def test_labels_ranges_mismatch(self):
with pytest.raises(ValueError):
search.RangeFacet(field='some_field',
ranges=self.ranges,
labels={
'first': 'First range',
'second': 'Second range',
})
with pytest.raises(ValueError):
search.RangeFacet(field='some_field',
ranges=self.ranges,
labels={
'first': 'First range',
'second': 'Second range',
'unknown': 'Third range',
})
class FakeSearchWithRange(FakeSearch):
facets = {
'range':
search.RangeFacet(field='a_range_field',
ranges=[('none', (None, 1)), ('little', (1, 5)),
('quite', (5, 10)), ('heavy', (10, None))],
labels=RANGE_LABELS)
}
def setUp(self):
self.ranges = [('first', (None, 1)), ('second', (1, 5)),
('third', (5, None))]
self.facet = search.RangeFacet(field='some_field',
ranges=self.ranges,
labels={
'first': 'First range',
'second': 'Second range',
'third': 'Third range',
})
class FakeSearch(search.ModelSearchAdapter):
model = Fake
fields = [
'title^2',
'description',
]
facets = {
'tag': search.TermFacet('tags'),
'other': search.TermFacet('other'),
'range': search.RangeFacet('a_num_field'),
'daterange': search.DateRangeFacet('a_daterange_field'),
'bool': search.BoolFacet('boolean'),
'extra': search.ExtrasFacet('extras'),
}
sorts = {
'title': search.Sort('title.raw'),
'description': search.Sort('description.raw'),
}
class OrganizationSearch(search.ModelSearchAdapter):
model = Organization
fuzzy = True
fields = (
'name^6',
'acronym^6',
'description',
)
sorts = {
'name': search.Sort('name.raw'),
'reuses': search.Sort('metrics.reuses'),
'datasets': search.Sort('metrics.datasets'),
'followers': search.Sort('metrics.followers'),
'views': search.Sort('metrics.views'),
'created': search.Sort('created'),
}
facets = {
'reuses': search.RangeFacet('metrics.reuses'),
'badge': search.TermFacet('badges',
labelizer=organization_badge_labelizer),
'permitted_reuses': search.RangeFacet('metrics.permitted_reuses'),
'datasets': search.RangeFacet('metrics.datasets'),
'followers': search.RangeFacet('metrics.followers'),
}
mapping = {
'properties': {
'name': {
'type': 'string',
'analyzer': search.i18n_analyzer,
'fields': {
'raw': {
'type': 'string',
'index': 'not_analyzed'
}
}
},
'acronym': {
'type': 'string',
'index': 'not_analyzed',
},
'description': {
'type': 'string',
'analyzer': search.i18n_analyzer
},
'badges': {
'type': 'string',
'index_name': 'badges',
'index': 'not_analyzed'
},
'url': {
'type': 'string'
},
'created': {
'type': 'date',
'format': 'date_hour_minute_second'
},
'metrics': search.metrics_mapping(Organization),
'org_suggest': {
'type': 'completion',
'index_analyzer': 'simple',
'search_analyzer': 'simple',
'payloads': True,
},
}
}
boosters = [
search.GaussDecay('metrics.followers', max_followers, decay=0.8),
search.GaussDecay('metrics.reuses', max_reuses, decay=0.9),
search.GaussDecay('metrics.datasets', max_datasets, decay=0.9),
]
@classmethod
def is_indexable(cls, org):
return org.deleted is None
@classmethod
def serialize(cls, organization):
completions = cls.completer_tokenize(organization.name)
completions.append(organization.id)
if organization.acronym:
completions.append(organization.acronym)
return {
'name': organization.name,
'acronym': organization.acronym,
'description': organization.description,
'url': organization.url,
'metrics': organization.metrics,
'badges': [badge.kind for badge in organization.badges],
'created': organization.created_at.strftime('%Y-%m-%dT%H:%M:%S'),
'org_suggest': {
'input': completions,
'output': str(organization.id),
'payload': {
'name': organization.name,
'acronym': organization.acronym,
'image_url': organization.logo(40),
'slug': organization.slug,
},
}
}
def setUp(self):
self.facet = search.RangeFacet('some_field')
