
'''simple docstring'''







from urllib.error import HTTPError

from bsa import BeautifulSoup
from requests import exceptions, get

_lowercase				:						str												= "https://www.wellrx.com/prescriptions/{0}/{1}/?freshSearch=true"
def       snake_case_	(       __SCREAMING_SNAKE_CASE      :				str   ,   __SCREAMING_SNAKE_CASE      :				str							):



						"""simple docstring"""





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

												lowercase_			:  str									= BASE_URL.format(__SCREAMING_SNAKE_CASE   ,   __SCREAMING_SNAKE_CASE							)
												lowercase_			:  Dict									= get(__SCREAMING_SNAKE_CASE							)

												# Is the response ok?
												response.raise_for_status()

												# Scrape the data using bs4
												lowercase_			:  Union[str, Any]									= BeautifulSoup(response.text   ,   '''html.parser'''							)

												# This list will store the name and price.
												lowercase_			:  str									= []

												# Fetch all the grids that contains the items.
												lowercase_			:  Tuple									= 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_			:  List[str]									= grid.find('''p'''   ,   {'''class''': '''list-title'''}							).text

																								# Get price of the drug.
																								lowercase_			:  str									= 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
							_lowercase				:						Any												= input("Enter drug name: ").strip()
							_lowercase				:						Dict												= input("Enter zip code: ").strip()

							_lowercase				:						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:
																					_lowercase				:						Optional[int]												= pharmacy_price["pharmacy_name"]
																					_lowercase				:						Optional[int]												= pharmacy_price["price"]

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





'''simple docstring'''







import multiprocessing
import os
from typing import BinaryIO, Optional, Union

from .. import Dataset, Features, NamedSplit, config
from ..formatting import query_table
from ..packaged_modules.csv.csv import Csv
from ..utils import logging
from ..utils.typing import NestedDataStructureLike, PathLike
from .abc import AbstractDatasetReader






class 				lowerCAmelCase__     (						lowerCamelCase_  ):






					def __init__(     self       ,							__SCREAMING_SNAKE_CASE       ,							__SCREAMING_SNAKE_CASE = None       ,							__SCREAMING_SNAKE_CASE = None       ,							__SCREAMING_SNAKE_CASE = None       ,							__SCREAMING_SNAKE_CASE = False       ,							__SCREAMING_SNAKE_CASE = False       ,							__SCREAMING_SNAKE_CASE = None       ,							**__SCREAMING_SNAKE_CASE       ,							):


											"""simple docstring"""





											super().__init__(
											    __SCREAMING_SNAKE_CASE       ,							split=__SCREAMING_SNAKE_CASE       ,							features=__SCREAMING_SNAKE_CASE       ,							cache_dir=__SCREAMING_SNAKE_CASE       ,							keep_in_memory=__SCREAMING_SNAKE_CASE       ,							streaming=__SCREAMING_SNAKE_CASE       ,							num_proc=__SCREAMING_SNAKE_CASE       ,							**__SCREAMING_SNAKE_CASE       ,							)
											lowercase_			:  int									= path_or_paths if isinstance(__SCREAMING_SNAKE_CASE       ,							__SCREAMING_SNAKE_CASE	) else {self.split: path_or_paths}
											lowercase_			:  List[Any]									= Csv(
											    cache_dir=__SCREAMING_SNAKE_CASE       ,							data_files=__SCREAMING_SNAKE_CASE       ,							features=__SCREAMING_SNAKE_CASE       ,							**__SCREAMING_SNAKE_CASE       ,							)






					def 			_snake_case					(     self	):


											"""simple docstring"""





											if self.streaming:
																	lowercase_			:  List[str]									= self.builder.as_streaming_dataset(split=self.split	)
											# Build regular (map-style) dataset
											else:
																	lowercase_			:  Any									= None
																	lowercase_			:  Optional[Any]									= None
																	lowercase_			:  str									= None
																	lowercase_			:  Optional[int]									= None

																	self.builder.download_and_prepare(
																	    download_config=__SCREAMING_SNAKE_CASE       ,							download_mode=__SCREAMING_SNAKE_CASE       ,							verification_mode=__SCREAMING_SNAKE_CASE       ,							base_path=__SCREAMING_SNAKE_CASE       ,							num_proc=self.num_proc       ,							)
																	lowercase_			:  Tuple									= self.builder.as_dataset(
																	    split=self.split       ,							verification_mode=__SCREAMING_SNAKE_CASE       ,							in_memory=self.keep_in_memory	)
											return dataset







class 				lowerCAmelCase__     :






					def __init__(     self       ,							__SCREAMING_SNAKE_CASE       ,							__SCREAMING_SNAKE_CASE       ,							__SCREAMING_SNAKE_CASE = None       ,							__SCREAMING_SNAKE_CASE = None       ,							**__SCREAMING_SNAKE_CASE       ,							):


											"""simple docstring"""





											if num_proc is not None and num_proc <= 0:
																	raise ValueError(F'''num_proc {num_proc} must be an integer > 0.'''	)

											lowercase_			:  List[Any]									= dataset
											lowercase_			:  Dict									= path_or_buf
											lowercase_			:  int									= batch_size if batch_size else config.DEFAULT_MAX_BATCH_SIZE
											lowercase_			:  int									= num_proc
											lowercase_			:  Optional[int]									= '''utf-8'''
											lowercase_			:  Optional[Any]									= to_csv_kwargs






					def 			_snake_case					(     self	):


											"""simple docstring"""





											lowercase_			:  List[str]									= self.to_csv_kwargs.pop('''path_or_buf'''       ,							__SCREAMING_SNAKE_CASE	)
											lowercase_			:  Optional[Any]									= self.to_csv_kwargs.pop('''header'''       ,							__SCREAMING_SNAKE_CASE	)
											lowercase_			:  Dict									= self.to_csv_kwargs.pop('''index'''       ,							__SCREAMING_SNAKE_CASE	)

											if isinstance(self.path_or_buf       ,							(str, bytes, os.PathLike)	):
																	with open(self.path_or_buf       ,							'''wb+'''	) as buffer:
																							lowercase_			:  Any									= self._write(file_obj=__SCREAMING_SNAKE_CASE       ,							header=__SCREAMING_SNAKE_CASE       ,							index=__SCREAMING_SNAKE_CASE       ,							**self.to_csv_kwargs	)
											else:
																	lowercase_			:  str									= self._write(file_obj=self.path_or_buf       ,							header=__SCREAMING_SNAKE_CASE       ,							index=__SCREAMING_SNAKE_CASE       ,							**self.to_csv_kwargs	)
											return written






					def 			_snake_case					(     self       ,							__SCREAMING_SNAKE_CASE	):


											"""simple docstring"""





											lowercase_		,				lowercase_		,				lowercase_		,				lowercase_			:  int									= args

											lowercase_			:  List[str]									= query_table(
											    table=self.dataset.data       ,							key=slice(__SCREAMING_SNAKE_CASE       ,							offset + self.batch_size	)       ,							indices=self.dataset._indices       ,							)
											lowercase_			:  Dict									= batch.to_pandas().to_csv(
											    path_or_buf=__SCREAMING_SNAKE_CASE       ,							header=header if (offset == 0) else False       ,							index=__SCREAMING_SNAKE_CASE       ,							**__SCREAMING_SNAKE_CASE	)
											return csv_str.encode(self.encoding	)






					def 			_snake_case					(     self       ,							__SCREAMING_SNAKE_CASE       ,							__SCREAMING_SNAKE_CASE       ,							__SCREAMING_SNAKE_CASE       ,							**__SCREAMING_SNAKE_CASE	):


											"""simple docstring"""





											lowercase_			:  Dict									= 0

											if self.num_proc is None or self.num_proc == 1:
																	for offset in logging.tqdm(
																	    range(0       ,							len(self.dataset	)       ,							self.batch_size	)       ,							unit='''ba'''       ,							disable=not logging.is_progress_bar_enabled()       ,							desc='''Creating CSV from Arrow format'''       ,							):
																							lowercase_			:  Any									= self._batch_csv((offset, header, index, to_csv_kwargs)	)
																							written += file_obj.write(__SCREAMING_SNAKE_CASE	)

											else:
																	lowercase_		,				lowercase_			:  Union[str, Any]									= len(self.dataset	), self.batch_size
																	with multiprocessing.Pool(self.num_proc	) as pool:
																							for csv_str in logging.tqdm(
																							    pool.imap(
																							        self._batch_csv       ,							[(offset, header, index, to_csv_kwargs) for offset in range(0       ,							__SCREAMING_SNAKE_CASE       ,							__SCREAMING_SNAKE_CASE	)]       ,							)       ,							total=(num_rows // batch_size) + 1 if num_rows % batch_size else num_rows // batch_size       ,							unit='''ba'''       ,							disable=not logging.is_progress_bar_enabled()       ,							desc='''Creating CSV from Arrow format'''       ,							):
																													written += file_obj.write(__SCREAMING_SNAKE_CASE	)

											return written



