase__  ):
       SCREAMING_SNAKE_CASE_						      = "nystromformer"







       def __init__(					self,				lowerCAmelCase__=3_0000,				lowerCAmelCase__=768,				lowerCAmelCase__=12,				lowerCAmelCase__=12,				lowerCAmelCase__=3072,				lowerCAmelCase__="gelu_new",				lowerCAmelCase__=0.1,				lowerCAmelCase__=0.1,				lowerCAmelCase__=510,				lowerCAmelCase__=2,				lowerCAmelCase__=64,				lowerCAmelCase__=64,				lowerCAmelCase__=65,				lowerCAmelCase__=False,				lowerCAmelCase__=0.02,				lowerCAmelCase__=1e-5,				lowerCAmelCase__=1,				lowerCAmelCase__=0,				lowerCAmelCase__=2,				**lowerCAmelCase__,				) -> Optional[Any]:
            snake_case_   			=   vocab_size
            snake_case_   			=   max_position_embeddings
            snake_case_   			=   hidden_size
            snake_case_   			=   num_hidden_layers
            snake_case_   			=   num_attention_heads
            snake_case_   			=   intermediate_size
            snake_case_   			=   hidden_act
            snake_case_   			=   hidden_dropout_prob
            snake_case_   			=   attention_probs_dropout_prob
            snake_case_   			=   initializer_range
            snake_case_   			=   type_vocab_size
            snake_case_   			=   segment_means_seq_len
            snake_case_   			=   num_landmarks
            snake_case_   			=   conv_kernel_size
            snake_case_   			=   inv_coeff_init_option
            snake_case_   			=   layer_norm_eps
            super().__init__(pad_token_id=lowerCAmelCase__,				bos_token_id=lowerCAmelCase__,				eos_token_id=lowerCAmelCase__,				**lowerCAmelCase__)

