Advanced usage examples

Advanced Django REST framework integration examples.

See the example project for sample models/views/serializers.

Contents:

Example app

Sample models

books/models.py

import json

from django.conf import settings
from django.db import models
from django.utils.translation import ugettext, ugettext_lazy as _

from six import python_2_unicode_compatible

BOOK_PUBLISHING_STATUS_PUBLISHED = 'published'
BOOK_PUBLISHING_STATUS_NOT_PUBLISHED = 'not_published'
BOOK_PUBLISHING_STATUS_IN_PROGRESS = 'in_progress'
BOOK_PUBLISHING_STATUS_CANCELLED = 'cancelled'
BOOK_PUBLISHING_STATUS_REJECTED = 'rejected'
BOOK_PUBLISHING_STATUS_CHOICES = (
    (BOOK_PUBLISHING_STATUS_PUBLISHED, "Published"),
    (BOOK_PUBLISHING_STATUS_NOT_PUBLISHED, "Not published"),
    (BOOK_PUBLISHING_STATUS_IN_PROGRESS, "In progress"),
    (BOOK_PUBLISHING_STATUS_CANCELLED, "Cancelled"),
    (BOOK_PUBLISHING_STATUS_REJECTED, "Rejected"),
)
BOOK_PUBLISHING_STATUS_DEFAULT = BOOK_PUBLISHING_STATUS_PUBLISHED


@python_2_unicode_compatible
class Publisher(models.Model):
    """Publisher."""

    name = models.CharField(max_length=30)
    info = models.TextField(null=True, blank=True)
    address = models.CharField(max_length=50)
    city = models.CharField(max_length=60)
    state_province = models.CharField(max_length=30)
    country = models.CharField(max_length=50)
    website = models.URLField()
    latitude = models.DecimalField(null=True,
                               blank=True,
                               decimal_places=15,
                               max_digits=19,
                               default=0)
    longitude = models.DecimalField(null=True,
                                    blank=True,
                                    decimal_places=15,
                                    max_digits=19,
                                    default=0)

    class Meta(object):
        """Meta options."""

        ordering = ["id"]

    def __str__(self):
        return self.name

    @property
    def location_field_indexing(self):
        """Location for indexing.

        Used in Elasticsearch indexing/tests of `geo_distance` native filter.
        """
        return {
            'lat': self.latitude,
            'lon': self.longitude,
        }


@python_2_unicode_compatible
class Author(models.Model):
    """Author."""

    salutation = models.CharField(max_length=10)
    name = models.CharField(max_length=200)
    email = models.EmailField()
    headshot = models.ImageField(upload_to='authors', null=True, blank=True)

    class Meta(object):
        """Meta options."""

        ordering = ["id"]

    def __str__(self):
        return self.name


class Tag(models.Model):
    """Simple tag model."""

    title = models.CharField(max_length=255, unique=True)

    class Meta(object):
        """Meta options."""

        verbose_name = _("Tag")
        verbose_name_plural = _("Tags")

    def __str__(self):
        return self.title


@python_2_unicode_compatible
class Book(models.Model):
    """Book."""

    title = models.CharField(max_length=100)
    description = models.TextField(null=True, blank=True)
    summary = models.TextField(null=True, blank=True)
    authors = models.ManyToManyField('books.Author', related_name='books')
    publisher = models.ForeignKey(Publisher, related_name='books')
    publication_date = models.DateField()
    state = models.CharField(max_length=100,
                             choices=BOOK_PUBLISHING_STATUS_CHOICES,
                             default=BOOK_PUBLISHING_STATUS_DEFAULT)
    isbn = models.CharField(max_length=100, unique=True)
    price = models.DecimalField(max_digits=10, decimal_places=2)
    pages = models.PositiveIntegerField(default=200)
    stock_count = models.PositiveIntegerField(default=30)
    tags = models.ManyToManyField('books.Tag',
                                  related_name='books',
                                  blank=True)

    class Meta(object):
        """Meta options."""

        ordering = ["isbn"]

    def __str__(self):
        return self.title

    @property
    def publisher_indexing(self):
        """Publisher for indexing.

        Used in Elasticsearch indexing.
        """
        if self.publisher is not None:
            return self.publisher.name

    @property
    def tags_indexing(self):
        """Tags for indexing.

        Used in Elasticsearch indexing.
        """
        return [tag.title for tag in self.tags.all()]

Sample document

Index definition

To separate dev/test/staging/production indexes, the following approach is recommended.

Settings

settings/base.py

# Name of the Elasticsearch index
ELASTICSEARCH_INDEX_NAMES = {
    'search_indexes.documents.book': 'book',
    'search_indexes.documents.publisher': 'publisher',
}

settings/testing.py

# Name of the Elasticsearch index
ELASTICSEARCH_INDEX_NAMES = {
    'search_indexes.documents.book': 'test_book',
    'search_indexes.documents.publisher': 'test_publisher',
}

settings/production.py

# Name of the Elasticsearch index
ELASTICSEARCH_INDEX_NAMES = {
    'search_indexes.documents.book': 'prod_book',
    'search_indexes.documents.publisher': 'prod_publisher',
}
Document index

search_indexes/documents/book.py

from django.conf import settings
from django_elasticsearch_dsl import DocType, Index, fields
from elasticsearch_dsl import analyzer

from books.models import Book

# Name of the Elasticsearch index
INDEX = Index(settings.ELASTICSEARCH_INDEX_NAMES[__name__])

# See Elasticsearch Indices API reference for available settings
INDEX.settings(
    number_of_shards=1,
    number_of_replicas=1
)

html_strip = analyzer(
    'html_strip',
    tokenizer="standard",
    filter=["standard", "lowercase", "stop", "snowball"],
    char_filter=["html_strip"]
)


@INDEX.doc_type
class BookDocument(DocType):
    """Book Elasticsearch document."""

    id = fields.IntegerField(attr='id')

    title = fields.StringField(
        analyzer=html_strip,
        fields={
            'raw': fields.StringField(analyzer='keyword'),
        }
    )

    description = fields.StringField(
        analyzer=html_strip,
        fields={
            'raw': fields.StringField(analyzer='keyword'),
        }
    )

    summary = fields.StringField(
        analyzer=html_strip,
        fields={
            'raw': fields.StringField(analyzer='keyword'),
        }
    )

    publisher = fields.StringField(
        attr='publisher_indexing',
        analyzer=html_strip,
        fields={
            'raw': fields.StringField(analyzer='keyword'),
        }
    )

    publication_date = fields.DateField()

    state = fields.StringField(
        analyzer=html_strip,
        fields={
            'raw': fields.StringField(analyzer='keyword'),
        }
    )

    isbn = fields.StringField(
        analyzer=html_strip,
        fields={
            'raw': fields.StringField(analyzer='keyword'),
        }
    )

    price = fields.FloatField()

    pages = fields.IntegerField()

    stock_count = fields.IntegerField()

    tags = fields.StringField(
        attr='tags_indexing',
        analyzer=html_strip,
        fields={
            'raw': fields.StringField(analyzer='keyword', multi=True),
            'suggest': fields.CompletionField(multi=True),
        },
        multi=True
    )

    class Meta(object):
        """Meta options."""

        model = Book  # The model associate with this DocType

Sample serializer

search_indexes/serializers.py

import json

from rest_framework import serializers

class TagSerializer(serializers.Serializer):
    """Helper serializer for the Tag field of the Book document."""

    title = serializers.CharField()

    class Meta(object):
        """Meta options."""

        fields = ('title',)
        read_only_fields = ('title',)


class BookDocumentSerializer(serializers.Serializer):
    """Serializer for the Book document."""

    id = serializers.SerializerMethodField()

    title = serializers.CharField(read_only=True)
    description = serializers.CharField(read_only=True)
    summary = serializers.CharField(read_only=True)

    publisher = serializers.CharField(read_only=True)
    publication_date = serializers.DateField(read_only=True)
    state = serializers.CharField(read_only=True)
    isbn = serializers.CharField(read_only=True)
    price = serializers.FloatField(read_only=True)
    pages = serializers.IntegerField(read_only=True)
    stock_count = serializers.IntegerField(read_only=True)
    tags = serializers.SerializerMethodField()

    class Meta(object):
        """Meta options."""

        fields = (
            'id',
            'title',
            'description',
            'summary',
            'publisher',
            'publication_date',
            'state',
            'isbn',
            'price',
            'pages',
            'stock_count',
            'tags',
        )
        read_only_fields = fields

    def get_tags(self, obj):
        """Get tags."""
        if obj.tags:
            return list(obj.tags)
        else:
            return []

Sample view

search_indexes/viewsets.py

from django_elasticsearch_dsl_drf.constants import (
    LOOKUP_FILTER_TERMS,
    LOOKUP_FILTER_RANGE,
    LOOKUP_FILTER_PREFIX,
    LOOKUP_FILTER_WILDCARD,
    LOOKUP_QUERY_IN,
    LOOKUP_QUERY_EXCLUDE,
)
from django_elasticsearch_dsl_drf.filter_backends import (
    FilteringFilterBackend,
    OrderingFilterBackend,
    DefaultOrderingFilterBackend,
    SearchFilterBackend,
)
from django_elasticsearch_dsl_drf.views import BaseDocumentViewSet

# Example app models
from search_indexes.documents.book import BookDocument
from search_indxes.serializers import BookDocumentSerializer


class BookDocumentView(BaseDocumentViewSet):
    """The BookDocument view."""

    document = BookDocument
    serializer_class = BookDocumentSerializer
    lookup_field = 'id'
    filter_backends = [
        FilteringFilterBackend,
        OrderingFilterBackend,
        DefaultOrderingFilterBackend,
        SearchFilterBackend,
    ]
    # Define search fields
    search_fields = (
        'title',
        'description',
        'summary',
    )
    # Define filtering fields
    filter_fields = {
        'id': {
            'field': '_id',
            'lookups': [
                LOOKUP_FILTER_RANGE,
                LOOKUP_QUERY_IN,
            ],
        },
        'publisher': 'publisher.raw',
        'publication_date': 'publication_date',
        'isbn': 'isbn.raw',
        'tags': {
            'field': 'tags',
            'lookups': [
                LOOKUP_FILTER_TERMS,
                LOOKUP_FILTER_PREFIX,
                LOOKUP_FILTER_WILDCARD,
                LOOKUP_QUERY_IN,
                LOOKUP_QUERY_EXCLUDE,
            ],
        },
        'tags.raw': {
            'field': 'tags.raw',
            'lookups': [
                LOOKUP_FILTER_TERMS,
                LOOKUP_FILTER_PREFIX,
                LOOKUP_FILTER_WILDCARD,
                LOOKUP_QUERY_IN,
                LOOKUP_QUERY_EXCLUDE,
            ],
        },
    }
    # Define ordering fields
    ordering_fields = {
        'id': 'id',
        'title': 'title.raw',
        'price': 'price.raw',
        'state': 'state.raw',
        'publication_date': 'publication_date',
    }
    # Specify default ordering
    ordering = ('id', 'title',)

Usage example

Considering samples above, you should be able to perform the search, sorting and filtering actions described below.

Sample queries

Filtering

Let’s assume we have a number of Book documents with the tags (education, politics, economy, biology, climate, environment, internet, technology).

Multiple filter terms are joined with AND.

Filter documents by field

Filter documents by field (state) “published”.

http://127.0.0.1:8080/search/books/?state=published

Filter documents by multiple fields

Filter documents by field (states) “published” and “in_progress”.

http://127.0.0.1:8080/search/books/?state__in=published|in_progress

Filter document by a single field

Filter documents by (field tag) “education”.

http://127.0.0.1:8080/search/books/?tag=education

Filter documents by multiple fields

Filter documents by multiple fields (field tags) “education” and “economy” with use of functional in query filter.

http://127.0.0.1:8080/search/books/?tags__in=education|economy

You can achieve the same effect by specifying multiple fields (tags) “education” and “economy”. Note, that in this case multiple filter terms are joined with OR.

http://127.0.0.1:8080/search/books/?tags=education&tags=economy

If you want the same as above, but joined with AND, add __term to each lookup.

http://127.0.0.1:8080/search/books/?tags__term=education&tags__term=economy

Filter documents by a word part of a single field

Filter documents by a part word part in single field (tags). Word part should match both “technology” and “biology”.

http://127.0.0.1:8080/search/books/?tags__wildcard=*logy
Ordering

The - prefix means ordering should be descending.

Order documents by field (ascending)

Order documents by field price (ascending).

http://127.0.0.1:8080/search/books/?search=title|lorem&ordering=price

Order documents by field (descending)

Order documents by field price (descending).

http://127.0.0.1:8080/search/books/?search=title|lorem&ordering=-price

Order documents by multiple fields

If you want to order by multiple fields, use multiple ordering query params. In the example below, documents would be ordered first by field publication_date (descending), then by field price (ascending).

http://127.0.0.1:8080/search/books/?search=title|lorem&ordering=-publication_date&ordering=price

Ids filter

Filters documents that only have the provided ids.

http://127.0.0.1:8000/api/articles/?ids=68|64|58

Or, alternatively:

http://127.0.0.1:8000/api/articles/?ids=68&ids=64&ids=58

Geo-spatial features

For testing the boundaries the following online services might be helpful:

Filtering

Geo-distance filtering

Filter documents by radius of 100000km from the given location.

http://localhost:8000/search/publishers/?location__geo_distance=100000km|12.04|-63.93

Geo-polygon filtering

Filter documents that are located in the given polygon.

http://localhost:8000/search/publishers/?location__geo_polygon=40,-70|30,-80|20,-90

Geo-bounding-box filtering

Filter documents that are located in the given bounding box.

http://localhost:8000/search/publishers/?location__geo_bounding_box=44.87,40.07|43.87,41.11

Ordering

Geo-distance ordering

http://localhost:8000/search/publishers/?ordering=location|48.85|2.30|km|plane

Suggestions

The suggest feature suggests similar looking terms based on a provided text by using a suggester.

Note

The SuggesterFilterBackend filter backend can be used in the suggest custom view action/route only. Usages outside of the are suggest action/route are restricted.

There are three options available here: term, phrase and completion.

Note

Suggestion functionality is exclusive. Once you have queried the SuggesterFilterBackend, the latter will transform your current search query into suggestion search query (which is very different). Therefore, always add it as the very last filter backend.

Completion suggesters

Document definition

To make use of suggestions, you should properly indexed your documents using fields.CompletionField.

search_indexes/documents/publisher.py

from django.conf import settings

from django_elasticsearch_dsl import DocType, Index, fields

from books.models import Publisher

# Name of the Elasticsearch index
INDEX = Index(settings.ELASTICSEARCH_INDEX_NAMES[__name__])

# See Elasticsearch Indices API reference for available settings
INDEX.settings(
    number_of_shards=1,
    number_of_replicas=1
)


@INDEX.doc_type
class PublisherDocument(DocType):
    """Publisher Elasticsearch document."""

    id = fields.IntegerField(attr='id')

    name = fields.StringField(
        fields={
            'raw': fields.StringField(analyzer='keyword'),
            'suggest': fields.CompletionField(),
        }
    )

    info = fields.StringField()

    address = fields.StringField(
        fields={
            'raw': fields.StringField(analyzer='keyword')
        }
    )

    city = fields.StringField(
        fields={
            'raw': fields.StringField(analyzer='keyword'),
            'suggest': fields.CompletionField(),
        }
    )

    state_province = fields.StringField(
        fields={
            'raw': fields.StringField(analyzer='keyword'),
            'suggest': fields.CompletionField(),
        }
    )

    country = fields.StringField(
        fields={
            'raw': fields.StringField(analyzer='keyword'),
            'suggest': fields.CompletionField(),
        }
    )

    website = fields.StringField()

    # Location
    location = fields.GeoPointField(attr='location_field_indexing')

    class Meta(object):
        """Meta options."""

        model = Publisher  # The model associate with this DocType

After that the name.suggest, city.suggest, state_province.suggest and country.suggest fields would be available for suggestions feature.

Serializer definition

This is how publisher serializer would look like.

search_indexes/serializers.py

import json

from django_elasticsearch_dsl_drf.serializers import DocumentSerializer

class PublisherDocumentSerializer(DocumentSerializer):
    """Serializer for Publisher document."""

    location = serializers.SerializerMethodField()

    class Meta(object):
        """Meta options."""

        # Note, that since we're using a dynamic serializer,
        # we only have to declare fields that we want to be shown. If
        # somehow, dynamic serializer doesn't work for you, either extend
        # or declare your serializer explicitly.
        fields = (
            'id',
            'name',
            'info',
            'address',
            'city',
            'state_province',
            'country',
            'website',
        )

    def get_location(self, obj):
    """Represent location value."""
    try:
        return obj.location.to_dict()
    except:
        return {}
ViewSet definition

In order to add suggestions support, we would have to extend our view set in the following way:

search_indexes/viewsets.py

# ...

from django_elasticsearch_dsl_drf.constants import SUGGESTER_COMPLETION
from django_elasticsearch_dsl_drf.filter_backends import (
    # ...
    SuggesterFilterBackend,
)

# ...

class PublisherDocumentViewSet(BaseDocumentViewSet):
    """The PublisherDocument view."""

    document = PublisherDocument

    # ...

    filter_backends = [
        # ...
        SuggesterFilterBackend,
    ]

    # ...

    # Suggester fields
    suggester_fields = {
        'name_suggest': {
            'field': 'name.suggest',
            'suggesters': [
                SUGGESTER_COMPLETION,
            ],
        },
        'city_suggest': {
            'field': 'city.suggest',
            'suggesters': [
                SUGGESTER_COMPLETION,
            ],
        },
        'state_province_suggest': {
            'field': 'state_province.suggest',
            'suggesters': [
                SUGGESTER_COMPLETION,
            ],
        },
        'country_suggest': {
            'field': 'country.suggest',
            'suggesters': [
                SUGGESTER_COMPLETION,
            ],
        },
    }

    # Geo-spatial filtering fields
    geo_spatial_filter_fields = {
        'location': {
            'lookups': [
                LOOKUP_FILTER_GEO_DISTANCE,
            ],
        },
    }

In the example below, we show suggestion results (auto-completion) for country field.

Sample requests/responses

Once you have extended your view set with SuggesterFilterBackend functionality, you can make use of the suggest custom action of your view set.

Request

GET http://127.0.0.1:8000/search/publishers/suggest/?country_suggest__completion=Ar

Response

{
    "_shards": {
        "failed": 0,
        "successful": 1,
        "total": 1
    },
    "country_suggest__completion": [
        {
            "options": [
                {
                    "score": 1.0,
                    "text": "Armenia"
                },
                {
                    "score": 1.0,
                    "text": "Argentina"
                }
            ],
            "offset": 0,
            "length": 2,
            "text": "Ar"
        }
    ]
}

You can also have multiple suggesters per request.

Request

GET http://127.0.0.1:8000/search/publishers/suggest/?name_suggest__completion=B&country_suggest__completion=Ar

Response

{
    "_shards": {
        "successful": 1,
        "total": 1,
        "failed": 0
    },
    "country_suggest__completion": [
        {
            "text": "Ar",
            "options": [
                {
                    "score": 1.0,
                    "text": "Armenia"
                },
                {
                    "score": 1.0,
                    "text": "Argentina"
                }
            ],
            "offset": 0,
            "length": 2
        }
    ],
    "name_suggest__completion": [
        {
            "text": "B",
            "options": [
                {
                    "score": 1.0,
                    "text": "Book Works"
                },
                {
                    "score": 1.0,
                    "text": "Brumleve LLC"
                },
                {
                    "score": 1.0,
                    "text": "Booktrope"
                },
                {
                    "score": 1.0,
                    "text": "Borman, Post and Wendt"
                },
                {
                    "score": 1.0,
                    "text": "Book League of America"
                }
            ],
            "offset": 0,
            "length": 1
        }
    ]
}
Suggestions on Array/List field

Suggestions on Array/List fields (typical use case - tags, where Tag model would be a many-to-many relation to a Book model) work almost the same.

Before checking the Sample requests/responses, do have in mind the following:

Sample requests/responses

Once you have extended your view set with SuggesterFilterBackend functionality, you can make use of the suggest custom action of your view set.

Request

GET http://127.0.0.1:8000/search/books/suggest/?tag_suggest__completion=bio

Response

{
    "_shards": {
        "failed": 0,
        "successful": 1,
        "total": 1
    },
    "country_suggest__completion": [
        {
            "options": [
                {
                    "score": 1.0,
                    "text": "Biography"
                },
                {
                    "score": 1.0,
                    "text": "Biology"
                }
            ],
            "offset": 0,
            "length": 2,
            "text": "bio"
        }
    ]
}

Term and Phrase suggestions

While for the completion suggesters to work the CompletionField shall be used, the term and phrase suggesters work on common text fields.

Document definition

search_indexes/documents/book.py

from django.conf import settings

from django_elasticsearch_dsl import DocType, Index, fields

from books.models import Book

# Name of the Elasticsearch index
INDEX = Index(settings.ELASTICSEARCH_INDEX_NAMES[__name__])

# See Elasticsearch Indices API reference for available settings
INDEX.settings(
    number_of_shards=1,
    number_of_replicas=1
)

@INDEX.doc_type
class BookDocument(DocType):
    """Book Elasticsearch document."""
    # ID
    id = fields.IntegerField(attr='id')

    title = StringField(
        analyzer=html_strip,
        fields={
            'raw': KeywordField(),
            'suggest': fields.CompletionField(),
        }
    )

    description = StringField(
        analyzer=html_strip,
        fields={
            'raw': KeywordField(),
        }
    )

    summary = StringField(
        analyzer=html_strip,
        fields={
            'raw': KeywordField()
        }
    )

    # Publisher
    publisher = StringField(
        attr='publisher_indexing',
        analyzer=html_strip,
        fields={
            'raw': KeywordField(),
            'suggest': fields.CompletionField(),
        }
    )

    # Publication date
    publication_date = fields.DateField()

    # State
    state = StringField(
        analyzer=html_strip,
        fields={
            'raw': KeywordField(),
        }
    )

    # ISBN
    isbn = StringField(
        analyzer=html_strip,
        fields={
            'raw': KeywordField(),
        }
    )

    # Price
    price = fields.FloatField()

    # Pages
    pages = fields.IntegerField()

    # Stock count
    stock_count = fields.IntegerField()

    # Tags
    tags = StringField(
        attr='tags_indexing',
        analyzer=html_strip,
        fields={
            'raw': KeywordField(multi=True),
            'suggest': fields.CompletionField(multi=True),
        },
        multi=True
    )

    null_field = fields.StringField(attr='null_field_indexing')

    class Meta(object):
        """Meta options."""

        model = Book  # The model associate with this DocType
ViewSet definition

search_indexes/viewsets.py

from django_elasticsearch_dsl_drf.constants import (
    LOOKUP_FILTER_PREFIX,
    LOOKUP_FILTER_RANGE,
    LOOKUP_FILTER_TERMS,
    LOOKUP_FILTER_WILDCARD,
    LOOKUP_QUERY_EXCLUDE,
    LOOKUP_QUERY_GT,
    LOOKUP_QUERY_GTE,
    LOOKUP_QUERY_IN,
    LOOKUP_QUERY_IN,
    LOOKUP_QUERY_ISNULL,
    LOOKUP_QUERY_LT,
    LOOKUP_QUERY_LTE,
    SUGGESTER_PHRASE,
    SUGGESTER_TERM,
)
from django_elasticsearch_dsl_drf.filter_backends import (
    # ...
    SuggesterFilterBackend,
)

class BookDocumentViewSet(BaseDocumentViewSet):
    """The BookDocument view."""

    document = BookDocument
    # serializer_class = BookDocumentSerializer
    serializer_class = BookDocumentSimpleSerializer
    lookup_field = 'id'
    filter_backends = [
        FilteringFilterBackend,
        OrderingFilterBackend,
        DefaultOrderingFilterBackend,
        SearchFilterBackend,
        SuggesterFilterBackend,
    ]
    # Define search fields
    search_fields = (
        'title',
        'description',
        'summary',
    )
    # Define filter fields
    filter_fields = {
        'id': {
            'field': 'id',
            'lookups': [
                LOOKUP_FILTER_RANGE,
                LOOKUP_QUERY_IN,
                LOOKUP_QUERY_GT,
                LOOKUP_QUERY_GTE,
                LOOKUP_QUERY_LT,
                LOOKUP_QUERY_LTE,
                LOOKUP_FILTER_TERMS,
            ],
        },
        'title': 'title.raw',
        'publisher': 'publisher.raw',
        'publication_date': 'publication_date',
        'state': 'state.raw',
        'isbn': 'isbn.raw',
        'price': {
            'field': 'price.raw',
            'lookups': [
                LOOKUP_FILTER_RANGE,
            ],
        },
        'pages': {
            'field': 'pages',
            'lookups': [
                LOOKUP_FILTER_RANGE,
                LOOKUP_QUERY_GT,
                LOOKUP_QUERY_GTE,
                LOOKUP_QUERY_LT,
                LOOKUP_QUERY_LTE,
            ],
        },
        'stock_count': {
            # 'field': 'stock_count',
            'lookups': [
                LOOKUP_FILTER_RANGE,
                LOOKUP_QUERY_GT,
                LOOKUP_QUERY_GTE,
                LOOKUP_QUERY_LT,
                LOOKUP_QUERY_LTE,
            ],
        },
        'tags': {
            'field': 'tags',
            'lookups': [
                LOOKUP_FILTER_TERMS,
                LOOKUP_FILTER_PREFIX,
                LOOKUP_FILTER_WILDCARD,
                LOOKUP_QUERY_IN,
                LOOKUP_QUERY_EXCLUDE,
                LOOKUP_QUERY_ISNULL,
            ],
        },
        'tags.raw': {
            'field': 'tags.raw',
            'lookups': [
                LOOKUP_FILTER_TERMS,
                LOOKUP_FILTER_PREFIX,
                LOOKUP_FILTER_WILDCARD,
                LOOKUP_QUERY_IN,
                LOOKUP_QUERY_EXCLUDE,
            ],
        },
        # This has been added to test `exists` filter.
        'non_existent_field': 'non_existent_field',
        # This has been added to test `isnull` filter.
        'null_field': 'null_field',
    }
    # Define ordering fields
    ordering_fields = {
        'id': 'id',
        'title': 'title.raw',
        'price': 'price.raw',
        'state': 'state.raw',
        'publication_date': 'publication_date',
    }
    # Specify default ordering
    ordering = ('id', 'title', 'price',)

    # Suggester fields
    suggester_fields = {
        'title_suggest': 'title.suggest',
        'publisher_suggest': 'publisher.suggest',
        'tag_suggest': 'tags.suggest',
        'summary_suggest': 'summary',
    }
Sample requests/responses

Once you have extended your view set with SuggesterFilterBackend functionality, you can make use of the suggest custom action of your view set.

Let’s considering, that one of our books has the following text in the summary:

Twas brillig, and the slithy toves
Did gyre and gimble in the wabe.
All mimsy were the borogoves
And the mome raths outgrabe.

"Beware the Jabberwock, my son!
The jaws that bite, the claws that catch!
Beware the Jubjub bird, and shun
The frumious Bandersnatch!"

He took his vorpal sword in his hand,
Long time the manxome foe he sought --
So rested he by the Tumtum tree,
And stood awhile in thought.
Term

Request

GET http://127.0.0.1:8000/search/books/suggest/?summary_suggest__term=tovse

Response

{
    "_shards": {
        "failed": 0,
        "total": 1,
        "successful": 1
    },
    "summary_suggest__term": [
        {
            "text": "tovs",
            "offset": 0,
            "options": [
                {
                    "text": "tove",
                    "score": 0.75,
                    "freq": 1
                },
                {
                    "text": "took",
                    "score": 0.5,
                    "freq": 1
                },
                {
                    "text": "twas",
                    "score": 0.5,
                    "freq": 1
                }
            ],
            "length": 5
        }
    ]
}
Phrase

Request

GET http://127.0.0.1:8000/search/books/suggest/?summary_suggest__phrase=slith%20tovs

Response

{
    "summary_suggest__phrase": [
        {
            "text": "slith tovs",
            "offset": 0,
            "options": [
                {
                    "text": "slithi tov",
                    "score": 0.00083028956
                }
            ],
            "length": 10
        }
    ],
    "_shards": {
        "failed": 0,
        "total": 1,
        "successful": 1
    }
}