Pure Postgresql search backend for Django Oscar
Project description
Careful: This is originally created inside a project not tested in a reusable environment, yet.
This creates a search handler without the need of any search backend. It is designed for the e-commerce framework Oscar.
It is implemented a little bit expensive but uses 4 annotated search vectors: * upc * title * meta_description * meta_title
This way the search can be manipulated through the meta fields. This package is not testet against generic sites, yet. It is running productive in a heavily customized env for many months now. I think it should scale up to 5000 Products with 10 Attributes depending on how the products are loaded. We use it fully lazy with endless scrolling.
To-Do
Dynamic creation of the filter fields
Writing Tests
Features
Don’t need to use some additional search backend like elastic
- Creates filters (facets) for:
Data that is directly attached to the Product model including foreign key choices
AttributeValues of the products
StockRecord entries
Installation
Install using pip:
pip install django-oscar-pg-search
# settings.py
INSTALLED_APPS = [
# ...
'oscar_pg_search.apps.PgSearchConfig',
# ...
]
Settings
If you want to add some fields that are directly attached to the Product model:
# settings.py
OSCAR_ATTACHED_PRODUCT_FIELDS = ['is_public', 'deposit', 'volume', 'weight',]
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