def test_generate_bounding_box(self):
downtown_bottom_left = Point(-95.23947, 38.9637903)
downtown_top_right = Point(-95.23362278938293, 38.973081081164715)
((min_lat, min_lng), (max_lat, max_lng)) = generate_bounding_box(downtown_bottom_left, downtown_top_right)
self.assertEqual(min_lat, 38.9637903)
self.assertEqual(min_lng, -95.23947)
self.assertEqual(max_lat, 38.973081081164715)
self.assertEqual(max_lng, -95.23362278938293)
def test_generate_bounding_box_crossing_line_date(self):
downtown_bottom_left = Point(95.23947, 38.9637903)
downtown_top_right = Point(-95.23362278938293, 38.973081081164715)
((south, west), (north, east)) = generate_bounding_box(downtown_bottom_left, downtown_top_right)
self.assertEqual(south, 38.9637903)
self.assertEqual(west, 95.23947)
self.assertEqual(north, 38.973081081164715)
self.assertEqual(east, -95.23362278938293)
def _build_search_query_within(self, within):
from haystack.utils.geo import generate_bounding_box
((south, west), (north, east)) = generate_bounding_box(
within["point_1"], within["point_2"]
)
return {
"geo_bounding_box": {
within["field"]: {
"top_left": {"lat": north, "lon": west},
"bottom_right": {"lat": south, "lon": east},
}
}
}
def _build_search_query_within(self, within):
from haystack.utils.geo import generate_bounding_box
((south, west), (north, east)) = generate_bounding_box(
within["point_1"], within["point_2"]
)
return {
"geo_bounding_box": {
within["field"]: {
"top_left": {"lat": north, "lon": west},
"bottom_right": {"lat": south, "lon": east},
}
}
}
def _build_search_filters_within(self, within):
from haystack.utils.geo import generate_bounding_box
((south, west), (north, east)) = generate_bounding_box(
within['point_1'], within['point_2'])
within_filter = {
"geo_bounding_box": {
within['field']: {
"top_left": {
"lat": north,
"lon": west
},
"bottom_right": {
"lat": south,
"lon": east
}
}
},
}
return within_filter
def build_search_kwargs(self, query_string, sort_by=None, start_offset=0, end_offset=None,
fields='', highlight=False, facets=None,
date_facets=None, query_facets=None,
narrow_queries=None, spelling_query=None,
within=None, dwithin=None, distance_point=None,
models=None, limit_to_registered_models=None,
result_class=None):
index = haystack.connections[self.connection_alias].get_unified_index()
content_field = index.document_field
if query_string == '*:*':
kwargs = {
'query': {
"match_all": {}
},
}
else:
kwargs = {
'query': {
'query_string': {
'default_field': content_field,
'default_operator': DEFAULT_OPERATOR,
'query': query_string,
'analyze_wildcard': True,
'auto_generate_phrase_queries': True,
},
},
}
# so far, no filters
filters = []
if fields:
if isinstance(fields, (list, set)):
fields = " ".join(fields)
kwargs['fields'] = fields
if sort_by is not None:
order_list = []
for field, direction in sort_by:
if field == 'distance' and distance_point:
# Do the geo-enabled sort.
lng, lat = distance_point['point'].get_coords()
sort_kwargs = {
"_geo_distance": {
distance_point['field']: [lng, lat],
"order": direction,
"unit": "km"
}
}
else:
if field == 'distance':
warnings.warn("In order to sort by distance, you must call the '.distance(...)' method.")
# Regular sorting.
sort_kwargs = {field: {'order': direction}}
order_list.append(sort_kwargs)
kwargs['sort'] = order_list
# From/size offsets don't seem to work right in Elasticsearch's DSL. :/
# if start_offset is not None:
# kwargs['from'] = start_offset
# if end_offset is not None:
# kwargs['size'] = end_offset - start_offset
if highlight is True:
kwargs['highlight'] = {
'fields': {
content_field: {'store': 'yes'},
}
}
if self.include_spelling:
kwargs['suggest'] = {
'suggest': {
'text': spelling_query or query_string,
'term': {
# Using content_field here will result in suggestions of stemmed words.
'field': '_all',
},
},
}
if narrow_queries is None:
narrow_queries = set()
if facets is not None:
kwargs.setdefault('facets', {})
for facet_fieldname, extra_options in facets.items():
facet_options = {
'terms': {
'field': facet_fieldname,
'size': 100,
},
}
# Special cases for options applied at the facet level (not the terms level).
if extra_options.pop('global_scope', False):
# Renamed "global_scope" since "global" is a python keyword.
facet_options['global'] = True
if 'facet_filter' in extra_options:
facet_options['facet_filter'] = extra_options.pop('facet_filter')
facet_options['terms'].update(extra_options)
kwargs['facets'][facet_fieldname] = facet_options
if date_facets is not None:
kwargs.setdefault('facets', {})
for facet_fieldname, value in date_facets.items():
# Need to detect on gap_by & only add amount if it's more than one.
interval = value.get('gap_by').lower()
# Need to detect on amount (can't be applied on months or years).
if value.get('gap_amount', 1) != 1 and interval not in ('month', 'year'):
# Just the first character is valid for use.
interval = "%s%s" % (value['gap_amount'], interval[:1])
kwargs['facets'][facet_fieldname] = {
'date_histogram': {
'field': facet_fieldname,
'interval': interval,
},
'facet_filter': {
"range": {
facet_fieldname: {
'from': self._from_python(value.get('start_date')),
'to': self._from_python(value.get('end_date')),
}
}
}
}
if query_facets is not None:
kwargs.setdefault('facets', {})
for facet_fieldname, value in query_facets:
kwargs['facets'][facet_fieldname] = {
'query': {
'query_string': {
'query': value,
}
},
}
if limit_to_registered_models is None:
limit_to_registered_models = getattr(settings, 'HAYSTACK_LIMIT_TO_REGISTERED_MODELS', True)
if models and len(models):
model_choices = sorted(get_model_ct(model) for model in models)
elif limit_to_registered_models:
# Using narrow queries, limit the results to only models handled
# with the current routers.
model_choices = self.build_models_list()
else:
model_choices = []
if len(model_choices) > 0:
filters.append({"terms": {DJANGO_CT: model_choices}})
for q in narrow_queries:
filters.append({
'fquery': {
'query': {
'query_string': {
'query': q
},
},
'_cache': True,
}
})
if within is not None:
from haystack.utils.geo import generate_bounding_box
((south, west), (north, east)) = generate_bounding_box(within['point_1'], within['point_2'])
within_filter = {
"geo_bounding_box": {
within['field']: {
"top_left": {
"lat": north,
"lon": west
},
"bottom_right": {
"lat": south,
"lon": east
}
}
},
}
filters.append(within_filter)
if dwithin is not None:
lng, lat = dwithin['point'].get_coords()
# NB: the 1.0.0 release of elasticsearch introduce an
# incompatible change on the distance filter formating
if elasticsearch.VERSION >= (1, 0, 0):
distance = "%(dist).6f%(unit)s" % {
'dist': dwithin['distance'].km,
'unit': "km"
}
else:
distance = dwithin['distance'].km
dwithin_filter = {
"geo_distance": {
"distance": distance,
dwithin['field']: {
"lat": lat,
"lon": lng
}
}
}
filters.append(dwithin_filter)
# if we want to filter, change the query type to filteres
if filters:
kwargs["query"] = {"filtered": {"query": kwargs.pop("query")}}
if len(filters) == 1:
kwargs['query']['filtered']["filter"] = filters[0]
else:
kwargs['query']['filtered']["filter"] = {"bool": {"must": filters}}
return kwargs
def build_search_kwargs(self, query_string, sort_by=None, start_offset=0, end_offset=None,
fields='', highlight=False, facets=None,
date_facets=None, query_facets=None,
narrow_queries=None, spelling_query=None,
within=None, dwithin=None, distance_point=None,
models=None, limit_to_registered_models=None,
result_class=None):
index = haystack.connections[self.connection_alias].get_unified_index()
content_field = index.document_field
if query_string == '*:*':
kwargs = {
'query': {
"match_all": {}
},
}
else:
kwargs = {
'query': {
'query_string': {
'default_field': content_field,
'default_operator': DEFAULT_OPERATOR,
'query': query_string,
'analyze_wildcard': True,
'auto_generate_phrase_queries': True,
},
},
}
# so far, no filters
filters = []
if fields:
if isinstance(fields, (list, set)):
fields = " ".join(fields)
kwargs['fields'] = fields
if sort_by is not None:
order_list = []
for field, direction in sort_by:
if field == 'distance' and distance_point:
# Do the geo-enabled sort.
lng, lat = distance_point['point'].get_coords()
sort_kwargs = {
"_geo_distance": {
distance_point['field']: [lng, lat],
"order": direction,
"unit": "km"
}
}
else:
if field == 'distance':
warnings.warn("In order to sort by distance, you must call the '.distance(...)' method.")
# Regular sorting.
sort_kwargs = {field: {'order': direction}}
order_list.append(sort_kwargs)
kwargs['sort'] = order_list
# From/size offsets don't seem to work right in Elasticsearch's DSL. :/
# if start_offset is not None:
# kwargs['from'] = start_offset
# if end_offset is not None:
# kwargs['size'] = end_offset - start_offset
if highlight is True:
kwargs['highlight'] = {
'fields': {
content_field: {'store': 'yes'},
}
}
if self.include_spelling:
kwargs['suggest'] = {
'suggest': {
'text': spelling_query or query_string,
'term': {
# Using content_field here will result in suggestions of stemmed words.
'field': '_all',
},
},
}
if narrow_queries is None:
narrow_queries = set()
if facets is not None:
kwargs.setdefault('facets', {})
for facet_fieldname, extra_options in facets.items():
facet_options = {
'terms': {
'field': facet_fieldname,
'size': 100,
},
}
# Special cases for options applied at the facet level (not the terms level).
if extra_options.pop('global_scope', False):
# Renamed "global_scope" since "global" is a python keyword.
facet_options['global'] = True
if 'facet_filter' in extra_options:
facet_options['facet_filter'] = extra_options.pop('facet_filter')
facet_options['terms'].update(extra_options)
kwargs['facets'][facet_fieldname] = facet_options
if date_facets is not None:
kwargs.setdefault('facets', {})
for facet_fieldname, value in date_facets.items():
# Need to detect on gap_by & only add amount if it's more than one.
interval = value.get('gap_by').lower()
# Need to detect on amount (can't be applied on months or years).
if value.get('gap_amount', 1) != 1 and not interval in ('month', 'year'):
# Just the first character is valid for use.
interval = "%s%s" % (value['gap_amount'], interval[:1])
kwargs['facets'][facet_fieldname] = {
'date_histogram': {
'field': facet_fieldname,
'interval': interval,
},
'facet_filter': {
"range": {
facet_fieldname: {
'from': self._from_python(value.get('start_date')),
'to': self._from_python(value.get('end_date')),
}
}
}
}
if query_facets is not None:
kwargs.setdefault('facets', {})
for facet_fieldname, value in query_facets:
kwargs['facets'][facet_fieldname] = {
'query': {
'query_string': {
'query': value,
}
},
}
if limit_to_registered_models is None:
limit_to_registered_models = getattr(settings, 'HAYSTACK_LIMIT_TO_REGISTERED_MODELS', True)
if models and len(models):
model_choices = sorted(['%s.%s' % (model._meta.app_label, model._meta.module_name) for model in models])
elif limit_to_registered_models:
# Using narrow queries, limit the results to only models handled
# with the current routers.
model_choices = self.build_models_list()
else:
model_choices = []
if len(model_choices) > 0:
if narrow_queries is None:
narrow_queries = set()
filters.append({"terms": {DJANGO_CT: model_choices}})
if narrow_queries:
filters.append({
'fquery': {
'query': {
'query_string': {
'query': u' AND '.join(list(narrow_queries)),
},
},
'_cache': True,
}
})
if within is not None:
from haystack.utils.geo import generate_bounding_box
((min_lat, min_lng), (max_lat, max_lng)) = generate_bounding_box(within['point_1'], within['point_2'])
within_filter = {
"geo_bounding_box": {
within['field']: {
"top_left": {
"lat": max_lat,
"lon": min_lng
},
"bottom_right": {
"lat": min_lat,
"lon": max_lng
}
}
},
}
filters.append(within_filter)
if dwithin is not None:
lng, lat = dwithin['point'].get_coords()
dwithin_filter = {
"geo_distance": {
"distance": dwithin['distance'].km,
dwithin['field']: {
"lat": lat,
"lon": lng
}
}
}
filters.append(dwithin_filter)
# if we want to filter, change the query type to filteres
if filters:
kwargs["query"] = {"filtered": {"query": kwargs.pop("query")}}
if len(filters) == 1:
kwargs['query']['filtered']["filter"] = filters[0]
else:
kwargs['query']['filtered']["filter"] = {"bool": {"must": filters}}
return kwargs
def build_search_kwargs(self,
query_string,
sort_by=None,
start_offset=0,
end_offset=None,
fields="",
highlight=False,
facets=None,
date_facets=None,
query_facets=None,
narrow_queries=None,
spelling_query=None,
within=None,
dwithin=None,
distance_point=None,
models=None,
limit_to_registered_models=None,
result_class=None,
stats=None,
collate=None,
**extra_kwargs):
index = haystack.connections[self.connection_alias].get_unified_index()
kwargs = {"fl": "* score", "df": index.document_field}
if fields:
if isinstance(fields, (list, set)):
fields = " ".join(fields)
kwargs["fl"] = fields
if sort_by is not None:
if sort_by in ["distance asc", "distance desc"] and distance_point:
# Do the geo-enabled sort.
lng, lat = distance_point["point"].coords
kwargs["sfield"] = distance_point["field"]
kwargs["pt"] = "%s,%s" % (lat, lng)
if sort_by == "distance asc":
kwargs["sort"] = "geodist() asc"
else:
kwargs["sort"] = "geodist() desc"
else:
if sort_by.startswith("distance "):
warnings.warn(
"In order to sort by distance, you must call the '.distance(...)' method."
)
# Regular sorting.
kwargs["sort"] = sort_by
if start_offset is not None:
kwargs["start"] = start_offset
if end_offset is not None:
kwargs["rows"] = end_offset - start_offset
if highlight:
# `highlight` can either be True or a dictionary containing custom parameters
# which will be passed to the backend and may override our default settings:
kwargs["hl"] = "true"
kwargs["hl.fragsize"] = "200"
if isinstance(highlight, dict):
# autoprefix highlighter options with 'hl.', all of them start with it anyway
# this makes option dicts shorter: {'maxAnalyzedChars': 42}
# and lets some of options be used as keyword arguments: `.highlight(preserveMulti=False)`
kwargs.update({
key if key.startswith("hl.") else ("hl." + key):
highlight[key]
for key in highlight.keys()
})
if collate is None:
collate = self.collate
if self.include_spelling is True:
kwargs["spellcheck"] = "true"
kwargs["spellcheck.collate"] = str(collate).lower()
kwargs["spellcheck.count"] = 1
if spelling_query:
kwargs["spellcheck.q"] = spelling_query
if facets is not None:
kwargs["facet"] = "on"
kwargs["facet.field"] = facets.keys()
for facet_field, options in facets.items():
for key, value in options.items():
kwargs["f.%s.facet.%s" %
(facet_field, key)] = self.conn._from_python(value)
if date_facets is not None:
kwargs["facet"] = "on"
kwargs["facet.date"] = date_facets.keys()
kwargs["facet.date.other"] = "none"
for key, value in date_facets.items():
kwargs["f.%s.facet.date.start" % key] = self.conn._from_python(
value.get("start_date"))
kwargs["f.%s.facet.date.end" % key] = self.conn._from_python(
value.get("end_date"))
gap_by_string = value.get("gap_by").upper()
gap_string = "%d%s" % (value.get("gap_amount"), gap_by_string)
if value.get("gap_amount") != 1:
gap_string += "S"
kwargs["f.%s.facet.date.gap" % key] = "+%s/%s" % (
gap_string,
gap_by_string,
)
if query_facets is not None:
kwargs["facet"] = "on"
kwargs["facet.query"] = [
"%s:%s" % (field, value) for field, value in query_facets
]
if limit_to_registered_models is None:
limit_to_registered_models = getattr(
settings, "HAYSTACK_LIMIT_TO_REGISTERED_MODELS", True)
if models and len(models):
model_choices = sorted(get_model_ct(model) for model in models)
elif limit_to_registered_models:
# Using narrow queries, limit the results to only models handled
# with the current routers.
model_choices = self.build_models_list()
else:
model_choices = []
if len(model_choices) > 0:
if narrow_queries is None:
narrow_queries = set()
narrow_queries.add("%s:(%s)" %
(DJANGO_CT, " OR ".join(model_choices)))
if narrow_queries is not None:
kwargs["fq"] = list(narrow_queries)
if stats:
kwargs["stats"] = "true"
for k in stats.keys():
kwargs["stats.field"] = k
for facet in stats[k]:
kwargs["f.%s.stats.facet" % k] = facet
if within is not None:
from haystack.utils.geo import generate_bounding_box
kwargs.setdefault("fq", [])
((min_lat, min_lng), (max_lat, max_lng)) = generate_bounding_box(
within["point_1"], within["point_2"])
# Bounding boxes are min, min TO max, max. Solr's wiki was *NOT*
# very clear on this.
bbox = "%s:[%s,%s TO %s,%s]" % (
within["field"],
min_lat,
min_lng,
max_lat,
max_lng,
)
kwargs["fq"].append(bbox)
if dwithin is not None:
kwargs.setdefault("fq", [])
lng, lat = dwithin["point"].coords
geofilt = "{!geofilt pt=%s,%s sfield=%s d=%s}" % (
lat,
lng,
dwithin["field"],
dwithin["distance"].km,
)
kwargs["fq"].append(geofilt)
# Check to see if the backend should try to include distances
# (Solr 4.X+) in the results.
if self.distance_available and distance_point:
# In early testing, you can't just hand Solr 4.X a proper bounding box
# & request distances. To enable native distance would take calculating
# a center point & a radius off the user-provided box, which kinda
# sucks. We'll avoid it for now, since Solr 4.x's release will be some
# time yet.
# kwargs['fl'] += ' _dist_:geodist()'
pass
if extra_kwargs:
kwargs.update(extra_kwargs)
return kwargs
def build_search_kwargs(
self,
query_string,
sort_by=None,
start_offset=0,
end_offset=None,
fields="",
highlight=False,
facets=None,
date_facets=None,
query_facets=None,
narrow_queries=None,
spelling_query=None,
within=None,
dwithin=None,
distance_point=None,
models=None,
limit_to_registered_models=None,
result_class=None,
):
index = haystack.connections[self.connection_alias].get_unified_index()
content_field = index.document_field
if query_string == "*:*":
kwargs = {"query": {"match_all": {}}}
elif query_string.startswith("(") and query_string.endswith(")"):
kwargs = {
"query": {
"query_string": {
"default_field": content_field,
"default_operator": DEFAULT_OPERATOR,
"query": query_string,
"analyze_wildcard": True,
"auto_generate_phrase_queries": True,
}
}
}
else:
kwargs = {
"query": {
"match": {
str(content_field): {
"query": query_string,
"analyzer": self.DEFAULT_ANALYZER, # setting courtesy of ConfigurableElasticBackend
"minimum_should_match": self.DEFAULT_MINIMUM_MATCH,
}
}
}
}
# so far, no filters
filters = []
if fields:
if isinstance(fields, (list, set)):
fields = " ".join(fields)
kwargs["fields"] = fields
if sort_by is not None:
order_list = []
for field, direction in sort_by:
if field == "distance" and distance_point:
# Do the geo-enabled sort.
lng, lat = distance_point["point"].get_coords()
sort_kwargs = {
"_geo_distance": {distance_point["field"]: [lng, lat], "order": direction, "unit": "km"}
}
else:
if field == "distance":
warnings.warn("In order to sort by distance, you must call the '.distance(...)' method.")
# Regular sorting.
sort_kwargs = {field: {"order": direction}}
order_list.append(sort_kwargs)
kwargs["sort"] = order_list
# From/size offsets don't seem to work right in Elasticsearch's DSL. :/
# if start_offset is not None:
# kwargs['from'] = start_offset
# if end_offset is not None:
# kwargs['size'] = end_offset - start_offset
if highlight is True:
kwargs["highlight"] = {"fields": {content_field: {"store": "yes"}}}
if self.include_spelling:
kwargs["suggest"] = {
"suggest": {
"text": spelling_query or query_string,
"term": {
# Using content_field here will result in suggestions of stemmed words.
"field": "_all"
},
}
}
if narrow_queries is None:
narrow_queries = set()
if facets is not None:
kwargs.setdefault("facets", {})
for facet_fieldname, extra_options in facets.items():
facet_options = {"terms": {"field": facet_fieldname, "size": 100}}
# Special cases for options applied at the facet level (not the terms level).
if extra_options.pop("global_scope", False):
# Renamed "global_scope" since "global" is a python keyword.
facet_options["global"] = True
if "facet_filter" in extra_options:
facet_options["facet_filter"] = extra_options.pop("facet_filter")
facet_options["terms"].update(extra_options)
kwargs["facets"][facet_fieldname] = facet_options
if date_facets is not None:
kwargs.setdefault("facets", {})
for facet_fieldname, value in date_facets.items():
# Need to detect on gap_by & only add amount if it's more than one.
interval = value.get("gap_by").lower()
# Need to detect on amount (can't be applied on months or years).
if value.get("gap_amount", 1) != 1 and interval not in ("month", "year"):
# Just the first character is valid for use.
interval = "%s%s" % (value["gap_amount"], interval[:1])
kwargs["facets"][facet_fieldname] = {
"date_histogram": {"field": facet_fieldname, "interval": interval},
"facet_filter": {
"range": {
facet_fieldname: {
"from": self._from_python(value.get("start_date")),
"to": self._from_python(value.get("end_date")),
}
}
},
}
if query_facets is not None:
kwargs.setdefault("facets", {})
for facet_fieldname, value in query_facets:
kwargs["facets"][facet_fieldname] = {"query": {"match": {"query": value}}}
if limit_to_registered_models is None:
limit_to_registered_models = getattr(settings, "HAYSTACK_LIMIT_TO_REGISTERED_MODELS", True)
if models and len(models):
model_choices = sorted(get_model_ct(model) for model in models)
elif limit_to_registered_models:
# Using narrow queries, limit the results to only models handled
# with the current routers.
model_choices = self.build_models_list()
else:
model_choices = []
if len(model_choices) > 0:
filters.append({"terms": {DJANGO_CT: model_choices}})
for q in narrow_queries:
filters.append({"fquery": {"query": {"query_string": {"query": q}}, "_cache": True}})
if within is not None:
from haystack.utils.geo import generate_bounding_box
((south, west), (north, east)) = generate_bounding_box(within["point_1"], within["point_2"])
within_filter = {
"geo_bounding_box": {
within["field"]: {
"top_left": {"lat": north, "lon": west},
"bottom_right": {"lat": south, "lon": east},
}
}
}
filters.append(within_filter)
if dwithin is not None:
lng, lat = dwithin["point"].get_coords()
# NB: the 1.0.0 release of elasticsearch introduce an
# incompatible change on the distance filter formating
if elasticsearch.VERSION >= (1, 0, 0):
distance = "%(dist).6f%(unit)s" % {"dist": dwithin["distance"].km, "unit": "km"}
else:
distance = dwithin["distance"].km
dwithin_filter = {"geo_distance": {"distance": distance, dwithin["field"]: {"lat": lat, "lon": lng}}}
filters.append(dwithin_filter)
# if we want to filter, change the query type to filteres
if filters:
kwargs["query"] = {"filtered": {"query": kwargs.pop("query")}}
if len(filters) == 1:
kwargs["query"]["filtered"]["filter"] = filters[0]
else:
kwargs["query"]["filtered"]["filter"] = {"bool": {"must": filters}}
return kwargs
def build_search_kwargs(self,
query_string,
sort_by=None,
start_offset=0,
end_offset=None,
fields='',
highlight=False,
boost_fields=None,
boost_negative=None,
filter_context=None,
narrow_queries=None,
spelling_query=None,
facets=None,
date_facets=None,
query_facets=None,
within=None,
dwithin=None,
distance_point=None,
models=None,
limit_to_registered_models=None,
result_class=None,
**extra_kwargs):
index = haystack.connections[self.connection_alias].get_unified_index()
content_field = index.document_field
filters = []
filters_with_score = []
filter_query_strings = {
'content': u'%s',
'contains': u'*%s*',
'endswith': u'*%s',
'startswith': u'%s*',
'exact': u'%s',
'gt': u'{%s TO *}',
'gte': u'[%s TO *]',
'lt': u'{* TO %s}',
'lte': u'[* TO %s]',
'fuzzy': u'%s~',
}
# if filter_context:
# for f in filter_context:
# if f.get('content'):
# content = str(f.pop('content'))
# if query_string == '*:*':
# query_string = content
# else:
# query_string = '%s %s' % (query_string, content)
# for k, v in f.items():
# _filter = None
# _filter_with_score = None
# try:
# _value = v.prepare()
# except AttributeError:
# _value = str(v)
# _field, _lookup = self.get_filter_lookup(k)
# _is_nested = NESTED_FILTER_SEPARATOR in _field
# _nested_path = None
# if _is_nested:
# _nested_path = _field.split(NESTED_FILTER_SEPARATOR)[0]
# _field = ('.').join(_field.split(NESTED_FILTER_SEPARATOR))
# if _lookup == 'exact':
# if _is_nested:
# _filter = {'term': {_field: _value}}
# else:
# _filter = {'term': {_field + '.raw': _value}}
# elif _lookup == 'content':
# _filter_with_score = {'match': {_field: _value}}
# elif _lookup == 'in':
# if not isinstance(_value, list):
# _value = ast.literal_eval(str(_value))
# _filter = {
# 'query_string': {
# 'fields': [_field],
# 'query': ' OR '.join(['"%s"' % i for i in _value])
# }}
# elif _lookup == 'range':
# if isinstance(_value, dict):
# _filter = {'range': {_field: _value}}
# elif _value:
# if not isinstance(_value, list):
# _value = _value.split(',')
# if len(_value) >= 2:
# _range = {}
# _range['gte'] = _value[0]
# _range['lte'] = _value[1]
# _filter = {'range': {_field: _range}}
# else:
# raise ValueError(
# _('Range lookup requires minimum and maximum values,'
# 'only one value was provided'))
# else:
# _filter = {
# 'query_string': {
# 'fields': [_field],
# 'query': filter_query_strings[_lookup] % _value,
# }}
#
# # nested filter
# if _is_nested:
# if _filter:
# _filter = {
# 'nested': {
# 'path': _nested_path,
# 'query': _filter
# }
# }
# if _filter_with_score:
# _filter_with_score = {
# 'nested': {
# 'path': _nested_path,
# 'query': _filter_with_score
# }
# }
#
# if _filter:
# filters.append(_filter)
# if _filter_with_score:
# filters.append(_filter_with_score)
if query_string == '*:*':
kwargs = {
'query': {
"match_all": {}
},
}
else:
kwargs = {
'query': {
'query_string': {
'fields': [content_field],
'default_operator': DEFAULT_OPERATOR,
'query': query_string,
'analyze_wildcard': True,
'auto_generate_phrase_queries': True,
'fuzzy_max_expansions': FUZZY_MAX_EXPANSIONS,
},
},
}
if boost_fields:
kwargs['query']['query_string']['fields'] = []
for boost_field, boost_value in boost_fields.items():
kwargs['query']['query_string']['fields'].append(
'%s^%s' % (boost_field, boost_value))
if boost_negative:
boosting = {
'positive': kwargs['query'],
'negative': boost_negative[0],
'negative_boost': boost_negative[1]
}
kwargs['query'] = {'boosting': boosting}
if filters_with_score:
kwargs['query'] = {"bool": {"must": [kwargs.pop("query")]}}
kwargs['query']['bool']['must'] += filters_with_score
if fields:
if isinstance(fields, (list, set)):
fields = " ".join(fields)
kwargs['stored_fields'] = fields
if sort_by is not None:
order_list = []
for field, direction in sort_by:
if field == 'distance' and distance_point:
lng, lat = distance_point['point'].get_coords()
sort_kwargs = {
"_geo_distance": {
distance_point['field']: [lng, lat],
"order": direction,
"unit": "km"
}
}
else:
if field == 'distance':
warnings.warn(
"In order to sort by distance, "
"you must call the '.distance(...)' method.")
sort_kwargs = {field: {'order': direction}}
order_list.append(sort_kwargs)
kwargs['sort'] = order_list
if highlight:
kwargs['highlight'] = {
'fields': {
content_field: {},
}
}
if isinstance(highlight, dict):
kwargs['highlight'].update(highlight)
if self.include_spelling:
kwargs['suggest'] = {
'suggest': {
'text': spelling_query or query_string,
'term': {
'field': '_all',
},
},
}
if narrow_queries is None:
narrow_queries = set()
if facets is not None:
kwargs.setdefault('aggregations', {})
for facet_fieldname, extra_options in facets.items():
facet_options = {
'terms': {
'field': facet_fieldname + '.raw',
'size': 100,
},
}
# Special cases for options applied at the facet level (not the terms level).
if extra_options.pop('global_scope', False):
# Renamed "global_scope" since "global" is a python keyword.
facet_options['global'] = True
if 'facet_filter' in extra_options:
facet_options['facet_filter'] = extra_options.pop(
'facet_filter')
facet_options['terms'].update(extra_options)
kwargs['aggregations'][facet_fieldname] = facet_options
if date_facets is not None:
kwargs.setdefault('aggregations', {})
for facet_fieldname, value in date_facets.items():
# Need to detect on gap_by & only add amount if it's more than one.
interval = value.get('gap_by').lower()
# Need to detect on amount (can't be applied on months or years).
if value.get('gap_amount',
1) != 1 and interval not in ('month', 'year'):
# Just the first character is valid for use.
interval = "%s%s" % (value['gap_amount'], interval[:1])
date_histogram_aggregation_name = "{0}{1}".format(
facet_fieldname, DATE_HISTOGRAM_FIELD_NAME_SUFFIX)
date_range_aggregation_name = "{0}{1}".format(
facet_fieldname, DATE_RANGE_FIELD_NAME_SUFFIX)
kwargs['aggregations'][date_histogram_aggregation_name] = {
'meta': {
'_type': 'haystack_date_histogram',
},
'date_histogram': {
'field': facet_fieldname,
'interval': interval,
},
}
kwargs['aggregations'][date_range_aggregation_name] = {
'meta': {
'_type': 'haystack_date_range',
},
'date_range': { # agg type
'field':
facet_fieldname,
'ranges': [{
'from':
self._from_python(value.get('start_date')),
'to':
self._from_python(value.get('end_date')),
}]
}
}
if query_facets is not None:
kwargs.setdefault('aggregations', {})
for facet_fieldname, value in query_facets:
kwargs['aggregations'][facet_fieldname] = {
'filter': {
'query_string': {
'query': value,
}
}
}
if limit_to_registered_models is None:
limit_to_registered_models = getattr(
settings, 'HAYSTACK_LIMIT_TO_REGISTERED_MODELS', True)
if models and len(models):
model_choices = sorted(get_model_ct(model) for model in models)
elif limit_to_registered_models:
# Using narrow queries, limit the results to only models handled
# with the current routers.
model_choices = self.build_models_list()
else:
model_choices = []
if len(model_choices) > 0:
filters.append({"terms": {DJANGO_CT: model_choices}})
if within is not None:
from haystack.utils.geo import generate_bounding_box
((south, west),
(north, east)) = generate_bounding_box(within['point_1'],
within['point_2'])
within_filter = {
"geo_bounding_box": {
within['field']: {
"top_left": {
"lat": north,
"lon": west
},
"bottom_right": {
"lat": south,
"lon": east
}
}
},
}
filters.append(within_filter)
if dwithin is not None:
lng, lat = dwithin['point'].get_coords()
# NB: the 1.0.0 release of elasticsearch introduce an
# incompatible change on the distance filter formating
if elasticsearch.VERSION >= (1, 0, 0):
distance = "%(dist).6f%(unit)s" % {
'dist': dwithin['distance'].km,
'unit': "km"
}
else:
distance = dwithin['distance'].km
dwithin_filter = {
"geo_distance": {
"distance": distance,
dwithin['field']: {
"lat": lat,
"lon": lng
}
}
}
filters.append(dwithin_filter)
# for q in narrow_queries:
# key, value = q.split(':')[0], ':'.join(q.split(':')[1:])
# filters.append({
# 'match': {
# key: value
# },
# })
for q in narrow_queries:
filters.append({'query_string': {'query': q}})
# if we want to filter, change the query type to filtered
if filters:
kwargs["query"] = {"bool": {"must": kwargs.pop("query")}}
if len(filters) == 1:
kwargs['query']['bool']["filter"] = filters[0]
else:
kwargs['query']['bool']["filter"] = {"bool": {"must": filters}}
if extra_kwargs:
kwargs.update(extra_kwargs)
return kwargs
def build_search_kwargs(
self,
query_string,
sort_by=None,
start_offset=0,
end_offset=None,
fields="",
highlight=False,
facets=None,
date_facets=None,
query_facets=None,
narrow_queries=None,
spelling_query=None,
within=None,
dwithin=None,
distance_point=None,
models=None,
limit_to_registered_models=None,
result_class=None,
custom_score=None,
):
index = haystack.connections[self.connection_alias].get_unified_index()
content_field = index.document_field
if query_string == "*:*":
kwargs = {"query": {"filtered": {"query": {"match_all": {}}}}}
else:
query_string_content = self._get_query_string_content(content_field, query_string)
kwargs = {"query": {"filtered": {"query": {"query_string": query_string_content}}}}
if fields:
if isinstance(fields, (list, set)):
fields = " ".join(fields)
kwargs["fields"] = fields
if sort_by is not None:
order_list = []
for field, direction in sort_by:
if field == "distance" and distance_point:
# Do the geo-enabled sort.
lng, lat = distance_point["point"].get_coords()
sort_kwargs = {
"_geo_distance": {distance_point["field"]: [lng, lat], "order": direction, "unit": "km"}
}
else:
if field == "distance":
warnings.warn("In order to sort by distance, you must call the '.distance(...)' method.")
# Regular sorting.
sort_kwargs = {field: {"order": direction}}
order_list.append(sort_kwargs)
kwargs["sort"] = order_list
# From/size offsets don't seem to work right in Elasticsearch's DSL. :/
# if start_offset is not None:
# kwargs['from'] = start_offset
# if end_offset is not None:
# kwargs['size'] = end_offset - start_offset
if highlight is True:
kwargs["highlight"] = {"fields": {content_field: {"store": "yes"}}}
if self.include_spelling is True:
warnings.warn("Elasticsearch does not handle spelling suggestions.", Warning, stacklevel=2)
if narrow_queries is None:
narrow_queries = set()
if facets is not None:
kwargs.setdefault("facets", {})
for facet_fieldname in facets:
kwargs["facets"][facet_fieldname] = {"terms": {"field": facet_fieldname, "size": 300}}
if date_facets is not None:
kwargs.setdefault("facets", {})
for facet_fieldname, value in date_facets.items():
# Need to detect on gap_by & only add amount if it's more than one.
interval = value.get("gap_by").lower()
# Need to detect on amount (can't be applied on months or years).
if value.get("gap_amount", 1) != 1 and not interval in ("month", "year"):
# Just the first character is valid for use.
interval = "%s%s" % (value["gap_amount"], interval[:1])
kwargs["facets"][facet_fieldname] = {
"date_histogram": {"field": facet_fieldname, "interval": interval},
"facet_filter": {
"range": {
facet_fieldname: {
"from": self._from_python(value.get("start_date")),
"to": self._from_python(value.get("end_date")),
}
}
},
}
if query_facets is not None:
kwargs.setdefault("facets", {})
for facet_fieldname, value in query_facets:
kwargs["facets"][facet_fieldname] = {"query": {"query_string": {"query": value}}}
if limit_to_registered_models is None:
limit_to_registered_models = getattr(settings, "HAYSTACK_LIMIT_TO_REGISTERED_MODELS", True)
if models and len(models):
model_choices = sorted(["%s.%s" % (model._meta.app_label, model._meta.module_name) for model in models])
elif limit_to_registered_models:
# Using narrow queries, limit the results to only models handled
# with the current routers.
model_choices = self.build_models_list()
else:
model_choices = []
if len(model_choices) > 0:
if narrow_queries is None:
narrow_queries = set()
narrow_queries.add("%s:(%s)" % (DJANGO_CT, " OR ".join(model_choices)))
if narrow_queries:
kwargs["query"].setdefault("filtered", {})
kwargs["query"]["filtered"].setdefault("filter", {})
kwargs["query"]["filtered"]["filter"] = {
"fquery": {"query": {"query_string": {"query": u" AND ".join(list(narrow_queries))}}, "_cache": True}
}
if within is not None:
from haystack.utils.geo import generate_bounding_box
((south, west), (north, east)) = generate_bounding_box(within["point_1"], within["point_2"])
within_filter = {
"geo_bounding_box": {
within["field"]: {
"top_left": {"lat": north, "lon": west},
"bottom_right": {"lat": south, "lon": east},
}
}
}
kwargs["query"].setdefault("filtered", {})
kwargs["query"]["filtered"].setdefault("filter", {})
if kwargs["query"]["filtered"]["filter"]:
compound_filter = {"and": [kwargs["query"]["filtered"]["filter"], within_filter]}
kwargs["query"]["filtered"]["filter"] = compound_filter
else:
kwargs["query"]["filtered"]["filter"] = within_filter
if dwithin is not None:
lng, lat = dwithin["point"].get_coords()
dwithin_filter = {
"geo_distance": {"distance": dwithin["distance"].km, dwithin["field"]: {"lat": lat, "lon": lng}}
}
kwargs["query"].setdefault("filtered", {})
kwargs["query"]["filtered"].setdefault("filter", {})
if kwargs["query"]["filtered"]["filter"]:
compound_filter = {"and": [kwargs["query"]["filtered"]["filter"], dwithin_filter]}
kwargs["query"]["filtered"]["filter"] = compound_filter
else:
kwargs["query"]["filtered"]["filter"] = dwithin_filter
# Remove the "filtered" key if we're not filtering. Otherwise,
# Elasticsearch will blow up.
if not kwargs["query"]["filtered"].get("filter"):
kwargs["query"] = kwargs["query"]["filtered"]["query"]
if custom_score:
new_kwargs = kwargs.copy()
new_kwargs["query"] = {}
new_kwargs["query"]["custom_score"] = custom_score.copy()
new_kwargs["query"]["custom_score"]["query"] = kwargs["query"].copy()
return new_kwargs
return kwargs
def build_search_kwargs(self,
query_string,
sort_by=None,
start_offset=0,
end_offset=None,
fields='',
highlight=False,
facets=None,
date_facets=None,
query_facets=None,
narrow_queries=None,
spelling_query=None,
within=None,
dwithin=None,
distance_point=None,
models=None,
limit_to_registered_models=None,
result_class=None,
**extra_kwargs):
index = haystack.connections[self.connection_alias].get_unified_index()
content_field = index.document_field
if query_string == '*:*':
kwargs = {
'query': {
"match_all": {}
},
}
else:
kwargs = {
'query': {
'query_string': {
'default_field': content_field,
'default_operator': DEFAULT_OPERATOR,
'query': query_string,
'analyze_wildcard': True,
'auto_generate_phrase_queries': True,
# elasticsearch.exceptions.RequestError: TransportError(400, 'parsing_exception', '[query_string] query does not support [fuzzy_min_sim]')
# 'fuzzy_min_sim': FUZZY_MIN_SIM,
'fuzzy_max_expansions': FUZZY_MAX_EXPANSIONS,
},
},
}
# so far, no filters
filters = []
if fields:
if isinstance(fields, (list, set)):
fields = " ".join(fields)
kwargs['stored_fields'] = fields
if sort_by is not None:
order_list = []
for field, direction in sort_by:
if field == 'distance' and distance_point:
# Do the geo-enabled sort.
lng, lat = distance_point['point'].get_coords()
sort_kwargs = {
"_geo_distance": {
distance_point['field']: [lng, lat],
"order": direction,
"unit": "km"
}
}
else:
if field == 'distance':
warnings.warn(
"In order to sort by distance, you must call the '.distance(...)' method."
)
# Regular sorting.
sort_kwargs = {field: {'order': direction}}
order_list.append(sort_kwargs)
kwargs['sort'] = order_list
# From/size offsets don't seem to work right in Elasticsearch's DSL. :/
# if start_offset is not None:
# kwargs['from'] = start_offset
# if end_offset is not None:
# kwargs['size'] = end_offset - start_offset
if highlight:
# `highlight` can either be True or a dictionary containing custom parameters
# which will be passed to the backend and may override our default settings:
kwargs['highlight'] = {
'fields': {
# content_field: {'store': 'yes'},
content_field: {},
}
}
if isinstance(highlight, dict):
kwargs['highlight'].update(highlight)
if self.include_spelling:
kwargs['suggest'] = {
'suggest': {
'text': spelling_query or query_string,
'term': {
# Using content_field here will result in suggestions of stemmed words.
'field': '_all',
},
},
}
if narrow_queries is None:
narrow_queries = set()
if facets is not None:
kwargs.setdefault('aggregations', {})
for facet_fieldname, extra_options in facets.items():
facet_options = {
'terms': {
'field': facet_fieldname,
'size': 100,
},
}
# Special cases for options applied at the facet level (not the terms level).
if extra_options.pop('global_scope', False):
# Renamed "global_scope" since "global" is a python keyword.
facet_options['global'] = True
if 'facet_filter' in extra_options:
facet_options['facet_filter'] = extra_options.pop(
'facet_filter')
facet_options['terms'].update(extra_options)
kwargs['aggregations'][facet_fieldname] = facet_options
if date_facets is not None:
kwargs.setdefault('aggregations', {})
for facet_fieldname, value in date_facets.items():
# Need to detect on gap_by & only add amount if it's more than one.
interval = value.get('gap_by').lower()
# Need to detect on amount (can't be applied on months or years).
if value.get('gap_amount',
1) != 1 and interval not in ('month', 'year'):
# Just the first character is valid for use.
interval = "%s%s" % (value['gap_amount'], interval[:1])
date_histogram_aggregation_name = "{0}{1}".format(
facet_fieldname, DATE_HISTOGRAM_FIELD_NAME_SUFFIX)
date_range_aggregation_name = "{0}{1}".format(
facet_fieldname, DATE_RANGE_FIELD_NAME_SUFFIX)
kwargs['aggregations'][date_histogram_aggregation_name] = {
'meta': {
'_type': 'haystack_date_histogram',
},
'date_histogram': {
'field': facet_fieldname,
'interval': interval,
},
}
kwargs['aggregations'][date_range_aggregation_name] = {
'meta': {
'_type': 'haystack_date_range',
},
'date_range': { # agg type
'field':
facet_fieldname,
'ranges': [{
'from':
self._from_python(value.get('start_date')),
'to':
self._from_python(value.get('end_date')),
}]
}
}
if query_facets is not None:
kwargs.setdefault('aggregations', {})
for facet_fieldname, value in query_facets:
kwargs['aggregations'][facet_fieldname] = {
'filter': {
'query_string': {
'query': value,
}
}
}
if limit_to_registered_models is None:
limit_to_registered_models = getattr(
settings, 'HAYSTACK_LIMIT_TO_REGISTERED_MODELS', True)
if models and len(models):
model_choices = sorted(get_model_ct(model) for model in models)
elif limit_to_registered_models:
# Using narrow queries, limit the results to only models handled
# with the current routers.
model_choices = self.build_models_list()
else:
model_choices = []
if len(model_choices) > 0:
filters.append({"terms": {DJANGO_CT: model_choices}})
for q in narrow_queries:
filters.append({'query_string': {'query': q}})
if within is not None:
from haystack.utils.geo import generate_bounding_box
((south, west),
(north, east)) = generate_bounding_box(within['point_1'],
within['point_2'])
within_filter = {
"geo_bounding_box": {
within['field']: {
"top_left": {
"lat": north,
"lon": west
},
"bottom_right": {
"lat": south,
"lon": east
}
}
},
}
filters.append(within_filter)
if dwithin is not None:
lng, lat = dwithin['point'].get_coords()
# NB: the 1.0.0 release of elasticsearch introduce an
# incompatible change on the distance filter formating
if elasticsearch.VERSION >= (1, 0, 0):
distance = "%(dist).6f%(unit)s" % {
'dist': dwithin['distance'].km,
'unit': "km"
}
else:
distance = dwithin['distance'].km
dwithin_filter = {
"geo_distance": {
"distance": distance,
dwithin['field']: {
"lat": lat,
"lon": lng
}
}
}
filters.append(dwithin_filter)
# if we want to filter, change the query type to filteres
if filters:
kwargs["query"] = {"bool": {"must": kwargs.pop("query")}}
if len(filters) == 1:
kwargs['query']['bool']["filter"] = filters[0]
else:
kwargs['query']['bool']["filter"] = {"bool": {"must": filters}}
if extra_kwargs:
kwargs.update(extra_kwargs)
return kwargs
def build_search_kwargs(
self,
query_string,
sort_by=None,
start_offset=0,
end_offset=None,
fields="",
highlight=False,
facets=None,
date_facets=None,
query_facets=None,
narrow_queries=None,
spelling_query=None,
within=None,
dwithin=None,
distance_point=None,
models=None,
limit_to_registered_models=None,
result_class=None,
pivot_facets=None,
rows=None,
group=None,
):
kwargs = {"fl": "* score"}
if fields:
if isinstance(fields, (list, set)):
fields = " ".join(fields)
kwargs["fl"] = fields
if sort_by is not None:
if distance_point:
# Do the geo-enabled sort.
lng, lat = distance_point["point"].get_coords()
kwargs["sfield"] = distance_point["field"]
kwargs["pt"] = "%s,%s" % (lat, lng)
if sort_by in ["distance asc", "distance desc"]:
if sort_by == "distance asc":
kwargs["sort"] = "geodist() asc"
else:
kwargs["sort"] = "geodist() desc"
else:
if sort_by.startswith("distance "):
warnings.warn("In order to sort by distance, you must call the '.distance(...)' method.")
# Regular sorting.
kwargs["sort"] = sort_by
if start_offset is not None:
kwargs["start"] = start_offset
if end_offset is not None:
kwargs["rows"] = end_offset - start_offset
if highlight is True:
kwargs["hl"] = "true"
kwargs["hl.fragsize"] = "200"
if self.include_spelling is True:
kwargs["spellcheck"] = "true"
kwargs["spellcheck.collate"] = "true"
kwargs["spellcheck.count"] = 1
if spelling_query:
kwargs["spellcheck.q"] = spelling_query
if facets is not None:
kwargs["facet"] = "on"
kwargs["facet.field"] = facets
kwargs["facet.limit"] = 350
if pivot_facets is not None:
kwargs["facet"] = "on"
kwargs["facet.pivot"] = pivot_facets
kwargs["facet.limit"] = 400
if group is not None:
kwargs["group"] = "true"
kwargs["group.field"] = group["field"]
kwargs["group.facet"] = "true" if group["facet"] else "false"
kwargs["group.ngroup"] = group["ngroup"]
if rows is not None:
kwargs["rows"] = rows
if date_facets is not None:
kwargs["facet"] = "on"
kwargs["facet.date"] = date_facets.keys()
kwargs["facet.date.other"] = "none"
for key, value in date_facets.items():
kwargs["f.%s.facet.date.start" % key] = self.conn._from_python(value.get("start_date"))
kwargs["f.%s.facet.date.end" % key] = self.conn._from_python(value.get("end_date"))
gap_by_string = value.get("gap_by").upper()
gap_string = "%d%s" % (value.get("gap_amount"), gap_by_string)
if value.get("gap_amount") != 1:
gap_string += "S"
kwargs["f.%s.facet.date.gap" % key] = "+%s/%s" % (gap_string, gap_by_string)
if query_facets is not None:
kwargs["facet"] = "on"
kwargs["facet.query"] = ["%s:%s" % (field, value) for field, value in query_facets]
if limit_to_registered_models is None:
limit_to_registered_models = getattr(settings, "HAYSTACK_LIMIT_TO_REGISTERED_MODELS", True)
if models and len(models):
model_choices = sorted(["%s.%s" % (model._meta.app_label, model._meta.module_name) for model in models])
elif limit_to_registered_models:
# Using narrow queries, limit the results to only models handled
# with the current routers.
model_choices = self.build_models_list()
else:
model_choices = []
if len(model_choices) > 0:
if narrow_queries is None:
narrow_queries = set()
narrow_queries.add("%s:(%s)" % (DJANGO_CT, " OR ".join(model_choices)))
if narrow_queries is not None:
kwargs["fq"] = list(narrow_queries)
if within is not None:
from haystack.utils.geo import generate_bounding_box
kwargs.setdefault("fq", [])
((min_lat, min_lng), (max_lat, max_lng)) = generate_bounding_box(within["point_1"], within["point_2"])
# Bounding boxes are min, min TO max, max. Solr's wiki was *NOT*
# very clear on this.
bbox = "%s:[%s,%s TO %s,%s]" % (within["field"], min_lat, min_lng, max_lat, max_lng)
kwargs["fq"].append(bbox)
if dwithin is not None:
kwargs.setdefault("fq", [])
lng, lat = dwithin["point"].get_coords()
geofilt = "{!geofilt pt=%s,%s sfield=%s d=%s}" % (lat, lng, dwithin["field"], dwithin["distance"].km)
kwargs["fq"].append(geofilt)
# Check to see if the backend should try to include distances
# (Solr 4.X+) in the results.
if self.distance_available and distance_point:
# In early testing, you can't just hand Solr 4.X a proper bounding box
# & request distances. To enable native distance would take calculating
# a center point & a radius off the user-provided box, which kinda
# sucks. We'll avoid it for now, since Solr 4.x's release will be some
# time yet.
# kwargs['fl'] += ' _dist_:geodist()'
pass
return kwargs
def build_search_kwargs(self, query_string, sort_by=None, start_offset=0, end_offset=None,
fields='', highlight=False, facets=None,
date_facets=None, query_facets=None,
narrow_queries=None, spelling_query=None,
within=None, dwithin=None, distance_point=None,
models=None, limit_to_registered_models=None,
result_class=None):
"""Build all kwargs necessaries to perform the query.
:param query_string: Query string.
:type query_string: str
:param sort_by:
:param start_offset: If query is partially done, this parameters will represents where the slice begins.
:type start_offset: int
:param end_offset: If query is partially done, this parameters will represents where the slice ends.
:type end_offset: int
:param fields: Fields that will be searched for.
:type fields: str
:param highlight:
:param facets:
:param date_facets:
:param query_facets:
:param narrow_queries:
:param spelling_query:
:param within:
:param dwithin:
:param distance_point:
:param models: List of models over the query will be performed.
:type models: list
:param limit_to_registered_models:
:param result_class: Class used for search results.
:type result_class: object
:return: Search kwargs.
:rtype: dict
"""
if query_string == '*:*':
kwargs = {
'query': {
"match_all": {}
},
}
else:
kwargs = {
'query': {
'query_string': {
'default_operator': DEFAULT_OPERATOR,
'query': query_string,
'analyze_wildcard': True,
'auto_generate_phrase_queries': True,
},
},
}
if limit_to_registered_models is None:
limit_to_registered_models = getattr(settings, 'HAYSTACK_LIMIT_TO_REGISTERED_MODELS', True)
if models and len(models):
model_choices = sorted(get_model_ct(model) for model in models)
elif limit_to_registered_models:
# Using narrow queries, limit the results to only models handled
# with the current routers.
model_choices = self.build_models_list()
else:
model_choices = []
kwargs['models'] = model_choices
filters = []
if fields:
if isinstance(fields, (list, set)):
fields = " ".join(fields)
kwargs['fields'] = fields
if sort_by is not None:
order_list = []
for field, direction in sort_by:
if field == 'distance' and distance_point:
# Do the geo-enabled sort.
lng, lat = distance_point['point'].get_coords()
sort_kwargs = {
"_geo_distance": {
distance_point['field']: [lng, lat],
"order": direction,
"unit": "km"
}
}
else:
if field == 'distance':
warnings.warn("In order to sort by distance, you must call the '.distance(...)' method.")
# Regular sorting.
sort_kwargs = {field: {'order': direction}}
order_list.append(sort_kwargs)
kwargs['sort'] = order_list
if highlight is True:
kwargs['highlight'] = {
'fields': {
'_all': {'store': 'yes'},
}
}
if self.include_spelling:
kwargs['suggest'] = {
'suggest': {
'text': spelling_query or query_string,
'term': {
# Using content_field here will result in suggestions of stemmed words.
'field': '_all',
},
},
}
if narrow_queries is None:
narrow_queries = set()
if facets is not None:
kwargs.setdefault('facets', {})
for facet_fieldname, extra_options in facets.items():
facet_options = {
'terms': {
'field': facet_fieldname,
'size': 100,
},
}
# Special cases for options applied at the facet level (not the terms level).
if extra_options.pop('global_scope', False):
# Renamed "global_scope" since "global" is a python keyword.
facet_options['global'] = True
if 'facet_filter' in extra_options:
facet_options['facet_filter'] = extra_options.pop('facet_filter')
facet_options['terms'].update(extra_options)
kwargs['facets'][facet_fieldname] = facet_options
if date_facets is not None:
kwargs.setdefault('facets', {})
for facet_fieldname, value in date_facets.items():
# Need to detect on gap_by & only add amount if it's more than one.
interval = value.get('gap_by').lower()
# Need to detect on amount (can't be applied on months or years).
if value.get('gap_amount', 1) != 1 and interval not in ('month', 'year'):
# Just the first character is valid for use.
interval = "%s%s" % (value['gap_amount'], interval[:1])
kwargs['facets'][facet_fieldname] = {
'date_histogram': {
'field': facet_fieldname,
'interval': interval,
},
'facet_filter': {
"range": {
facet_fieldname: {
'from': self._from_python(value.get('start_date')),
'to': self._from_python(value.get('end_date')),
}
}
}
}
if query_facets is not None:
kwargs.setdefault('facets', {})
for facet_fieldname, value in query_facets:
kwargs['facets'][facet_fieldname] = {
'query': {
'query_string': {
'query': value,
}
},
}
for q in narrow_queries:
filters.append({
'fquery': {
'query': {
'query_string': {
'query': q
},
},
'_cache': True,
}
})
if within is not None:
from haystack.utils.geo import generate_bounding_box
((south, west), (north, east)) = generate_bounding_box(within['point_1'], within['point_2'])
within_filter = {
"geo_bounding_box": {
within['field']: {
"top_left": {
"lat": north,
"lon": west
},
"bottom_right": {
"lat": south,
"lon": east
}
}
},
}
filters.append(within_filter)
if dwithin is not None:
lng, lat = dwithin['point'].get_coords()
dwithin_filter = {
"geo_distance": {
"distance": dwithin['distance'].km,
dwithin['field']: {
"lat": lat,
"lon": lng
}
}
}
filters.append(dwithin_filter)
# if we want to filter, change the query type to filteres
if filters:
kwargs["query"] = {"filtered": {"query": kwargs.pop("query")}}
if len(filters) == 1:
kwargs['query']['filtered']["filter"] = filters[0]
else:
kwargs['query']['filtered']["filter"] = {"bool": {"must": filters}}
return kwargs
def build_search_kwargs(self, query_string, sort_by=None, start_offset=0, end_offset=None,
fields='', highlight=False, facets=None,
date_facets=None, query_facets=None,
narrow_queries=None, spelling_query=None,
within=None, dwithin=None, distance_point=None,
models=None, limit_to_registered_models=None,
result_class=None, stats=None):
kwargs = {'fl': '* score'}
if fields:
if isinstance(fields, (list, set)):
fields = " ".join(fields)
kwargs['fl'] = fields
if sort_by is not None:
if sort_by in ['distance asc', 'distance desc'] and distance_point:
# Do the geo-enabled sort.
lng, lat = distance_point['point'].get_coords()
kwargs['sfield'] = distance_point['field']
kwargs['pt'] = '%s,%s' % (lat, lng)
if sort_by == 'distance asc':
kwargs['sort'] = 'geodist() asc'
else:
kwargs['sort'] = 'geodist() desc'
else:
if sort_by.startswith('distance '):
warnings.warn("In order to sort by distance, you must call the '.distance(...)' method.")
# Regular sorting.
kwargs['sort'] = sort_by
if start_offset is not None:
kwargs['start'] = start_offset
if end_offset is not None:
kwargs['rows'] = end_offset - start_offset
if highlight is True:
kwargs['hl'] = 'true'
kwargs['hl.fragsize'] = '200'
if self.include_spelling is True:
kwargs['spellcheck'] = 'true'
kwargs['spellcheck.collate'] = 'true'
kwargs['spellcheck.count'] = 1
if spelling_query:
kwargs['spellcheck.q'] = spelling_query
if facets is not None:
kwargs['facet'] = 'on'
kwargs['facet.field'] = facets.keys()
for facet_field, options in facets.items():
for key, value in options.items():
kwargs['f.%s.facet.%s' % (facet_field, key)] = self.conn._from_python(value)
if date_facets is not None:
kwargs['facet'] = 'on'
kwargs['facet.date'] = date_facets.keys()
kwargs['facet.date.other'] = 'none'
for key, value in date_facets.items():
kwargs["f.%s.facet.date.start" % key] = self.conn._from_python(value.get('start_date'))
kwargs["f.%s.facet.date.end" % key] = self.conn._from_python(value.get('end_date'))
gap_by_string = value.get('gap_by').upper()
gap_string = "%d%s" % (value.get('gap_amount'), gap_by_string)
if value.get('gap_amount') != 1:
gap_string += "S"
kwargs["f.%s.facet.date.gap" % key] = '+%s/%s' % (gap_string, gap_by_string)
if query_facets is not None:
kwargs['facet'] = 'on'
kwargs['facet.query'] = ["%s:%s" % (field, value) for field, value in query_facets]
if limit_to_registered_models is None:
limit_to_registered_models = getattr(settings, 'HAYSTACK_LIMIT_TO_REGISTERED_MODELS', True)
if models and len(models):
model_choices = sorted(get_model_ct(model) for model in models)
elif limit_to_registered_models:
# Using narrow queries, limit the results to only models handled
# with the current routers.
model_choices = self.build_models_list()
else:
model_choices = []
if len(model_choices) > 0:
if narrow_queries is None:
narrow_queries = set()
narrow_queries.add('%s:(%s)' % (DJANGO_CT, ' OR '.join(model_choices)))
if narrow_queries is not None:
kwargs['fq'] = list(narrow_queries)
if stats:
kwargs['stats'] = "true"
for k in stats.keys():
kwargs['stats.field'] = k
for facet in stats[k]:
kwargs['f.%s.stats.facet' % k] = facet
if within is not None:
from haystack.utils.geo import generate_bounding_box
kwargs.setdefault('fq', [])
((min_lat, min_lng), (max_lat, max_lng)) = generate_bounding_box(within['point_1'], within['point_2'])
# Bounding boxes are min, min TO max, max. Solr's wiki was *NOT*
# very clear on this.
bbox = '%s:[%s,%s TO %s,%s]' % (within['field'], min_lat, min_lng, max_lat, max_lng)
kwargs['fq'].append(bbox)
if dwithin is not None:
kwargs.setdefault('fq', [])
lng, lat = dwithin['point'].get_coords()
geofilt = '{!geofilt pt=%s,%s sfield=%s d=%s}' % (lat, lng, dwithin['field'], dwithin['distance'].km)
kwargs['fq'].append(geofilt)
# Check to see if the backend should try to include distances
# (Solr 4.X+) in the results.
if self.distance_available and distance_point:
# In early testing, you can't just hand Solr 4.X a proper bounding box
# & request distances. To enable native distance would take calculating
# a center point & a radius off the user-provided box, which kinda
# sucks. We'll avoid it for now, since Solr 4.x's release will be some
# time yet.
# kwargs['fl'] += ' _dist_:geodist()'
pass
return kwargs
def build_search_kwargs(
self,
query_string,
sort_by=None,
start_offset=0,
end_offset=None,
fields="",
highlight=False,
facets=None,
date_facets=None,
query_facets=None,
narrow_queries=None,
spelling_query=None,
within=None,
dwithin=None,
distance_point=None,
models=None,
limit_to_registered_models=None,
result_class=None,
stats=None,
collate=None,
**extra_kwargs
):
index = haystack.connections[self.connection_alias].get_unified_index()
kwargs = {"fl": "* score", "df": index.document_field}
if fields:
if isinstance(fields, (list, set)):
fields = " ".join(fields)
kwargs["fl"] = fields
if sort_by is not None:
if sort_by in ["distance asc", "distance desc"] and distance_point:
# Do the geo-enabled sort.
lng, lat = distance_point["point"].coords
kwargs["sfield"] = distance_point["field"]
kwargs["pt"] = "%s,%s" % (lat, lng)
if sort_by == "distance asc":
kwargs["sort"] = "geodist() asc"
else:
kwargs["sort"] = "geodist() desc"
else:
if sort_by.startswith("distance "):
warnings.warn(
"In order to sort by distance, you must call the '.distance(...)' method."
)
# Regular sorting.
kwargs["sort"] = sort_by
if start_offset is not None:
kwargs["start"] = start_offset
if end_offset is not None:
kwargs["rows"] = end_offset - start_offset
if highlight:
# `highlight` can either be True or a dictionary containing custom parameters
# which will be passed to the backend and may override our default settings:
kwargs["hl"] = "true"
kwargs["hl.fragsize"] = "200"
if isinstance(highlight, dict):
# autoprefix highlighter options with 'hl.', all of them start with it anyway
# this makes option dicts shorter: {'maxAnalyzedChars': 42}
# and lets some of options be used as keyword arguments: `.highlight(preserveMulti=False)`
kwargs.update(
{
key if key.startswith("hl.") else ("hl." + key): highlight[key]
for key in highlight.keys()
}
)
if collate is None:
collate = self.collate
if self.include_spelling is True:
kwargs["spellcheck"] = "true"
kwargs["spellcheck.collate"] = str(collate).lower()
kwargs["spellcheck.count"] = 1
if spelling_query:
kwargs["spellcheck.q"] = spelling_query
if facets is not None:
kwargs["facet"] = "on"
kwargs["facet.field"] = facets.keys()
for facet_field, options in facets.items():
for key, value in options.items():
kwargs[
"f.%s.facet.%s" % (facet_field, key)
] = self.conn._from_python(value)
if date_facets is not None:
kwargs["facet"] = "on"
kwargs["facet.date"] = date_facets.keys()
kwargs["facet.date.other"] = "none"
for key, value in date_facets.items():
kwargs["f.%s.facet.date.start" % key] = self.conn._from_python(
value.get("start_date")
)
kwargs["f.%s.facet.date.end" % key] = self.conn._from_python(
value.get("end_date")
)
gap_by_string = value.get("gap_by").upper()
gap_string = "%d%s" % (value.get("gap_amount"), gap_by_string)
if value.get("gap_amount") != 1:
gap_string += "S"
kwargs["f.%s.facet.date.gap" % key] = "+%s/%s" % (
gap_string,
gap_by_string,
)
if query_facets is not None:
kwargs["facet"] = "on"
kwargs["facet.query"] = [
"%s:%s" % (field, value) for field, value in query_facets
]
if limit_to_registered_models is None:
limit_to_registered_models = getattr(
settings, "HAYSTACK_LIMIT_TO_REGISTERED_MODELS", True
)
if models and len(models):
model_choices = sorted(get_model_ct(model) for model in models)
elif limit_to_registered_models:
# Using narrow queries, limit the results to only models handled
# with the current routers.
model_choices = self.build_models_list()
else:
model_choices = []
if len(model_choices) > 0:
if narrow_queries is None:
narrow_queries = set()
narrow_queries.add("%s:(%s)" % (DJANGO_CT, " OR ".join(model_choices)))
if narrow_queries is not None:
kwargs["fq"] = list(narrow_queries)
if stats:
kwargs["stats"] = "true"
for k in stats.keys():
kwargs["stats.field"] = k
for facet in stats[k]:
kwargs["f.%s.stats.facet" % k] = facet
if within is not None:
from haystack.utils.geo import generate_bounding_box
kwargs.setdefault("fq", [])
((min_lat, min_lng), (max_lat, max_lng)) = generate_bounding_box(
within["point_1"], within["point_2"]
)
# Bounding boxes are min, min TO max, max. Solr's wiki was *NOT*
# very clear on this.
bbox = "%s:[%s,%s TO %s,%s]" % (
within["field"],
min_lat,
min_lng,
max_lat,
max_lng,
)
kwargs["fq"].append(bbox)
if dwithin is not None:
kwargs.setdefault("fq", [])
lng, lat = dwithin["point"].coords
geofilt = "{!geofilt pt=%s,%s sfield=%s d=%s}" % (
lat,
lng,
dwithin["field"],
dwithin["distance"].km,
)
kwargs["fq"].append(geofilt)
# Check to see if the backend should try to include distances
# (Solr 4.X+) in the results.
if self.distance_available and distance_point:
# In early testing, you can't just hand Solr 4.X a proper bounding box
# & request distances. To enable native distance would take calculating
# a center point & a radius off the user-provided box, which kinda
# sucks. We'll avoid it for now, since Solr 4.x's release will be some
# time yet.
# kwargs['fl'] += ' _dist_:geodist()'
pass
if extra_kwargs:
kwargs.update(extra_kwargs)
return kwargs
def search(self, query_string, sort_by=None, start_offset=0, end_offset=None,
fields='', highlight=False, facets=None, date_facets=None, query_facets=None,
narrow_queries=None, spelling_query=None, within=None,
dwithin=None, distance_point=None,
limit_to_registered_models=None, result_class=None, **kwargs):
if len(query_string) == 0:
return {
'results': [],
'hits': 0,
}
if not self.setup_complete:
self.setup()
index = haystack.connections[self.connection_alias].get_unified_index()
content_field = index.document_field
if query_string == '*:*':
kwargs = {
'query': {
'filtered': {
'query': {
'query_string': {
'query': '*:*',
},
},
},
},
}
else:
kwargs = {
'query': {
'filtered': {
'query': {
'query_string': {
'default_field': content_field,
'default_operator': DEFAULT_OPERATOR,
'query': query_string,
'analyze_wildcard': True,
'auto_generate_phrase_queries': True,
},
},
},
},
}
geo_sort = False
if fields:
if isinstance(fields, (list, set)):
fields = " ".join(fields)
kwargs['fields'] = fields
if sort_by is not None:
if sort_by in ['distance asc', 'distance desc'] and distance_point:
# Do the geo-enabled sort.
lng, lat = distance_point['point'].get_coords()
sort_kwargs = {
"_geo_distance": {
distance_point['field']: [lng, lat],
"order" : "asc",
"unit" : "km"
}
}
geo_sort = True
if sort_by == 'distance asc':
sort_kwargs['sort']['_geo_distance']['order'] = 'asc'
else:
sort_kwargs['sort']['_geo_distance']['order'] = 'desc'
kwargs['sort'] = [sort_kwargs]
else:
if sort_by.startswith('distance '):
warnings.warn("In order to sort by distance, you must call the '.distance(...)' method.")
# Regular sorting.
order_by_list = []
for order_by in self.order_by:
if order_by.startswith('-'):
order_by_list.append({order_by[1:]: 'desc'})
else:
order_by_list.append({order_by: 'asc'})
kwargs['sort'] = order_by_list
# From/size offsets don't seem to work right in Elasticsearch's DSL. :/
# if start_offset is not None:
# kwargs['from'] = start_offset
# if end_offset is not None:
# kwargs['size'] = end_offset - start_offset
if highlight is True:
kwargs['highlight'] = {
'fields': {
content_field: {'store': 'yes'},
}
}
if self.include_spelling is True:
warnings.warn("Elasticsearch does not handle spelling suggestions.", Warning, stacklevel=2)
if narrow_queries is None:
narrow_queries = set()
if facets is not None:
kwargs.setdefault('facets', {})
for facet_fieldname in facets:
kwargs['facets'][facet_fieldname] = {
'terms': {
'field': facet_fieldname,
},
}
if date_facets is not None:
kwargs.setdefault('facets', {})
for facet_fieldname, value in date_facets.items():
# Need to detect on gap_by & only add amount if it's more than one.
interval = value.get('gap_by').lower()
# Need to detect on amount (can't be applied on months or years).
if value.get('gap_amount', 1) != 1 and not interval in ('month', 'year'):
# Just the first character is valid for use.
interval = "%s%s" % (value['gap_amount'], interval[:1])
kwargs['facets'][facet_fieldname] = {
'date_histogram': {
'field': facet_fieldname,
'interval': interval,
},
'facet_filter': {
"range": {
facet_fieldname: {
'from': self.conn.from_python(value.get('start_date')),
'to': self.conn.from_python(value.get('end_date')),
}
}
}
}
if query_facets is not None:
kwargs.setdefault('facets', {})
for facet_fieldname, value in query_facets:
kwargs['facets'][facet_fieldname] = {
'query': {
'query_string': {
'query': value,
}
},
}
if limit_to_registered_models is None:
limit_to_registered_models = getattr(settings, 'HAYSTACK_LIMIT_TO_REGISTERED_MODELS', True)
if limit_to_registered_models:
# Using narrow queries, limit the results to only models handled
# with the current routers.
registered_models = self.build_models_list()
if len(registered_models) > 0:
narrow_queries.add('%s:(%s)' % (DJANGO_CT, ' OR '.join(registered_models)))
if narrow_queries:
kwargs['query'].setdefault('filtered', {})
kwargs['query']['filtered'].setdefault('filter', {})
kwargs['query']['filtered']['filter'] = {
'fquery': {
'query': {
'query_string': {
'query': u' AND '.join(list(narrow_queries)),
},
},
'_cache': True,
}
}
if within is not None:
from haystack.utils.geo import generate_bounding_box
((min_lat, min_lng), (max_lat, max_lng)) = generate_bounding_box(within['point_1'], within['point_2'])
kwargs['query'].setdefault('filtered', {})
kwargs['query']['filtered'].setdefault('filter', {})
kwargs['query']['filtered']['filter'] = {
"geo_bounding_box": {
within['field']: {
"top_left": {
"lat": max_lat,
"lon": max_lng
},
"bottom_right": {
"lat": min_lat,
"lon": min_lng
}
}
},
}
if dwithin is not None:
lng, lat = dwithin['point'].get_coords()
kwargs['query'].setdefault('filtered', {})
kwargs['query']['filtered'].setdefault('filter', {})
kwargs['query']['filtered']['filter'] = {
"geo_distance": {
"distance": dwithin['distance'].km,
dwithin['field']: {
"lat": lat,
"lon": lng
}
}
}
# Remove the "filtered" key if we're not filtering. Otherwise,
# Elasticsearch will blow up.
if not kwargs['query']['filtered'].get('filter'):
kwargs['query'] = kwargs['query']['filtered']['query']
# Because Elasticsearch.
query_params = {
'from': start_offset,
}
if end_offset is not None and end_offset > start_offset:
query_params['size'] = end_offset - start_offset
try:
raw_results = self.conn.search(None, kwargs, indexes=[self.index_name], doc_types=['modelresult'], **query_params)
except (requests.RequestException, pyelasticsearch.ElasticSearchError), e:
if not self.silently_fail:
raise
self.log.error("Failed to query Elasticsearch using '%s': %s", query_string, e)
raw_results = {}
def search(
self,
query_string,
sort_by=None,
start_offset=0,
end_offset=None,
fields="",
highlight=False,
facets=None,
date_facets=None,
query_facets=None,
narrow_queries=None,
spelling_query=None,
within=None,
dwithin=None,
distance_point=None,
models=None,
limit_to_registered_models=None,
result_class=None,
**kwargs
):
if len(query_string) == 0:
return {"results": [], "hits": 0}
if not self.setup_complete:
self.setup()
index = haystack.connections[self.connection_alias].get_unified_index()
content_field = index.document_field
if query_string == "*:*":
kwargs = {"query": {"filtered": {"query": {"query_string": {"query": "*:*"}}}}}
else:
kwargs = {
"query": {
"filtered": {
"query": {
"query_string": {
"default_field": content_field,
"default_operator": DEFAULT_OPERATOR,
"query": query_string,
"analyze_wildcard": True,
"auto_generate_phrase_queries": True,
}
}
}
}
}
geo_sort = False
if fields:
if isinstance(fields, (list, set)):
fields = " ".join(fields)
kwargs["fields"] = fields
if sort_by is not None:
order_list = []
for field, direction in sort_by:
if field == "distance" and distance_point:
# Do the geo-enabled sort.
lng, lat = distance_point["point"].get_coords()
sort_kwargs = {
"_geo_distance": {distance_point["field"]: [lng, lat], "order": direction, "unit": "km"}
}
else:
if field == "distance":
warnings.warn("In order to sort by distance, you must call the '.distance(...)' method.")
# Regular sorting.
sort_kwargs = {field: {"order": direction}}
order_list.append(sort_kwargs)
kwargs["sort"] = order_list
# From/size offsets don't seem to work right in Elasticsearch's DSL. :/
# if start_offset is not None:
# kwargs['from'] = start_offset
# if end_offset is not None:
# kwargs['size'] = end_offset - start_offset
if highlight is True:
kwargs["highlight"] = {"fields": {content_field: {"store": "yes"}}}
if self.include_spelling is True:
warnings.warn("Elasticsearch does not handle spelling suggestions.", Warning, stacklevel=2)
if narrow_queries is None:
narrow_queries = set()
if facets is not None:
kwargs.setdefault("facets", {})
for facet_fieldname in facets:
kwargs["facets"][facet_fieldname] = {"terms": {"field": facet_fieldname}}
if date_facets is not None:
kwargs.setdefault("facets", {})
for facet_fieldname, value in date_facets.items():
# Need to detect on gap_by & only add amount if it's more than one.
interval = value.get("gap_by").lower()
# Need to detect on amount (can't be applied on months or years).
if value.get("gap_amount", 1) != 1 and not interval in ("month", "year"):
# Just the first character is valid for use.
interval = "%s%s" % (value["gap_amount"], interval[:1])
kwargs["facets"][facet_fieldname] = {
"date_histogram": {"field": facet_fieldname, "interval": interval},
"facet_filter": {
"range": {
facet_fieldname: {
"from": self.conn.from_python(value.get("start_date")),
"to": self.conn.from_python(value.get("end_date")),
}
}
},
}
if query_facets is not None:
kwargs.setdefault("facets", {})
for facet_fieldname, value in query_facets:
kwargs["facets"][facet_fieldname] = {"query": {"query_string": {"query": value}}}
if limit_to_registered_models is None:
limit_to_registered_models = getattr(settings, "HAYSTACK_LIMIT_TO_REGISTERED_MODELS", True)
if models and len(models):
model_choices = sorted(["%s.%s" % (model._meta.app_label, model._meta.module_name) for model in models])
elif limit_to_registered_models:
# Using narrow queries, limit the results to only models handled
# with the current routers.
model_choices = self.build_models_list()
else:
model_choices = []
if len(model_choices) > 0:
if narrow_queries is None:
narrow_queries = set()
narrow_queries.add("%s:(%s)" % (DJANGO_CT, " OR ".join(model_choices)))
if narrow_queries:
kwargs["query"].setdefault("filtered", {})
kwargs["query"]["filtered"].setdefault("filter", {})
kwargs["query"]["filtered"]["filter"] = {
"fquery": {"query": {"query_string": {"query": u" AND ".join(list(narrow_queries))}}, "_cache": True}
}
if within is not None:
from haystack.utils.geo import generate_bounding_box
((min_lat, min_lng), (max_lat, max_lng)) = generate_bounding_box(within["point_1"], within["point_2"])
kwargs["query"].setdefault("filtered", {})
kwargs["query"]["filtered"].setdefault("filter", {})
kwargs["query"]["filtered"]["filter"] = {
"geo_bounding_box": {
within["field"]: {
"top_left": {"lat": max_lat, "lon": max_lng},
"bottom_right": {"lat": min_lat, "lon": min_lng},
}
}
}
if dwithin is not None:
lng, lat = dwithin["point"].get_coords()
kwargs["query"].setdefault("filtered", {})
kwargs["query"]["filtered"].setdefault("filter", {})
kwargs["query"]["filtered"]["filter"] = {
"geo_distance": {"distance": dwithin["distance"].km, dwithin["field"]: {"lat": lat, "lon": lng}}
}
# Remove the "filtered" key if we're not filtering. Otherwise,
# Elasticsearch will blow up.
if not kwargs["query"]["filtered"].get("filter"):
kwargs["query"] = kwargs["query"]["filtered"]["query"]
# Because Elasticsearch.
query_params = {"from": start_offset}
if end_offset is not None and end_offset > start_offset:
query_params["size"] = end_offset - start_offset
try:
raw_results = self.conn.search(
None, kwargs, indexes=[self.index_name], doc_types=["modelresult"], **query_params
)
except (requests.RequestException, pyelasticsearch.ElasticSearchError), e:
if not self.silently_fail:
raise
self.log.error("Failed to query Elasticsearch using '%s': %s", query_string, e)
raw_results = {}
def search(self,
query_string,
sort_by=None,
start_offset=0,
end_offset=None,
fields='',
highlight=False,
facets=None,
date_facets=None,
query_facets=None,
narrow_queries=None,
spelling_query=None,
within=None,
dwithin=None,
distance_point=None,
limit_to_registered_models=None,
result_class=None,
**kwargs):
if len(query_string) == 0:
return {
'results': [],
'hits': 0,
}
kwargs = {
'fl': '* score',
}
geo_sort = False
if fields:
if isinstance(fields, (list, set)):
fields = " ".join(fields)
kwargs['fl'] = fields
if sort_by is not None:
if sort_by in ['distance asc', 'distance desc'] and distance_point:
# Do the geo-enabled sort.
lng, lat = distance_point['point'].get_coords()
kwargs['sfield'] = distance_point['field']
kwargs['pt'] = '%s,%s' % (lat, lng)
geo_sort = True
if sort_by == 'distance asc':
kwargs['sort'] = 'geodist() asc'
else:
kwargs['sort'] = 'geodist() desc'
else:
if sort_by.startswith('distance '):
warnings.warn(
"In order to sort by distance, you must call the '.distance(...)' method."
)
# Regular sorting.
kwargs['sort'] = sort_by
if start_offset is not None:
kwargs['start'] = start_offset
if end_offset is not None:
kwargs['rows'] = end_offset - start_offset
if highlight is True:
kwargs['hl'] = 'true'
kwargs['hl.fragsize'] = '200'
if self.include_spelling is True:
kwargs['spellcheck'] = 'true'
kwargs['spellcheck.collate'] = 'true'
kwargs['spellcheck.count'] = 1
if spelling_query:
kwargs['spellcheck.q'] = spelling_query
if facets is not None:
kwargs['facet'] = 'on'
kwargs['facet.field'] = facets
if date_facets is not None:
kwargs['facet'] = 'on'
kwargs['facet.date'] = date_facets.keys()
kwargs['facet.date.other'] = 'none'
for key, value in date_facets.items():
kwargs["f.%s.facet.date.start" % key] = self.conn._from_python(
value.get('start_date'))
kwargs["f.%s.facet.date.end" % key] = self.conn._from_python(
value.get('end_date'))
gap_by_string = value.get('gap_by').upper()
gap_string = "%d%s" % (value.get('gap_amount'), gap_by_string)
if value.get('gap_amount') != 1:
gap_string += "S"
kwargs["f.%s.facet.date.gap" %
key] = '+%s/%s' % (gap_string, gap_by_string)
if query_facets is not None:
kwargs['facet'] = 'on'
kwargs['facet.query'] = [
"%s:%s" % (field, value) for field, value in query_facets
]
if limit_to_registered_models is None:
limit_to_registered_models = getattr(
settings, 'HAYSTACK_LIMIT_TO_REGISTERED_MODELS', True)
if limit_to_registered_models:
# Using narrow queries, limit the results to only models handled
# with the current routers.
if narrow_queries is None:
narrow_queries = set()
registered_models = self.build_models_list()
if len(registered_models) > 0:
narrow_queries.add('%s:(%s)' %
(DJANGO_CT, ' OR '.join(registered_models)))
if narrow_queries is not None:
kwargs['fq'] = list(narrow_queries)
if within is not None:
kwargs.setdefault('fq', [])
((min_lat, min_lng), (max_lat, max_lng)) = generate_bounding_box(
within['point_1'], within['point_2'])
# Bounding boxes are min, min TO max, max. Solr's wiki was *NOT*
# very clear on this.
bbox = '%s:[%s,%s TO %s,%s]' % (within['field'], min_lat, min_lng,
max_lat, max_lng)
kwargs['fq'].append(bbox)
if dwithin is not None:
kwargs.setdefault('fq', [])
lng, lat = dwithin['point'].get_coords()
geofilt = '{!geofilt pt=%s,%s sfield=%s d=%s}' % (
lat, lng, dwithin['field'], dwithin['distance'].km)
kwargs['fq'].append(geofilt)
# Check to see if the backend should try to include distances
# (Solr 4.X+) in the results.
if self.distance_available and distance_point:
# In early testing, you can't just hand Solr 4.X a proper bounding box
# & request distances. To enable native distance would take calculating
# a center point & a radius off the user-provided box, which kinda
# sucks. We'll avoid it for now, since Solr 4.x's release will be some
# time yet.
# kwargs['fl'] += ' _dist_:geodist()'
pass
try:
raw_results = self.conn.search(query_string, **kwargs)
except (IOError, SolrError), e:
if not self.silently_fail:
raise
self.log.error("Failed to query Solr using '%s': %s", query_string,
e)
raw_results = EmptyResults()
def build_search_kwargs(self,
query_string,
sort_by=None,
start_offset=0,
end_offset=None,
fields='',
highlight=False,
facets=None,
date_facets=None,
query_facets=None,
narrow_queries=None,
spelling_query=None,
within=None,
dwithin=None,
distance_point=None,
models=None,
limit_to_registered_models=None,
result_class=None,
stats=None,
**extra_kwargs):
kwargs = {'fl': '* score'}
if fields:
if isinstance(fields, (list, set)):
fields = " ".join(fields)
kwargs['fl'] = fields
if sort_by is not None:
if sort_by in ['distance asc', 'distance desc'] and distance_point:
# Do the geo-enabled sort.
lng, lat = distance_point['point'].get_coords()
kwargs['sfield'] = distance_point['field']
kwargs['pt'] = '%s,%s' % (lat, lng)
if sort_by == 'distance asc':
kwargs['sort'] = 'geodist() asc'
else:
kwargs['sort'] = 'geodist() desc'
else:
if sort_by.startswith('distance '):
warnings.warn(
"In order to sort by distance, you must call the '.distance(...)' method."
)
# Regular sorting.
kwargs['sort'] = sort_by
if start_offset is not None:
kwargs['start'] = start_offset
if end_offset is not None:
kwargs['rows'] = end_offset - start_offset
if highlight:
# `highlight` can either be True or a dictionary containing custom parameters
# which will be passed to the backend and may override our default settings:
kwargs['hl'] = 'true'
kwargs['hl.fragsize'] = '200'
if isinstance(highlight, dict):
kwargs.update(highlight)
if self.include_spelling is True:
kwargs['spellcheck'] = 'true'
kwargs['spellcheck.collate'] = 'true'
kwargs['spellcheck.count'] = 1
if spelling_query:
kwargs['spellcheck.q'] = spelling_query
if facets is not None:
kwargs['facet'] = 'on'
kwargs['facet.field'] = facets.keys()
for facet_field, options in facets.items():
for key, value in options.items():
kwargs['f.%s.facet.%s' %
(facet_field, key)] = self.conn._from_python(value)
if date_facets is not None:
kwargs['facet'] = 'on'
kwargs['facet.date'] = date_facets.keys()
kwargs['facet.date.other'] = 'none'
for key, value in date_facets.items():
kwargs["f.%s.facet.date.start" % key] = self.conn._from_python(
value.get('start_date'))
kwargs["f.%s.facet.date.end" % key] = self.conn._from_python(
value.get('end_date'))
gap_by_string = value.get('gap_by').upper()
gap_string = "%d%s" % (value.get('gap_amount'), gap_by_string)
if value.get('gap_amount') != 1:
gap_string += "S"
kwargs["f.%s.facet.date.gap" %
key] = '+%s/%s' % (gap_string, gap_by_string)
if query_facets is not None:
kwargs['facet'] = 'on'
kwargs['facet.query'] = [
"%s:%s" % (field, value) for field, value in query_facets
]
if limit_to_registered_models is None:
limit_to_registered_models = getattr(
settings, 'HAYSTACK_LIMIT_TO_REGISTERED_MODELS', True)
if models and len(models):
model_choices = sorted(get_model_ct(model) for model in models)
elif limit_to_registered_models:
# Using narrow queries, limit the results to only models handled
# with the current routers.
model_choices = self.build_models_list()
else:
model_choices = []
if len(model_choices) > 0:
if narrow_queries is None:
narrow_queries = set()
narrow_queries.add('%s:(%s)' %
(DJANGO_CT, ' OR '.join(model_choices)))
if narrow_queries is not None:
kwargs['fq'] = list(narrow_queries)
if stats:
kwargs['stats'] = "true"
for k in stats.keys():
kwargs['stats.field'] = k
for facet in stats[k]:
kwargs['f.%s.stats.facet' % k] = facet
if within is not None:
from haystack.utils.geo import generate_bounding_box
kwargs.setdefault('fq', [])
((min_lat, min_lng), (max_lat, max_lng)) = generate_bounding_box(
within['point_1'], within['point_2'])
# Bounding boxes are min, min TO max, max. Solr's wiki was *NOT*
# very clear on this.
bbox = '%s:[%s,%s TO %s,%s]' % (within['field'], min_lat, min_lng,
max_lat, max_lng)
kwargs['fq'].append(bbox)
if dwithin is not None:
kwargs.setdefault('fq', [])
lng, lat = dwithin['point'].get_coords()
geofilt = '{!geofilt pt=%s,%s sfield=%s d=%s}' % (
lat, lng, dwithin['field'], dwithin['distance'].km)
kwargs['fq'].append(geofilt)
# Check to see if the backend should try to include distances
# (Solr 4.X+) in the results.
if self.distance_available and distance_point:
# In early testing, you can't just hand Solr 4.X a proper bounding box
# & request distances. To enable native distance would take calculating
# a center point & a radius off the user-provided box, which kinda
# sucks. We'll avoid it for now, since Solr 4.x's release will be some
# time yet.
# kwargs['fl'] += ' _dist_:geodist()'
pass
if extra_kwargs:
kwargs.update(extra_kwargs)
return kwargs
def build_search_kwargs(self,
query_string,
sort_by=None,
start_offset=0,
end_offset=None,
fields="",
highlight=False,
facets=None,
date_facets=None,
query_facets=None,
narrow_queries=None,
spelling_query=None,
within=None,
dwithin=None,
distance_point=None,
models=None,
limit_to_registered_models=None,
result_class=None,
**extra_kwargs):
index = haystack.connections[self.connection_alias].get_unified_index()
content_field = index.document_field
if query_string == "*:*":
kwargs = {"query": {"match_all": {}}}
else:
kwargs = {
"query": {
"query_string": {
"default_field": content_field,
"default_operator": DEFAULT_OPERATOR,
"query": query_string,
"analyze_wildcard": True,
"auto_generate_phrase_queries": True,
"fuzzy_min_sim": FUZZY_MIN_SIM,
"fuzzy_max_expansions": FUZZY_MAX_EXPANSIONS,
}
}
}
# so far, no filters
filters = []
if fields:
if isinstance(fields, (list, set)):
fields = " ".join(fields)
kwargs["fields"] = fields
if sort_by is not None:
order_list = []
for field, direction in sort_by:
if field == "distance" and distance_point:
# Do the geo-enabled sort.
lng, lat = distance_point["point"].coords
sort_kwargs = {
"_geo_distance": {
distance_point["field"]: [lng, lat],
"order": direction,
"unit": "km",
}
}
else:
if field == "distance":
warnings.warn(
"In order to sort by distance, you must call the '.distance(...)' method."
)
# Regular sorting.
sort_kwargs = {field: {"order": direction}}
order_list.append(sort_kwargs)
kwargs["sort"] = order_list
# From/size offsets don't seem to work right in Elasticsearch's DSL. :/
# if start_offset is not None:
# kwargs['from'] = start_offset
# if end_offset is not None:
# kwargs['size'] = end_offset - start_offset
if highlight:
# `highlight` can either be True or a dictionary containing custom parameters
# which will be passed to the backend and may override our default settings:
kwargs["highlight"] = {"fields": {content_field: {"store": "yes"}}}
if isinstance(highlight, dict):
kwargs["highlight"].update(highlight)
if self.include_spelling:
kwargs["suggest"] = {
"suggest": {
"text": spelling_query or query_string,
"term": {
# Using content_field here will result in suggestions of stemmed words.
"field": "_all"
},
}
}
if narrow_queries is None:
narrow_queries = set()
if facets is not None:
kwargs.setdefault("facets", {})
for facet_fieldname, extra_options in facets.items():
facet_options = {
"terms": {
"field": facet_fieldname,
"size": 100
}
}
# Special cases for options applied at the facet level (not the terms level).
if extra_options.pop("global_scope", False):
# Renamed "global_scope" since "global" is a python keyword.
facet_options["global"] = True
if "facet_filter" in extra_options:
facet_options["facet_filter"] = extra_options.pop(
"facet_filter")
facet_options["terms"].update(extra_options)
kwargs["facets"][facet_fieldname] = facet_options
if date_facets is not None:
kwargs.setdefault("facets", {})
for facet_fieldname, value in date_facets.items():
# Need to detect on gap_by & only add amount if it's more than one.
interval = value.get("gap_by").lower()
# Need to detect on amount (can't be applied on months or years).
if value.get("gap_amount", 1) != 1 and interval not in (
"month",
"year",
):
# Just the first character is valid for use.
interval = "%s%s" % (value["gap_amount"], interval[:1])
kwargs["facets"][facet_fieldname] = {
"date_histogram": {
"field": facet_fieldname,
"interval": interval
},
"facet_filter": {
"range": {
facet_fieldname: {
"from":
self._from_python(value.get("start_date")),
"to": self._from_python(value.get("end_date")),
}
}
},
}
if query_facets is not None:
kwargs.setdefault("facets", {})
for facet_fieldname, value in query_facets:
kwargs["facets"][facet_fieldname] = {
"query": {
"query_string": {
"query": value
}
}
}
if limit_to_registered_models is None:
limit_to_registered_models = getattr(
settings, "HAYSTACK_LIMIT_TO_REGISTERED_MODELS", True)
if models and len(models):
model_choices = sorted(get_model_ct(model) for model in models)
elif limit_to_registered_models:
# Using narrow queries, limit the results to only models handled
# with the current routers.
model_choices = self.build_models_list()
else:
model_choices = []
if len(model_choices) > 0:
filters.append({"terms": {DJANGO_CT: model_choices}})
for q in narrow_queries:
filters.append({
"fquery": {
"query": {
"query_string": {
"query": q
}
},
"_cache": True
}
})
if within is not None:
from haystack.utils.geo import generate_bounding_box
((south, west),
(north, east)) = generate_bounding_box(within["point_1"],
within["point_2"])
within_filter = {
"geo_bounding_box": {
within["field"]: {
"top_left": {
"lat": north,
"lon": west
},
"bottom_right": {
"lat": south,
"lon": east
},
}
}
}
filters.append(within_filter)
if dwithin is not None:
lng, lat = dwithin["point"].coords
# NB: the 1.0.0 release of elasticsearch introduce an
# incompatible change on the distance filter formating
if elasticsearch.VERSION >= (1, 0, 0):
distance = "%(dist).6f%(unit)s" % {
"dist": dwithin["distance"].km,
"unit": "km",
}
else:
distance = dwithin["distance"].km
dwithin_filter = {
"geo_distance": {
"distance": distance,
dwithin["field"]: {
"lat": lat,
"lon": lng
},
}
}
filters.append(dwithin_filter)
# if we want to filter, change the query type to filteres
if filters:
kwargs["query"] = {"filtered": {"query": kwargs.pop("query")}}
if len(filters) == 1:
kwargs["query"]["filtered"]["filter"] = filters[0]
else:
kwargs["query"]["filtered"]["filter"] = {
"bool": {
"must": filters
}
}
if extra_kwargs:
kwargs.update(extra_kwargs)
return kwargs
def build_search_kwargs(self, query_string, sort_by=None, start_offset=0, end_offset=None,
fields='', highlight=False, facets=None,
date_facets=None, query_facets=None,
narrow_queries=None, spelling_query=None,
within=None, dwithin=None, distance_point=None, polygon=None,
models=None, limit_to_registered_models=None,
result_class=None):
index = haystack.connections[self.connection_alias].get_unified_index()
content_field = index.document_field
if query_string == '*:*':
kwargs = {
'query': {
'filtered': {
'query': {
"match_all": {}
},
},
},
}
else:
kwargs = {
'query': {
'filtered': {
'query': {
'query_string': {
'default_field': content_field,
'default_operator': DEFAULT_OPERATOR,
'query': query_string,
'analyze_wildcard': True,
'auto_generate_phrase_queries': True,
},
},
},
},
}
if fields:
if isinstance(fields, (list, set)):
fields = " ".join(fields)
kwargs['fields'] = fields
if sort_by is not None:
order_list = []
for field, direction in sort_by:
if field == 'distance' and distance_point:
# Do the geo-enabled sort.
lng, lat = distance_point['point'].get_coords()
sort_kwargs = {
"_geo_distance": {
distance_point['field']: [lng, lat],
"order": direction,
"unit": "km"
}
}
else:
if field == 'distance':
warnings.warn("In order to sort by distance, you must call the '.distance(...)' method.")
# Regular sorting.
sort_kwargs = {field: {'order': direction}}
order_list.append(sort_kwargs)
kwargs['sort'] = order_list
# From/size offsets don't seem to work right in Elasticsearch's DSL. :/
# if start_offset is not None:
# kwargs['from'] = start_offset
# if end_offset is not None:
# kwargs['size'] = end_offset - start_offset
if highlight is True:
kwargs['highlight'] = {
'fields': {
content_field: {'store': 'yes'},
}
}
if self.include_spelling:
kwargs['suggest'] = {
'suggest': {
'text': spelling_query or query_string,
'term': {
# Using content_field here will result in suggestions of stemmed words.
'field': '_all',
},
},
}
if narrow_queries is None:
narrow_queries = set()
if facets is not None:
kwargs.setdefault('facets', {})
for facet_fieldname, extra_options in facets.items():
facet_options = {
'terms': {
'field': facet_fieldname,
'size': 100,
},
}
# Special cases for options applied at the facet level (not the terms level).
if extra_options.pop('global_scope', False):
# Renamed "global_scope" since "global" is a python keyword.
facet_options['global'] = True
if 'facet_filter' in extra_options:
facet_options['facet_filter'] = extra_options.pop('facet_filter')
facet_options['terms'].update(extra_options)
kwargs['facets'][facet_fieldname] = facet_options
if date_facets is not None:
kwargs.setdefault('facets', {})
for facet_fieldname, value in date_facets.items():
# Need to detect on gap_by & only add amount if it's more than one.
interval = value.get('gap_by').lower()
# Need to detect on amount (can't be applied on months or years).
if value.get('gap_amount', 1) != 1 and not interval in ('month', 'year'):
# Just the first character is valid for use.
interval = "%s%s" % (value['gap_amount'], interval[:1])
kwargs['facets'][facet_fieldname] = {
'date_histogram': {
'field': facet_fieldname,
'interval': interval,
},
'facet_filter': {
"range": {
facet_fieldname: {
'from': self._from_python(value.get('start_date')),
'to': self._from_python(value.get('end_date')),
}
}
}
}
if query_facets is not None:
kwargs.setdefault('facets', {})
for facet_fieldname, value in query_facets:
kwargs['facets'][facet_fieldname] = {
'query': {
'query_string': {
'query': value,
}
},
}
if limit_to_registered_models is None:
limit_to_registered_models = getattr(settings, 'HAYSTACK_LIMIT_TO_REGISTERED_MODELS', True)
if models and len(models):
model_choices = sorted(['%s.%s' % (model._meta.app_label, model._meta.module_name) for model in models])
elif limit_to_registered_models:
# Using narrow queries, limit the results to only models handled
# with the current routers.
model_choices = self.build_models_list()
else:
model_choices = []
if len(model_choices) > 0:
if narrow_queries is None:
narrow_queries = set()
narrow_queries.add('%s:(%s)' % (DJANGO_CT, ' OR '.join(model_choices)))
if narrow_queries:
kwargs['query'].setdefault('filtered', {})
kwargs['query']['filtered'].setdefault('filter', {})
kwargs['query']['filtered']['filter'] = {
'fquery': {
'query': {
'query_string': {
'query': u' AND '.join(list(narrow_queries)),
},
},
'_cache': True,
}
}
if within is not None:
from haystack.utils.geo import generate_bounding_box
((min_lat, min_lng), (max_lat, max_lng)) = generate_bounding_box(within['point_1'], within['point_2'])
within_filter = {
"geo_bounding_box": {
within['field']: {
"top_left": {
"lat": max_lat,
"lon": min_lng
},
"bottom_right": {
"lat": min_lat,
"lon": max_lng
}
}
},
}
kwargs['query'].setdefault('filtered', {})
kwargs['query']['filtered'].setdefault('filter', {})
if kwargs['query']['filtered']['filter']:
compound_filter = {
"and": [
kwargs['query']['filtered']['filter'],
within_filter,
]
}
kwargs['query']['filtered']['filter'] = compound_filter
else:
kwargs['query']['filtered']['filter'] = within_filter
if dwithin is not None:
lng, lat = dwithin['point'].get_coords()
dwithin_filter = {
"geo_distance": {
"distance": dwithin['distance'].km,
dwithin['field']: {
"lat": lat,
"lon": lng
}
}
}
kwargs['query'].setdefault('filtered', {})
kwargs['query']['filtered'].setdefault('filter', {})
if kwargs['query']['filtered']['filter']:
compound_filter = {
"and": [
kwargs['query']['filtered']['filter'],
dwithin_filter
]
}
kwargs['query']['filtered']['filter'] = compound_filter
else:
kwargs['query']['filtered']['filter'] = dwithin_filter
if polygon is not None:
points = map(lambda x: {"lat": x[1], "lon": x[0]},
polygon['polygon'].coords[0])
polygon_filter = {
"geo_polygon": {
polygon['field']: {
"points": points
}
},
}
kwargs['query'].setdefault('filtered', {})
kwargs['query']['filtered'].setdefault('filter', {})
if kwargs['query']['filtered']['filter']:
compound_filter = {
"and": [
kwargs['query']['filtered']['filter'],
polygon_filter,
]
}
kwargs['query']['filtered']['filter'] = compound_filter
else:
kwargs['query']['filtered']['filter'] = polygon_filter
# Remove the "filtered" key if we're not filtering. Otherwise,
# Elasticsearch will blow up.
if not kwargs['query']['filtered'].get('filter'):
kwargs['query'] = kwargs['query']['filtered']['query']
return kwargs
def search(self, query_string, sort_by=None, start_offset=0, end_offset=None,
fields='', highlight=False, facets=None, date_facets=None, query_facets=None,
narrow_queries=None, spelling_query=None, within=None,
dwithin=None, distance_point=None, models=None,
limit_to_registered_models=None, result_class=None, **kwargs):
if len(query_string) == 0:
return {
'results': [],
'hits': 0,
}
if not self.setup_complete:
self.setup()
index = haystack.connections[self.connection_alias].get_unified_index()
content_field = index.document_field
if query_string == '*:*':
kwargs = {
'query': {
'filtered': {
'query': {
'query_string': {
'query': '*:*',
},
},
},
},
}
else:
kwargs = {
'query': {
'filtered': {
'query': {
'query_string': {
'default_field': content_field,
'default_operator': DEFAULT_OPERATOR,
'query': query_string,
'analyze_wildcard': True,
'auto_generate_phrase_queries': True,
},
},
},
},
}
geo_sort = False
if fields:
if isinstance(fields, (list, set)):
fields = " ".join(fields)
kwargs['fields'] = fields
if sort_by is not None:
order_list = []
for field, direction in sort_by:
if field == 'distance' and distance_point:
# Do the geo-enabled sort.
lng, lat = distance_point['point'].get_coords()
sort_kwargs = {
"_geo_distance": {
distance_point['field']: [lng, lat],
"order" : direction,
"unit" : "km"
}
}
else:
if field == 'distance':
warnings.warn("In order to sort by distance, you must call the '.distance(...)' method.")
# Regular sorting.
sort_kwargs = {field: {'order': direction}}
order_list.append(sort_kwargs)
kwargs['sort'] = order_list
# From/size offsets don't seem to work right in Elasticsearch's DSL. :/
# if start_offset is not None:
# kwargs['from'] = start_offset
# if end_offset is not None:
# kwargs['size'] = end_offset - start_offset
if highlight is True:
kwargs['highlight'] = {
'fields': {
content_field: {'store': 'yes'},
}
}
if self.include_spelling is True:
warnings.warn("Elasticsearch does not handle spelling suggestions.", Warning, stacklevel=2)
if narrow_queries is None:
narrow_queries = set()
if facets is not None:
kwargs.setdefault('facets', {})
for facet_fieldname in facets:
kwargs['facets'][facet_fieldname] = {
'terms': {
'field': facet_fieldname,
},
}
if date_facets is not None:
kwargs.setdefault('facets', {})
for facet_fieldname, value in date_facets.items():
# Need to detect on gap_by & only add amount if it's more than one.
interval = value.get('gap_by').lower()
# Need to detect on amount (can't be applied on months or years).
if value.get('gap_amount', 1) != 1 and not interval in ('month', 'year'):
# Just the first character is valid for use.
interval = "%s%s" % (value['gap_amount'], interval[:1])
kwargs['facets'][facet_fieldname] = {
'date_histogram': {
'field': facet_fieldname,
'interval': interval,
},
'facet_filter': {
"range": {
facet_fieldname: {
'from': self.conn.from_python(value.get('start_date')),
'to': self.conn.from_python(value.get('end_date')),
}
}
}
}
if query_facets is not None:
kwargs.setdefault('facets', {})
for facet_fieldname, value in query_facets:
kwargs['facets'][facet_fieldname] = {
'query': {
'query_string': {
'query': value,
}
},
}
if limit_to_registered_models is None:
limit_to_registered_models = getattr(settings, 'HAYSTACK_LIMIT_TO_REGISTERED_MODELS', True)
if models and len(models):
model_choices = sorted(['%s.%s' % (model._meta.app_label, model._meta.module_name) for model in models])
elif limit_to_registered_models:
# Using narrow queries, limit the results to only models handled
# with the current routers.
model_choices = self.build_models_list()
else:
model_choices = []
if len(model_choices) > 0:
if narrow_queries is None:
narrow_queries = set()
narrow_queries.add('%s:(%s)' % (DJANGO_CT, ' OR '.join(model_choices)))
if narrow_queries:
kwargs['query'].setdefault('filtered', {})
kwargs['query']['filtered'].setdefault('filter', {})
kwargs['query']['filtered']['filter'] = {
'fquery': {
'query': {
'query_string': {
'query': u' AND '.join(list(narrow_queries)),
},
},
'_cache': True,
}
}
if within is not None:
from haystack.utils.geo import generate_bounding_box
((min_lat, min_lng), (max_lat, max_lng)) = generate_bounding_box(within['point_1'], within['point_2'])
kwargs['query'].setdefault('filtered', {})
kwargs['query']['filtered'].setdefault('filter', {})
kwargs['query']['filtered']['filter'] = {
"geo_bounding_box": {
within['field']: {
"top_left": {
"lat": max_lat,
"lon": max_lng
},
"bottom_right": {
"lat": min_lat,
"lon": min_lng
}
}
},
}
if dwithin is not None:
lng, lat = dwithin['point'].get_coords()
kwargs['query'].setdefault('filtered', {})
kwargs['query']['filtered'].setdefault('filter', {})
kwargs['query']['filtered']['filter'] = {
"geo_distance": {
"distance": dwithin['distance'].km,
dwithin['field']: {
"lat": lat,
"lon": lng
}
}
}
# Remove the "filtered" key if we're not filtering. Otherwise,
# Elasticsearch will blow up.
if not kwargs['query']['filtered'].get('filter'):
kwargs['query'] = kwargs['query']['filtered']['query']
# Because Elasticsearch.
query_params = {
'from': start_offset,
}
if end_offset is not None and end_offset > start_offset:
query_params['size'] = end_offset - start_offset
try:
raw_results = self.conn.search(None, kwargs, indexes=[self.index_name], doc_types=['modelresult'], **query_params)
except (requests.RequestException, pyelasticsearch.ElasticSearchError), e:
if not self.silently_fail:
raise
self.log.error("Failed to query Elasticsearch using '%s': %s", query_string, e)
raw_results = {}
