.. _wagtailsearch_searching:
=========
Searching
=========
.. _wagtailsearch_searching_pages:
Searching QuerySets
===================
Wagtail search is built on Django's `QuerySet API `_. You should be able to search any Django QuerySet provided the model and the fields being filtered on have been added to the search index.
Searching Pages
---------------
Wagtail provides a shortcut for searching pages: the ``.search()`` ``QuerySet`` method. You can call this on any ``PageQuerySet``. For example:
.. code-block:: python
# Search future EventPages
>>> from wagtail.core.models import EventPage
>>> EventPage.objects.filter(date__gt=timezone.now()).search("Hello world!")
All other methods of ``PageQuerySet`` can be used with ``search()``. For example:
.. code-block:: python
# Search all live EventPages that are under the events index
>>> EventPage.objects.live().descendant_of(events_index).search("Event")
[, ]
.. note::
The ``search()`` method will convert your ``QuerySet`` into an instance of one of Wagtail's ``SearchResults`` classes (depending on backend). This means that you must perform filtering before calling ``search()``.
.. _wagtailsearch_images_documents_custom_models:
Searching Images, Documents and custom models
---------------------------------------------
Wagtail's document and image models provide a ``search`` method on their QuerySets, just as pages do:
.. code-block:: python
>>> from wagtail.images.models import Image
>>> Image.objects.filter(uploaded_by_user=user).search("Hello")
[, ]
:ref:`Custom models ` can be searched by using the ``search`` method on the search backend directly:
.. code-block:: python
>>> from myapp.models import Book
>>> from wagtail.search.backends import get_search_backend
# Search books
>>> s = get_search_backend()
>>> s.search("Great", Book)
[, ]
You can also pass a QuerySet into the ``search`` method which allows you to add filters to your search results:
.. code-block:: python
>>> from myapp.models import Book
>>> from wagtail.search.backends import get_search_backend
# Search books
>>> s = get_search_backend()
>>> s.search("Great", Book.objects.filter(published_date__year__lt=1900))
[]
.. _wagtailsearch_specifying_fields:
Specifying the fields to search
-------------------------------
By default, Wagtail will search all fields that have been indexed using ``index.SearchField``.
This can be limited to a certain set of fields by using the ``fields`` keyword argument:
.. code-block:: python
# Search just the title field
>>> EventPage.objects.search("Event", fields=["title"])
[, ]
.. _wagtailsearch_faceted_search:
Faceted search
--------------
Wagtail supports faceted search which is a kind of filtering based on a taxonomy
field (such as category or page type).
The ``.facet(field_name)`` method returns an ``OrderedDict``. The keys are
the IDs of the related objects that have been referenced by the specified field, and the
values are the number of references found for each ID. The results are ordered by number
of references descending.
For example, to find the most common page types in the search results:
.. code-block:: python
>>> Page.objects.search("Test").facet("content_type_id")
# Note: The keys correspond to the ID of a ContentType object; the values are the
# number of pages returned for that type
OrderedDict([
('2', 4), # 4 pages have content_type_id == 2
('1', 2), # 2 pages have content_type_id == 1
])
Changing search behaviour
-------------------------
Search operator
^^^^^^^^^^^^^^^
The search operator specifies how search should behave when the user has typed in multiple search terms. There are two possible values:
- "or" - The results must match at least one term (default for Elasticsearch)
- "and" - The results must match all terms (default for database search)
Both operators have benefits and drawbacks. The "or" operator will return many more results but will likely contain a lot of results that aren't relevant. The "and" operator only returns results that contain all search terms, but require the user to be more precise with their query.
We recommend using the "or" operator when ordering by relevance and the "and" operator when ordering by anything else (note: the database backend doesn't currently support ordering by relevance).
Here's an example of using the ``operator`` keyword argument:
.. code-block:: python
# The database contains a "Thing" model with the following items:
# - Hello world
# - Hello
# - World
# Search with the "or" operator
>>> s = get_search_backend()
>>> s.search("Hello world", Things, operator="or")
# All records returned as they all contain either "hello" or "world"
[, , ]
# Search with the "and" operator
>>> s = get_search_backend()
>>> s.search("Hello world", Things, operator="and")
# Only "hello world" returned as that's the only item that contains both terms
[]
For page, image and document models, the ``operator`` keyword argument is also supported on the QuerySet's ``search`` method:
.. code-block:: python
>>> Page.objects.search("Hello world", operator="or")
# All pages containing either "hello" or "world" are returned
[, , ]
Phrase searching
^^^^^^^^^^^^^^^^
Phrase searching is used for finding whole sentence or phrase rather than individual terms.
The terms must appear together and in the same order.
For example:
.. code-block:: python
>>> from wagtail.search.query import Phrase
>>> Page.objects.search(Phrase("Hello world"))
[]
>>> Page.objects.search(Phrase("World hello"))
[]
If you are looking to implement phrase queries using the double-quote syntax, see :ref:`wagtailsearch_query_string_parsing`.
.. _wagtailsearch_complex_queries:
Complex search queries
^^^^^^^^^^^^^^^^^^^^^^
Through the use of search query classes, Wagtail also supports building search queries as Python
objects which can be wrapped by and combined with other search queries. The following classes are
available:
``PlainText(query_string, operator=None, boost=1.0)``
This class wraps a string of separate terms. This is the same as searching without query classes.
It takes a query string, operator and boost.
For example:
.. code-block:: python
>>> from wagtail.search.query import PlainText
>>> Page.objects.search(PlainText("Hello world"))
# Multiple plain text queries can be combined. This example will match both "hello world" and "Hello earth"
>>> Page.objects.search(PlainText("Hello") & (PlainText("world") | PlainText("earth")))
``Phrase(query_string)``
This class wraps a string containing a phrase. See previous section for how this works.
For example:
.. code-block:: python
# This example will match both the phrases "hello world" and "Hello earth"
>>> Page.objects.search(Phrase("Hello world") | Phrase("Hello earth"))
``Boost(query, boost)``
This class boosts the score of another query.
For example:
.. code-block:: python
>>> from wagtail.search.query import PlainText, Boost
# This example will match both the phrases "hello world" and "Hello earth" but matches for "hello world" will be ranked higher
>>> Page.objects.search(Boost(Phrase("Hello world"), 10.0) | Phrase("Hello earth"))
Note that this isn't supported by the PostgreSQL or database search backends.
.. _wagtailsearch_query_string_parsing:
Query string parsing
^^^^^^^^^^^^^^^^^^^^
The previous sections show how to construct a phrase search query manually, but a lot of search engines (Wagtail admin included, try it!)
support writing phrase queries by wrapping the phrase with double-quotes. In addition to phrases, you might also want to allow users to
add filters into the query using the colon syntax (``hello world published:yes``).
These two features can be implemented using the ``parse_query_string`` utility function. This function takes a query string that a user
typed and returns returns a query object and dictionary of filters:
For example:
.. code-block:: python
>>> from wagtail.search.utils import parse_query_string
>>> filters, query = parse_query_string('my query string "this is a phrase" this-is-a:filter', operator='and')
>>> filters
{
'this-is-a': 'filter',
}
>>> query
And([
PlainText("my query string", operator='and'),
Phrase("this is a phrase"),
])
Here's an example of how this function can be used in a search view:
.. code-block:: python
from wagtail.search.utils import parse_query_string
def search(request):
query_string = request.GET['query']
# Parse query
filters, query = parse_query_string(query_string, operator='and')
# Published filter
# An example filter that accepts either `published:yes` or `published:no` and filters the pages accordingly
published_filter = filters.get('published')
published_filter = published_filter and published_filter.lower()
if published_filter in ['yes', 'true']:
pages = pages.filter(live=True)
elif published_filter in ['no', 'false']:
pages = pages.filter(live=False)
# Search
pages = pages.search(query)
return render(request, 'search_results.html', {'pages': pages})
Custom ordering
^^^^^^^^^^^^^^^
By default, search results are ordered by relevance, if the backend supports it. To preserve the QuerySet's existing ordering, the ``order_by_relevance`` keyword argument needs to be set to ``False`` on the ``search()`` method.
For example:
.. code-block:: python
# Get a list of events ordered by date
>>> EventPage.objects.order_by('date').search("Event", order_by_relevance=False)
# Events ordered by date
[, , ]
.. _wagtailsearch_annotating_results_with_score:
Annotating results with score
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
For each matched result, Elasticsearch calculates a "score", which is a number
that represents how relevant the result is based on the user's query. The
results are usually ordered based on the score.
There are some cases where having access to the score is useful (such as
programmatically combining two queries for different models). You can add the
score to each result by calling the ``.annotate_score(field)`` method on the
``SearchQuerySet``.
For example:
.. code-block:: python
>>> events = EventPage.objects.search("Event").annotate_score("_score")
>>> for event in events:
... print(event.title, event._score)
...
("Easter", 2.5),
("Haloween", 1.7),
("Christmas", 1.5),
Note that the score itself is arbitrary and it is only useful for comparison
of results for the same query.
.. _wagtailsearch_frontend_views:
An example page search view
===========================
Here's an example Django view that could be used to add a "search" page to your site:
.. code-block:: python
# views.py
from django.shortcuts import render
from wagtail.core.models import Page
from wagtail.search.models import Query
def search(request):
# Search
search_query = request.GET.get('query', None)
if search_query:
search_results = Page.objects.live().search(search_query)
# Log the query so Wagtail can suggest promoted results
Query.get(search_query).add_hit()
else:
search_results = Page.objects.none()
# Render template
return render(request, 'search_results.html', {
'search_query': search_query,
'search_results': search_results,
})
And here's a template to go with it:
.. code-block:: html
{% extends "base.html" %}
{% load wagtailcore_tags %}
{% block title %}Search{% endblock %}
{% block content %}
{% if search_results %}
{% for result in search_results %}
-
{% if result.search_description %}
{{ result.search_description|safe }}
{% endif %}
{% endfor %}
{% elif search_query %}
No results found
{% else %}
Please type something into the search box
{% endif %}
{% endblock %}
Promoted search results
=======================
"Promoted search results" allow editors to explicitly link relevant content to search terms, so results pages can contain curated content in addition to results from the search engine.
This functionality is provided by the :mod:`~wagtail.contrib.search_promotions` contrib module.