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import os
import sys
import csv
import subprocess
import time
import random
import re
import simplejson as json
import click
from s2 import SemanticScholarAPI
from util import *
'''
s2 search API format:
results
matchedAuthors
matchedPresentations
query
querySuggestions
results
stats
totalPages
totalResults
'''
@click.command()
@click.option('--index', '-n', default=0, help='Index of CSV (query,)')
def fetch_entries(index):
keys, lines = read_citation_list(index)
citation_lookup = []
s2 = SemanticScholarAPI()
for line in lines:
key = line[0]
name = line[1]
title = line[2].trim()
clean_title = re.sub(r'[^-0-9a-zA-Z ]+', '', line[2])
if len(clean_title) < 2:
continue
dump_fn = './datasets/s2/dumps/{}.json'.format(key)
entry_fn = './datasets/s2/entries/{}.json'.format(key)
result = None
if os.path.exists(entry_fn):
result = read_json(entry_fn)
else:
results = s2.search(clean_title)
write_json(dump_fn, results)
if len(results['results']) == 0:
print("- {}".format(title))
else:
print("+ {}".format(title))
result = results['results'][0]
write_json(entry_fn, result)
if result:
paper_id = result['id']
paper = fetch_paper(s2, paper_id)
citation_lookup.append([key, name, title, paper_id])
write_csv("datasets/citation_lookup.csv", keys=['key', 'name', 'title', 'paper_id'], rows=citation_lookup)
def fetch_paper(s2, paper_id):
os.makedirs('./datasets/s2/papers/{}/{}'.format(paper_id[0:2], paper_id), exist_ok=True)
paper_fn = './datasets/s2/papers/{}/{}/paper.json'.format(paper_id[0:2], paper_id)
if os.path.exists(paper_fn):
return read_json(paper_fn)
print(paper_id)
paper = s2.paper(paper_id)
if paper is None:
print("Got none paper??")
# time.sleep(random.randint(1, 2))
paper = s2.paper(paper_id)
if paper is None:
print("Paper not found")
return None
write_json(paper_fn, paper)
# time.sleep(random.randint(1, 2))
return paper
if __name__ == '__main__':
fetch_entries()
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