CircuitPython vs MicroPython: Which One Should You Choose?

Table of Contents
Introduction
When diving into Python programming for microcontrollers, you'll quickly encounter two major platforms: MicroPython and CircuitPython. Both allow you to use Python to program microcontrollers instead of traditional languages like C or C++, but they have distinct differences that might make one more suitable for your specific project or learning style.
In this article, we'll compare these two Python implementations for microcontrollers, highlighting their strengths, weaknesses, and ideal use cases to help you decide which platform is right for your next project.
Origins and Background
MicroPython
MicroPython was created by Damien George and was initially funded through a Kickstarter campaign in 2013. It's an open-source implementation of Python 3 that's optimized to run on microcontrollers and in constrained environments. MicroPython was originally developed for the PyBoard but has since been ported to many other microcontroller platforms.
CircuitPython
CircuitPython is a fork of MicroPython that was developed by Adafruit Industries starting in 2017. Adafruit created CircuitPython to make hardware programming more accessible, with a focus on education and beginners. While it maintains compatibility with much of MicroPython's core functionality, CircuitPython has evolved to follow its own development path with different priorities.
Key Differences
Feature | MicroPython | CircuitPython |
---|---|---|
Philosophy | Lean, efficient implementation of Python 3 | Education-focused, beginner-friendly |
USB Detection | Requires additional setup | Shows up as a USB drive automatically |
File Structure | More flexible, similar to full Python | Simplified, uses code.py as main file |
Library Management | Manual library installation | Library bundles, drag-and-drop installation |
Community Focus | General purpose, many industries | Education, makers, hobbyists |
Documentation | Comprehensive but technical | Extensive tutorials and examples |
Hardware Support
MicroPython
MicroPython supports a wide range of hardware platforms including:
- PyBoard (the original MicroPython board)
- ESP32 and ESP8266
- STM32 microcontrollers
- Raspberry Pi Pico
- BBC micro:bit
- WiPy and other platforms
MicroPython can be compiled for almost any microcontroller with sufficient resources, making it highly versatile for professional and industrial applications.
CircuitPython
CircuitPython focuses primarily on Adafruit's own hardware, though support has expanded to include:
- Adafruit's Circuit Playground Express
- Adafruit Feather boards
- SAMD21 and SAMD51 based boards
- ESP32-S2 and ESP32-S3
- Raspberry Pi Pico
- Selected Arduino boards
CircuitPython tends to provide a more polished experience on its supported hardware, with pre-configured pin definitions and board-specific optimizations.
Libraries and Ecosystem
MicroPython Libraries
MicroPython includes a subset of the Python standard library, reimplemented for efficiency on microcontrollers. The ecosystem also includes:
- Low-level hardware access libraries
- Network and IoT communication libraries
- Various third-party modules across GitHub and other repositories
The MicroPython library ecosystem is extensive but somewhat fragmented, requiring more research to find the right libraries for specific hardware.
CircuitPython Libraries
CircuitPython's library ecosystem is more centralized and curated:
- Adafruit maintains over 300 CircuitPython libraries
- Libraries are bundled together for easy installation
- Consistent API design across libraries
- Extensive support for sensors, displays, and other components
The structured approach of CircuitPython's libraries makes it easier to get started, especially when using Adafruit hardware.
Development Experience
MicroPython Workflow
Developing with MicroPython typically involves:
- Writing code in your preferred editor or IDE
- Using tools like
ampy
,rshell
, or an IDE plugin to upload code - Using REPL (Read-Eval-Print Loop) for interactive development
- Debugging via print statements or REPL exploration
This workflow is more similar to traditional microcontroller development and provides more flexibility but requires more setup.
CircuitPython Workflow
CircuitPython offers a more streamlined approach:
- Connect your device to your computer
- Edit the
code.py
file directly on the device, which appears as a USB drive - Save changes and they run automatically
- View output on a serial console
This simplicity makes CircuitPython particularly appealing to beginners and educators, as it eliminates many common setup hurdles.
Ideal Use Cases
When to Choose MicroPython
MicroPython might be the better choice when:
- You need maximum performance or memory efficiency
- You're working with hardware not directly supported by CircuitPython
- Your project requires advanced networking capabilities
- You need more flexibility in file structure and imports
- You're developing for industrial or professional applications
When to Choose CircuitPython
CircuitPython excels in these situations:
- You're a beginner or working with beginners
- You're using Adafruit hardware
- You want a simplified development workflow
- Your project involves many sensors or components
- You value extensive documentation and examples
- You're using microcontrollers in educational settings
Conclusion: Making Your Choice
Both MicroPython and CircuitPython are excellent options for programming microcontrollers with Python, but they serve slightly different audiences and use cases:
Choose MicroPython if you value flexibility, wider hardware support, and are comfortable with a more traditional development workflow. It's particularly well-suited for professional developers and projects where performance and customization are priorities.
Choose CircuitPython if you prioritize ease of use, extensive documentation, and a beginner-friendly experience. It's ideal for educational settings, beginners, and projects using Adafruit hardware.
In many cases, the hardware you're using might make the decision for you. But if you have the flexibility to choose either platform, consider your experience level, project requirements, and desired workflow.
Remember that skills learned in one platform largely transfer to the other, so you aren't locked into your initial choice forever. Many developers even use both platforms, selecting the best tool for each specific project.
Comments (0)