def setUp(self):
# Create ES mapping
self.es_mapping = ElasticSearchMapping(models.SearchTestChild)
# Create ES document
self.obj = models.SearchTestChild(title="Hello", subtitle="World", page_id=1)
self.obj.save()
self.obj.tags.add("a tag")
def setUp(self):
# Create ES mapping
self.es_mapping = ElasticSearchMapping(models.SearchTest)
# Create ES document
self.obj = models.SearchTest(title="Hello")
self.obj.save()
self.obj.tags.add("a tag")
def setUp(self):
# Import using a try-catch block to prevent crashes if the elasticsearch-py
# module is not installed
try:
from wagtail.wagtailsearch.backends.elasticsearch import ElasticSearchMapping
from elasticsearch.serializer import JSONSerializer
except ImportError:
raise unittest.SkipTest("elasticsearch-py not installed")
self.JSONSerializer = JSONSerializer
# Create ES mapping
self.es_mapping = ElasticSearchMapping(models.SearchTestChild)
# Create ES document
self.obj = models.SearchTestChild(title="Hello", subtitle="World")
self.obj.save()
def test_add_model(self):
self.rebuilder.start()
# Add model
self.rebuilder.add_model(models.SearchTest)
# Check the mapping went into Elasticsearch correctly
mapping = ElasticSearchMapping(models.SearchTest)
response = self.es.indices.get_mapping(self.backend.es_index, mapping.get_document_type())
# Make some minor tweaks to the mapping so it matches what is in ES
# These are generally minor issues with the way Wagtail is
# generating the mapping that are being cleaned up by Elasticsearch
# TODO: Would be nice to fix these
expected_mapping = mapping.get_mapping()
expected_mapping['searchtests_searchtest']['properties']['pk']['store'] = True
expected_mapping['searchtests_searchtest']['properties']['live_filter'].pop('index')
expected_mapping['searchtests_searchtest']['properties']['live_filter'].pop('include_in_all')
expected_mapping['searchtests_searchtest']['properties']['published_date_filter']['format'] = \
'dateOptionalTime'
expected_mapping['searchtests_searchtest']['properties']['published_date_filter'].pop('index')
self.assertDictEqual(expected_mapping, response[self.backend.es_index]['mappings'])
def related_articles(self):
if not self.pk:
# In preview mode
return []
max_results = getattr(settings, "MAX_RELATED_RESULTS", 4)
es_backend = get_search_backend()
mapping = ElasticSearchMapping(self.__class__)
search_fields = []
for ii in self.search_fields:
if getattr(ii, "boost", None):
search_fields.append("{0}^{1}".format(ii.field_name, ii.boost))
else:
search_fields.append(ii.field_name)
query = {
"query": {
"filtered": {
"filter": {
"term": {
"live_filter": True
}
},
"query": {
"more_like_this": {
"docs": [{
"_id": mapping.get_document_id(self),
"_type": mapping.get_document_type()
}],
"min_doc_freq":
1,
"min_term_freq":
2,
"max_query_terms":
500,
"min_word_length":
4,
"fields":
search_fields
}
}
}
}
}
try:
mlt = es_backend.es.search(index=es_backend.index_name,
doc_type=mapping.get_document_type(),
body=query)
except ConnectionError:
return []
# Get pks from results
pks = [hit['_source']['pk']
for hit in mlt['hits']['hits']][:max_results]
# Initialise results dictionary
results = dict((str(pk), None) for pk in pks)
# Find objects in database and add them to dict
queryset = self._default_manager.filter(pk__in=pks)
for obj in queryset:
results[str(obj.pk)] = obj
# Return results in order given by ElasticSearch
return [results[str(pk)] for pk in pks if results[str(pk)]]
def related_articles(self):
if not self.pk:
# In preview mode
return []
max_results = getattr(settings, "MAX_RELATED_RESULTS", 4)
es_backend = get_search_backend()
mapping = ElasticSearchMapping(self.__class__)
minimal_locations = ""
if (self.get_minimal_locations()):
minimal_locations = self.get_minimal_locations()
state_locations = ""
if (self.get_state_from_locations()):
state_locations = self.get_state_from_locations()
authors_of_article = ""
if self.authors:
for author in self.authors.all():
authors_of_article += author.name
query = {
"track_scores": "true",
"query": {
"bool": {
"must": [
{"match": {"language": self.language}},
{"term": {"live_filter": "true"}}
],
"must_not": [
{"term": {"title_filter": self.title}}
],
"should": [
{
"multi_match": {
"fields": "get_authors_or_photographers_filter",
"query": ["" + authors_of_article + ""]
}
},
{
"multi_match": {
"fields": "get_authors",
"query": ["" + authors_of_article + ""]
}
},
{
"multi_match": {
"fields": "get_minimal_locations_filter",
"query":minimal_locations
}
},
{
"multi_match":{
"fields":"get_state_from_locations_filter",
"query":state_locations
}
},
{
"match":{
"title":self.title
}
}
],
"minimum_should_match": 1
}
},
"sort": [
{"_score": {"order": "desc"}},
{"get_authors":{"order": "desc"}},
{"first_published_at_filter": "desc"}
]
}
try:
mlt = es_backend.es.search(
index=es_backend.index_name,
doc_type=mapping.get_document_type(),
body=query
)
except ConnectionError:
return []
# Get pks from results
pks = [hit['_source']['pk'] for hit in mlt['hits']['hits']][:max_results]
# Initialise results dictionary
results = dict((str(pk), None) for pk in pks)
# Find objects in database and add them to dict
queryset = self._default_manager.filter(pk__in=pks)
for obj in queryset:
results[str(obj.pk)] = obj
# Return results in order given by ElasticSearch
return [results[str(pk)] for pk in pks if results[str(pk)]]
