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"description": "=============================\nDjango Haystack ES\n=============================\n\n.. image:: https://badge.fury.io/py/django-haystack-es.svg\n :target: https://badge.fury.io/py/django-haystack-es\n\n.. image:: https://travis-ci.org/tehamalab/django-haystack-es.svg?branch=master\n :target: https://travis-ci.org/tehamalab/django-haystack-es\n\n.. image:: https://codecov.io/gh/tehamalab/django-haystack-es/branch/master/graph/badge.svg\n :target: https://codecov.io/gh/tehamalab/django-haystack-es\n\nDjango Haystack backend for Elasticsearch 5.\n\n\nQuickstart\n----------\n\nInstall Django Haystack ES::\n\n pip install django-haystack-es\n\nAdd ``haystack_es.backends.ElasticsearchSearchEngine`` to your ``HAYSTACK_CONNECTIONS`` engine in ``settings.py``\n\nExample\n\n.. code-block:: python\n\n HAYSTACK_CONNECTIONS = {\n 'default': {\n 'ENGINE': 'haystack_es.backends.Elasticsearch5SearchEngine',\n # ...\n }\n }\n\nDefine your indexes using ``haystack_es.indexes`` instead of ``haystack.indexes``.\n\nExample\n\n.. code-block:: python\n\n # myapp/search_indexes.py\n\n from haystack_es import indexes\n from myapp.models import MyModel\n\n\n class MyModelIndex(indexes.SearchIndex, indexes.Indexable):\n text = indexes.CharField(document=True, use_template=True)\n # ...\n\nIf you have `celery-haystack `_ installed you can use\n``haystack_es.indexes.CelerySearchIndex`` for defining your SearchIndex utilizing celery-haystack\n\nIf you want to utilize additional SearchQuerySet methods use ``haystack_es.query.SearchQuerySet``\ninstead of ``haystack.query.SearchQuerySet``.\n\nExample\n\n.. code-block:: python\n\n from haystack_es.query import SearchQuerySet\n\n sqs = SearchQuerySet().filter(content='some query')\n sqs.boost_fields({'field_name': 2, 'some_field': 1.5, 'another_field': 1})\n sqs.facet('some_field')\n # ...\n\n\nDifferences compared to the default django-haystack Elasticsearch backend\n---------------------------------------------------------------------------\n\n* Intended for Elasticsearch >= 5\n* Allows query-time fields boosting.\n* Allows query-time\n `negative boost `_ \n* Provides additional SearchFields; ``DictField``, ``NestedField`` and ``GeometryField``\n* Tries to use Elasticsearch\n `filter context `_\n instead of query string for filtering results.\n* Uses `multi-fields `_\n for creating shadow fields which are useful for performing operations like\n faceting and exact matches which need non-analyzed values.\n\nQuery-time fields boosting\n----------------------------\n\n::\n\n from haystack_es.query import SearchQuerySet\n SearchQuerySet().boost_fields(boost_fields)\n\n\nExample ``SearchQuerySet().boost_fields({'field_name': 2, 'another_field': 1})``\n\n\nNegative boosting\n------------------\n\n::\n\n from haystack_es.query import SearchQuerySet\n SearchQuerySet().boost_negative(query, negative_boost)\n\n\nexample\n``SearchQuerySet().boost_negative({'match': {'category.raw': 'awful type'}}, negative_boost)``\n\n\nRunning Tests\n-------------\n\nDoes the code actually work?\n\n::\n\n source /bin/activate\n (myenv) $ pip install tox\n (myenv) $ tox\n\nCredits\n-------\n\nInspired by\n\n* `haystack-elasticsearch5`: https://github.com/Alkalit/haystack-elasticsearch5\n\nTools used in rendering this package:\n\n* Cookiecutter_\n* `cookiecutter-djangopackage`_\n\n.. _Cookiecutter: https://github.com/audreyr/cookiecutter\n.. _`cookiecutter-djangopackage`: https://github.com/pydanny/cookiecutter-djangopackage\n\n\n\n\nHistory\n-------\n\n0.1.0 (2017-07-27)\n++++++++++++++++++\n\n* First release on PyPI.\n\n0.2.8 (2019-07-18)\n++++++++++++++++++\n\n* Simplify Django Version in Tox.",
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