MicroPython VS Cython

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.

The approach that I favour is to use Cython. The nice thing with this approach is that your code is still written as (almost) Python, but so long as you define all required types correctly it will automatically create the C extension for you. Early versions of Cython required using Cython specific typing (Python didn't have type hints when Cython was created), but it can now use Python's type hints.

and again, everything that was released after using an older version of cython.

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

Profile and optimize the hotspots with cython (or whatever the cool kids are using these days... It's been a while.)

JIT essentially means generating machine code for the language on the fly, either during loading of the interpreter (method JIT), or by profiling and optimizing hotspots (tracing JIT). The language itself can be statically or dynamically typed. You could also compile a dynamic language ahead of time, for example, cython.

Cython - - embed demo