def search(cls, **kwargs):
kwargs.update({
'using': connections.get_connection(),
'index': cls.get_index(),
'doc_type': {
cls._doc_type.name: cls.from_es
},
})
sq = Search(**kwargs)
# Add highlighting.
sq = sq.highlight(*cls.excerpt_fields)
sq = sq.highlight_options(order='score')
return sq
def put(self) -> dict:
"""
search for a group in Elasticsearch
Returns:
dict -- search results
"""
args = self.parser.parse_args()
# init search
search: Search = Group.search()
search_query: dict = {
"bool": {
"should": [
{"query_string": {"query": args["query"], "fields": ["*"]}},
{
"nested": {
"path": "topics",
"score_mode": "avg",
"query": {
"bool": {
"must": [
{
"query_string": {
"query": args["query"],
"fields": ["*"],
}
}
]
}
},
}
},
{
"nested": {
"path": "events",
"score_mode": "avg",
"query": {
"bool": {
"must": [
{
"query_string": {
"query": args["query"],
"fields": ["*"],
}
}
]
}
},
}
},
],
"must": [],
}
}
# set event time filter
if args["event_time_gte"] or args["event_time_lte"]:
range_query: dict = {}
if args["event_time_gte"]:
range_query["gte"] = args["event_time_gte"]
if args["event_time_lte"]:
range_query["lte"] = args["event_time_lte"]
search_query["bool"]["must"].append(
{
"nested": {
"path": "events",
"score_mode": "avg",
"query": {
"bool": {"must": [{"range": {"events.time": range_query}}]}
},
}
}
)
# set geo_distance filter
if args["geo_distance"] and args["geo_lat"] and args["geo_lon"]:
search_query["bool"]["must"].append(
{
"nested": {
"path": "events",
"score_mode": "avg",
"query": {
"bool": {
"must": [
{
"geo_distance": {
"distance": args["geo_distance"],
"events.venue_location": {
"lat": args["geo_lat"],
"lon": args["geo_lon"],
},
}
}
]
}
},
}
}
)
# pagination
strat_entry: int = args["page"] * args["limit"]
end_entry: int = strat_entry + args["limit"]
search = search[strat_entry:end_entry]
# sort
if args["sort"]:
search = Search().sort(args["sort"])
# execute search
search = search.query(Q(search_query))
# set highlight score
search.highlight_options(order="score")
# load response from elasticsearch
results: Response = search.execute()
# get response
found_groups: List[dict] = []
map_center_lat: float = 0
map_center_lon: float = 0
for group in results.hits:
group_dict: dict = {}
if isinstance(group, Hit):
group_object = Group.get_group(urlname=group.to_dict()["urlname"])
group_dict = group_object.to_json_dict(load_events=args["load_events"])
else:
group_dict = group.to_json_dict(load_events=args["load_events"])
if "venue_location_average" in group_dict:
map_center_lat = (
map_center_lat + group_dict["venue_location_average"]["lat"]
)
map_center_lon = (
map_center_lon + group_dict["venue_location_average"]["lon"]
)
else:
map_center_lat = map_center_lat + group_dict["location"]["lat"]
map_center_lon = map_center_lon + group_dict["location"]["lon"]
# add group dict to array
found_groups.append(
{**group_dict,}
)
if len(found_groups) > 0:
map_center_lat = map_center_lat / len(found_groups)
map_center_lon = map_center_lon / len(found_groups)
return {
"results": found_groups,
"hits": results.hits.total["value"],
"map_center": {"lat": map_center_lat, "lon": map_center_lon},
}
