Configuration¶
Seeker Settings¶
SEEKER_INDEX¶
Default: seeker
The name of the ES index that should be used by default. This can be overridden per mapping.
SEEKER_DEFAULT_OPERATOR¶
Default: AND
The default operator to use when performing keyword queries. This can be overridden per view.
SEEKER_DEFAULT_FACET_TEMPLATE¶
Default: seeker/facets/terms.html
The default template to use when rendering facets. Can be overridden per facet.
SEEKER_MAPPING_MODULE¶
Default: mappings
The name of the python module to try to automatically import from each app. Setting to False or None will cause
seeker to skip doing any automatic imports.
SEEKER_DEFAULT_ANALYZER¶
Default: snowball
The analyzer to use by default when creating elasticsearch_dsl.String fields. Also used by default in SeekerView
to determine how query strings should be analyzed (it’s important that queries are analyzed the same way as your data).
Model Indexing Middleware¶
For sites that want model instances to be automatically indexed when they are created, updated, or deleted, Seeker
includes a ModelIndexingMiddleware that connects to Django’s post_save and post_delete signals. To use it,
simply add seeker.middleware.ModelIndexingMiddleware to your MIDDLEWARE_CLASSES setting above any middleware
that might alter model instances you want indexed.
Models are not automatically indexed when outside of a request cycle (with ModelIndexingMiddleware installed), to
prevent unwanted or premature indexing during load scripts, bulk updates, etc. Instances may be indexed manually using
seeker.index. If automatic updating is desired outside of the request cycle, it is possible to simply instantiate
ModelIndexingMiddleware and keep a reference to it. The class connects to post_save and post_delete when
created, so you may do something like:
from seeker.middleware import ModelIndexingMiddleware
middleware = ModelIndexingMiddleware()
# Update your model instances as necessary, they will be automatically indexed.
del middleware