openorg-timeseries 0.1.1

An implementation of the OpenOrg time-series API

This is an implementation of the OpenOrg time-series API specification as a Django application.

Features

• Stores data in a compact binary format for quick retrieval

• Archives data in CSV format to negate format-based lock-in

• Time-zone aware

• Customisable aggregation (e.g. for daily and weekly averages, minima and maxima)

• Implements an API used by other time-series implementations

• Allows creation, modification and updating of time-series from a RESTful web service

• Has a fine-grained permissions model for administering time-series

Features yet to be implemented

• Administration interface is still somewhat human-unfriendly

• Customisable alerts for when series haven’t been updated for some period of time

• Gauge and counter-based series (currently only period-based series)

• Virtual time-series (i.e. time-series which are some function of other time-series)

Architecture

This project comprises a Django application that you can include in an existing Django project by adding 'openorg_timeseries' to your INSTALLED_APPS variable in your Django settings file.

openorg_timeseries.longliving contains a threading.Thread which mediates access to the underlying data, and which prevents …

Demonstration application

This project comes with a demonstration web service which you can use to quickly evaluate its usefulness.

Running

First, install the necessary dependencies using pip:

$ pip install -r requirements.txt

Next, start the demonstration server using the following:

$ django-admin.py rundemo –settings=openorg_timeseries.demo.settings –pythonpath=.

Give it a few seconds, after which you can point a web browser at http://localhost:8000/ <http://localhost:8000/ to see it in action.

Details

The demo site performs the following steps on start-up:

1. Creates a demo-data directory in the current directory to store data used by the demo

2. Runs the syncdb Django management command to create a sqlite3 database in the demo-data directory

3. Starts a long-living process which manages the data storage and retrieval

4. Creates a new time-series and loads in some example data

5. Runs the runserver management command (without the auto-reloader) to start the Django development server