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import re
import os
import gzip
import glob
import simplejson as json
import click
import operator
from util import *
from bs4 import BeautifulSoup
from urllib.parse import unquote
from importlib import import_module
doi = import_module('s2-fetch-doi')
raw_paper = import_module('s2-raw-papers')
DOI_DIR = 'datasets/s2/doi'
@click.command()
def doi_report():
rows = []
domains = {}
institutions = {}
# geocode_lookup = load_geocode_lookup()
addresses = AddressBook()
geocoded_papers = []
unknown_papers = []
unattributed_papers = []
paper_count = 0
ieee_count = 0
springer_count = 0
sciencedirect_count = 0
acm_count = 0
computerorg_count = 0
elsevier_count = 0
unparsed_count = 0
for fn in glob.iglob('{}/**/*.url'.format(DOI_DIR), recursive=True):
paper_count += 1
url_info = read_json(fn)
domain = url_info['domain']
paper_id = url_info['paper_id']
paper = load_paper(paper_id)
if paper is None:
raw_paper.fetch_raw_paper(paper_id, freshen=False)
paper = load_paper(paper_id)
if paper is None:
print("Problem fetching raw paper {}".format(paper_id))
continue
if paper.data is None:
continue
doi_fn = fn.replace('.url', '.doi')
address = None
if domain in domains:
domains[domain] += 1
else:
domains[domain] = 1
affiliations = None
paper_affiliation_count = 0
if 'ieee.org' in domain:
ieee_count += 1
affiliations = load_ieee(paper, doi_fn)
elif 'link.springer.com' in domain:
springer_count += 1
affiliations = load_springer(paper, doi_fn)
elif 'sciencedirect.com' in domain:
sciencedirect_count += 1
affiliations = load_sciencedirect(paper, doi_fn)
elif 'acm.org' in domain:
acm_count += 1
affiliations = load_acm(paper, doi_fn)
elif 'computer.org' in domain:
computerorg_count += 1
affiliations = load_computerorg(paper, doi_fn)
elif 'elsevier.com' in domain:
elsevier_count += 1
affiliations = load_elsevier(paper, doi_fn)
else:
unparsed_count += 1
if affiliations:
for affiliation in affiliations:
if affiliation:
paper_affiliation_count += 1
if affiliation in institutions:
institutions[affiliation] += 1
else:
institutions[affiliation] = 1
address = addresses.find(affiliation)
if not address:
unknown_papers.append([paper.paper_id, paper.title, affiliation])
if paper_affiliation_count == 0:
unattributed_papers.append([paper.paper_id, paper.title])
if address:
geocoded_papers.append([paper.paper_id, paper.title] + address)
domain_list = reversed(sorted(domains.items(), key=operator.itemgetter(1)))
# for domain, count in domain_list:
# print('{}\t{}'.format(count, domain))
institution_list = reversed(sorted(institutions.items(), key=operator.itemgetter(1)))
# for institution, count in institution_list:
# print('{}\t{}'.format(count, institution))
display_institution_list = []
unknown_institution_list = []
for inst in institution_list:
addr = addresses.find(inst[0])
if addr:
display_institution_list.append((BoldLine(inst[0]), inst[1],))
elif len(inst[0]) > 1:
display_institution_list.append(inst)
unknown_institution_list.append(inst)
write_report('reports/doi_domains.html', title='DOI Domains', keys=None, rows=domain_list)
write_report('reports/doi_institutions.html', title='Institutions from IEEE', keys=None, rows=display_institution_list)
write_report('reports/doi_institutions_unknown.html', title='Unknown Institutions from DOI', keys=None, rows=unknown_institution_list)
write_csv('reports/doi_institutions_geocoded.csv', keys=None, rows=geocoded_papers)
write_csv('reports/doi_institutions_unknown.csv', keys=None, rows=unknown_papers)
write_csv('reports/doi_institutions_unattributed.csv', keys=None, rows=unattributed_papers)
print("total papers: {}".format(paper_count))
print(".. ieee: {}".format(ieee_count))
print(".. springer: {}".format(springer_count))
print(".. acm: {}".format(acm_count))
print(".. computerorg: {}".format(computerorg_count))
print(".. sciencedirect: {}".format(sciencedirect_count))
print(".. elsevier: {}".format(elsevier_count))
print(".. unparsed: {}".format(unparsed_count))
print("geocoded papers: {}".format(len(geocoded_papers)))
print("unknown papers: {}".format(len(unknown_papers)))
print("unattributed papers: {}".format(len(unattributed_papers)))
def load_ieee(paper, fn):
with open(fn, 'r') as f:
try:
data = f.read().split('global.document.metadata=')[1].split('</script>')[0].strip()[:-1]
data = json.loads(data)
write_json(fn.replace('paper.doi', 'ieee.json'), data)
# print(data)
except:
#print('ieee: could not read data')
return None
if 'authors' in data:
affiliations = [ author['affiliation'] for author in data['authors'] if 'affiliation' in author ]
institutions = [ [ paper.paper_id, author['affiliation'], author['affiliation'] ] for author in data['authors'] if 'affiliation' in author ]
# print(affiliations)
write_json('{}/{}'.format(paper_path(paper.paper_id), 'institutions.json'), { 'institutions': institutions })
return affiliations
return None
def load_springer(paper, fn):
# print('springer: {}'.format(paper.paper_id))
with open(fn, 'r') as f:
try:
soup = BeautifulSoup(f.read(), 'html.parser')
except:
# print('springer: could not read data')
return None
items = soup.find_all(class_='affiliation__item')
affiliations = [ ', '.join(item.strings) for item in items ]
institutions = [ [ paper.paper_id, affiliation ] for affiliation in affiliations ]
write_json('{}/{}'.format(paper_path(paper.paper_id), 'institutions.json'), { 'institutions': institutions })
return affiliations
def load_sciencedirect(paper, fn):
# print('sciencedirect: {}'.format(paper.paper_id))
with open(fn, 'r') as f:
try:
soup = BeautifulSoup(f.read(), 'html.parser')
except:
# print('sciencedirect: could not read data')
return None
items = soup.find_all("script", type='application/json', limit=1)
if len(items) == 0:
return None
try:
data = json.loads(items[0].string)
write_json(fn.replace('paper.doi', 'sciencedirect.json'), data)
# print(data)
except:
# print('sciencedirect: json error')
return None
affiliations = [value['$$'][0]['_'] for value in data['authors']['affiliations'].values()]
institutions = [ [ paper.paper_id, affiliation ] for affiliation in affiliations ]
write_json('{}/{}'.format(paper_path(paper.paper_id), 'institutions.json'), { 'institutions': institutions })
return affiliations
def load_acm(paper, fn):
# print('acm: {}'.format(paper.paper_id))
with open(fn, 'r') as f:
try:
soup = BeautifulSoup(f.read(), 'html.parser')
except:
#print('acm: could not read data')
return None
items = soup.find_all("a", title='Institutional Profile Page')
affiliations = [ item.string for item in items ]
# print(affiliations)
institutions = [ [ paper.paper_id, affiliation ] for affiliation in affiliations ]
write_json('{}/{}'.format(paper_path(paper.paper_id), 'institutions.json'), { 'institutions': institutions })
return affiliations
def load_computerorg(paper, fn):
# print('computerorg: {}'.format(paper.paper_id))
# if not os.path.exists(doi.old_doi_fn(fn)):
pass
# with open(fn, 'r') as f:
# try:
# soup = BeautifulSoup(f.read(), 'html.parser')
# except:
# print('computerorg: could not read data')
# return None
# items = soup.find_all("a", title='Institutional Profile Page')
# affiliations = [ item.string for item in items ]
# print(affiliations)
# institutions = [ [ paper.paper_id, affiliation ] for affiliation in affiliations ]
# write_json('{}/{}'.format(paper_path(paper.paper_id), 'institutions.json'), { 'institutions': institutions })
# return affiliations
def load_elsevier(paper, fn):
#print('elsevier: {}'.format(paper.paper_id))
if not os.path.exists(doi.old_doi_fn(paper.paper_id)):
with open(fn, 'r') as f:
try:
soup = BeautifulSoup(f.read(), 'html.parser')
except:
#print('elsevier: could not read data')
return None
item = soup.find_all("input", attrs={"name": 'redirectURL'})[0]
#new_url = unquote(item['value'])
#if new_url:
# print(new_url)
# doi.fetch_doi(paper.paper_id, new_url, replace=True)
#else:
# print("missing redirect url: {}".format(paper.paper_id))
# print('elsevier: {}'.format(paper.paper_id))
# with open(fn, 'r') as f:
# try:
# soup = BeautifulSoup(f.read(), 'html.parser')
# except:
# print('elsevier: could not read data')
# return None
# items = soup.find_all("a", title='Institutional Profile Page')
# affiliations = [ item.string for item in items ]
# # print(affiliations)
# institutions = [ [ paper.paper_id, affiliation ] for affiliation in affiliations ]
# write_json('{}/{}'.format(paper_path(paper.paper_id), 'institutions.json'), { 'institutions': institutions })
# return affiliations
def find_authors(authors, line):
for a in authors:
if a[2] in line:
return a
return None
def paper_path(paper_id):
return '{}/{}/{}'.format(DOI_DIR, paper_id[0:2], paper_id)
if __name__ == '__main__':
doi_report()
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