1. 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. It also contains an optional fast_io variant of uasyncio.

The fast_io variant

This comprises two parts.

1. The fast_io version of uasyncio is a "drop in" replacement for the official version providing bug fixes, additional functionality and, in certain respects, higher performance.
2. An optional extension module enabling the fast_io version to run with very low power draw.

Resources for users of all versions

• A tutorial An introductory tutorial on asynchronous programming and the use of the uasyncio library.
• Asynchronous device drivers. A module providing drivers for devices such as switches and pushbuttons.
• Synchronisation primitives. Provides commonly used synchronisation primitives plus an API for task cancellation and monitoring.
• A driver for an IR remote control This is intended as an example of an asynchronous device driver. It decodes signals received from infra red remote controls using the popular NEC protocol.
• A driver for the HTU21D temperature and humidity sensor. This is intended to be portable across platforms and is another example of an asynchronous device driver.
• A driver for character LCD displays. A simple asynchronous interface to displays based on the Hitachi HD44780 chip.
• A driver for GPS modules Runs a background task to read and decode NMEA sentences, providing constantly updated position, course, altitude and time/date information.
• Communication using I2C slave mode. Enables a Pyboard to to communicate with another MicroPython device using stream I/O. The Pyboard achieves bidirectional communication with targets such as an ESP8266.
• Communication between devices Enables MicroPython boards to communicate without using a UART. This is hardware agnostic but slower than the I2C version.
• Under the hood A guide to help understand the uasyncio code. For scheduler geeks and those wishing to modify uasyncio.

2. Version and installation of uasyncio

Paul Sokolovsky (uasyncio author) has released uasyncio V2.2.1. This version is on PyPi and requires his Pycopy fork of MicroPython firmware. His uasyncio code may also be found in his fork of micropython-lib.

I support only the official build of MicroPython. The library code guaranteed to work with this build is in micropython-lib. Most of the resources in here should work with Paul's forks (most work with CPython).

Most documentation and code in this repository assumes the current official version of uasyncio. This is V2.0 from micropython-lib. If release build of MicroPython V1.10 or later is used, V2.0 is incorporated and no installation is required. Some examples illustrate the features of the fast_io fork and therefore require this version.

See tutorial for installation instructions where a realease build is not used.

3. uasyncio development state

These notes are intended for users familiar with asyncio under CPython.

The MicroPython language is based on CPython 3.4. The uasyncio library supports a subset of the CPython 3.4 asyncio library with some V3.5 extensions. In addition there are non-standard extensions to optimise services such as millisecond level timing and task cancellation. Its design focus is on high performance and scheduling is performed without RAM allocation.

The uasyncio library supports the following Python 3.5 features:

• async def and await syntax.
• Awaitable classes (using __iter__ rather than __await__).
• Asynchronous context managers.
• Asynchronous iterators.
• Event loop methods call_soon and call_later.
• sleep(seconds).

It supports millisecond level timing with the following:

• Event loop method call_later_ms
• uasyncio sleep_ms(time)

uasyncio V2 supports coroutine timeouts and cancellation.

• wait_for(coro, t_secs) runs coro with a timeout.
• cancel(coro) tags coro for cancellation when it is next scheduled.

Classes Task and Future are not supported.

3.1 Asynchronous I/O

Asynchronous I/O (StreamReader and StreamWriter classes) support devices with streaming drivers, such as UARTs and sockets. It is now possible to write streaming device drivers in Python.

3.2 Time values

For timing asyncio uses floating point values of seconds. The uasyncio.sleep method accepts floats (including sub-second values) or integers. Note that in MicroPython the use of floats implies RAM allocation which incurs a performance penalty. The design of uasyncio enables allocation-free scheduling. In applications where performance is an issue, integers should be used and the millisecond level functions (with integer arguments) employed where necessary.

The loop.time method returns an integer number of milliseconds whereas CPython returns a floating point number of seconds. call_at follows the same convention.

4. The "fast_io" version.

Official uasyncio suffers from high levels of latency when scheduling I/O in typical applications. It also has an issue which can cause bidirectional devices such as UART's to block. The fast_io version fixes the bug. It also provides a facility for reducing I/O latency which can substantially improve the performance of stream I/O drivers. It provides other features aimed at providing greater control over scheduling behaviour.

To take advantage of the reduced latency device drivers should be written to employ stream I/O. To operate at low latency they are simply run under the fast_io version. The tutorial has details of how to write streaming drivers.

The current fast_io version 0.24 fixes an issue with task cancellation and timeouts. In uasyncio version 2.0, where a coroutine is waiting on a sleep() or on I/O, a timeout or cancellation is deferred until the coroutine is next scheduled. This introduces uncertainty into when the coroutine is stopped. This issue is also addressed in Paul Sokolovsky's fork.

4.1 A Pyboard-only low power module

This is documented here. In essence a Python file is placed on the device which configures the fast_io version of uasyncio to reduce power consumption at times when it is not busy. This provides a means of using uasyncio in battery powered projects.

5. The asyn.py library

This library (docs) provides 'micro' implementations of the asyncio synchronisation primitives. CPython docs

It also supports a Barrier class to facilitate coroutine synchronisation.

Coroutine cancellation is performed in an efficient manner in uasyncio. The asyn library uses this, further enabling the cancelling coro to pause until cancellation is complete. It also provides a means of checking the 'running' status of individual coroutines.

A lightweight implementation of asyncio.gather is provided.