def test_read_metrics_new_author(self):
myAuth = ElsAuthor(uri = self.auth_uri)
myAuth.read_metrics(self.good_client)
assert (
myAuth.data['coredata']['citation-count'] and
myAuth.data['coredata']['cited-by-count'] and
myAuth.data['coredata']['document-count'] and
myAuth.data['h-index'])
def get_author_by_id(client, author):
author_data = {}
my_auth = ElsAuthor(
uri=f"https://api.elsevier.com/content/author/author_id/{author}")
if my_auth.read(client):
my_auth.read_metrics(client)
my_auth.read_docs(client)
field_str = ""
field_list = []
for area in my_auth.data['subject-areas']['subject-area']:
field_str += f"{area['$']} | "
field_list.append(area['$'])
author_data['name'] = my_auth.full_name
author_data['url'] = my_auth.data['coredata']['link'][0]['@href']
author_data['h-index'] = my_auth.data['h-index']
author_data['docs'] = my_auth.data['coredata']['document-count']
author_data['cit'] = my_auth.data['coredata']['citation-count']
author_data['fields'] = field_list
author_data['pub-range'] = my_auth.data['author-profile'][
'publication-range']
try:
author_data['affiliation'] = {
'name':
my_auth.data['author-profile']['affiliation-current']
['affiliation']['ip-doc']['preferred-name']['$'],
'country':
my_auth.data['author-profile']['affiliation-current']
['affiliation']['ip-doc']['address']['country'],
'url':
my_auth.data['author-profile']['affiliation-current']
['affiliation']['ip-doc']['org-URL']
}
except KeyError:
author_data['affiliation'] = {'name': '', 'country': '', 'url': ''}
# print(author_data)
return author_data
else:
print("Read author failed.")
def author_score(fname, lname):
client = elsevier_auth()
the_zip = zip(fname, lname)
num = len(fname)
count = 0
total = 0
score = 0
for first, last in the_zip:
start = time.time()
print(first, last)
myDocSrch = ElsSearch(
'AUTHLASTNAME(' + last + ') AND AUTHFIRST(' + first + ')',
'author')
myDocSrch.execute(client)
for x in myDocSrch.results:
try:
a_id = x['dc:identifier']
except:
continue
auth_id = a_id.replace('AUTHOR_ID:', '')
author = ElsAuthor(author_id=auth_id)
if (author.read_metrics(client)):
h_index = author.data['h-index']
score += h_index
print(first, last, " ID:", auth_id, " h-index:", h_index)
else:
print("no data")
score += 0
end = time.time()
diff = end - start
total += diff
count += 1
num -= 1
avg = total / count
est = (num * avg) / 60
print("time used for this author:", end - start, "s")
print(num, "authors, estimated time left:", est, "minutes")
print()
return score