Python Asyncio On Raspberry Pi

Last Updated on February 19, 2024

Python developers on Raspberry Pi can use asynchronous programming via asyncio.

MicroPython is the dominant version of Python for Raspberry Pi and it supports the async/await language syntax and a simplified version of the asyncio module (formally called uasyncio).

This allows coroutines and cooperative multitasking to be used directly in MicroPython for Raspberry Pi projects.

In this tutorial, you will discover asyncio with MicroPython for Raspberry Pi.

Let’s get started.

Table of Contents

Python Asyncio on Raspberry Pi

Raspberry Pi is an extremely popular platform for DIY electronics projects.

Perhaps the most popular programming language for developing programs to run on the Raspberry Pi platform.

Asynchronous programming via asyncio with coroutines and the asyncio module in the standard library offer benefits when developing Python programs for Raspberry Pi projects.

In this section, we will take a moment to review the Raspberry Pi platform, the use of Python on Raspberry Pi, and the benefits of asyncio.

What is Raspberry Pi

The Raspberry Pi is a versatile single-board computer that has transformed the world of DIY electronics and education.

Initially designed to promote computer science learning, it has gained immense popularity due to its affordability, compact size, and adaptability.

The Raspberry Pi project originally leaned toward the promotion of teaching basic computer science in schools. The original model became more popular than anticipated, selling outside its target market for uses such as robotics. It is widely used in many areas, such as for weather monitoring, because of its low cost, modularity, and open design. It is typically used by computer and electronic hobbyists, due to its adoption of the HDMI and USB standards.
— Raspberry Pi, Wikipedia.

Its primary use cases span a wide spectrum, including but not limited to:

Education: One of its core purposes was to introduce students to programming, computing, and electronics. It has become a staple in classrooms and workshops, teaching basic coding, hardware interfacing, and robotics.
DIY Projects and Prototyping: Its low cost and diverse I/O options make it perfect for enthusiasts and hobbyists to build various projects like media centers, game consoles, home automation systems, weather stations, and more.
IoT (Internet of Things): Due to its small form factor and low power consumption, the Raspberry Pi is extensively used in IoT projects for managing and collecting data from sensors, controlling devices, and running small-scale servers.
Embedded Systems: It’s also employed in creating embedded systems for businesses and industries, such as digital displays, smart vending machines, and industrial automation.

The Pi’s immense popularity is largely driven by its open-source nature, which fosters a vast community of developers and enthusiasts.

Its constant evolution through various iterations with upgraded features and improved capabilities has solidified its place in the tech world as an accessible, yet powerful, computing platform.

Python On Raspberry Pi

Python’s association with the Raspberry Pi is significant due to its ease of use, versatility, and strong community support.

As such, it is the main programming language for many users exploring the Raspberry Pi ecosystem.

Python’s popularity on the Pi can be attributed to several factors:

Simplicity and Readability: Python’s straightforward syntax and readability make it an excellent choice for beginners and seasoned developers alike. This simplicity aligns well with the Raspberry Pi’s educational and hobbyist-focused objectives.
Extensive Libraries: Python boasts a vast collection of libraries and modules, covering a wide array of functionalities. These libraries simplify development tasks, enabling users to leverage existing code to create various projects seamlessly.
Supportive Community: Python enjoys a robust and active community. On the Raspberry Pi, this community actively shares projects, tutorials, and troubleshooting tips, fostering a collaborative environment for users of all skill levels.
Educational Emphasis: Python is extensively used in educational settings, and its integration with the Raspberry Pi furthers this purpose. It facilitates a smooth learning curve for students and educators, encouraging exploration and experimentation.
IoT and Embedded Applications: Python’s flexibility allows it to be applied across different domains, including IoT and embedded systems. Its support for interacting with hardware components aligns well with the Raspberry Pi’s capabilities in these areas.

Benefit of Asyncio on Raspberry Pi

Python’s asyncio on the Raspberry Pi enables efficient and concurrent asynchronous programming, allowing developers to create responsive and scalable applications. Here’s a breakdown of its role:

Efficient I/O Handling: Raspberry Pi devices often interact with various peripherals and sensors. asyncio simplifies handling these I/O operations by providing an asynchronous interface. This capability is especially valuable in scenarios where multiple I/O tasks need simultaneous handling without blocking the main program execution.
Resource-Efficient Concurrency: asyncio facilitates concurrent execution of multiple tasks within a single-threaded event loop. This approach is beneficial on resource-constrained devices like the Raspberry Pi, as it minimizes overhead and maximizes system resource utilization.
Event-Driven Paradigm: Many applications on the Raspberry Pi involve event-driven interactions, such as handling sensor inputs or responding to external events. asyncio’s event loop model aligns well with these scenarios, enabling responsive applications by efficiently managing events and callbacks.
Web Server and IoT Applications: asyncio supports web server implementations and IoT applications, allowing developers to create responsive web services or manage numerous concurrent connections efficiently. This capability is particularly useful when building IoT devices or handling network-heavy tasks on the Raspberry Pi.

Next, let’s take a closer look at Python on Raspberry Pi.

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MicroPython

Raspberry Pi does not run regular Python, instead simplified versions of Python are preferred.

Dominant among them is MicroPython.

MicroPython is a software implementation of a programming language largely compatible with Python 3, written in C, that is optimized to run on a microcontroller.
— MicroPython, Wikipedia.

MicroPython is a lean and efficient implementation of Python 3, specifically designed for microcontrollers and embedded systems.

It brings the simplicity and ease of use of Python to constrained devices, offering a reduced memory footprint while retaining much of Python’s functionality.

MicroPython is a full Python compiler and runtime that runs on the bare-metal. […] MicroPython strives to be as compatible as possible with normal Python (known as CPython) so that if you know Python you already know MicroPython.
— MicroPython Homepage

MicroPython has some specific differences from regular Python (CPython), including:

Platform Adaptability: MicroPython is tailored for microcontrollers and IoT devices with limited resources, making it suitable for low-power and resource-constrained hardware. It’s optimized to run on microcontrollers with relatively small amounts of RAM and Flash memory.
Interactive REPL: Like standard Python, MicroPython supports an interactive REPL (Read-Eval-Print Loop), allowing developers to execute Python code directly on the device. This feature is beneficial for rapid prototyping and debugging.
Small Memory Footprint: MicroPython is designed to operate within the constraints of embedded systems. It optimizes memory usage and offers a subset of Python’s features to fit within the limited resources available on microcontrollers.
Hardware Interfacing: One of the core strengths of MicroPython is its ability to interface with hardware components such as sensors, actuators, and other peripherals commonly found in embedded systems.
Cross-Platform Support: MicroPython can run on various microcontroller architectures, making it versatile and adaptable to a wide range of embedded devices.
Extensible Architecture: It allows developers to extend the core functionality by writing MicroPython modules in C or assembly language, enabling customizations and integration with device-specific features.

You can learn more about MicroPython here:

Importantly, MicroPython supports concurrency, including threads and interrupts, although the documentation recommends using cooperative multitasking via asyncio for concurrency.

In most cases the best approach is known as cooperative multi-tasking and the Python implementation is a library called asyncio.
— Concurrency, MicroPython Wiki

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Asyncio With MicroPython (Formally Uasyncio)

MicroPython supports the async/await syntax and a version of the asyncio module.

MicroPython implements the entire Python 3.4 syntax …, and additionally async/await keywords from Python 3.5 […] Select ports have support for _thread module (multithreading), socket and ssl for networking, and asyncio.
— MicroPython GitHub Project.

This allows Python asynchronous programming or asyncio-first Python programs to be developed to drive Raspberry Pi projects.

You can see the full documentation for the asyncio module in MicroPython here:

asyncio — asynchronous I/O scheduler

Previously, the asyncio module in MicroPython was called “uasyncio”.

In fact, most ports of Python standard library modules to MicroPython had a “u” prefix.

This prefix was removed from the “asyncio” module (and many other modules) in MicroPython version 1.21.0.

The renaming of built-in modules to remove the u-prefix — for example utime becomes time, uasyncio becomes asyncio — is done to improve compatibility with CPython and eliminate confusion about whether to import the u-version or the non-u-version of the name.
— MicroPython v1.21.0 Release Notes

You can see the older uasyncio API documentation (e.g. MicroPython version 1.20) here:

uasyncio — asynchronous I/O scheduler

Peter Hinch provides an outstanding resources for asyncio with MicroPython in his micropython-async project:

Asynchronous programming in MicroPython

CPython supports asynchronous programming via the asyncio library. MicroPython provides uasyncio which is a subset of this, optimised for small code size and high performance on bare metal targets. This repository provides documentation, tutorial material and code to aid in its effective use.
— micropython-async GitHub Project

Specifically, the latest version of his guide (V3) are available from here:

Guide to asyncio

MicroPython’s asyncio is pre-installed on all platforms except severely constrained ones such as the 1MB ESP8266. It supports CPython 3.8 syntax and aims to be a compatible subset of asyncio. The current version is 3.0.0.
— Guide to asyncio

Among his resources include a tutorial on how to get started and use asyncio with MicroPython for Raspberry Pi project:

MicroPython asyncio: a tutorial

This tutorial is intended for users having varying levels of experience with asyncio and includes a section for complete beginners. It is based on the current version of asyncio, V3.0.0. Most code samples are complete scripts which can be cut and pasted at the REPL.
— MicroPython asyncio: a tutorial

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Takeaways

You now know about asyncio with MicroPython for Raspberry Pi.

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Python Asyncio On Raspberry Pi