django-lexorank 0.1.4

This package implements an algorithm similar to JIRA's lexorank, but without using buckets for rebalancing that can be used with Django projects.

django-lexorank

This package implements an algorithm similar to JIRA's lexorank, but without using buckets for rebalancing that can be used with Django projects.

Installation

pip install django-lexorank

Configuration

Add django_lexorank to your INSTALLED_APPS setting:

INSTALLED_APPS = [
    ...
    "django_lexorank",
]

Usage

Defining models

To add ranking to your model, you need to inherit it from RankedModel.

There are 2 ways of using RankedModel:

Globally

This way, all the objects will be ranked together in the global scope.

Example:

from django_lexorank.models import RankedModel
from django.db import models


class Board(RankedModel):
    name = models.CharField(max_length=255)

Per group

This way, instances of the model will be ranked separately per group.

To do that, you have to set a name of the foreign key to the group to the order_with_respect_to parameter of the model.

Example:

from django_lexorank.models import RankedModel
from django.db import models


class Task(RankedModel):
    name = models.CharField(max_length=255)
    board = models.ForeignKey("Board", on_delete=models.CASCADE, related_name="tasks")
    order_with_respect_to = "board"

Field parameters

By default, new instances of the model will be ranked at the top of the list. Rank field may accept boolean parameter insert_to_bottom to override this behaviour.

Example:

from django_lexorank.models import RankedModel
from django_lexorank.fields import RankField
from django.db import models


class User(RankedModel):
    name = models.CharField(max_length=255)
    rank = RankField(insert_to_bottom=True)

Manager methods

There are 3 ways to insert models using manager methods:

model.objects.create(**kwargs) - will use the default behaviour specified on RankField definition.

model.objects.add_to_bottom(**kwargs) - will insert the model at the bottom of the list.

model.objects.add_to_top(**kwargs) - will insert the model at the top of the list.

Instance methods

obj.place_after(after_obj) - places model instance after provided instance. If rank length exceeds the limit after the move, rebalancing will be scheduled.

obj.place_before(before_obj) - places model instance before provided instance. If rank length exceeds the limit after the move, rebalancing will be scheduled.

obj.place_on_top() - moves model instance to the bottom of the list. If rank length exceeds the limit after the move, rebalancing will be scheduled.

obj.place_on_bottom() - moves model instance to the bottom of the list. If rank length exceeds the limit after the move, rebalancing will be scheduled.

obj.get_previous_object() - return previous object in the list

obj.get_next_object() - return next object in the list

obj.get_previous_object_rank() - return previous object rank in the list

obj.get_next_object_rank() - return next object rank in the list

obj.schedule_rebalancing() - schedule rebalancing for the whole list or a group if order_with_respect_to is set

obj.rebalance() - rebalance the whole list or a group if order_with_respect_to is set

obj.rebalancing_required() - returns True if rebalancing is required for the whole list, or for a group if order_with_respect_to is set

obj.rebalancing_scheduled() - returns True if rebalancing is scheduled for the whole list, or for a group if order_with_respect_to is set

Model methods

model.get_first_object() - return first object in the list

model.get_last_object() - return last object in the list

model.get_first_object_rank() - return first object rank in the list

model.get_last_object_rank() - return last object rank in the list

Rebalancing Schedule

Each time, a rank length exceeds the limit, rebalancing is scheduled for the whole list or a group, according to the value of order_with_respect_to parameter.

SheduledRebalancing model can be used to create a task for rebalancing ranks.