libffi VS Cython

Ok, there is a missing dependency, libffi6, which cannot be installed, because it isn't at repos. You can either install it via downloading from other repos (there is a chance in the debian repo), or via compiling on your own (you can start with paying a visit to official site: https://sourceware.org/libffi/). Either way, move carefully and never forget when a dependency is missing, it may be a start of a "missing dependencies hell". And please, be caution, because you can break your system quite easily.

I've been working in implementing libffi into Euphoria so we can call Raylib functions directly. Previously, Euphoria did not support passing structures by value and only occasionally could we get away with "faking" it by passing int type values directly (but not float types). Raylib is the first library I've run into that makes heavy use of passing structures by value, so it's been an interesting challenge. My original proof of concept worked well with libffi built as a shared library, so now I'm working on building libffi directly into the backend of Euphoria. Then we'll be off and running with full support for Raylib!

I did some more looking around, and I think you should take a look into libffi. It has most of the dirty work done for you, and you can hook it up with your language.

The last line of output is from configure and appears to be during building of libffi recipe - apparently executing the generate-darwin-source-and-headers.py from libffi repository

ok... I did my python 3.9 upgrade on my Rpi3b+ ... here's what I learned: 1) If you're running Debian Buster, you really probably want to upgrade to Bullseye first https://www.tomshardware.com/how-to/upgrade-raspberry-pi-os-to-bullseye-from-buster If you stay on buster, then homeassistant won't start until you build libffi-3.3 as below: 2021-12-29 16:51:14 ERROR (MainThread) [homeassistant.auth.providers] Unable to load auth provider homeassistant: libffi.so.7: cannot open shared object file: No such file or directory https://community.home-assistant.io/t/python-install-on-raspberry-pi-os/241558/12 wget "https://github.com/libffi/libffi/releases/download/v3.3/libffi-3.3.tar.gz" tar zxf libffi-3.3.tar.gz cd libffi-3.3 ./configure sudo make install sudo ldconfig Other than that, it was pretty straightforward. Do be aware that after you redeploy home assistant, a LOT of stuff is happening in the background and it will take a while before everything comes up. Don't freak out. Don't reboot or power cycle. Instead, do this: tail -f /var/log/homeassistant/home-assistant.log and watch the updates

build-essential installs everything required for compiling basic software written in C and C++ in this case Python. Read more... zlib1g-devis the development package of the compression library that implements the deflate compression methods and essential in Python's installation and other installations as well. Read more... libncurses5-dev is the development package for the curses library that provides a terminal-independent screen-painting and keyboard-handling tool. Read more... libgdbm-dev is a development library for GDBM whose functionality is to store key/data pairs in a data file. Read more... libnss3-dev Read more... libssl-dev Read more... libreadline-dev Read more... libffi-dev Read more... libsqlite3-dev Read more... wget Read more... libbz2-dev Read more... In the next step we can either manually download the latest release of Python from the Python Official Release page or use wget which we have installed in previous command. To download using wget, paste the following command in the terminal to download Python in the computer.

[INFO]: -> running basename https://github.com/libffi/libffi/archive/v3.3.tar.gz

libffi C library

If you have read my earlier posts you know I love multilingual programming. One important part of multilingual programming is how to interface one language with other. Typically this is called FFI or foreign function interface. At the lowest level often there are libraries (aka bindings) to talk across languages or across implementations of same language e.g. libffi. In my undergrad we did a group project where we created language bindings to separate algorithmic part written in python and opencv and X11 logic in c.

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