django-haystack/queued_search

A queuing setup for integration with Haystack.

Haystack

author

Daniel Lindsley

date

2013/07/28

Haystack provides modular search for Django. It features a unified, familiar API that allows you to plug in different search backends (such as Solr, Elasticsearch, Whoosh, Xapian, etc.) without having to modify your code.

Haystack is BSD licensed, plays nicely with third-party app without needing to modify the source and supports advanced features like faceting, More Like This, highlighting, spatial search and spelling suggestions.

You can find more information at http://haystacksearch.org/.

Getting Help

There is a mailing list (http://groups.google.com/group/django-haystack/) available for general discussion and an IRC channel (#haystack on irc.freenode.net).

Documentation

• Development version: http://docs.haystacksearch.org/
• v2.8.X: https://django-haystack.readthedocs.io/en/v2.8.1/
• v2.7.X: https://django-haystack.readthedocs.io/en/v2.7.0/
• v2.6.X: https://django-haystack.readthedocs.io/en/v2.6.0/

See the changelog

Requirements

Haystack has a relatively easily-met set of requirements.

• A supported version of Python: https://devguide.python.org/versions/#supported-versions
• A supported version of Django: https://www.djangoproject.com/download/#supported-versions

Additionally, each backend has its own requirements. You should refer to https://django-haystack.readthedocs.io/en/latest/installing_search_engines.html for more details.

Experimental support for Django v5.0

The current release on PyPI does not yet support Django v5.0.

To run on Django v5.0, please install by using: pip install git+https://github.com/django-haystack/django-haystack.git

queued_search's Issues

using elastic search in QUEUE BACKEND : Unable to import QUEUE BACKEND 'elasticsearch'

raise InvalidBackend("Unable to import QUEUE BACKEND '%s'" % BACKEND)
queues.InvalidBackend: Unable to import QUEUE BACKEND 'elasticsearch'

ERROR:queued_search:Couldn't find a SearchIndex for <class 'django.contrib.sessions.models.Session'>.

Hi! I followed the installation steps, and I get the following error, when trying to run process_search_queue. Do you know why might this happen?

ERROR:queued_search:Couldn't find a SearchIndex for < class 'django.contrib.sessions.models.Session' >.
ERROR:queued_search:Skipping.

Prevent indexing of unwanted items

Just a suggestion.

queued_search puts all models in the queue unconditionally. Some of my models implement get_queryset() on the SearchIndex to control which items get indexed. Is there a way that queued_search can either check to see if the item to be queued is in the get_queryset(), or perhaps call some new method on search index to see if the item should be indexed?

Or perhaps I should just subclass QueuedSearchIndex and override the enqueue method and do this myself?

Thanks.

typo in README.rst

1. Alter all of your SearchIndex subclasses to inherit from queued_seearch.indexes.QueuedSearchIndex.

additional note: queued_seearch is fun to say.

Beanstalkc requires jobs to be str (not unicode)

See https://github.com/earl/beanstalkc/blob/master/beanstalkc.py#L124 - I'm not sure which library this problem belongs to, but I'm going to fix it for now by patching queued_search

Filter/exclude objects to index

In Haystack itself, I had overwritten the index_queryset method to pick objects of a model with certain attributes to index. In queued_search it seems that all objects, for which a ModelIndex is defined, get indexed. Do you have plans on allowing some filtering here too? I might try a PR if you want..

Out of date README.rst still refers to QueuedSearchIndex

I think the README.rst might be out of date for Haystack 2.x.

This part:

Alter all of your SearchIndex subclasses to inherit from queued_search.indexes.QueuedSearchIndex (as well as indexes.Indexable).

should maybe read:

In your settings.py:

HAYSTACK_SIGNAL_PROCESSOR = 'queued_search.signals.QueuedSignalProcessor'