nanoleaf 0.4.1
Python interface for Nanoleaf Aurora.
Keywords: nanoleaf,aurora,lighting,openAPI

Python interface for Nanoleaf Aurora
====================================

A Python module for the coolest lights with the worst software support.

This module aims to do more than just act as a wrapper for API calls. It
provides several convenience functions to perform more complicated and
robust actions than are possible in some of the other Aurora wrappers
I've seen. For instance, being able to switch to a random new effect, or
toggle the on/off state with a single command.

Support The Project
~~~~~~~~~~~~~~~~~~~

This is a pet project, and I'm doing it because I need API support just
as badly as you do. But, if it really does make your life better, I'd
appreciate a cup of coffee.

::

    BTC: 1Gr31rgb6UXEdXwbwQGUsadcd7AnY7okXT
    LTC: Lajqnm28UipLbzJqvyy4tRQFf39xQy6B48

Install
-------

It's super easy - just use pip to get the latest version.

::

    pip install nanoleaf --upgrade

Setup
-----

There are two pieces of information you'll need to control your Aurora:
The IP address and an auth token.

Finding IP Address
~~~~~~~~~~~~~~~~~~

For most people, the IP address that the Aurora uses to communicate is
the one assigned by your router, but this might not necessarily be true
depending on your network setup. Either way, you can get this by using
the setup class. After about 90 seconds, this will return a list of the
IP address of every Aurora found on the network.

.. code:: python

    from nanoleaf import setup

    ipAddressList = setup.find_auroras()

Generate Auth Token
~~~~~~~~~~~~~~~~~~~

To generate an auth token, you must first press and hold the power
button on the Aurora for about 5-7 seconds, until the white LED flashes
briefly. Then, call the Setup class like so:

.. code:: python

    from nanoleaf import setup

    token = setup.generate_auth_token("192.168.1.129")

Be sure to store this auth token somewhere for future use. If you lose
this token, you'll have to generate another. Personally, I just keep it
in the scripts I've written that call this library.

Examples
--------

Turn on and set to an effect
~~~~~~~~~~~~~~~~~~~~~~~~~~~~

.. code:: python

    from nanoleaf import Aurora

    my_aurora = Aurora("169.254.123.123", "5EvbR2FjfmYfAkEtOkEnolnZbe6qOB")
    my_aurora.on = True
    my_aurora.effect = "Violets Are Blue"

Set multiple Auroras to the same random effect
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

.. code:: python

    left_side = Aurora("192.168.1.56", "5EvbR2FjfmYfAkEtOkEnolnZbe6qOB")
    right_side = Aurora("192.168.1.78", "fAkeR2FjfmYfAkEtOkEnolnZtOkEn")
    left_side.effect = right_side.effect_random()

Add a new effect
~~~~~~~~~~~~~~~~

Presently, you must create your own raw dict that exactly matches the
structure found on the `API
documentation <http://forum.nanoleaf.me/docs/openapi#_e5qyi8m8u68>`__.
Methods of making this much easier are planned for future updates.

.. code:: python

    effect_data = {
        "command": "add",
        "animName": "My Random Animation",
        "animType": "random",
        "colorType": "HSB",
        "animData": None,
        "palette": [
            {
                "hue": 0,
                "saturation": 100,
                "brightness": 100
            },
            {
                "hue": 120,
                "saturation": 100,
                "brightness": 100
            },
            {
                "hue": 240,
                "saturation": 100,
                "brightness": 100
            }
        ],
        "brightnessRange": {
            "minValue": 25,
            "maxValue": 100
        },
        "transTime": {
            "minValue": 25,
            "maxValue": 100
        },
        "delayTime": {
            "minValue": 25,
            "maxValue": 100
        },
        "loop": True
    }

    my_aurora.effect_add_raw(effect_data)

Delete an effect
~~~~~~~~~~~~~~~~

.. code:: python

    my_aurora.effect_delete("My Random Animation")