






"""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__  ,     UpperCamelCase__       ):



		'''simple docstring'''

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

				_a						: Tuple    =			BASE_URL.format(UpperCamelCase__  ,     UpperCamelCase__       )
				_a						: Dict    =			get(UpperCamelCase__       )

				# Is the response ok?
				response.raise_for_status()

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

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

				# Fetch all the grids that contains the items.
				_a						: Dict    =			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						: Tuple    =			grid.find("""p"""  ,     {"""class""": """list-title"""}       ).text

								# Get price of the drug.
								_a						: Optional[int]    =			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"""




import os
import unittest

from transformers.models.bertweet.tokenization_bertweet import VOCAB_FILES_NAMES, BertweetTokenizer

from ...test_tokenization_common import TokenizerTesterMixin






class  UpperCamelCase    (			snake_case_	,  unittest.TestCase   ):
 UpperCamelCase      : Union[str, Any]    =      BertweetTokenizer
 UpperCamelCase      : Optional[Any]    =      False


 def _lowercase			(  self	:		Dict							)      -> List[Any]:
   super().setUp()

   # Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
   _a						: Tuple    =			["""I""", """m""", """V@@""", """R@@""", """r""", """e@@"""]
   _a						: str    =			dict(zip(UpperCAmelCase__							,		range(len(UpperCAmelCase__							)							)							)							)
   _a						: Dict    =			["""#version: 0.2""", """a m</w>"""]
   _a						: int    =			{"""unk_token""": """<unk>"""}

   _a						: Union[str, Any]    =			os.path.join(self.tmpdirname							,		VOCAB_FILES_NAMES["""vocab_file"""]							)
   _a						: List[Any]    =			os.path.join(self.tmpdirname							,		VOCAB_FILES_NAMES["""merges_file"""]							)
   with open(self.vocab_file							,		"""w"""							,		encoding="""utf-8"""							) as fp:
     for token in vocab_tokens:
       fp.write(f"""{token} {vocab_tokens[token]}\n"""							)
   with open(self.merges_file							,		"""w"""							,		encoding="""utf-8"""							) as fp:
     fp.write("""\n""".join(UpperCAmelCase__							)							)


 def _lowercase			(  self	:		Any							,		**UpperCAmelCase__	:		Optional[Any]							)      -> Dict:
   kwargs.update(self.special_tokens_map							)
   return BertweetTokenizer.from_pretrained(self.tmpdirname							,		**UpperCAmelCase__							)


 def _lowercase			(  self	:		Dict							,		UpperCAmelCase__	:		Optional[int]							)      -> Dict:
   _a						: List[str]    =			"""I am VinAI Research"""
   _a						: Optional[int]    =			"""I <unk> m V<unk> <unk> <unk> I Re<unk> e<unk> <unk> <unk> <unk>"""
   return input_text, output_text







 def _lowercase			(  self	:		Tuple							)      -> Optional[int]:
   _a						: Optional[int]    =			BertweetTokenizer(self.vocab_file							,		self.merges_file							,		**self.special_tokens_map							)
   _a						: Tuple    =			"""I am VinAI Research"""
   _a						: Dict    =			"""I a@@ m V@@ i@@ n@@ A@@ I R@@ e@@ s@@ e@@ a@@ r@@ c@@ h""".split()
   _a						: str    =			tokenizer.tokenize(UpperCAmelCase__							)
   self.assertListEqual(UpperCAmelCase__							,		UpperCAmelCase__							)

   _a						: Tuple    =			tokens + [tokenizer.unk_token]

   _a						: Tuple    =			[4, 3, 5, 6, 3, 3, 3, 4, 7, 9, 3, 9, 3, 3, 3, 3, 3]
   self.assertListEqual(tokenizer.convert_tokens_to_ids(UpperCAmelCase__							)							,		UpperCAmelCase__							)

