MicroPython VS Numba

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.

Around the same time, I discovered Numba and was fascinated by how easily it could bring huge performance improvements to Python code.

Simulations are, at least in my experience, numba’s [0] wheelhouse.

[0]: https://numba.pydata.org/

That's very cool. Numba introduces just-in-time compilation to Python via decorators and its sole reason for being is to turn everything it can into abstract syntax trees.

A super-fast backtesting engine built in NumPy and accelerated with Numba.

Regarding speed, I don't agree this is a good argument against Python. For example, it seems no one here has yet mentioned numba, a Python JIT compiler. With a simple decorator you can compile a function to machine code with speeds on par with C. Numba also allows you to easily write cuda kernels for GPU computation. I've never had to drop down to writing C or C++ to write fast and performant Python code that does computationally demanding tasks thanks to numba.

Just for reference,

* Nuitka[0] "is a Python compiler written in Python. It's fully compatible with Python 2.6, 2.7, 3.4, 3.5, 3.6, 3.7, 3.8, 3.9, 3.10, and 3.11."

* Pypy[1] "is a replacement for CPython" with builtin optimizations such as on the fly JIT compiles.

* Cython[2] "is an optimising static compiler for both the Python programming language and the extended Cython programming language... makes writing C extensions for Python as easy as Python itself."

* Numba[3] "is an open source JIT compiler that translates a subset of Python and NumPy code into fast machine code."

* Pyston[4] "is a performance-optimizing JIT for Python, and is drop-in compatible with ... CPython 3.8.12"

[0] https://github.com/Nuitka/Nuitka

[1] https://www.pypy.org/

[2] https://cython.org/

[3] https://numba.pydata.org/

[4] https://github.com/pyston/pyston

For the benefit of future readers: https://numba.pydata.org/

Taichi (similar to numba) is a python library that allows you to write high speed code within python. So your program consists of slow python that gets interpreted regularly, and fast python (fully type annotated and restricted to a subset of the language) that gets parallellized and jitted for CPU or GPU. And you can mix the two within the same source file.