



"""simple docstring"""





import requests
from bsa import BeautifulSoup




def 						UpperCAmelCase  (		A						:    str  ,					A						:    dict							):

		'''simple docstring'''


		_UpperCAmelCase							=		BeautifulSoup(requests.get(__A  ,					params=__A							).content  ,					'html.parser'							)
		_UpperCAmelCase							=		soup.find('div'  ,					attrs={'class': 'gs_ri'}							)
		_UpperCAmelCase							=		div.find('div'  ,					attrs={'class': 'gs_fl'}							).find_all('a'							)
		return anchors[2].get_text()


if __name__ == "__main__":
					lowercase					=       {
					    'title': (
					        'Precisely geometry controlled microsupercapacitors for ultrahigh areal '
					        'capacitance, volumetric capacitance, and energy density'
					    ),
					    'journal': 'Chem. Mater.',
					    'volume': 30,
					    'pages': '3979-3990',
					    'year': 20_18,
					    'hl': 'en',
					}
					print(get_citation('''https://scholar.google.com/scholar_lookup''', params=params))







"""simple docstring"""

import argparse
import json

from tqdm import tqdm
def  __snake_case							(	)     ->       Any:






				'''simple docstring'''
				SCREAMING_SNAKE_CASE						:							str							=     argparse.ArgumentParser()

				# Required parameters
				parser.add_argument(
				    '--src_path'							,		type=__A							,		default='biencoder-nq-dev.json'							,		help='Path to raw DPR training data'							,		)
				parser.add_argument(
				    '--evaluation_set'							,		type=__A							,		help='where to store parsed evaluation_set file'							,		)
				parser.add_argument(
				    '--gold_data_path'							,		type=__A							,		help='where to store parsed gold_data_path file'							,		)
				SCREAMING_SNAKE_CASE						:							Tuple							=     parser.parse_args()

				with open(args.src_path							,		'r'     ) as src_file, open(args.evaluation_set							,		'w'     ) as eval_file, open(
				    args.gold_data_path							,		'w'     ) as gold_file:
								SCREAMING_SNAKE_CASE						:							Tuple							=     json.load(__A     )
								for dpr_record in tqdm(__A     ):
												SCREAMING_SNAKE_CASE						:							Tuple							=     dpr_record['question']
												SCREAMING_SNAKE_CASE						:							Optional[int]							=     [context['title'] for context in dpr_record['positive_ctxs']]
												eval_file.write(question + '\n'     )
												gold_file.write('\t'.join(__A     ) + '\n'     )


if __name__ == "__main__":
							main()





