Wifi Thermostat with Android and Arduino

I finally got around to pushing my thermostat app to the app store and putting the code on github. I must admit the whole project is overkill, I could have done it in a few hours with react-native (or just bought a thermostat like everyone else) but instead I created an entire framework to write it in python.

You can find everything here https://github.com/frmdstryr/thermostat .

I did a video earlier showing my Kivy version controlling the fireplace. This app is now written in enaml-native and starts up about 50% faster (but still pretty slow).

I want to add a few more features and do a mircopython port of the arduino code but will have to do that some other time.
If requested, I'll do a more detailed post on how to set it all up, but the code is out in the wild now so have fun!

Stay warm!

Comments

Kivy vs React-Native for building cross platform mobile apps

I've built three apps now using Kivy and one with React-Native, just wanted to share my thoughts on both. Just a warning, I am strongly biased towards python and this is all based on opinion and experience and is thus worth what you pay for it. I don't claim to be an expert in either of these, just have worked with each for several months. If something is incorrect I'd love to hear advice. Kivy Demo of one of the apps Pros: Nice to be able to run natively on the desktop WITHOUT a simulator Python is easy to work with Use (almost) any python library Very easy to create custom widgets Kivy properties and data binding just work. Way nicer than React's "state" / flux / redux whatever you want to call it (stupid?). Native interfaces (pyjnius) and (pyobjc) Runs and feels pretty smooth Cons: Default widget toolkit looks like Android 4.4. Requiring you use your own widgets or a theming kit like KivyMD if styling bothers you Creating dy

Control Systems in Python - Part 2 - Routh Hurwitz

In my last post Control Systems in Python Part 1 , i described how to setup and use Python for doing some basic plotting of transfer functions. One of the biggest benefits of using sympy vs numeric packages like matlab/numpy/scipy is the fact that you can use symbolic variables. This post includes a function for computing the Routh Hurwitz table (Note: It does not work for row's of zeros). Lets do my control systems design homework problem together :) (Warning: I have not verified if this answer is right so please correct me if it’s not!) The Problem The problem is DP 9.11 from Dorf & Bishop’s Modern Control Systems. ISBN 0136024580. Basically we have to design a controller to compensate for a system with a time delay. The controller is: And the system is: First we approximate the exponential term with a 2nd order polynomial using pade(0.4,2) such that: Thus the approximated system is: Using frequency response methods, design the controller so that th

Control Systems in Python - Part 1 - Bode and Step Response

I hate matlab with passion, yet sadly, nearly everyone uses it. I'm a fan of Python and open source stuff so here's a simple article on how to do some common control systems stuff in Python. First we need to make sure the environment is setup. Install IPython (or you can use any other python shell, but a unicode supported shell is preferred) Install python-control (numpy, scipy) Install sympy These should do if your on Ubuntu/debian: sudo apt - get install python - sympy python-numpy python-scipy python-matplotlib ipython Then you need to install python control, see How to download and install python-control Intro to using Sympy Open ipython and run the following: import sympy from sympy import * sympy.init_printing() s = Symbol('s') Now we can do things like define transfer functions using the symbolic variable s. We can expand the bottom using the .simplify() method and we can do something more complex like... which is really nice because it

Code LV

Search This Blog