





'''simple docstring'''






from urllib.error import HTTPError

from bsa import BeautifulSoup
from requests import exceptions, get

snake_case_     			=						"""https://www.wellrx.com/prescriptions/{0}/{1}/?freshSearch=true"""
def 				_lowerCamelCase(	UpperCamelCase__     :			str     ,							UpperCamelCase__     :			str		)		->	list | None:

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

        A							:							Tuple				=    BASE_URL.format(UpperCamelCase__     ,							UpperCamelCase__		)
        A							:							List[Any]				=    get(UpperCamelCase__		)

        # Is the response ok?
        response.raise_for_status()

        # Scrape the data using bs4
        A							:							List[Any]				=    BeautifulSoup(response.text     ,							'''html.parser'''		)

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

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

                # Get price of the drug.
                A							:							List[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
     snake_case_     			=						input("""Enter drug name: """).strip()
     snake_case_     			=						input("""Enter zip code: """).strip()

     snake_case_     			=						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:
               snake_case_     			=						pharmacy_price["""pharmacy_name"""]
               snake_case_     			=						pharmacy_price["""price"""]

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







'''simple docstring'''






from collections import OrderedDict
from typing import Mapping

from packaging import version

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


snake_case_     			=						logging.get_logger(__name__)

snake_case_     			=						{
    """apple/mobilevit-small""": """https://huggingface.co/apple/mobilevit-small/resolve/main/config.json""",
    """apple/mobilevit-x-small""": """https://huggingface.co/apple/mobilevit-x-small/resolve/main/config.json""",
    """apple/mobilevit-xx-small""": """https://huggingface.co/apple/mobilevit-xx-small/resolve/main/config.json""",
    """apple/deeplabv3-mobilevit-small""": (
        """https://huggingface.co/apple/deeplabv3-mobilevit-small/resolve/main/config.json"""
    ),
    """apple/deeplabv3-mobilevit-x-small""": (
        """https://huggingface.co/apple/deeplabv3-mobilevit-x-small/resolve/main/config.json"""
    ),
    """apple/deeplabv3-mobilevit-xx-small""": (
        """https://huggingface.co/apple/deeplabv3-mobilevit-xx-small/resolve/main/config.json"""
    ),
    # See all MobileViT models at https://huggingface.co/models?filter=mobilevit
}


class 	_lowercase    (				a					):
   _UpperCamelCase									= """mobilevit"""


   def __init__(			self     , _UpperCAmelCase=3     , _UpperCAmelCase=256     , _UpperCAmelCase=2     , _UpperCAmelCase=[144, 192, 240]     , _UpperCAmelCase=[16, 32, 64, 96, 128, 160, 640]     , _UpperCAmelCase=4     , _UpperCAmelCase=2.0     , _UpperCAmelCase=4.0     , _UpperCAmelCase="silu"     , _UpperCAmelCase=3     , _UpperCAmelCase=32     , _UpperCAmelCase=0.1     , _UpperCAmelCase=0.0     , _UpperCAmelCase=0.1     , _UpperCAmelCase=0.02     , _UpperCAmelCase=1E-5     , _UpperCAmelCase=True     , _UpperCAmelCase=256     , _UpperCAmelCase=[6, 12, 18]     , _UpperCAmelCase=0.1     , _UpperCAmelCase=255     , **_UpperCAmelCase     , ):
       super().__init__(**_UpperCAmelCase       )

       A							:							Union[str, Any]				=    num_channels
       A							:							Union[str, Any]				=    image_size
       A							:							List[str]				=    patch_size
       A							:							Any				=    hidden_sizes
       A							:							Dict				=    neck_hidden_sizes
       A							:							int				=    num_attention_heads
       A							:							List[str]				=    mlp_ratio
       A							:							List[Any]				=    expand_ratio
       A							:							Dict				=    hidden_act
       A							:							List[Any]				=    conv_kernel_size
       A							:							List[str]				=    output_stride
       A							:							Dict				=    hidden_dropout_prob
       A							:							List[str]				=    attention_probs_dropout_prob
       A							:							Optional[Any]				=    classifier_dropout_prob
       A							:							Any				=    initializer_range
       A							:							Union[str, Any]				=    layer_norm_eps
       A							:							Union[str, Any]				=    qkv_bias

       # decode head attributes for semantic segmentation
       A							:							int				=    aspp_out_channels
       A							:							Any				=    atrous_rates
       A							:							Tuple				=    aspp_dropout_prob
       A							:							List[Any]				=    semantic_loss_ignore_index







class 	_lowercase    (				a					):
   _UpperCamelCase									= version.parse("""1.11"""					)


   @property
   def        snake_case					(			self       ):
       return OrderedDict([('''pixel_values''', {0: '''batch''', 1: '''num_channels''', 2: '''height''', 3: '''width'''})]       )


   @property
   def        snake_case					(			self       ):
       if self.task == "image-classification":
           return OrderedDict([('''logits''', {0: '''batch'''})]       )
       else:
           return OrderedDict([('''last_hidden_state''', {0: '''batch'''}), ('''pooler_output''', {0: '''batch'''})]       )


   @property
   def        snake_case					(			self       ):
       return 1E-4
