django-timeseries-tables supports Django_ 1.8 to 2.1.
Django: http://www.djangoproject.com/
This app is available on PyPI.
PyPI: https://pypi.python.org/pypi/django-timeseries-tables/
Documentation for django-timeseries-tables is available https://django-timeseries-tables.readthedocs.io/
Let's say you want to qualify companies to see if they'd make good clients for your SaaS business.
Normally when you create django models, you would write something like this:
from django.db import models
class Company(models.Model):
name = models.TextField()
revenue = models.FloatField()
phone_number = models.TextField()
number_of_employees = models.IntegerField(null=True)
is_qualified = models.BooleanField(default=True)
And wind up with a single table company with 6 columns (id, phone_number, name, revenue, number_of_employees, is_qualified).
But what if you want to the value of all those fields over all of time for your data/eng teams, but still provide a Company table for your business team to query against?
You'd have to write separate models for all the columns you want to track, and then either a (possibly materlized) view or a real Company model that you would update periodically.
That's exactly what this package does for you:
from django_timeseries_tables import TimeSeriesModel, NormalField, ForeignKey
from django.db import models
class TimeSeriesCompany(TimeSeriesModel):
name = models.TextField()
revenue = models.FloatField()
number_of_employees = models.IntegerField(null=True)
phone_number = NormalField(models.TextField())
is_qualified = NormalField(models.BooleanField(default=True))
This will create 4 tables and a materialized view. You'll have access to the full history of name, revenue and number_of_employees in their own tables: timeseriescompany_name, timeseriescompany_revenue, timeseriescompany_number_of_employees, respectively. It will also create a timeseriescompany_historical table that will hold an ID as well as any fields that are wrapped with NormalField. Finally, it creates a ready-only materialized view timeseriescompany, that can be used to access the data. (To update the view, call TimeSeriesCompany.refresh())
Please file bugs and send pull requests to the GitHub repository_ and issue tracker. See CONTRIBUTING.rst for details.