def filter_query(q, filters, skip=None):
""" Apply a list of filters to the given query. """
or_filters = defaultdict(list)
for field, value in filters:
if field == skip:
continue
if field in OR_FIELDS:
or_filters[field].append(value)
else:
q = add_filter(q, {'term': {field: value}})
for field, value in or_filters.items():
q = add_filter(q, {'terms': {field: value}})
return q
def filter_query(q, filters, skip=None):
""" Apply a list of filters to the given query. """
or_filters = defaultdict(list)
for field, value in filters:
if field == skip:
continue
if field in OR_FIELDS:
or_filters[field].append(value)
else:
q = add_filter(q, {'term': {field: value}})
for field, value in or_filters.items():
q = add_filter(q, {'terms': {field: value}})
return q
def suggest_entity(args):
""" Auto-complete API. """
config = get_loom_config()
text = args.get('text')
options = []
if text is not None and len(text.strip()):
q = authz_filter({'match': {'$suggest': text}})
schema = args.get('$schema')
if schema is not None:
# Find matching sub-schemas as well.
schemas = config.implied_schemas(schema)
q = add_filter(q, {"terms": {"$schema": schemas}})
boost_collection = args.get('boost_collection')
if boost_collection is not None:
q = {
'function_score': {
'query': q,
'functions': [{
'boost_factor': 2,
'filter': {
'term': {
'$collections': boost_collection
}
}
}]
}
}
exclude_collection = args.get('exclude_collection')
if exclude_collection is not None:
q = add_filter(q, {'not': {
'term': {'$collections': exclude_collection}
}})
q = {
'size': 5,
'query': q,
'_source': ['name', 'id', '$schema']
}
result = get_es().search(index=get_es_index(), body=q)
for res in result.get('hits', {}).get('hits', []):
options.append(res.get('_source'))
return {
'text': text,
'options': options
}
def suggest_entity(args):
""" Auto-complete API. """
config = get_loom_config()
text = args.get('text')
options = []
if text is not None and len(text.strip()):
q = authz_filter({'match': {'$suggest': text}})
schema = args.get('$schema')
if schema is not None:
# Find matching sub-schemas as well.
schemas = config.implied_schemas(schema)
q = add_filter(q, {"terms": {"$schema": schemas}})
boost_collection = args.get('boost_collection')
if boost_collection is not None:
q = {
'function_score': {
'query':
q,
'functions': [{
'boost_factor': 2,
'filter': {
'term': {
'$collections': boost_collection
}
}
}]
}
}
exclude_collection = args.get('exclude_collection')
if exclude_collection is not None:
q = add_filter(
q, {'not': {
'term': {
'$collections': exclude_collection
}
}})
q = {'size': 5, 'query': q, '_source': ['name', 'id', '$schema']}
result = get_es().search(index=get_es_index(), body=q)
for res in result.get('hits', {}).get('hits', []):
options.append(res.get('_source'))
return {'text': text, 'options': options}
