Django Inelastic Models

Introduction

This package provides a small library for declaratively specifying indexes for Django models using an Elasticsearch backend.

It requires Django, elasticsearch-dsl and an available Elasticsearch instance.

Usage

  1. Add inelastic_models to INSTALLED_APPS.

  2. Mixin the type inelastic_models.indexes.SearchMixin to your models.

  3. Implement a type inelastic_models.indexes.Search and bind it to models:

    from .models import Foo

class FooIndex(Search):
    attribute_fields = ('foo', 'baz')

FooIndex.bind_to_model(Foo)

You must define ELASTICSEARCH_CONNECTIONS. Pass index and connection parameters to the generated indices and the underlying Elasticsearch instance via the INDEX_OPTIONS and CONNECTION_OPTIONS mappings, respectively:

ELASTICSEARCH_CONNECTIONS = {
    'default': {
        'HOSTS': ['http://localhost:9200'],
        'INDEX_NAME': 'inelastic_models',
        'INDEX_OPTIONS': {
            'number_of_replicas': 3
        },
        'CONNECTION_OPTIONS': {
            'timeout': 42,
            'retry_on_timeout': True
        }
    }
},

Tests

Run tests using the make rule:

make test [venv=<path>] [python=<python executable name, e.g., 'python3.5'>]

It is assumed that you have and Elasticsearch index available at elasticsearch:9200 and that virtualenv available on your path.

Table of contents

Indices and tables