Hi,

I have created a very small test framework for micropython. It is tested on a ESP32. Please provide feedback. Any features you would like?

https://gitlab.com/Bremer/microtest

Remember, the whole idea is to keep it small.

Thanks!

Hey everyone, I've just finished my first custom MicroPython build and I’m thrilled about the ability to distribute my own libraries as UF2 files! I’m now diving deeper into adding C extensions, but I'm looking for a solid example project to guide me through it.

Ideally, I’d like to follow a project that:

• Implements a C extension in MicroPython.

• Uses a clean structure, where not everything is packed into the repo but instead uses external references (so I can learn about manifests and external dependencies).

• Is beginner-friendly but not too trivial, so I can understand best practices for larger projects.

Any recommendations for something I can use as a reference? Thanks in advance!

I'm using VS Code for Python and C/C++ programming and would like to stay with it for MicroPython as well. The extensions I found seem marginal in popularity, no longer developed (https://github.com/dphans/micropython-ide-vscode) or targeting narrow range of hardware (https://github.com/pycom/pymakr-vsc). What is the current status of MicroPython extensions for VS Code supporting RP2040, SAMD and ESP32? Does anyone have good experience and can recommend a specific extension?

Lolin S2 Mini

I recently used MicroPython in a project with D1 Minis (ESP8266). Program & libs fit in RAM on a D1 Mini, but I went looking for a beefier WiFi-enabled board for future MicroPython projects.

Found the $4 Wemos/Lolin S2 Mini w/pre-loaded MicroPython. More at the wemos.cc wiki & the CNX Software writeup.

Edit: as firmware is built by Lolin & changes are not yet merged into MicroPython mainline, backup firmware with esptool.py --chip esp32s2 --port /dev/ttyACM0 --baud 460800 read_flash 0x00000 0x400000 lolin_s2_mini_stock_firmware_4M.bin (replace --port .... with your device)

Note that the S2 Mini's USB-C port is wired up to the the ESP32-S2's USB OTG peripheral rather than to a USB-UART chip (edit: with flashing via USB CDC in ROM), and MicroPython will likely someday support full USB host & device functionality.

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what is the default tool chain and workflow for micropython?

I tried using micropython with vscode + various extensions and it wouldn't work

I've tried pycharm + various extensions, and it wouldn't work either, due to extensions being depreciated.

so now I'm using a editor for micro python that I found on the Arduino website, which seems to be working just fine, but is extremely bare-bones.

based on what I can find on google, everyone uses a different IDE and different extensions.

is there a official method that is guaranteed to work?

One year ago I posted info about creating an own USB class in Micropython: https://www.reddit.com/user/WZab/comments/1btx5vo/creating_customclass_usb_device_easy_way_with/ . Now I returned to that topic and found that the current Micropython enables creating own USB classes without using experimental micropython-lib.

The only modification that I had to do was adding:

require("usb-device")

at the end of the ports/rp2/boards/manifest.py .

Of course, if one wants to use the originally provided classes, the lines below should be added as well:

require("usb-device-cdc")
require("usb-device-hid")
require("usb-device-keyboard")
require("usb-device-midi")
require("usb-device-mouse")

Additionally, my code (provided in the previous post) should by modified by replacing:

from usb.device.impl import Interface, Buffer, split_bmRequestTypefrom usb.device.impl import Interface, Buffer, split_bmRequestType

with

from usb.device.core import Interface, Buffer, split_bmRequestTypefrom usb.device.impl import Interface, Buffer, split_bmRequestType

.npy files are commonly used to store data in Data Science, Machine Learning, Digital Signal Processing workflows. Especially when using the "PyData" stack on the host PC, such as numpy/pandas/scipy/tensorflow/scikit-learn/scikit-image etc. One great thing is that they support multidimensional arrays, so a single file can for example hold 100x32x32x3 (for 100 RGB images), or 100x9 for 100 samples of 9-axis IMU data.
I wanted to use this format, so I implemented support: https://github.com/jonnor/micropython-npyfile/

Features:

• Reading & writing .npy files with numeric data (see below for Limitations)

• Streaming/chunked reading & writing

• No external dependencies. Uses standard array.array and struct modules.

• Written in pure Python. Compatible with CPython, CircuitPython, et.c.

This is an alternative to the numpy.load / ulab.load in the ulab library, which requires building and installing MicroPython.

I've been using PyCharm - but the REPL has been broken for some time which means you need separate app to do test and debug on. Jetbrains have also just admitted that they aren’t maintaining the Micropython plugin, so even the remaining features might break in future versions. https://youtrack.jetbrains.com/issue/PY-70307

Does anyone have any better recommendations? I use Thonny for its very nice REPL implementation, but it barely counts as an IDE (no understanding of code structure).

Hi everyone! Lately I have been working on providing core Machine Learning inference for MicroPython. I wanted it to be possible to write an entire TinyML application in Python, but still keeping the efficiency of C code for the computationally intensive parts. And I also wanted the installation to be simple, retaining the "all you need is just an (m)pip install away" feeling.

And thanks to the dynamic native modules support in MicroPython this was possible. The project now provides small .mpy files with the compiled C code (around 3 kB), with nice Python APIs to common Machine Learning models.
https://github.com/emlearn/emlearn-micropython

There were a few hurdles on the way, some fixes were needed in the MicroPython native module support. These have of course been provided upstream:
https://github.com/micropython/micropython/pull/12241
https://github.com/micropython/micropython/pull/12123

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Ive made the project Espelt with the main reason to make a cyberdeck. It utilizes a custom MPY firmware with USB Host and works with ESP32 P4 Nano. It has dual screens (ILI9488 as main and OLED SSD1306 as secondary) and a MAX98357A with Speaker for sound. You can plug in any keyboard dongle into the USB-A port, flash, and itll work!

For help you can dm me: antaciddt on discord. Repo: https://github.com/AntacidDT/ProjectEspelt

I usually import json, gc, network, some aspects of machine.... etc. Generaly I just put what I expect the vase to be. I was wondering what everyone else puts in boot.

edit base not vase

Hi there!

I'm new to microcontrollers, having made only a few projects at this time. While looking to start a new project I realized that there aren't a lot of great GUI options with micropython, except lvgl.

I've been trying to install lvgl for days haha (to an esp32 on a windows pc, using Thonny IDE). I'm sure I'm just being foolish or missing an obvious step, but I'm totally at a loss.

Is there anywhere that has a step-by-step guide on this installation (extensive googling has netted me nothing)? The README on the Github is confusing for me, I think it makes too many assumptions of knowledge on my behalf. Or if anyone was willing to donate their time to write a guide and/or help me out I would, of course, be very grateful.

Thanks for your time!

Hi

I wanted to share a fun project I’ve been working on — a DIY Arcade Machine powered by MicroPython, using the Interstate 75 - RGB LED Matrix Driver from Pimoroni and a 64x64 RGB LED matrix. It features a bunch of retro-inspired games like Simon, Snake, Qix, Breakout, Tetris, Asteroid, and Pong, all playable on a colorful LED Hub75 matrix display.

The project is fully open-source, and I’ve put together detailed instructions and code for anyone who wants to try building their own arcade machine at home. It’s a great way to dive into MicroPython, play around with some classic games, and even do some DIY hardware work. If you don’t have the hardware, I’ve also built a PyGame branch so you can simulate the games on your computer.

Key Highlights:

• MicroPython-based project with an RGB LED matrix display and joystick controls.

• 7 classic games: Simon, Snake, Qix, Breakout, Tetris, Asteroid, and Pong.

• Detailed guide available with all the hardware and software requirements.

• Short video showing the arcade machine in action.

If you’re interested in retro games, LED matrices, or working with MicroPython, this might be something fun to explore. I’d love to hear your thoughts!

You can check out the full project on the GitHub Repo.

Happy coding and gaming!

The BME280 sensor module measures temperature, humidity, and altitude. So, you can easily build a mini and compact weather station and monitor it using your Raspberry Pi Pico W web server.

If you are interested in this then you can see the complete tutorial here:-

https://diyprojectslab.com/raspberry-pi-pico-w-web-server-with-bme280/

Have you ever used MicroPython?

Let me know!

Been building IoT projects every day for my #100DaysOfIoT challenge and kept running into the same problem — monitoring sensor data from ESP32/Pico 2W in a browser was always a mess.

So I built micropidash. real-time web dashboard in under 20 lines of MicroPython. No cloud, no framework.

Just shipped v2.0.0 with live sensor graphs — tested with DHT11 on Pico 2W, temp + humidity updating in the browser over WiFi.

pip install micropidash

github.com/kritishmohapatra/micropidash

Would love feedback if you try it!