Wagtail Personalisation
A Wagtail add-on for showing personalized content.
Wagtail Personalisation is a fully-featured personalisation module for Wagtail CMS. It enables editors to create customised pages - or parts of pages - based on segments whose rules are configured directly in the admin interface.
Instructions
Wagtail Personalisation requires Wagtail 7.0+ and Django 5.2+
To install the package with pip:
pip install wagtail-personalisation
Next, include the wagtail_personalisation, wagtail_modeladmin and wagtailfontawesomesvg apps in your project's INSTALLED_APPS:
INSTALLED_APPS = [
# ...
'wagtail.contrib.modeladmin', # Don't repeat if it's there already
'wagtail_personalisation',
'wagtailfontawesomesvg',
# ...
]
Make sure that django.contrib.sessions.middleware.SessionMiddleware has been added in first, this is a prerequisite for this project.
MIDDLEWARE = [
'django.contrib.sessions.middleware.SessionMiddleware',
# ...
]
Documentation
The full documentation is available at wagtail-nest.github.io/wagtail-personalisation. For LLM-assisted tooling, there is also a concise llms.txt and a complete llms-full.txt.
Sandbox
To experiment with the package you can use the sandbox provided in this repository. To install this you will need to create and activate a virtualenv and then run make sandbox. This will start a fresh Wagtail install, with the personalisation module enabled, on http://localhost:8000 and http://localhost:8000/cms/. The superuser credentials are superuser@example.com with the password testing.
Contributing
See anything you like in here? Anything missing? We welcome all support, whether on bug reports, feature requests, code, design, reviews, tests, documentation, and more. Please have a look at our contribution guidelines.
Acknowledgements
This project is currently maintained by the Wagtail Nest team.
It was originally developed by Boris Besemer (@blurrah) and Jasper Berghoef (@jberghoef) for Lab Digital (https://labdigital.nl).
Metadata
Release files for wagtail-personalisation 1.0.0
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Total release size: 136.4 kB
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