


from urllib.error import HTTPError

from bsa import BeautifulSoup
from requests import exceptions, get

__SCREAMING_SNAKE_CASE	:							Optional[Any]           =  '''https://www.wellrx.com/prescriptions/{0}/{1}/?freshSearch=true'''

def 		snake_case_   (				lowercase__     :    str       ,     lowercase__     :    str     ):






				'''simple docstring'''






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

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

								# 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(lowercase__     ) > 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
		__SCREAMING_SNAKE_CASE	:							Any           =  input('''Enter drug name: ''').strip()
		__SCREAMING_SNAKE_CASE	:							Optional[int]           =  input('''Enter zip code: ''').strip()

		__SCREAMING_SNAKE_CASE	:							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:
						__SCREAMING_SNAKE_CASE	:							List[str]           =  pharmacy_price['''pharmacy_name''']
						__SCREAMING_SNAKE_CASE	:							Union[str, Any]           =  pharmacy_price['''price''']

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





from typing import TYPE_CHECKING

# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available, is_torch_available


__SCREAMING_SNAKE_CASE	:							str           =  {
    '''configuration_ernie_m''': ['''ERNIE_M_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''ErnieMConfig'''],
}

try:
		if not is_sentencepiece_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		__SCREAMING_SNAKE_CASE	:							Any           =  ['''ErnieMTokenizer''']

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		__SCREAMING_SNAKE_CASE	:							Tuple           =  [
		    '''ERNIE_M_PRETRAINED_MODEL_ARCHIVE_LIST''',
		    '''ErnieMForMultipleChoice''',
		    '''ErnieMForQuestionAnswering''',
		    '''ErnieMForSequenceClassification''',
		    '''ErnieMForTokenClassification''',
		    '''ErnieMModel''',
		    '''ErnieMPreTrainedModel''',
		    '''ErnieMForInformationExtraction''',
		]


if TYPE_CHECKING:
		from .configuration_ernie_m import ERNIE_M_PRETRAINED_CONFIG_ARCHIVE_MAP, ErnieMConfig

		try:
				if not is_sentencepiece_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .tokenization_ernie_m import ErnieMTokenizer

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_ernie_m import (
				    ERNIE_M_PRETRAINED_MODEL_ARCHIVE_LIST,
				    ErnieMForInformationExtraction,
				    ErnieMForMultipleChoice,
				    ErnieMForQuestionAnswering,
				    ErnieMForSequenceClassification,
				    ErnieMForTokenClassification,
				    ErnieMModel,
				    ErnieMPreTrainedModel,
				)


else:
		import sys

		__SCREAMING_SNAKE_CASE	:							str           =  _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)

