Search and django CMS¶
If you already have a background in django CMS and are coming from the 3.x days, you may
be familiar with the package aldryn-search
which was the recommended way for setting up
search inside your django CMS project. However, with the deprecation of it and the new
versioning primitives in django CMS 4.x being incompatible with it, you may wonder where to
go from here.
To keep it simple, you can install an external package that handles implementing the search index for you. There are multiple options, such as
… and others
The idea is that we implement the search index just as we would for normal Django models,
e.g. use an external library to handle the indexing (django-haystack
in the above examples)
and just implement the logic that builds the querysets and filters the languages depending on
what index is currently active. django-haystack
exposes many helpful utilities for
interacting with the indexes and return the appropriate results for indexing.
To get an idea on how this works, feel free to look at the code of the above projects. A very simple index could look something like this:
from cms.models import PageContent
from django.db import models
from haystack import indexes
class PageContentIndex(indexes.SearchIndex, indexes.Indexable):
text = indexes.CharField(document=True, use_template=False)
title = indexes.CharField(indexed=False, stored=True)
url = indexes.CharField(indexed=False, stored=True)
def get_model(self):
return PageContent
def index_queryset(self, using=None) -> models.QuerySet:
return self.get_model().objects.filter(language=using)
def prepare(self, instance: PageContent) -> dict:
self.prepared_data = super().prepare(instance)
self.prepared_data["url"] = instance.page.get_absolute_url()
self.prepared_data["title"] = instance.title
self.prepared_data["text"] = (
self.prepared_data["title"] + (instance.meta_description or "")
)
return self.prepared_data
Hint
Your index should be placed inside a search_indexes.py
in one of your
INSTALLED_APPS
!
The above snippet uses the standard text
field that is recommended by
django-haystack
to store all the indexable content. There is also a
separate field for the title because you may want to display it as a heading
in your search result, and a field for the URL so you can link to the pages.
The indexed content here is not using a template (which is one of the options
to compose fields into an indexable field) but rather concatenates it manually
using the prepare
method which gets called by django-haystack
to prepare data
before the indexing starts.
As you can see in the index_queryset
method, we only return those PageContent
instances that are published
and have a language matching the currently used
Haystack connection key.
The PageContent
then get passed into the prepare
method one by one, so we can
use the instance.page
attribute to get the page meta description and use it as
indexable text as well as the title of the current PageContent
version.
Finally, you need to set your HAYSTACK_CONNECTIONS
to contain a default key as
well as any language that you want to be indexed as additional keys.
You could also use different backends for your languages as well, this is up to you
and how you want to configure your haystack installation.
An example could look somewhat like this:
...
HAYSTACK_CONNECTIONS = {
'default': {
"ENGINE": "haystack.backends.whoosh_backend.WhooshEngine",
"PATH": os.path.join(ROOT_DIR, "search_index", "whoosh_index_default"),
},
"en": {
"ENGINE": "haystack.backends.whoosh_backend.WhooshEngine",
"PATH": os.path.join(ROOT_DIR, "search_index", "whoosh_index_en"),
},
"de": {
"ENGINE": "haystack.backends.whoosh_backend.WhooshEngine",
"PATH": os.path.join(ROOT_DIR, "search_index", "whoosh_index_de"),
}
}
...
Hint
This should be configured in your projects settings.py
!
Now run python manage.py rebuild_index
to start building your index. Depending on
what backend you chose you should now see your index at the configured location.
You can inspect your index using a SearchQuerySet
:
from haystack.query import SearchQuerySet
qs = SearchQuerySet(using="<your haystack connection alias / language key>")
for result in qs.all():
print(result.text)
Now it’s up to you to add custom indexes to your own models, build views for your
SearchQuerySet
to implement a search form and much more.