



from typing import List, Optional, Tuple

from tokenizers import pre_tokenizers

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_clip import CLIPTokenizer


A__     				=	logging.get_logger(__name__)

A__     				=	{"""vocab_file""": """vocab.json""", """merges_file""": """merges.txt""", """tokenizer_file""": """tokenizer.json"""}

A__     				=	{
    """vocab_file""": {
        """openai/clip-vit-base-patch32""": """https://huggingface.co/openai/clip-vit-base-patch32/resolve/main/vocab.json""",
    },
    """merges_file""": {
        """openai/clip-vit-base-patch32""": """https://huggingface.co/openai/clip-vit-base-patch32/resolve/main/merges.txt""",
    },
    """tokenizer_file""": {
        """openai/clip-vit-base-patch32""": (
            """https://huggingface.co/openai/clip-vit-base-patch32/resolve/main/tokenizer.json"""
        ),
    },
}

A__     				=	{
    """openai/clip-vit-base-patch32""": 77,
}





class  __lowerCAmelCase			(					lowerCamelCase__	):
				__lowerCamelCase			=    VOCAB_FILES_NAMES
				__lowerCamelCase			=    PRETRAINED_VOCAB_FILES_MAP
				__lowerCamelCase			=    PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
				__lowerCamelCase			=    ['''input_ids''', '''attention_mask''']
				__lowerCamelCase			=    CLIPTokenizer




				def __init__(							self						,    _snake_case=None						,    _snake_case=None						,    _snake_case=None						,    _snake_case="<|endoftext|>"						,    _snake_case="<|startoftext|>"						,    _snake_case="<|endoftext|>"						,    _snake_case="<|endoftext|>"						,    **_snake_case						,    ):



									"""simple docstring"""





									super().__init__(
									    _snake_case						,    _snake_case						,    tokenizer_file=_snake_case						,    unk_token=_snake_case						,    bos_token=_snake_case						,    eos_token=_snake_case						,    pad_token=_snake_case						,    **_snake_case						,    )

									if not isinstance(self.backend_tokenizer.pre_tokenizer						,    pre_tokenizers.Sequence		):
														raise ValueError(
														    """The `backend_tokenizer` provided does not match the expected format. The CLIP tokenizer has been"""
														    """ heavily modified from transformers version 4.17.0. You need to convert the tokenizer you are using"""
														    """ to be compatible with this version.The easiest way to do so is"""
														    """ `CLIPTokenizerFast.from_pretrained(\"path_to_local_folder_or_hub_repo, from_slow=True)`. If you want"""
														    """ to use your existing tokenizer, you will have to revert to a version prior to 4.17.0 of"""
														    """ transformers."""		)

									self._wrap_decode_method_backend_tokenizer()




				def 							snake_case       (							self		):



									"""simple docstring"""





									_lowerCAmelCase      =   self.backend_tokenizer.decode

									def new_decode_method(*_snake_case						,    **_snake_case		):
														_lowerCAmelCase      =   orig_decode_method(*_snake_case						,    **_snake_case		)
														_lowerCAmelCase      =   text.replace(self.backend_tokenizer.model.end_of_word_suffix						,    """ """		).strip()
														return text

									_lowerCAmelCase      =   new_decode_method




				def 							snake_case       (							self						,    _snake_case						,    _snake_case = None		):



									"""simple docstring"""





									_lowerCAmelCase      =   [self.bos_token_id]
									_lowerCAmelCase      =   [self.eos_token_id]

									if token_ids_a is None:
														return bos_token + token_ids_a + eos_token
									return bos_token + token_ids_a + eos_token + eos_token + token_ids_a + eos_token




				def 							snake_case       (							self						,    _snake_case						,    _snake_case = None		):



									"""simple docstring"""





									_lowerCAmelCase      =   [self.bos_token_id]
									_lowerCAmelCase      =   [self.eos_token_id]

									if token_ids_a is None:
														return len(bos_token + token_ids_a + eos_token		) * [0]
									return len(bos_token + token_ids_a + eos_token + eos_token + token_ids_a + eos_token		) * [0]




				def 							snake_case       (							self						,    _snake_case						,    _snake_case = None		):



									"""simple docstring"""





									_lowerCAmelCase      =   self._tokenizer.model.save(_snake_case						,    name=_snake_case		)
									return tuple(_snake_case		)








from urllib.error import HTTPError

from bsa import BeautifulSoup
from requests import exceptions, get

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


def 		_UpperCAmelCase    (				snake_case     ,						snake_case      ):





					"""simple docstring"""

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

										_lowerCAmelCase      =   BASE_URL.format(snake_case     ,						snake_case      )
										_lowerCAmelCase      =   get(snake_case      )

										# Is the response ok?
										response.raise_for_status()

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

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

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

																				# Get price of the drug.
																				_lowerCAmelCase      =   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__     				=	input("""Enter drug name: """).strip()
	A__     				=	input("""Enter zip code: """).strip()

	A__     				=	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__     				=	pharmacy_price["""pharmacy_name"""]
			A__     				=	pharmacy_price["""price"""]

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



