
from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_sentencepiece_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


A		:   Dict         =    {
    '''configuration_big_bird''': ['''BIG_BIRD_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''BigBirdConfig''', '''BigBirdOnnxConfig'''],
}

try:
							if not is_sentencepiece_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							A		:   List[Any]         =    ['''BigBirdTokenizer''']

try:
							if not is_tokenizers_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							A		:   Tuple         =    ['''BigBirdTokenizerFast''']

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							A		:   Optional[Any]         =    [
							    '''BIG_BIRD_PRETRAINED_MODEL_ARCHIVE_LIST''',
							    '''BigBirdForCausalLM''',
							    '''BigBirdForMaskedLM''',
							    '''BigBirdForMultipleChoice''',
							    '''BigBirdForPreTraining''',
							    '''BigBirdForQuestionAnswering''',
							    '''BigBirdForSequenceClassification''',
							    '''BigBirdForTokenClassification''',
							    '''BigBirdLayer''',
							    '''BigBirdModel''',
							    '''BigBirdPreTrainedModel''',
							    '''load_tf_weights_in_big_bird''',
							]

try:
							if not is_flax_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							A		:   Union[str, Any]         =    [
							    '''FlaxBigBirdForCausalLM''',
							    '''FlaxBigBirdForMaskedLM''',
							    '''FlaxBigBirdForMultipleChoice''',
							    '''FlaxBigBirdForPreTraining''',
							    '''FlaxBigBirdForQuestionAnswering''',
							    '''FlaxBigBirdForSequenceClassification''',
							    '''FlaxBigBirdForTokenClassification''',
							    '''FlaxBigBirdModel''',
							    '''FlaxBigBirdPreTrainedModel''',
							]

if TYPE_CHECKING:
							from .configuration_big_bird import BIG_BIRD_PRETRAINED_CONFIG_ARCHIVE_MAP, BigBirdConfig, BigBirdOnnxConfig

							try:
														if not is_sentencepiece_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .tokenization_big_bird import BigBirdTokenizer

							try:
														if not is_tokenizers_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .tokenization_big_bird_fast import BigBirdTokenizerFast

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_big_bird import (
														    BIG_BIRD_PRETRAINED_MODEL_ARCHIVE_LIST,
														    BigBirdForCausalLM,
														    BigBirdForMaskedLM,
														    BigBirdForMultipleChoice,
														    BigBirdForPreTraining,
														    BigBirdForQuestionAnswering,
														    BigBirdForSequenceClassification,
														    BigBirdForTokenClassification,
														    BigBirdLayer,
														    BigBirdModel,
														    BigBirdPreTrainedModel,
														    load_tf_weights_in_big_bird,
														)

							try:
														if not is_flax_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_flax_big_bird import (
														    FlaxBigBirdForCausalLM,
														    FlaxBigBirdForMaskedLM,
														    FlaxBigBirdForMultipleChoice,
														    FlaxBigBirdForPreTraining,
														    FlaxBigBirdForQuestionAnswering,
														    FlaxBigBirdForSequenceClassification,
														    FlaxBigBirdForTokenClassification,
														    FlaxBigBirdModel,
														    FlaxBigBirdPreTrainedModel,
														)

else:
							import sys

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

from urllib.error import HTTPError

from bsa import BeautifulSoup
from requests import exceptions, get

A		:   Union[str, Any]         =    '''https://www.wellrx.com/prescriptions/{0}/{1}/?freshSearch=true'''




def   UpperCamelCase__     (    SCREAMING_SNAKE_CASE_  :  str		,      SCREAMING_SNAKE_CASE_  :  str					)     ->    list | None:

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

												_lowercase									=				BASE_URL.format(SCREAMING_SNAKE_CASE_		,      SCREAMING_SNAKE_CASE_					)
												_lowercase									=				get(SCREAMING_SNAKE_CASE_					)

												# Is the response ok?
												response.raise_for_status()

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

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

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

																								# Get price of the drug.
																								_lowercase									=				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		:   Union[str, Any]         =    input('''Enter drug name: ''').strip()
		A		:   Dict         =    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		:   List[str]         =    pharmacy_price['''pharmacy_name''']
						A		:   Dict         =    pharmacy_price['''price''']

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