MicroPython vs. CircuitPython for Raspberry Pi (with examples)

Ben
Ben
@benjislab

When it comes to programming microcontrollers and small computing devices like the Raspberry Pi, Python enthusiasts have two powerful options: MicroPython and CircuitPython. Both offer the simplicity and ease of Python, but they cater to different needs and preferences. This blog post dives into the nuances of MicroPython and CircuitPython, especially in the context of Raspberry Pi projects, providing examples to help you choose the best fit for your next project.

Introduction to MicroPython

MicroPython is a lean and efficient implementation of Python 3, designed to run on microcontrollers and in constrained environments. It brings the Python language to the world of microelectronics, making it accessible for programmers of all levels to dive into hardware projects. MicroPython aims to be as compatible with standard Python as possible, allowing for a seamless transition from desktop development to embedded systems.

Example: Blinking an LED on Raspberry Pi with MicroPython

import machine
import time

led = machine.Pin(18, machine.Pin.OUT)

while True:
    led.value(1)  
    time.sleep(1) 
    led.value(0)  
    time.sleep(1)

This simple example demonstrates how to control an LED using MicroPython, utilizing the machine module for interacting with hardware.

Introduction to CircuitPython

CircuitPython, a fork of MicroPython, is developed by Adafruit and is designed to simplify hardware programming, making it more accessible and educational. It's tailored for beginners and aims to make the learning curve as smooth as possible. CircuitPython emphasizes simplicity, with an easy-to-use API and a focus on getting projects up and running quickly. It's particularly well-suited for Adafruit's boards and accessories but can also be used on other microcontrollers and small computing devices like the Raspberry Pi.

Example: Reading a Sensor on Raspberry Pi with CircuitPython

import time
import board
import adafruit_dht

dhtSensor = adafruit_dht.DHT22(board.D4)

while True:
    try:
        temperature = dhtSensor.temperature
        humidity = dhtSensor.humidity
        print("Temp: {:.1f} C    Humidity: {}% ".format(temperature, humidity))
    except RuntimeError as e:
        print("Reading from DHT sensor failed:", e.args)

    time.sleep(2)

This example showcases the use of CircuitPython to read temperature and humidity data from a DHT22 sensor, highlighting the library's ease of use.

Key Differences

  • Target Audience: MicroPython is aimed at a broader audience, including hobbyists, educators, and professionals, while CircuitPython is specifically tailored for beginners and education, with a strong focus on Adafruit’s ecosystem.
  • Library Support: MicroPython supports a wide range of libraries and modules, making it versatile for various projects. CircuitPython, on the other hand, offers a curated selection of libraries optimized for ease of use and compatibility with Adafruit products.
  • Development Environment: MicroPython can be used with various development environments and tools, while CircuitPython encourages the use of the Mu Editor or any text editor, coupled with the simplicity of the REPL for interactive development.
  • Hardware Compatibility: MicroPython is designed to run on a wide range of hardware, including ESP8266, ESP32, and the Raspberry Pi series. CircuitPython, while also compatible with some of these devices, is primarily focused on Adafruit's line of microcontrollers.

Conclusion

Choosing between MicroPython and CircuitPython for your Raspberry Pi project depends on your specific needs, experience level, and project goals. MicroPython offers flexibility and a wide range of features for more complex projects, while CircuitPython provides an easy and accessible entry point for beginners, with a strong community and educational resources.

Whether you're building a simple sensor project or an intricate IoT device, both MicroPython and CircuitPython offer the powerful simplicity of Python to bring your ideas to life. Experiment with both and see which one aligns best with your project requirements and personal preferences.