def neessearch(offset=0, limit=100, query_string='', limit_fields=True, *args):
nees_pi_query = Q({
"nested": {
"path": "pis",
"ignore_unmapped": True,
"query": {
"query_string": {
"query": query_string,
"fields": ["pis.firstName", "pis.lastName"],
"lenient": True
}
}
}
})
nees_query_string_query = Q('query_string',
query=query_string,
default_operator='and')
pub_query = IndexedPublicationLegacy.search().filter(
nees_pi_query | nees_query_string_query)
pub_query = pub_query.extra(from_=offset, size=limit)
if limit_fields:
pub_query = pub_query.source(
includes=['project', 'pis', 'title', 'startDate', 'path'])
pub_query = pub_query.sort(
{'created': {
'order': 'desc',
'unmapped_type': 'long'
}})
res = pub_query.execute()
hits = list(map(lambda h: h.to_dict(), res.hits))
return {'listing': hits}
def reindex_nees_projects(*args):
try:
srch = IndexedPublicationLegacy.search()
res = srch.execute()
if res.hits.total > 0:
return
search = PublicProjectIndexed.search()
res = search.execute()
esrch = PublicExperimentIndexed.search()
for pub in search.scan():
pub_dict = pub.to_dict()
pub_dict['path'] = pub_dict['projectPath']
pub_dict.pop('projectPath', '')
pub_dict['system'] = pub_dict['systemId']
pub_dict.pop('systemId', '')
pub_doc = IndexedPublicationLegacy(**pub_dict)
esrch.query = Q('bool',
must=Q({'term': {
'project._exact': pub.name
}}))
esrch.execute()
experiments = []
for exp in esrch.scan():
exp_dict = exp.to_dict()
exp_dict['path'] = exp_dict['experimentPath']
exp_dict.pop('systemId')
exp_dict.pop('experimentPath', '')
exp_dict.pop('project')
experiments.append(exp_dict)
pub_doc.experiments = experiments
pub_doc.save()
except TransportError as exc:
if exc.status_code != 404:
raise
def neeslisting(offset=0, limit=100, limit_fields=True, *args):
pub_query = IndexedPublicationLegacy.search()
pub_query = pub_query.extra(from_=offset, size=limit)
if limit_fields:
pub_query = pub_query.source(
includes=['project', 'pis', 'title', 'startDate', 'path'])
pub_query = pub_query.sort(
{'created': {
'order': 'desc',
'unmapped_type': 'long'
}})
res = pub_query.execute()
hits = list(map(lambda h: h.to_dict(), res.hits))
return {'listing': hits}
def neesdescription(project_id, *args):
pub_query = IndexedPublicationLegacy.search()\
.filter(Q({'term': {'project._exact': project_id}}))\
.source(includes=['description'])
desc = next(hit.description for hit in pub_query.execute().hits)
return {'description': desc}