So, you have somehow bumped into micropython, fallen in love with it in an instance, broken your piggy bank, and run off, head over heels, to order a pyboard. You have probably paid extra for the expedited shipping. Once the pyboard arrived, you became excited like a puppy with a bone. You played with the hardware, learnt how to access the accelerometer, switch, LEDs, and temperature sensor, and you successfully communicated with other devices via the I2C, SPI, USART, or CAN interfaces. You have plugged the board in a computer, and driven someone crazy by emulating a seemingly disoriented mouse on it. You have even tried to divide by zero, just to see if the chip would go up in flames (this was vicious, by the way), and noticed that the interpreter smartly prevented such things from happening. You have written your own python functions, even compiled them into frozen modules, and burnt the whole damn thing onto the microcontroller. Then you have toyed with the on-board assembler, because you hoped that you could gain some astronomical factors in speed. (But you couldn’t.)

And yet, after all this, you feel somewhat unsatisfied. You find that you want to access the periphery in a special way, or you need some fancy function that, when implemented in python itself, seems to consume too much RAM, and takes an eternity to execute, and assembly, with its limitations, is just far too awkward for it. Or perhaps, you are simply dead against making your code easily readable by writing everything in python, and you want to hide the magic, just for the heck of it. But you still want to retain the elegance of python.

If, after thorough introspection and soul-searching, you have discovered these latter symptoms in yourself, you have two choices: either you despair, scrap your idea, and move on, or you learn how the heavy lifting behind the micropython facade is done, and spin your own functions, classes, and methods in C. As it turns out, it is not that hard, once you get the hang of it. The sole trick is to get the hang of it. And this is, where this document intends to play a role.

On the following pages, I would like to show how new functionality can be added and exposed to the python interpreter. I will try to discuss all aspects of micropython in an approachable way. Each concept will be presented in an implementation, stripped to the bare minimum, that you can compile right away, and try yourself. (The code here has been tested against micropython v.1.11.) At the end of each chapter, I will list the discussed code in its entirety, and I also include a link the the source, so that copying and pasting does not involve copious amounts of work. Moreover, I include a small demonstration, so that we can actually see that our code works. The code, as well as the source of this document are also available under The simplest way of getting started is probably cloning the repository with

git clone

As for the source: all that you see here originates from a single jupyter notebook. That’s right, the documentation, the C source, the compilation, and the testing. You can find the notebook at And should you wonder, everything is under the MIT licence.

I start out with a very simple module and slowly build upon it. At the very end of the discussion, I will outline my version of a general-purpose math library, similar to numpy. In fact, it was when I was working on this math module that I realised that a decent programming guide to micropython is sorely missing, hence this document. Obviously, numpy is a gigantic library, and we are not going to implement all aspects of it. But we will be able to define efficiently stored arrays on which we can do vectorised computations, work with matrices, invert and contract them, fit polynomials to measurement data, and get the Fourier transform of an arbitrary sequence. I do hope that you find the agenda convincing enough!

One last comment: I believe, all examples in this document could be implemented with little effort in python itself, and I am definitely not advocating the inclusion of such trivial cases in the firmware. I chose these examples on two grounds: First, they are all simple, almost primitive, but for this very reason, they demonstrate a single idea without distraction. Second, having a piece of parallel python code is useful insofar as it tells us what to expect, and it also encourages us to implement the C version such that it results in pythonic functions.

Code blocks

You’ll encounter various kinds of code blocks in this document. These have various scopes, which are listed here:

  • if a code block begins with an exclamation mark, the content is meant to be executed on the command line.
  • if the code block looks like a piece of python code, it should be run in a python interpreter.
  • if the heading of the code block is %%micropython, then, well, you guessed it right, the content should be passed to the micropython interpreter of your port of choice.
  • other code segments can be C code, or a makefile. These should be easy to recognise, because both of these have a header with a link to the location of the file.