kopia lustrzana https://github.com/wagtail/wagtail
63 wiersze
2.1 KiB
ReStructuredText
63 wiersze
2.1 KiB
ReStructuredText
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.. _wagtailsearch_backends:
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========
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Backends
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========
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Wagtail can degrade to a database-backed text search, but we strongly recommend `Elasticsearch`_.
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.. _Elasticsearch: http://www.elasticsearch.org/
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.. _wagtailsearch_backends_database:
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Database Backend
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================
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The default DB search backend uses Django's ``__icontains`` filter.
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Elasticsearch Backend
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=====================
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Prerequisites are the Elasticsearch service itself and, via pip, the `elasticsearch-py`_ package:
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.. code-block:: guess
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pip install elasticsearch
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The backend is configured in settings:
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.. code-block:: python
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WAGTAILSEARCH_BACKENDS = {
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'default': {
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'BACKEND': 'wagtail.wagtailsearch.backends.elasticsearch.ElasticSearch',
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'URLS': ['http://localhost:9200'],
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'INDEX': 'wagtail',
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'TIMEOUT': 5,
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}
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}
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Other than ``BACKEND`` the keys are optional and default to the values shown. In addition, any other keys are passed directly to the Elasticsearch constructor as case-sensitive keyword arguments (e.g. ``'max_retries': 1``).
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If you prefer not to run an Elasticsearch server in development or production, there are many hosted services available, including `Searchly`_, who offer a free account suitable for testing and development. To use Searchly:
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- Sign up for an account at `dashboard.searchly.com/users/sign\_up`_
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- Use your Searchly dashboard to create a new index, e.g. 'wagtaildemo'
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- Note the connection URL from your Searchly dashboard
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- Configure ``URLS`` and ``INDEX`` in the Elasticsearch entry in ``WAGTAILSEARCH_BACKENDS``
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- Run ``./manage.py update_index``
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.. _elasticsearch-py: http://elasticsearch-py.readthedocs.org
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.. _Searchly: http://www.searchly.com/
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.. _dashboard.searchly.com/users/sign\_up: https://dashboard.searchly.com/users/sign_up
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Rolling Your Own
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================
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Wagtail search backends implement the interface defined in ``wagtail/wagtail/wagtailsearch/backends/base.py``. At a minimum, the backend's ``search()`` method must return a collection of objects or ``model.objects.none()``. For a fully-featured search backend, examine the Elasticsearch backend code in ``elasticsearch.py``.
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