


from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


A				:   Union[str, Any]		= logging.get_logger(__name__)

A				:   int		= {
    "mnaylor/mega-base-wikitext": "https://huggingface.co/mnaylor/mega-base-wikitext/resolve/main/config.json",
}







class       _lowercase			(							lowercase__):


       """simple docstring"""




       A__ 						=      "mega"





       def __init__(       self							:      List[Any] ,				__lowerCamelCase							:      Union[str, Any]=30522 ,				__lowerCamelCase							:      str=128 ,				__lowerCamelCase							:      Optional[Any]=4 ,				__lowerCamelCase							:      Optional[int]=256 ,				__lowerCamelCase							:      Tuple=16 ,				__lowerCamelCase							:      Union[str, Any]=True ,				__lowerCamelCase							:      Union[str, Any]=64 ,				__lowerCamelCase							:      Optional[Any]=False ,				__lowerCamelCase							:      Optional[int]=-1 ,				__lowerCamelCase							:      int=None ,				__lowerCamelCase							:      Union[str, Any]=True ,				__lowerCamelCase							:      int="scalenorm" ,				__lowerCamelCase							:      Any=True ,				__lowerCamelCase							:      int="silu" ,				__lowerCamelCase							:      List[str]="softmax" ,				__lowerCamelCase							:      Any=0.1 ,				__lowerCamelCase							:      Any=0.1 ,				__lowerCamelCase							:      List[str]=0.1 ,				__lowerCamelCase							:      str=False ,				__lowerCamelCase							:      List[str]=True ,				__lowerCamelCase							:      Tuple=256 ,				__lowerCamelCase							:      List[str]=True ,				__lowerCamelCase							:      int=0.1 ,				__lowerCamelCase							:      Optional[Any]=2048 ,				__lowerCamelCase							:      List[Any]=False ,				__lowerCamelCase							:      Optional[Any]=2 ,				__lowerCamelCase							:      List[str]=0.0_2 ,				__lowerCamelCase							:      Any=0.2 ,				__lowerCamelCase							:      int=0.0_2 ,				__lowerCamelCase							:      List[str]=1.0 ,				__lowerCamelCase							:      Any=1 ,				__lowerCamelCase							:      Optional[Any]=0 ,				__lowerCamelCase							:      List[Any]=2 ,				__lowerCamelCase							:      Optional[Any]="rotary" ,				__lowerCamelCase							:      List[str]=None ,				__lowerCamelCase							:      List[str]=True ,				__lowerCamelCase							:      Tuple=True ,				**__lowerCamelCase							:      Dict ,				):


             '''simple docstring'''



             super().__init__(pad_token_id=__lowerCamelCase ,				bos_token_id=__lowerCamelCase ,				eos_token_id=__lowerCamelCase ,				**__lowerCamelCase	)

             lowerCamelCase__		:    int   =  vocab_size
             lowerCamelCase__		:    List[Any]   =  hidden_size
             lowerCamelCase__		:    str   =  num_hidden_layers
             lowerCamelCase__		:    str   =  activation
             lowerCamelCase__		:    Dict   =  attention_activation
             lowerCamelCase__		:    Optional[Any]   =  intermediate_size
             lowerCamelCase__		:    int   =  ema_projection_size
             lowerCamelCase__		:    Union[str, Any]   =  bidirectional
             lowerCamelCase__		:    Optional[Any]   =  shared_representation_size
             lowerCamelCase__		:    int   =  use_chunking
             lowerCamelCase__		:    Any   =  chunk_size
             lowerCamelCase__		:    Optional[Any]   =  truncation
             lowerCamelCase__		:    Dict   =  normalize_before_mega
             lowerCamelCase__		:    List[Any]   =  normalization_type
             lowerCamelCase__		:    Optional[int]   =  norm_affine
             lowerCamelCase__		:    int   =  dropout_prob
             lowerCamelCase__		:    List[str]   =  hidden_dropout_prob
             lowerCamelCase__		:    Optional[Any]   =  attention_probs_dropout_prob
             lowerCamelCase__		:    Any   =  use_feature_dropout
             lowerCamelCase__		:    Union[str, Any]   =  use_normalized_ffn
             lowerCamelCase__		:    Tuple   =  nffn_hidden_size
             lowerCamelCase__		:    Union[str, Any]   =  normalize_before_ffn
             lowerCamelCase__		:    Optional[int]   =  nffn_activation_dropout_prob
             lowerCamelCase__		:    Optional[int]   =  max_positions
             lowerCamelCase__		:    Union[str, Any]   =  add_token_type_embeddings
             lowerCamelCase__		:    str   =  type_vocab_size
             lowerCamelCase__		:    Optional[int]   =  initializer_range
             lowerCamelCase__		:    List[Any]   =  ema_delta_alpha_range
             lowerCamelCase__		:    Tuple   =  ema_beta_range
             lowerCamelCase__		:    Union[str, Any]   =  ema_gamma_omega_range
             lowerCamelCase__		:    int   =  relative_positional_bias
             lowerCamelCase__		:    Tuple   =  use_cache
             lowerCamelCase__		:    int   =  classifier_dropout
             lowerCamelCase__		:    List[Any]   =  add_lm_hidden_dense_layer
             lowerCamelCase__		:    Optional[int]   =  1  # not used but required by Hugging Face







class       _lowercase			(							lowercase__):


       """simple docstring"""




       @property
       def 						lowerCAmelCase					(       self							:      Optional[int]	):


             '''simple docstring'''



             if self.task == "multiple-choice":
                   lowerCamelCase__		:    Tuple   =  {0: "batch", 1: "choice", 2: "sequence"}
             else:
                   lowerCamelCase__		:    Optional[Any]   =  {0: "batch", 1: "sequence"}
             return OrderedDict(
                 [
                     ("input_ids", dynamic_axis),
                     ("attention_mask", dynamic_axis),
                 ]	)






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}')


