MicroPython VS PyO3

Just putting my hand up to say that MicroPython is awesome (and runs on the RP2040). https://micropython.org

Gah, I just ordered one on impulse [1]. I've wanted to build out a WiFi PDA for quite some time now and I like this hardware.

I'm quite liking the idea of running tulip MicroPython [2] on it, or going back to pure MicroPython [3] and writing some drivers. Apparently something like ampy can be used to upload/download Python files [4].

Threads could be quite exciting for running multiple programs at once [5], although I have no idea what it means for two programs to fight over GPIO! It does seem as though MicroPython can only utilise a single core [6].

[1] https://www.lilygo.cc/products/t-deck?variant=43087936487605

[2] https://github.com/bwhitman/tulipcc/tree/main/tulip/tdeck

[3] https://docs.micropython.org/en/latest/esp32/tutorial/intro....

[4] https://www.digikey.co.uk/en/maker/projects/micropython-basi...

[5] https://docs.micropython.org/en/latest/library/_thread.html

[6] https://github.com/micropython/micropython/issues/8197

If you really want to engage in the travesty that is shoehorning a high level scripting language into an environment that has 512 bytes of RAM and less clock cycles than an electric toothbrush, there is micropython.

There is some work to implement a common CAN interface in micropython but it's some way off yet: https://github.com/micropython/micropython/pull/13149

https://github.com/raspberrypi/pico-sdk/ links to a PDF about connecting to the interwebs with a pi pico.

micropython/micropython//ports/rp2/boards/RPI_PICO_W: https://github.com/micropython/micropython/tree/master/ports...

raspberrypi/pico-sdk /lib: btstack, cyw43-driver, lwip, mbedtls, tinyusb https://github.com/raspberrypi/pico-sdk/tree/master/lib

raspberrypi/pico-examples//pico_w/wifi/access_point/picow_access_point.c:

https://github.com/raspberrypi/pico-examples/blob/master/pic...

There's an iperf opkg pkg, or is it just netperf (which works with fluent)?

raspberrypi/pico-examples//pico_w/wifi/iperf/picow_iperf.c:

Needed for hobby project, maintained by very small team. Haven't decided on specific microcontroller. Needed for general bit-banging, speed and code size are not priorities.

So far have considered MicroPython [0] [1] and Lua [2] [3], but open for suggestions for others.

What are experiences?

[0] https://micropython.org/

Python is also a general-purpose programming language. It's typically used on desktop / laptop computers. But Micropython is a variant that can be used to program embedded devices.

Integrating Rust into Python, Edward Wright, 2021-04-12 Examples for making rustpython run actual python code Calling Rust from Python using PyO3 Writing Python inside your Rust code — Part 1, 2020-04-17 RustPython, RustPython Rust for Python developers: Using Rust to optimize your Python code PyO3 (Rust bindings for Python) Musing About Pythonic Design Patterns In Rust, Teddy Rendahl, 2023-07-14

This story unfolds as a captivating journey where the agile Flounder, representing the Python programming language, navigates the vast seas of coding under the wise guidance of Sebastian, symbolizing Rust. Central to their adventure are three powerful tridents: cargo, PyO3, and maturin.

I would not recommend FFI + ctypes. Maintaining the bindings is tedious and error-prone. Also, Rust FFI/unsafe can be tricky even for experienced Rust devs.

Instead PyO3 [1] lets you "write a native Python module in Rust", and it works great. A much better choice IMO.

[1] https://github.com/PyO3/pyo3

Same w/ Rust and Python, this is really neat because now each thread could have a GIL without doing exactly what you said. The pyO3 commit to allow subinterpreters was merged 21 days ago, so this might "just work" today: https://github.com/PyO3/pyo3/pull/3446

I expected someone to write a rust-based scripting language which tightly integrated with rust itself.

In reality, it seems like the python developers and toolchain are embracing rust enough to reduce the benefits to a new alternative.

https://github.com/PyO3/pyo3

Hey HN! I am one of the people working on Bytewax. Bytewax came out of our experience working with ML infrastructure at GitHub. We wanted to use Python because we could move fast, the team was very fluent in it, and the rest of our tooling was Python-native already. We didn't want to introduce JVM-based solutions into our stack because of the lack of experience and the friction we had trying to get Python-centric tooling working with existing solutions like Flink.

In our research, we found Timely Dataflow (https://timelydataflow.github.io/timely-dataflow/, https://news.ycombinator.com/item?id=24837031) and the Naiad project (https://www.microsoft.com/en-us/research/project/naiad/) as well as PyO3 (https://github.com/PyO3/pyo3) and we thought we found a match made in heaven :). Bytewax leverages both of these projects and builds on them to provide a clean API (at least we think so) and table stakes features like connectors, state recovery, and cloud-native scaling. It has been really cool to learn about the dataflow computation model, Rust, and how to wrangle the GIL with Rust and Python :P.

Would love to get your feedback :).

`pip install bytewax` to get started. We have a page of guides (https://www.bytewax.io/guides) with ready-to-run examples.

You can practice your Rust skills by writing performant and/or gluey extensions for higher-level language such as NodeJS (checkout napi-rs) and Python or complementing JS in the browser if you target Webassembly.

For instance, checkout Llama-node https://github.com/Atome-FE/llama-node for an involved Rust-based NodeJS extension. Python has PyO3, a Rust-Python extension toolset: https://github.com/PyO3/pyo3.

They can help you leverage your Rust for writing cool new stuff.