Django Stretch

Elasticsearch for Django, Made Friendly

Stretch lets you index and search Django models in Elasticsearch. It sits on top of the elasticsearch_dsl package for easy access to most of Elasticsearch’s features.

See the complete Documentation

Installation

Currently you can only install django-stretch via git.

pip install git+git@github.com:cbredev/django-stretch.git

Quickstart

1. Make sure you have Elasticsearch installed

2. Add to INSTALLED_APPS

   INSTALLED_APPS = (
       ...
       'stretch',
   )
   

3. Create a stretch_indices.py file in one of your apps

   from stretch.indices import StretchIndex
   from stretch.signals import RealtimeSignalHandler
   from elasticsearch_dsl import String
   from yourapp.models import Foo
   
   
   
   class FooIndex(StretchIndex):
       name = String(source='name')
       bar = String(source='get_bar')
   
       class Meta:
           # Specify the model to track with this index
           model = Foo
           index = 'foos'      # (Optional) specify a custom index name
           doc_type = 'deal'   # (Optional) specify a custom doc type
   
           # (Optional) Specify any custom index settings
           index_settings = {
               'number_of_replicas': 1
           }
           # Automatically track model updates in realtime or with celery
           signal_handler = RealtimeSignalHandler
   
       # The bar field is populated by this custom method
       def get_bar(self, obj):
           return 'custom value'
   

4. Create the index & add all the documents

   ./manage.py stretch_update_all
   

Your models are now being indexed in Elasticsearch!

Features

• Specify custom analyzers and other field attributes
• Dynamically update mapping and per index settings
• Django Rest Framework (DRF) Search Filter
• Management Commands to update indices and documents
• post_save / post_delete signals

Philosophy

Stretch sits on top of the Elasticsearch DSL python library. This makes it really easy to create document mappings and use custom analyzers in a declarative, pythonic syntax. It also includes an up to date interface for performing complex searches. This tool focuses on making it easy to manage your Elasticsearch indices over the long term as you add new fields and analyzers.

Why not [Haystack|Bungiesearch]?

Both Haystack and Bungieserach are great tools. Haystack works great as a general search engine wrapper, but makes it difficult to use the majority of Elasticsearch’s built in features. Bungiesearch does a slightly better job at this, but does not provide good tooling for adding new analyzers or updating index settings. We wanted a tool that let us easily manage indices as well as documents.

Settings

STRETCH_SETTINGS = {
    'HOSTS': ['localhost'],
    'APPS': None,               # If not specified, searches all apps for indices
    'EXCLUDED_INDICES': None,   # Manually ignore an index. You can also set the index attribute to `IS_INDEX = False`
    'SIGNAL_PROCESSOR': None,   # Set a global default signal processor. None by default
    'TEST': False               # Uses a mock backend so you can run tests in your project without trying to make a real connection to Elasticsearch
    'RAISE_EXCEPTIONS': False   # By default, Stretch will use a `logging.exception` to notify your application of failures without crashing your threads. If you prefer to have your application fail on write errors, set this to `True`
}