Extended haystack backend for Elasticsearch
Project description
Django Haystack backend for Elasticsearch 5.
Quickstart
Install Django Haystack ES:
pip install django-haystack-es
Add haystack_es.backends.ElasticsearchSearchEngine to your HAYSTACK_CONNECTIONS engine in settings.py
Example
HAYSTACK_CONNECTIONS = {
'default': {
'ENGINE': 'haystack_es.backends.Elasticsearch5SearchEngine',
# ...
}
}
Define your indexes using haystack_es.indexes instead of haystack.indexes.
Example
# myapp/search_indexes.py
from haystack_es import indexes
from myapp.models import MyModel
class MyModelIndex(indexes.SearchIndex, indexes.Indexable):
text = indexes.CharField(document=True, use_template=True)
# ...
If you have celery-haystack installed you can use haystack_es.indexes.CelerySearchIndex for defining your SearchIndex utilizing celery-haystack
If you want to utilize additional SearchQuerySet methods use haystack_es.query.SearchQuerySet instead of haystack.query.SearchQuerySet.
Example
from haystack_es.query import SearchQuerySet
sqs = SearchQuerySet().filter(content='some query')
sqs.boost_fields({'field_name': 2, 'some_field': 1.5, 'another_field': 1})
sqs.facet('some_field')
# ...
Differences compared to the default django-haystack Elasticsearch backend
Intended for Elasticsearch >= 5
Allows query-time fields boosting.
Allows query-time negative boost
Provides additional SearchFields; DictField, NestedField and GeometryField
Tries to use Elasticsearch filter context instead of query string for filtering results.
Uses multi-fields for creating shadow fields which are useful for performing operations like faceting and exact matches which need non-analyzed values.
Query-time fields boosting
from haystack_es.query import SearchQuerySet SearchQuerySet().boost_fields(boost_fields)
Example SearchQuerySet().boost_fields({'field_name': 2, 'another_field': 1})
Negative boosting
from haystack_es.query import SearchQuerySet SearchQuerySet().boost_negative(query, negative_boost)
example SearchQuerySet().boost_negative({'match': {'category.raw': 'awful type'}}, negative_boost)
Running Tests
Does the code actually work?
source <YOURVIRTUALENV>/bin/activate (myenv) $ pip install tox (myenv) $ tox
Credits
Inspired by
haystack-elasticsearch5: https://github.com/Alkalit/haystack-elasticsearch5
Tools used in rendering this package:
History
0.1.0 (2017-07-27)
First release on PyPI.
0.2.8 (2019-07-18)
Simplify Django Version in Tox.
Project details
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