Skip to main content

PostgreSQL full text search backend for Wagtail CMS

Project description

A PostgreSQL full text search backend for Wagtail CMS.


PostgreSQL full text search in Wagtail requires PostgreSQL >= 9.2 (noticable speed improvements are in place for PostgreSQL >= 9.5), Django >= 1.10 and Wagtail >= 1.8.

First, install the module using:

pip install wagtail-pg-search-backend

Then you’ll need to do a little bit of configuration.

Add the following to the project settings:


    'default': {
        'BACKEND': 'wagtail_pgsearchbackend.backend',
        'SEARCH_CONFIG': 'english'

Then run migrations to add the required database table:

./ migrate wagtail_pgsearchbackend


The SEARCH_CONFIG key takes a text search configuration name. This controls the stemming, stopwords etc. used when searching and indexing the database. To get a list of the available config names use this query:

SELECT cfgname FROM pg_catalog.pg_ts_config


This backend implements the required methods to be compatible with most features mentioned in the the Wagtail search docs.

Known limitations

  • SearchField.partial_match behaviour is not implemented.

  • Due to a PostgreSQL limitation, SearchField.boost is only partially respected. It is changed so that there can only be 4 different boosts. If you define 4 or less different boosts, everything will be perfectly accurate. However, your search will be a little less accurate if you define more than 4 different boosts. That being said, it will work and be roughly the same.

  • SearchField.es_extra is not handled because it is specific to ElasticSearch.

  • Using while limiting to specific field(s) is only supported for database fields, not methods.


The PostgreSQL search backend has been tried and tested on a few small to medium sized website and its performance compares favorably to that of ElasticSearch.

Some noticeable speed improvements are in place when using PostgreSQL >= 9.5.

Features to add

These features would awesome to have once this project is merged with Wagtail:

  • Per-object boosting

  • Faceting

  • Autocomplete (maybe it should replace partial search?)

  • Spelling suggestions


Install the package and dev requirements:

pip install -e . -r requirements-dev.txt

Creating migrations

First create a database:

createdb -Upostgres wagtail_pgsearchbackend

Then call makemigrations using the test settings:

django-admin makemigrations --settings=tests.settings


To run the unittests for the current environment’s Python version and Wagtail run:

make unittests

To check the code for style errors run:

make flaketest

To combine these tasks run:


To run the unittest against all supported versions of Python and Wagtail run:


The tox run will also create a coverage report combining the results of all runs. This report is located in htmlcov/index.html.

To run individual tests by name use the script and give the dotted path the the test module(s), class(es) or method(s) that you want to test e.g.:

./ tests.test_module.TestClass.test_method

Project details

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

wagtail-pg-search-backend-1.3.2.tar.gz (17.5 kB view hashes)

Uploaded source

Built Distribution

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page