class AltmetricUpdate:
QUERY_INTERVAL_SEC = 0.0
def __init__(self, api_key):
self.altmetric = Altmetric(api_key=api_key)
self.last_query = None
def update(self, paper):
if self.last_query:
elapsed_time_sec = time.time() - self.last_query
if self.QUERY_INTERVAL_SEC > 0.0 and elapsed_time_sec < self.QUERY_INTERVAL_SEC:
time.sleep(int(ceil(self.QUERY_INTERVAL_SEC - elapsed_time_sec)))
if paper.data_source_value == DataSource.ARXIV:
data = self.altmetric.arxiv(paper.doi[6:])
else:
data = self.altmetric.doi(paper.doi)
self.last_query = time.time()
if data and data['score'] > 0.0:
if not paper.altmetric_data:
paper.altmetric_data = AltmetricData.objects.create()
paper.altmetric_data.score = data['score']
paper.altmetric_data.score_d = data['history']['1d']
paper.altmetric_data.score_w = data['history']['1w']
paper.altmetric_data.score_1m = data['history']['1m']
paper.altmetric_data.score_3m = data['history']['3m']
paper.altmetric_data.score_6m = data['history']['6m']
paper.altmetric_data.score_y = data['history']['1y']
paper.altmetric_data.save()
paper.last_altmetric_update = timezone.now()
paper.save()
def update(self):
print("Pulling questions from RM site...")
data = {
get_qid(q): {
'doi': get_doi(q)
}
for q in Bot(api_key=API_KEY).get_citation_questions()
}
print("Done!\n")
if 'alt' in self.services:
print("Pulling data from altmetrics...")
for i, (qid, paper) in enumerate(data.items()):
print(f"Paper {i+1} of {len(data)}...")
data[qid]['mendeley'] = int(Altmetric().article_from_doi(
paper["doi"]).readers['mendeley'])
print("Done!\n")
if 'scite' in self.services:
pass
self._data = data
self.save()
# fetch_multiple_doi.py
#
# This example shows how to use pyAltmetric to make multiple calls for
# citations using a list of DOIs (Digital Object Identifier).
#
from pyaltmetric import Altmetric, Citation
import json
# list of target DOIs
dois = ('10.1038/news.2011.49', '10.1038/nj7361-479a', '10.1136/bmj.c6801',
'10.1038/nature.2014.14583', '10.1038/news.2011.498')
# initialize an Altmetric instance
a = Altmetric()
# iterate through DOIs fetching each citation from api.altmetric.com
citations = map(a.doi, dois)
# write citation objects as json to a file
with open('citations_as_json.txt', 'w+') as outfile:
json.dump(citations, outfile)
def get_altmetric(thisdoi):
a = Altmetric()
alt = a.doi(thisdoi.split("doi.org/")[1])
return int(alt["score"])
from pyaltmetric import Altmetric, Citation, HTTPException
import csv
# initialize Altmetric
a = Altmetric()
with open('doi.list', 'r') as infile:
with open('results.csv', 'w') as outfile:
writer = csv.writer(outfile)
for x in infile:
x = x.rstrip()
# search for article using doi
c = a.doi(x)
if c:
# initialize Citation and fetch fields
citation = Citation(c)
result = citation.get_fields('title', 'doi', 'journal',
'cited_by_posts_count', 'cited_by_tweeters_count',
'cited_by_fbwalls_count', 'cited_by_gplus_count',
'cited_by_rdts_count', 'cited_by_feeds_count')
else:
result = [x, 'no data']
# write row to file
writer.writerow(result)
#Altmetric.com asks users not to hammer the server. If needed, add a delay to the API-calls.
#Packages:
from pyaltmetric import Altmetric, Citation, HTTPException
import csv
# initialize Altmetric
a = Altmetric()
with open('Name of CSV-file with DOIs', 'r') as infile:
with open('Name of file with results', 'w') as outfile:
writer = csv.writer(outfile)
for x in infile:
x = x.rstrip()
# search for article using doi
c = a.doi(x)
if c:
# initialize Citation and fetch fields
citation = Citation(c)
result = citation.get_fields('doi','title','cited_by_msm_count') #Choose which data to retrieve msm=news media.
else:
result = [x, 'no data'] #No data = DOI not found.
# write row to file
writer.writerow(result)
def __init__(self, api_key):
self.altmetric = Altmetric(api_key=api_key)
self.last_query = None
def altmetric(pmids):
a = Altmetric()
url = 'http://api.altmetric.com/v1/id/'
#pmids = [pmids[i:i+900] for i in range(0, len(pmids), 900)]
# initialize the altmetric dataframe so it can be appended by the loop
altmet_df = pd.DataFrame(columns=[
'title', 'doi', 'pmid', 'pmc', 'ads_id', 'isbns', 'altmetric_jid',
'issns', 'journal', 'cohorts', 'abstract', 'context', 'authors',
'type', 'handles', 'altmetric_id', 'schema', 'is_oa',
'cited_by_posts_count', 'cited_by_tweeters_count',
'cited_by_accounts_count', 'last_updated', 'score', 'history', 'url',
'added_on', 'published_on', 'subjects', 'readers', 'readers_count',
'images', 'details_url', 'uri', 'publisher_subjects',
'cited_by_policies_count', 'scopus_subjects', 'cited_by_msm_count',
'cited_by_fbwalls_count', 'abstract_source', 'cited_by_patents_count',
'cited_by_wikipedia_count', 'downloads', 'cited_by_weibo_count',
'cited_by_feeds_count', 'cited_by_peer_review_sites_count',
'cited_by_rdts_count', 'cited_by_videos_count', 'cited_by_gplus_count',
'cited_by_rh_count', 'handle', 'ordinal_number',
'cited_by_linkedin_count', 'cited_by_pinners_count', 'arxiv_id',
'cited_by_qna_count', 'attribution', 'editors'
])
for pmid in pmids:
try:
response = a.pmid(pmid)
except Exception as err:
print("Failed altmetric query for " + str(pmid))
response = None
if response != None:
df = pd.DataFrame.from_dict(response, orient='index').transpose()
else:
df = pd.DataFrame(columns=[
'title', 'doi', 'pmid', 'pmc', 'ads_id', 'isbns',
'altmetric_jid', 'issns', 'journal', 'cohorts', 'abstract',
'context', 'authors', 'type', 'handles', 'altmetric_id',
'schema', 'is_oa', 'cited_by_posts_count',
'cited_by_tweeters_count', 'cited_by_accounts_count',
'last_updated', 'score', 'history', 'url', 'added_on',
'published_on', 'subjects', 'readers', 'readers_count',
'images', 'details_url', 'uri', 'publisher_subjects',
'cited_by_policies_count', 'scopus_subjects',
'cited_by_msm_count', 'cited_by_fbwalls_count',
'abstract_source', 'cited_by_patents_count',
'cited_by_wikipedia_count', 'downloads',
'cited_by_weibo_count', 'cited_by_feeds_count',
'cited_by_peer_review_sites_count', 'cited_by_rdts_count',
'cited_by_videos_count', 'cited_by_gplus_count',
'cited_by_rh_count', 'handle', 'ordinal_number',
'cited_by_linkedin_count', 'cited_by_pinners_count',
'arxiv_id', 'cited_by_qna_count', 'attribution', 'editors'
])
#df['pmid'] = str(pmid)
altmet_df = altmet_df.append(df)
#altmet_df = altmet_df.append(pd.DataFrame(response))
altmet_df['pmid'] = altmet_df['pmid'].astype(str)
altmet_df['last_import'] = [
datetime.datetime.today().strftime("%Y-%m-%d")
] * len(altmet_df['pmid'])
time.sleep(2)
return altmet_df
if __name__ == '__main__':
#https://github.com/wearp/pyaltmetric
#https://api.altmetric.com/version/citations/timeframe
#http://api.altmetric.com/docs/call_citations.html
timeframe = '1d'
resultsPerPage = 100
resultsPage = 1
doiPrefix = '10.7202' #erudit's doi prefix
pause = 1
myTime = datetime.now().strftime('%Y-%m-%d_%H-%M-%S-%f')
a = Altmetric(altmetricKey)
query = a.citations(timeframe, doi_prefix=doiPrefix)
totalResults = query['query']['total']
print totalResults
time.sleep(pause)
for i, r in enumerate(range(1, totalResults, resultsPerPage), 1):
print(i, r)
query = a.citations(timeframe,
num_results=resultsPerPage,
page=i,
doi_prefix=doiPrefix)
print(query)