


import itertools
from dataclasses import dataclass
from typing import Optional

import pandas as pd
import pyarrow as pa

import datasets
from datasets.table import table_cast







@dataclass
class 	__lowercase    (datasets.BuilderConfig  ):





							"""simple docstring"""







							_UpperCAmelCase      =						None







class 	__lowercase    (datasets.ArrowBasedBuilder  ):





							"""simple docstring"""







							_UpperCAmelCase      =						PandasConfig






							def 					UpperCamelCase__     (      self       ):





										"""simple docstring"""




										return datasets.DatasetInfo(features=self.config.features       )






							def 					UpperCamelCase__     (      self			,						lowerCAmelCase__       ):





										"""simple docstring"""




										if not self.config.data_files:
													raise ValueError(F'''At least one data file must be specified, but got data_files={self.config.data_files}'''       )
										SCREAMING_SNAKE_CASE_		:     str					=					dl_manager.download_and_extract(self.config.data_files       )
										if isinstance(lowerCAmelCase__			,						(str, list, tuple)       ):
													SCREAMING_SNAKE_CASE_		:     int					=					data_files
													if isinstance(lowerCAmelCase__			,						lowerCAmelCase__       ):
																SCREAMING_SNAKE_CASE_		:     int					=					[files]
													# Use `dl_manager.iter_files` to skip hidden files in an extracted archive
													SCREAMING_SNAKE_CASE_		:     Optional[Any]					=					[dl_manager.iter_files(lowerCAmelCase__       ) for file in files]
													return [datasets.SplitGenerator(name=datasets.Split.TRAIN			,						gen_kwargs={'files': files}       )]
										SCREAMING_SNAKE_CASE_		:     Dict					=					[]
										for split_name, files in data_files.items():
													if isinstance(lowerCAmelCase__			,						lowerCAmelCase__       ):
																SCREAMING_SNAKE_CASE_		:     str					=					[files]
													# Use `dl_manager.iter_files` to skip hidden files in an extracted archive
													SCREAMING_SNAKE_CASE_		:     Optional[int]					=					[dl_manager.iter_files(lowerCAmelCase__       ) for file in files]
													splits.append(datasets.SplitGenerator(name=lowerCAmelCase__			,						gen_kwargs={'files': files}       )       )
										return splits






							def 					UpperCamelCase__     (      self			,						lowerCAmelCase__       ):





										"""simple docstring"""




										if self.config.features is not None:
													# more expensive cast to support nested features with keys in a different order
													# allows str <-> int/float or str to Audio for example
													SCREAMING_SNAKE_CASE_		:     List[str]					=					table_cast(lowerCAmelCase__			,						self.config.features.arrow_schema       )
										return pa_table






							def 					UpperCamelCase__     (      self			,						lowerCAmelCase__       ):





										"""simple docstring"""




										for i, file in enumerate(itertools.chain.from_iterable(lowerCAmelCase__       )       ):
													with open(lowerCAmelCase__			,						'rb'       ) as f:
																SCREAMING_SNAKE_CASE_		:     Union[str, Any]					=					pa.Table.from_pandas(pd.read_pickle(lowerCAmelCase__       )       )
																yield i, self._cast_table(lowerCAmelCase__       )







"""simple docstring"""




from json import JSONDecodeError  # Workaround for requests.exceptions.JSONDecodeError

import requests



def 							_lowerCamelCase			(			__a = "isbn/0140328726"     ):
		SCREAMING_SNAKE_CASE_    			=			olid.strip().strip('''/'''     )  # Remove leading/trailing whitespace & slashes
		if new_olid.count('''/'''     ) != 1:
				SCREAMING_SNAKE_CASE_    			=			F'{olid} is not a valid Open Library olid'
				raise ValueError(__a     )
		return requests.get(F'https://openlibrary.org/{new_olid}.json'     ).json()



def 							_lowerCamelCase			(			__a     ):
		SCREAMING_SNAKE_CASE_    			=			{
		    '''title''': '''Title''',
		    '''publish_date''': '''Publish date''',
		    '''authors''': '''Authors''',
		    '''number_of_pages''': '''Number of pages:''',
		    '''first_sentence''': '''First sentence''',
		    '''isbn_10''': '''ISBN (10)''',
		    '''isbn_13''': '''ISBN (13)''',
		}
		SCREAMING_SNAKE_CASE_    			=			{better_key: ol_book_data[key] for key, better_key in desired_keys.items()}
		SCREAMING_SNAKE_CASE_    			=			[
		    get_openlibrary_data(author['''key''']     )['''name'''] for author in data['''Authors''']
		]
		SCREAMING_SNAKE_CASE_    			=			data['''First sentence''']['''value''']
		for key, value in data.items():
				if isinstance(__a,				__a     ):
						SCREAMING_SNAKE_CASE_    			=			''', '''.join(__a     )
		return data


if __name__ == "__main__":
						import doctest

						doctest.testmod()

						while True:
												lowerCAmelCase__				=					input('\nEnter the ISBN code to search (or \'quit\' to stop): ').strip()
												if isbn.lower() in ("", "q", "quit", "exit", "stop"):
																		break

												if len(isbn) not in (10, 13) or not isbn.isdigit():
																		print(f'''Sorry, {isbn} is not a valid ISBN.  Please, input a valid ISBN.''')
																		continue

												print(f'''\nSearching Open Library for ISBN: {isbn}...\n''')

												try:
																		lowerCAmelCase__				=					summarize_book(get_openlibrary_data(f'''isbn/{isbn}'''))
																		print('\n'.join(f'''{key}: {value}''' for key, value in book_summary.items()))
												except JSONDecodeError:  # Workaround for requests.exceptions.RequestException:
																		print(f'''Sorry, there are no results for ISBN: {isbn}.''')