django_sieve 0.1.0

Filter user-data based on multiple criteria.

Filter user-data based on multiple criteria.

Installation

We are at the cheeseshop:

pip install django_sieve

Usage

To use django_sieve in a project:

1. Include it in INSTALLED_APPS in your settings file.

2. Define a sieve model. A sieve model is the control for defining the filtering criteria for user data. For instance, in our example, we have a bookstore in which a user can subscribe to all the books from a particular author or all the books from a particular publisher. In this case, his book list need to only contain books from the publisher and author that he has chosen. In order to do this, we define a sieve model like so:

   class Sieve(models.Model):
           user = models.ForeignKey('auth.User')
           publisher = models.ForeignKey(Publisher)
           author = models.ForeignKey(Author)

3. Declare your project-wide sieve model in settings.py. For instance, if the sieve model is called Sieve and resides in the bookstore app:

   SIEVE_MODEL = 'bookstore.Sieve'

4. Use SieveManager as the ModelManager for all the models in your project that you want to filter based on the criteria defined in the sieve model:

   class Author(models.Model):
           first_name = models.CharField(max_length=30)
           last_name = models.CharField(max_length=40)
           email = models.EmailField()
           objects = SieveManager()

5. Use the sieve method to define your queryset in your views like so:

   class BookView(ListView):
           queryset = Book.objects.sieve(user=request.user)

That is all. Site-wide filtering of user-data based on pre-defined criteria without having to write queries for all the views. Please be wary of performance issues though - in our experience, django-sieve works for 90% cases especially when you need to bring everything up for a quick demo. However, as your site matures and the number of users increase, you may want to invest in profiling your views and hand-crafting these queries when and where required.

History

0.1.0 (2013)

• First release on PyPI.