Writing code that runs in the terminal or in your web browser is good fun. Writing code that affects the real world, however, can be satisfying on a whole other level. Writing this sort of code is called embedded development, and Python is making it more accessible than ever!
In this tutorial, you’ll learn:
- What embedded development is and why you would use Python to do it
- What your hardware and software options are for running Python on an embedded system
- When Python is a good fit for an embedded system and when it’s not
- How to write a basic game on the BBC micro:bit with MicroPython
This tutorial contains code snippets that allow you to build a simple game on the BBC micro:bit. To access the full code and get a sneak preview on what you’ll be building, click the link below:
Get Sample Code: Click here to get the sample code you’ll use to learn about embedded development with Python in this tutorial.
What Is Embedded Development?
Embedded development is writing code for any device that isn’t a general-purpose computer. This definition is a little bit ambiguous, so some examples might help:
- General-purpose computers include laptops, desktop PCs, smartphones, and so on.
- Embedded systems include washing machines, digital machines, robots, and so on.
As a general rule of thumb, if you wouldn’t call something a computer, but it still has code running on it, then it’s probably an embedded system. The name comes from the idea of embedding a computer into a physical system to perform some task.
Embedded systems tend to be designed to do a single task, which is why we refer to regular computers as “general purpose”: they are designed to do more than one task.
In the same way that you need a computer to run regular code, to run embedded code, you need some kind of hardware. These pieces of hardware are usually referred to as development boards, and this tutorial will introduce you to a few designed to run Python.
Python for Embedded Development
One of the best things about learning Python is that it’s applicable in so many places. You can write code that runs anywhere, even on embedded systems. In this section, you’ll learn about the trade-offs that come with using Python for your embedded project and some things to be aware of when starting out.
Benefits of Using Python
The core benefit that Python brings when building an embedded system is development speed. Python has libraries available for most tasks, and this still mostly holds true for its embedded implementations. You can focus on building your system since many of the problems you’d encounter have been solved already.
Since Python is higher level than other common embedded languages, the code you’ll write will be more concise. This helps development speed, meaning you’ll write code faster, but it also helps keep your code understandable.
Python is memory managed. C++, a common choice for embedded development, is not. In C++, you are responsible for freeing up memory when you’re done with it, something that is very easy to forget, leading to your program running out of memory. Python does this for you.
Disadvantages of Using Python
While Python’s memory management is a big help, it does incur a minor speed and memory cost. The MicroPython docs have a good discussion on memory issues.
Another thing to consider is that the Python interpreter itself takes up space. With a compiled language, the size of your program depends just on your program, but Python programs need the interpreter that runs them. The Python interpreter also takes up RAM. On the micro:bit, you can’t write Bluetooth code with Python since there’s not enough room for Python and Bluetooth at the same time.
Since Python is interpreted, it can never be quite as fast as a compiled language. An interpreted language needs to decode each instruction before running it, but a compiled language can just run. In practice, though, this rarely matters as Python programs still run fast enough for most use cases.
Things to Watch Out for When New to Embedded Development
Modern computers have lots of memory to work with. When you’re programming them, you don’t have to worry too much about the size of lists you create or loading a whole file at once. Embedded systems, however, have limited memory. You have to be careful when writing your programs not to have too many things in memory at once.
Similarly, processor speeds on embedded systems are much slower than on desktop computers. The processor speed determines how quickly your code gets executed, so running a program on an embedded computer will take longer than running it on a desktop computer. It’s more important to think about the efficiency of embedded code—you don’t want it to take forever to run!
Perhaps the biggest change when programming embedded systems is power requirements. Laptops, phones and desktop computers either plug into the wall or have large batteries. Embedded systems often have tiny batteries and have to last for a really long time, sometimes even years. Every line of code that you run costs a little bit of battery life, and it all adds up.
Read the full article at https://realpython.com/embedded-python/ »
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