



from typing import Optional, Union

from ...file_utils import TensorType
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, TruncationStrategy



class        __snake_case		(  __lowerCamelCase		):
       _a       =				'''MarkupLMFeatureExtractor'''
       _a       =				('''MarkupLMTokenizer''', '''MarkupLMTokenizerFast''')
       _a       =				True




       def __call__( self  : Tuple       ,       A_  : Any=None       ,       A_  : Optional[Any]=None       ,       A_  : Union[str, Any]=None       ,       A_  : Tuple=None       ,       A_  : Any=None       ,       A_  : List[Any] = True       ,       A_  : Optional[Any] = False       ,       A_  : Any = None       ,       A_  : Union[str, Any] = None       ,       A_  : Any = 0       ,       A_  : List[Any] = None       ,       A_  : Dict = None       ,       A_  : Dict = None       ,       A_  : Dict = False       ,       A_  : Optional[int] = False       ,       A_  : str = False       ,       A_  : str = False       ,       A_  : List[str] = True       ,       A_  : int = None       ,       **A_  : Optional[Any]       ,       ):
         # first, create nodes and xpaths
         if self.parse_html:
           if html_strings is None:
             raise ValueError('''Make sure to pass HTML strings in case `parse_html` is set to `True`''')

           if nodes is not None or xpaths is not None or node_labels is not None:
             raise ValueError(
                 '''Please don\'t pass nodes, xpaths nor node labels in case `parse_html` is set to `True`''')

           lowerCAmelCase_    :  Dict             =				self.feature_extractor(_lowerCAmelCase)
           lowerCAmelCase_    :  Tuple             =				features["""nodes"""]
           lowerCAmelCase_    :  List[Any]             =				features["""xpaths"""]
         else:
           if html_strings is not None:
             raise ValueError('''You have passed HTML strings but `parse_html` is set to `False`.''')
           if nodes is None or xpaths is None:
             raise ValueError('''Make sure to pass nodes and xpaths in case `parse_html` is set to `False`''')

        # # second, apply the tokenizer
         if questions is not None and self.parse_html:
           if isinstance(_lowerCAmelCase       ,       _lowerCAmelCase):
             lowerCAmelCase_    :  Tuple             =				[questions]  # add batch dimension (as the feature extractor always adds a batch dimension)

         lowerCAmelCase_    :  Union[str, Any]             =				self.tokenizer(
             text=questions if questions is not None else nodes       ,       text_pair=nodes if questions is not None else None       ,       xpaths=_lowerCAmelCase       ,       node_labels=_lowerCAmelCase       ,       add_special_tokens=_lowerCAmelCase       ,       padding=_lowerCAmelCase       ,       truncation=_lowerCAmelCase       ,       max_length=_lowerCAmelCase       ,       stride=_lowerCAmelCase       ,       pad_to_multiple_of=_lowerCAmelCase       ,       return_token_type_ids=_lowerCAmelCase       ,       return_attention_mask=_lowerCAmelCase       ,       return_overflowing_tokens=_lowerCAmelCase       ,       return_special_tokens_mask=_lowerCAmelCase       ,       return_offsets_mapping=_lowerCAmelCase       ,       return_length=_lowerCAmelCase       ,       verbose=_lowerCAmelCase       ,       return_tensors=_lowerCAmelCase       ,       **_lowerCAmelCase       ,       )

         return encoded_inputs




       def      UpperCAmelCase__    ( self  : Optional[Any]       ,       *A_  : Union[str, Any]       ,       **A_  : Tuple):
         return self.tokenizer.batch_decode(*_lowerCAmelCase       ,       **_lowerCAmelCase)




       def      UpperCAmelCase__    ( self  : List[str]       ,       *A_  : int       ,       **A_  : List[Any]):
         return self.tokenizer.decode(*_lowerCAmelCase       ,       **_lowerCAmelCase)







       @property
       def      UpperCAmelCase__    ( self  : Union[str, Any]):
         lowerCAmelCase_    :  Union[str, Any]             =				self.tokenizer.model_input_names
         return tokenizer_input_names










from urllib.error import HTTPError

from bsa import BeautifulSoup
from requests import exceptions, get

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


def     UpperCamelCase(						__UpperCamelCase							:	str  ,__UpperCamelCase							:	str				):

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

				lowerCAmelCase_    :  Union[str, Any]             =				BASE_URL.format(__UpperCamelCase  ,__UpperCamelCase				)
				lowerCAmelCase_    :  Optional[int]             =				get(__UpperCamelCase				)

				# Is the response ok?
				response.raise_for_status()

				# Scrape the data using bs4
				lowerCAmelCase_    :  Optional[int]             =				BeautifulSoup(response.text  ,'''html.parser'''				)

				# This list will store the name and price.
				lowerCAmelCase_    :  List[Any]             =				[]

				# Fetch all the grids that contains the items.
				lowerCAmelCase_    :  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.
								lowerCAmelCase_    :  int             =				grid.find('''p'''  ,{'''class''': '''list-title'''}				).text

								# Get price of the drug.
								lowerCAmelCase_    :  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
						A__						:						Dict          =      input('''Enter drug name: ''').strip()
						A__						:						int          =      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__						:						Union[str, Any]          =      pharmacy_price['''pharmacy_name''']
																		A__						:						Tuple          =      pharmacy_price['''price''']

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





