Donald Norris MicroPython: A Comprehensive Guide

MicroPython is a lean and efficient implementation of the Python 3 programming language that includes a small subset of the Python standard library and is optimized to run on microcontrollers and in constrained environments. Donald Norris is well - known in the MicroPython community for his contributions and educational efforts. His work has helped many beginners and professionals alike to understand and utilize MicroPython effectively. In this blog, we will explore the fundamental concepts of Donald Norris MicroPython, how to use it, common practices, and best practices.

Table of Contents#

  1. Fundamental Concepts
  2. Usage Methods
  3. Common Practices
  4. Best Practices
  5. Conclusion
  6. References

1. Fundamental Concepts#

What is MicroPython?#

MicroPython is a version of Python designed to run on microcontrollers. It allows developers to write Python code that can interact directly with hardware components such as sensors, actuators, and displays. This is in contrast to traditional Python, which is typically run on larger computers.

Donald Norris's Contribution#

Donald Norris has created numerous tutorials, examples, and projects that showcase the power of MicroPython. His work often focuses on making MicroPython accessible to beginners by providing clear explanations and easy - to - follow code examples.

Key Features of MicroPython#

  • Low - level Hardware Access: MicroPython can directly control GPIO (General - Purpose Input/Output) pins, communicate with sensors via protocols like I2C and SPI, and control motors.
  • Interactive REPL: It comes with an interactive Read - Evaluate - Print - Loop (REPL) environment, which allows developers to test code snippets immediately.

Example of Low - level Hardware Access#

import machine
 
# Configure a GPIO pin as an output
led = machine.Pin(2, machine.Pin.OUT)
 
# Turn the LED on
led.on()

2. Usage Methods#

Setting up the Environment#

  1. Select a Microcontroller: Popular MicroPython - compatible microcontrollers include the ESP8266, ESP32, and Raspberry Pi Pico.
  2. Flash MicroPython: Download the appropriate MicroPython firmware for your microcontroller and use a tool like esptool (for ESP8266/ESP32) or Thonny (for Raspberry Pi Pico) to flash it onto the device.
  3. Connect to the REPL: Use a serial terminal emulator like PuTTY or the built - in REPL in Thonny to connect to the microcontroller and start writing code.

Writing and Running Code#

  1. Simple Scripts: You can write simple Python scripts and save them with a .py extension. For example, a script to blink an LED:
import machine
import time
 
led = machine.Pin(2, machine.Pin.OUT)
 
while True:
    led.on()
    time.sleep(1)
    led.off()
    time.sleep(1)
  1. Uploading Code: Use an IDE like Thonny or a tool like ampy (Adafruit MicroPython Tool) to upload your Python script to the microcontroller.

3. Common Practices#

Error Handling#

In MicroPython, just like in regular Python, it's important to handle errors properly. For example, when reading data from a sensor, the sensor might not respond correctly, leading to an error.

import machine
import time
 
try:
    i2c = machine.I2C(scl=machine.Pin(5), sda=machine.Pin(4))
    data = i2c.readfrom(0x50, 2)
    print(data)
except OSError as e:
    print('Error reading from sensor:', e)

Memory Management#

Microcontrollers have limited memory, so it's crucial to manage memory efficiently. Avoid creating large data structures or using unnecessary variables.

# Instead of creating a large list
# big_list = [i for i in range(1000)]
 
# Use a generator if possible
generator = (i for i in range(1000))

Modular Programming#

Break your code into smaller functions and modules. This makes the code more organized and easier to maintain.

# main.py
import led_control
 
led_control.blink_led(5)
 
 
# led_control.py
import machine
import time
 
def blink_led(times):
    led = machine.Pin(2, machine.Pin.OUT)
    for _ in range(times):
        led.on()
        time.sleep(1)
        led.off()
        time.sleep(1)

4. Best Practices#

Code Optimization#

  • Use Native Functions: MicroPython has native functions that are optimized for the microcontroller. For example, use machine.time_pulse_us() for measuring pulse widths instead of writing your own timing code.
  • Reduce Function Calls: Function calls in MicroPython can be relatively expensive. If a piece of code is called frequently, consider inlining it.

Documentation#

Document your code with comments and docstrings. This will help other developers (and your future self) understand what the code does.

def calculate_average(numbers):
    """
    Calculate the average of a list of numbers.
 
    Args:
        numbers (list): A list of numerical values.
 
    Returns:
        float: The average of the numbers in the list.
    """
    if not numbers:
        return 0
    return sum(numbers) / len(numbers)

Testing#

Test your code thoroughly. You can use the REPL to test individual functions and small code snippets. For more complex projects, consider using unit testing frameworks if available.

5. Conclusion#

Donald Norris's work has played a significant role in popularizing MicroPython and making it more accessible to a wider audience. By understanding the fundamental concepts, usage methods, common practices, and best practices of MicroPython, you can create powerful and efficient applications on microcontrollers. Whether you're a beginner or an experienced developer, MicroPython offers a great way to quickly prototype and build hardware - based projects.

6. References#

2025-10