def search_terms(request):
lang = request.GET.get('lang', settings.LANGUAGE_CODE)
se = SearchEngineFactory().create()
searchString = request.GET.get('q', '')
user_is_reviewer = request.user.groups.filter(name='Resource Reviewer').exists()
i = 0
ret = {}
for index in ['terms', 'concepts']:
query = Query(se, start=0, limit=0)
boolquery = Bool()
boolquery.should(Match(field='value', query=searchString.lower(), type='phrase_prefix'))
boolquery.should(Match(field='value.folded', query=searchString.lower(), type='phrase_prefix'))
boolquery.should(Match(field='value.folded', query=searchString.lower(), fuzziness='AUTO', prefix_length=settings.SEARCH_TERM_SENSITIVITY))
if user_is_reviewer is False and index == 'terms':
boolquery.filter(Terms(field='provisional', terms=['false']))
query.add_query(boolquery)
base_agg = Aggregation(name='value_agg', type='terms', field='value.raw', size=settings.SEARCH_DROPDOWN_LENGTH, order={"max_score": "desc"})
nodegroupid_agg = Aggregation(name='nodegroupid', type='terms', field='nodegroupid')
top_concept_agg = Aggregation(name='top_concept', type='terms', field='top_concept')
conceptid_agg = Aggregation(name='conceptid', type='terms', field='conceptid')
max_score_agg = MaxAgg(name='max_score', script='_score')
top_concept_agg.add_aggregation(conceptid_agg)
base_agg.add_aggregation(max_score_agg)
base_agg.add_aggregation(top_concept_agg)
base_agg.add_aggregation(nodegroupid_agg)
query.add_aggregation(base_agg)
ret[index] = []
results = query.search(index=index)
for result in results['aggregations']['value_agg']['buckets']:
if len(result['top_concept']['buckets']) > 0:
for top_concept in result['top_concept']['buckets']:
top_concept_id = top_concept['key']
top_concept_label = get_preflabel_from_conceptid(top_concept['key'], lang)['value']
for concept in top_concept['conceptid']['buckets']:
ret[index].append({
'type': 'concept',
'context': top_concept_id,
'context_label': top_concept_label,
'id': i,
'text': result['key'],
'value': concept['key']
})
i = i + 1
else:
ret[index].append({
'type': 'term',
'context': '',
'context_label': get_resource_model_label(result),
'id': i,
'text': result['key'],
'value': result['key']
})
i = i + 1
return JSONResponse(ret)
def search_terms(request):
lang = request.GET.get('lang', settings.LANGUAGE_CODE)
se = SearchEngineFactory().create()
searchString = request.GET.get('q', '')
query = Query(se, start=0, limit=0)
user_is_reviewer = request.user.groups.filter(name='Resource Reviewer').exists()
boolquery = Bool()
boolquery.should(Match(field='value', query=searchString.lower(), type='phrase_prefix', fuzziness='AUTO'))
boolquery.should(Match(field='value.folded', query=searchString.lower(), type='phrase_prefix', fuzziness='AUTO'))
boolquery.should(Match(field='value.folded', query=searchString.lower(), fuzziness='AUTO'))
if user_is_reviewer is False:
boolquery.filter(Terms(field='provisional', terms=['false']))
query.add_query(boolquery)
base_agg = Aggregation(name='value_agg', type='terms', field='value.raw', size=settings.SEARCH_DROPDOWN_LENGTH, order={"max_score": "desc"})
nodegroupid_agg = Aggregation(name='nodegroupid', type='terms', field='nodegroupid')
top_concept_agg = Aggregation(name='top_concept', type='terms', field='top_concept')
conceptid_agg = Aggregation(name='conceptid', type='terms', field='conceptid')
max_score_agg = MaxAgg(name='max_score', script='_score')
top_concept_agg.add_aggregation(conceptid_agg)
base_agg.add_aggregation(max_score_agg)
base_agg.add_aggregation(top_concept_agg)
base_agg.add_aggregation(nodegroupid_agg)
query.add_aggregation(base_agg)
results = query.search(index='strings') or {'hits': {'hits':[]}}
i = 0;
ret = []
for result in results['aggregations']['value_agg']['buckets']:
if len(result['top_concept']['buckets']) > 0:
for top_concept in result['top_concept']['buckets']:
top_concept_id = top_concept['key']
top_concept_label = get_preflabel_from_conceptid(top_concept['key'], lang)['value']
for concept in top_concept['conceptid']['buckets']:
ret.append({
'type': 'concept',
'context': top_concept_id,
'context_label': top_concept_label,
'id': i,
'text': result['key'],
'value': concept['key']
})
i = i + 1
else:
ret.append({
'type': 'term',
'context': '',
'context_label': get_resource_model_label(result),
'id': i,
'text': result['key'],
'value': result['key']
})
i = i + 1
return JSONResponse(ret)
def search_terms(request):
lang = request.GET.get('lang', settings.LANGUAGE_CODE)
se = SearchEngineFactory().create()
searchString = request.GET.get('q', '')
query = Query(se, start=0, limit=0)
boolquery = Bool()
boolquery.should(Match(field='value', query=searchString.lower(), type='phrase_prefix', fuzziness='AUTO'))
boolquery.should(Match(field='value.folded', query=searchString.lower(), type='phrase_prefix', fuzziness='AUTO'))
boolquery.should(Match(field='value.folded', query=searchString.lower(), fuzziness='AUTO'))
query.add_query(boolquery)
base_agg = Aggregation(name='value_agg', type='terms', field='value.raw', size=settings.SEARCH_DROPDOWN_LENGTH, order={"max_score": "desc"})
nodegroupid_agg = Aggregation(name='nodegroupid', type='terms', field='nodegroupid')
top_concept_agg = Aggregation(name='top_concept', type='terms', field='top_concept')
conceptid_agg = Aggregation(name='conceptid', type='terms', field='conceptid')
max_score_agg = MaxAgg(name='max_score', script='_score')
top_concept_agg.add_aggregation(conceptid_agg)
base_agg.add_aggregation(max_score_agg)
base_agg.add_aggregation(top_concept_agg)
base_agg.add_aggregation(nodegroupid_agg)
query.add_aggregation(base_agg)
results = query.search(index='strings') or {'hits': {'hits':[]}}
i = 0;
ret = []
for result in results['aggregations']['value_agg']['buckets']:
if len(result['top_concept']['buckets']) > 0:
for top_concept in result['top_concept']['buckets']:
top_concept_id = top_concept['key']
top_concept_label = get_preflabel_from_conceptid(top_concept['key'], lang)['value']
for concept in top_concept['conceptid']['buckets']:
ret.append({
'type': 'concept',
'context': top_concept_id,
'context_label': top_concept_label,
'id': i,
'text': result['key'],
'value': concept['key']
})
i = i + 1
else:
ret.append({
'type': 'term',
'context': '',
'context_label': '',
'id': i,
'text': result['key'],
'value': result['key']
})
i = i + 1
return JSONResponse(ret)
def search_terms(request):
lang = request.GET.get("lang", settings.LANGUAGE_CODE)
se = SearchEngineFactory().create()
searchString = request.GET.get("q", "")
user_is_reviewer = user_is_resource_reviewer(request.user)
i = 0
ret = {}
for index in ["terms", "concepts"]:
query = Query(se, start=0, limit=0)
boolquery = Bool()
boolquery.should(
Match(field="value",
query=searchString.lower(),
type="phrase_prefix"))
boolquery.should(
Match(field="value.folded",
query=searchString.lower(),
type="phrase_prefix"))
boolquery.should(
Match(field="value.folded",
query=searchString.lower(),
fuzziness="AUTO",
prefix_length=settings.SEARCH_TERM_SENSITIVITY))
if user_is_reviewer is False and index == "terms":
boolquery.filter(Terms(field="provisional", terms=["false"]))
query.add_query(boolquery)
base_agg = Aggregation(name="value_agg",
type="terms",
field="value.raw",
size=settings.SEARCH_DROPDOWN_LENGTH,
order={"max_score": "desc"})
nodegroupid_agg = Aggregation(name="nodegroupid",
type="terms",
field="nodegroupid")
top_concept_agg = Aggregation(name="top_concept",
type="terms",
field="top_concept")
conceptid_agg = Aggregation(name="conceptid",
type="terms",
field="conceptid")
max_score_agg = MaxAgg(name="max_score", script="_score")
top_concept_agg.add_aggregation(conceptid_agg)
base_agg.add_aggregation(max_score_agg)
base_agg.add_aggregation(top_concept_agg)
base_agg.add_aggregation(nodegroupid_agg)
query.add_aggregation(base_agg)
ret[index] = []
results = query.search(index=index)
if results is not None:
for result in results["aggregations"]["value_agg"]["buckets"]:
if len(result["top_concept"]["buckets"]) > 0:
for top_concept in result["top_concept"]["buckets"]:
top_concept_id = top_concept["key"]
top_concept_label = get_preflabel_from_conceptid(
top_concept["key"], lang)["value"]
for concept in top_concept["conceptid"]["buckets"]:
ret[index].append({
"type": "concept",
"context": top_concept_id,
"context_label": top_concept_label,
"id": i,
"text": result["key"],
"value": concept["key"],
})
i = i + 1
else:
ret[index].append({
"type":
"term",
"context":
"",
"context_label":
get_resource_model_label(result),
"id":
i,
"text":
result["key"],
"value":
result["key"],
})
i = i + 1
return JSONResponse(ret)