Wagtailmeili

A search backend for Wagtail using MeiliSearch.

Caution

This package is still in development and until version 1.0.0, I will not maintain a DeprecationWarning pattern. I built the integration with meilisearch about 2 years ago for a project and decided to make it a public package to improve it and integrate more features.

Tip

If you need support or require help with a Wagtail project, you can hire me 😊

Introduction

en - https://softquantum.com/resources/wagtailmeili-integrating-a-blazing-fast-search-engine-with-wagtail

fr - https://softquantum.com/fr/ressources/wagtailmeili-integrer-un-moteur-de-recherche-rapide-avec-wagtail/

Requirements

Wagtailmeili requires the following:

• Python >= 3.11
• Wagtail >= 5.2

Installation

In your Wagtail project

Configure your MeiliSearch instance in your settings.py file.

Install Meilisearch python client e.g., using pip

  pip install meilisearch

Add wagtailmeili to your INSTALLED_APPS

INSTALLED_APPS = [
    # ...
    "wagtailmeili",
    # ...
]

add the search backend to your WAGTAILSEARCH_BACKENDS

import os

WAGTAILSEARCH_BACKENDS = {
    "default": {
        "BACKEND": "wagtailmeili.backend",
        "HOST":  os.environ.get("MEILISEARCH_HOST", "http://127.0.0.1"),
        "PORT": os.environ.get("MEILISEARCH_PORT", "7700"),
        "MASTER_KEY": os.environ.get("MEILISEARCH_MASTER_KEY", "your-master-key"),
        # "STOP_WORDS": ...
        # "RANKING_RULES: ...
        # "SKIP_MODELS": ...
        # "SKIP_MODELS_BY_FIELD_VALUE": ...
    },
}

Features

Default search configs

• STOP_WORDS: see defaults in settings.py
• RANKING_RULES: see defaults in settings.py
• SKIP_MODELS: "skip_models" is a list of models that you want to skip from indexing no matter the model setup.

WAGTAILSEARCH_BACKENDS = {
    "default": {
        "SKIP_MODELS": ["app_label.Model1", "app_label.Model2",],
        # ...
    }
}

• SKIP_MODELS_BY_FIELD_VALUE: A convenient way to skip instances based on attributes

WAGTAILSEARCH_BACKENDS = {
    "default": {
        # add this to not index pages that are not published for example
        "SKIP_MODELS_BY_FIELD_VALUE": {
            "wagtailmeili_testapp.MoviePage": {
                "field": "live",
                "value": False,
            },
        },
        # ...
    }
}

Model fields

To declare sortable attributes or add ranking rules for the model, just add, for example:

from wagtail.models import Page


class MySuperPage(Page):
    """A Super Page to do incredible things."""
    
    sortable_attributes = [
        "published_last_timestamp", 
        # ...
    ]
    ranking_rules = [
        "published_last_timestamp:desc",
        # ...
    ]

Template Tag filter

{% load meilisearch %}

{% get_matches_position result %}

Roadmap before 1.0.0 (unsorted)

• Adding tests
• Refactoring index.py to be with easier testing
• Exploring Meilisearch and bringing more of its features for Wagtail
• Getting a leaner implementation (looking at Autocomplete and rebuilder)
• Giving more love to the Sample project with a frontend
• official documentation

Sample Project: WMDB

The Wagtail Movie Database (WMDB) is a sample project for testing purposes. To run the project, follow these steps:

1. start the local meilisearch instance

meilisearch --master-key=<your masterKey>

2. copy the directory wagtail_moviedb wherever you want
3. create a virtualenv and activate it (instructions on linux/macOS)

python -m venv .venv
source .venv/bin/activate

4. install the dependencies

pip install -r requirements.txt

5. add an .env file

MEILISEARCH_MASTER_KEY="your masterKey"

6. apply migrations

python manage.py migrate

7. Create a superuser (optional)

python manage.py createsuperuser

8. load movies & start local web server

python manage.py load_movies
python manage.py runserver

9. visit your meilisearch local instance: https://127.0.0.1:7700, give it your master-key. You should see some movies loaded.
10. update index (optional):

python manage.py update_index

Contributions

Welcome to all contributions!

Prerequisites

• Install Meilisearch locally following their documentation
• Start Meilisearch instance in your favorite terminal

meilisearch --master-key correctmasterkey

Install

To make changes to this project, first clone this repository:

git clone git@github.com:softquantum/wagtailmeili.git
cd wagtailmeili

With your preferred virtualenv activated, install testing dependencies:

Using pip

pip install "pip>=21.3"
pip install -e '.[dev]' -U

How to run tests

You can run tests as shown below:

pytest 

or with tox

tox

License

This project is released under the 3-Clause BSD License.