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Extended haystack backend for Elasticsearch

Project description

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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

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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