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import os
import sys
import csv
import subprocess
import time
import random
import re
import json
import click
from s2 import SemanticScholarAPI
from util import *
s2 = SemanticScholarAPI()
@click.command()
@click.option('--fn', '-i', default='db_paper_pdf.csv', help='Filename of CSV (id, url,)')
def fetch_pdfs(fn):
lines = read_csv(fn, keys=False)
for line in lines:
paper_id, url = line
fetch_pdf(paper_id, url)
print("{} papers processed".format(len(lines)))
def fetch_pdf(paper_id, url):
os.makedirs(make_pdf_path(paper_id), exist_ok=True)
pdf_fn = make_pdf_fn(paper_id)
txt_fn = make_txt_fn(paper_id)
if os.path.exists(pdf_fn) or os.path.exists(txt_fn):
# return read_json(pdf_fn)
return
size = s2.fetch_file(url, pdf_fn)
if size is None:
print("{} empty?".format(paper_id))
time.sleep(random.randint(5, 10))
return None
print("{} {} kb".format(paper_id, int(size / 1024)))
time.sleep(random.randint(5, 10))
return
# return paper
def make_pdf_path(paper_id):
return './datasets/s2/pdf/{}/{}'.format(paper_id[0:2], paper_id)
def make_pdf_fn(paper_id):
return './datasets/s2/pdf/{}/{}/paper.pdf'.format(paper_id[0:2], paper_id)
def make_txt_fn(paper_id):
return './datasets/s2/pdf/{}/{}/paper.txt'.format(paper_id[0:2], paper_id)
if __name__ == '__main__':
fetch_pdfs()
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