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()