
"""simple docstring"""




import argparse
import logging
import pickle
import random
import time

import numpy as np

from transformers import BertTokenizer, GPTaTokenizer, RobertaTokenizer


logging.basicConfig(
    format='%(asctime)s - %(levelname)s - %(name)s - %(message)s', datefmt='%m/%d/%Y %H:%M:%S', level=logging.INFO
)
lowerCAmelCase__				=					logging.getLogger(__name__)



def 							_lowerCamelCase			(			):
		SCREAMING_SNAKE_CASE_    			=			argparse.ArgumentParser(
		    description='''Preprocess the data to avoid re-doing it several times by (tokenization + token_to_ids).'''     )
		parser.add_argument('''--file_path''',				type=__a,				default='''data/dump.txt''',				help='''The path to the data.'''     )
		parser.add_argument('''--tokenizer_type''',				type=__a,				default='''bert''',				choices=['''bert''', '''roberta''', '''gpt2''']     )
		parser.add_argument('''--tokenizer_name''',				type=__a,				default='''bert-base-uncased''',				help='''The tokenizer to use.'''     )
		parser.add_argument('''--dump_file''',				type=__a,				default='''data/dump''',				help='''The dump file prefix.'''     )
		SCREAMING_SNAKE_CASE_    			=			parser.parse_args()

		logger.info(F'Loading Tokenizer ({args.tokenizer_name})'     )
		if args.tokenizer_type == "bert":
				SCREAMING_SNAKE_CASE_    			=			BertTokenizer.from_pretrained(args.tokenizer_name     )
				SCREAMING_SNAKE_CASE_    			=			tokenizer.special_tokens_map['''cls_token''']  # `[CLS]`
				SCREAMING_SNAKE_CASE_    			=			tokenizer.special_tokens_map['''sep_token''']  # `[SEP]`
		elif args.tokenizer_type == "roberta":
				SCREAMING_SNAKE_CASE_    			=			RobertaTokenizer.from_pretrained(args.tokenizer_name     )
				SCREAMING_SNAKE_CASE_    			=			tokenizer.special_tokens_map['''cls_token''']  # `<s>`
				SCREAMING_SNAKE_CASE_    			=			tokenizer.special_tokens_map['''sep_token''']  # `</s>`
		elif args.tokenizer_type == "gpt2":
				SCREAMING_SNAKE_CASE_    			=			GPTaTokenizer.from_pretrained(args.tokenizer_name     )
				SCREAMING_SNAKE_CASE_    			=			tokenizer.special_tokens_map['''bos_token''']  # `<|endoftext|>`
				SCREAMING_SNAKE_CASE_    			=			tokenizer.special_tokens_map['''eos_token''']  # `<|endoftext|>`

		logger.info(F'Loading text from {args.file_path}'     )
		with open(args.file_path,				'''r''',				encoding='''utf8'''     ) as fp:
				SCREAMING_SNAKE_CASE_    			=			fp.readlines()

		logger.info('''Start encoding'''     )
		logger.info(F'{len(__a     )} examples to process.'     )

		SCREAMING_SNAKE_CASE_    			=			[]
		SCREAMING_SNAKE_CASE_    			=			0
		SCREAMING_SNAKE_CASE_    			=			10_000
		SCREAMING_SNAKE_CASE_    			=			time.time()
		for text in data:
				SCREAMING_SNAKE_CASE_    			=			F'{bos} {text.strip()} {sep}'
				SCREAMING_SNAKE_CASE_    			=			tokenizer.encode(__a,				add_special_tokens=__a     )
				rslt.append(__a     )

				iter += 1
				if iter % interval == 0:
						SCREAMING_SNAKE_CASE_    			=			time.time()
						logger.info(F'{iter} examples processed. - {(end-start):.2f}s/{interval}expl'     )
						SCREAMING_SNAKE_CASE_    			=			time.time()
		logger.info('''Finished binarization'''     )
		logger.info(F'{len(__a     )} examples processed.'     )

		SCREAMING_SNAKE_CASE_    			=			F'{args.dump_file}.{args.tokenizer_name}.pickle'
		SCREAMING_SNAKE_CASE_    			=			tokenizer.vocab_size
		if vocab_size < (1 << 16):
				SCREAMING_SNAKE_CASE_    			=			[np.uintaa(__a     ) for d in rslt]
		else:
				SCREAMING_SNAKE_CASE_    			=			[np.intaa(__a     ) for d in rslt]
		random.shuffle(rslt_     )
		logger.info(F'Dump to {dp_file}'     )
		with open(__a,				'''wb'''     ) as handle:
				pickle.dump(rslt_,				__a,				protocol=pickle.HIGHEST_PROTOCOL     )


if __name__ == "__main__":
						main()

"""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}.''')