Enrico's blog

Gtk4 has interesting ways of splitting models and views. One that I didn't find very well documented, especially for Python bindings, is a set of radio buttons backed by a common model.

The idea is to define an action that takes a string as a state. Each radio button is assigned a string matching one of the possible states, and when the state of the backend action is changed, the radio buttons are automatically updated.

All the examples below use a string for a value type, but anything can be used that fits into a GLib.Variant.

The model

This defines the action. Note that enables all the usual declarative ways of a status change:

mode = Gio.SimpleAction.new_stateful(
        name="mode-selection",
        parameter_type=GLib.VariantType("s"),
        state=GLib.Variant.new_string(""))
gtk_app.add_action(self.mode)

The view

def add_radio(model: Gio.SimpleAction, id: str, label: str):
    button = Gtk.CheckButton(label=label)

    # Tell this button to activate when the model has the given value
    button.set_action_target_value(GLib.Variant.new_string(id))

    # Build the name under which the action is registesred, plus the state
    # value controlled by this button: clicking the button will set this state
    detailed_name = Gio.Action.print_detailed_name(
            "app." + model.get_name(),
            GLib.Variant.new_string(id))
    button.set_detailed_action_name(detailed_name)

    # If the model has no current value set, this sets the first radio button
    # as selected
    if not model.get_state().get_string():
        model.set_state(GLib.Variant.new_string(id))

Accessing the model

To read the currently selected value:

current = model.get_state().get_string()

To set the currently selected value:

model.set_state(GLib.Variant.new_string(id))

I acquired some unusual input devices to experiment with, like a CNC control panel and a bluetooth pedal page turner.

These identify and behave like a keyboard, sending nice and simple keystrokes, and can be accessed with no drivers or other special software. However, their keystrokes appear together with keystrokes from normal keyboards, which is the expected default when plugging in a keyboard, but not what I want in this case.

I'd also like them to be readable via evdev and accessible by my own user.

Here's the udev rule I cooked up to handle this use case:

# Handle the CNC control panel
SUBSYSTEM=="input", ENV{ID_VENDOR}=="04d9", ENV{ID_MODEL}=="1203", \
   OWNER="enrico", ENV{ID_INPUT}=""

# Handle the Bluetooth page turner
SUBSYSTEM=="input", ENV{ID_BUS}=="bluetooth", ENV{LIBINPUT_DEVICE_GROUP}=="*/…mac…", ENV{ID_INPUT_KEYBOARD}="1" \
   OWNER="enrico", ENV{ID_INPUT}="", SYMLINK+="input/by-id/bluetooth-…mac…-kbd"
SUBSYSTEM=="input", ENV{ID_BUS}=="bluetooth", ENV{LIBINPUT_DEVICE_GROUP}=="*/…mac…", ENV{ID_INPUT_TABLET}="1" \
   OWNER="enrico", ENV{ID_INPUT}="", SYMLINK+="input/by-id/bluetooth-…mac…-tablet"

The bluetooth device didn't have standard rules to create /dev/input/by-id/ symlinks so I added them. In my own code, I watch /dev/input/by-id with inotify to handle when devices appear or disappear.

I used udevadm info /dev/input/event… to see what I could use to identify the device.

The Static device configuration via udev page of libinput's documentation has documentation on the various elements specific to the input subsystem

Grepping rule files in /usr/lib/udev/rules.d was useful to see syntax examples.

udevadm test /dev/input/event… was invaluable for syntax checking and testing my rule file while working on it.

Finally, this is an extract of a quick prototype Python code to read keys from the CNC control panel:

import libevdev

KEY_MAP = {
    libevdev.EV_KEY.KEY_GRAVE: "EMERGENCY",
    # InputEvent(EV_KEY, KEY_LEFTALT, 1)
    libevdev.EV_KEY.KEY_R: "CYCLE START",

    libevdev.EV_KEY.KEY_F5: "SPINDLE ON/OFF",

    # InputEvent(EV_KEY, KEY_RIGHTCTRL, 1)
    libevdev.EV_KEY.KEY_W: "REDO",

    # InputEvent(EV_KEY, KEY_LEFTALT, 1)
    libevdev.EV_KEY.KEY_N: "SINGLE STEP",

    # InputEvent(EV_KEY, KEY_LEFTCTRL, 1)
    libevdev.EV_KEY.KEY_O: "ORIGIN POINT",

    libevdev.EV_KEY.KEY_ESC: "STOP",
    libevdev.EV_KEY.KEY_KPPLUS: "SPEED UP",
    libevdev.EV_KEY.KEY_KPMINUS: "SLOW DOWN",

    libevdev.EV_KEY.KEY_F11: "F+",
    libevdev.EV_KEY.KEY_F10: "F-",
    libevdev.EV_KEY.KEY_RIGHTBRACE: "J+",
    libevdev.EV_KEY.KEY_LEFTBRACE: "J-",

    libevdev.EV_KEY.KEY_UP: "+Y",
    libevdev.EV_KEY.KEY_DOWN: "-Y",
    libevdev.EV_KEY.KEY_LEFT: "-X",
    libevdev.EV_KEY.KEY_RIGHT: "+X",

    libevdev.EV_KEY.KEY_KP7: "+A",
    libevdev.EV_KEY.KEY_Q: "-A",
    libevdev.EV_KEY.KEY_PAGEDOWN: "-Z",
    libevdev.EV_KEY.KEY_PAGEUP: "+Z",
}


class KeyReader:
    def __init__(self, path: str):
        self.path = path
        self.fd: IO[bytes] | None = None
        self.device: libevdev.Device | None = None

    def __enter__(self):
        self.fd = open(self.path, "rb")
        self.device = libevdev.Device(self.fd)
        return self

    def __exit__(self, exc_type, exc, tb):
        self.device = None
        self.fd.close()
        self.fd = None

    def events(self) -> Iterator[dict[str, Any]]:
        for e in self.device.events():
            if e.type == libevdev.EV_KEY:
                if (val := KEY_MAP.get(e.code)):
                    yield {
                        "name": val,
                        "value": e.value,
                        "sec": e.sec,
                        "usec": e.usec,
                    }

Edited: added rules to handle the Bluetooth page turner

• str.endswith() can take a tuple of possible endings instead of a single string

About JACK and Debian

• There are 3 JACK implementations: jackd1, jackd2, pipewire-jack.
• jackd1 is mostly superseded in favour of jackd2, and as far as I understand, can be ignored
• pipewire-jack integrates well with pipewire and the rest of the Linux audio world
• jackd2 is the native JACK server. When started it handles the sound card directly, and will steal it from pipewire. Non-JACK audio applications will likely cease to see the sound card until JACK is stopped and wireplumber is restarted. Pipewire should be able to keep working as a JACK client but I haven't gone down that route yet
• pipewire-jack mostly works. At some point I experienced glitches in complex JACK apps like giada or ardour that went away after switching to jackd2. I have not investigated further into the glitches
• So: try things with pw-jack. If you see odd glitches, try without pw-jack to use the native jackd2. Keep in mind, if you do so, that you will lose standard pipewire until you stop jackd2 and restart wireplumber.

I have Python code for reading a heart rate monitor.

I have Python code to generate MIDI events.

Could I resist putting them together? Clearly not.

Here's Jack Of Hearts, a JACK MIDI drum loop generator that uses the heart rate for BPM, and an improvised way to compute heart rate increase/decrease to add variations in the drum pattern.

It's very simple minded and silly. To me it was a fun way of putting unrelated things together, and Python worked very well for it.

I had a go at trying to figure out how to generate arbitrary MIDI events and send them out over a JACK MIDI channel.

Setting up JACK and Pipewire

Pipewire has a JACK interface, which in theory means one could use JACK clients out of the box without extra setup.

In practice, one need to tell JACK clients which set of libraries to use to communicate to servers, and Pipewire's JACK server is not the default choice.

To tell JACK clients to use Pipewire's server, you can either:

• on a client-by-client basis, wrap the commands with pw-jack
• to change the system default: cp /usr/share/doc/pipewire/examples/ld.so.conf.d/pipewire-jack-*.conf /etc/ld.so.conf.d/ and run ldconfig (see the Debian wiki for details)

Programming with JACK

Python has a JACK client library that worked flawlessly for me so far.

Everything with JACK is designed around minimizing latency. Everything happens around a callback that gets called form a separate thread, and which gets a buffer to fill with events.

All the heavy processing needs to happen outside the callback, and the callback is only there to do the minimal amount of work needed to shovel the data your application produced into JACK channels.

Generating MIDI messages

The Mido library can be used to parse and create MIDI messages and it also worked flawlessly for me so far.

One needs to study a bit what kind of MIDI message one needs to generate (like "note on", "note off", "program change") and what arguments they get.

It also helps to read about the General MIDI standard which defines mappings between well-known instruments and channels and instrument numbers in MIDI messages.

A timed message queue

To keep a queue of events that happen over time, I implemented a Delta List that indexes events by their future frame number.

I called the humble container for my audio experiments pyeep and here's my delta list implementation.

A JACK player

The simple JACK MIDI player backend is also in pyeep.

It needs to protect the delta list with a mutex since we are working across thread boundaries, but it tries to do as little work under lock as possible, to minimize the risk of locking the realtime thread for too long.

The play method converts delays in seconds to frame counts, and the on_process callback moves events from the queue to the jack output.

Here's an example script that plays a simple drum pattern:

#!/usr/bin/python3

# Example JACK midi event generator
#
# Play a drum pattern over JACK

import time

from pyeep.jackmidi import MidiPlayer

# See:
# https://soundprogramming.net/file-formats/general-midi-instrument-list/
# https://www.pgmusic.com/tutorial_gm.htm

DRUM_CHANNEL = 9

with MidiPlayer("pyeep drums") as player:
    beat: int = 0
    while True:
        player.play("note_on", velocity=64, note=35, channel=DRUM_CHANNEL)
        player.play("note_off", note=38, channel=DRUM_CHANNEL, delay_sec=0.5)
        if beat == 0:
            player.play("note_on", velocity=100, note=38, channel=DRUM_CHANNEL)
            player.play("note_off", note=36, channel=DRUM_CHANNEL, delay_sec=0.3)
        if beat + 1 == 2:
            player.play("note_on", velocity=100, note=42, channel=DRUM_CHANNEL)
            player.play("note_off", note=42, channel=DRUM_CHANNEL, delay_sec=0.3)

        beat = (beat + 1) % 4
        time.sleep(0.3)

Running the example

I ran the jack_drums script, and of course not much happened.

First I needed a MIDI synthesizer. I installed fluidsynth, and ran it on the command line with no arguments. it registered with JACK, ready to do its thing.

Then I connected things together. I used qjackctl, opened the graph view, and connected the MIDI output of "pyeep drums" to the "FLUID Synth input port".

fluidsynth's output was already automatically connected to the audio card and I started hearing the drums playing! 🥁️🎉️

I bought myself a cheap wearable Bluetooth LE heart rate monitor in order to play with it, and this is a simple Python script to monitor it and plot data.

Bluetooth LE

I was surprised that these things seem decently interoperable.

You can use hcitool to scan for devices:

hcitool lescan

You can then use gatttool to connect to device and poke at them interactively from a command line.

Bluetooth LE from Python

There is a nice library called Bleak which is also packaged in Debian. It's modern Python with asyncio and works beautifully!

Heart rate monitors

Things I learnt:

• The UUID for the heart rate interface starts with 00002a37.
• The UUID for checking battery status starts with 00002a19.
• A longer list of UUIDs is here.
• The layout of heart rate data packets and some Python code to parse them
• What are RR values

How about a proper fitness tracker?

I found OpenTracks, also on F-Droid, which seems nice

Why script it from a desktop computer?

The question is: why not?

A fitness tracker on a phone is useful, but there are lots of silly things one can do from one's computer that one can't do from a phone. A heart rate monitor is, after all, one more input device, and there are never enough input devices!

There are so many extremely important use cases that seem entirely unexplored:

• Log your heart rate with your git commits!
• Add your heart rate as a header in your emails!
• Correlate heart rate information with your work activity tracker to find out what tasks stress you the most!
• Sync ping intervals with your own heartbeat, so you get faster replies when you're more anxious!
• Configure workrave to block your keyboard if you get too excited, to improve the quality of your mailing list contributions!
• You can monitor the monitor script of the heart rate monitor that monitors you! Forget buffalo, be your monitor monitor monitor monitor monitor monitor monitor monitor...

These are some notes about my redesign work in staticsite 2.x.

Maping constraints and invariants

I started keeping notes of constraints and invariants, and this helped a lot in keeping bounds on the cognitive efforts of design.

I particularly liked how mapping the set of constraints added during site generation has helped breaking down processing into a series of well defined steps. Code that handles each step now has a specific task, and can rely on clear assumptions.

Declarative page metadata

I designed page metadata as declarative fields added to the Page class.

I used typed descriptors for the fields, so that metadata fields can now have logic and validation, and are self-documenting!

This is the core of the Field implementation.

Lean core

I tried to implement as much as possible in feature plugins, leaving to the staticsite core only what is essential to create the structure for plugins to build on.

The core provides a tree structure, an abstract Page object that can render to a file and resolve references to other pages, a Site that holds settings and controls the various loading steps, and little else.

The only type of content supported by the core is static asset files: Markdown, RestructuredText, images, taxonomies, feeds, directory indices, and so on, are all provided via feature plugins.

Feature plugins

Feature plugins work by providing functions to be called at the various loading steps, and mixins to be added to site pages.

Mixins provided by feature plugins can add new declarative metadata fields, and extend Page methods: this ends up being very clean and powerful, and plays decently well with mypy's static type checking, too!

See for example the code of the alias feature, that allows a page to declare aliases that redirect to it, useful for example when moving content around.

It has a mixin (AliasPageMixin) that adds an aliases field that holds a list of page paths.

During the "generate" step, when autogenerated pages can be created, the aliases feature iterates through all pages that defined an aliases metadata, and generates the corresponding redirection pages.

Self-documenting code

Staticsite can list loaded features, features can list the page subclasses that they use, and pages can list metadata fields.

As a result, each feature, each type of page, and each field of each page can generate documentation about itself: the staticsite reference is autogenerated in that way, mostly from Feature, Page, and Field docstrings.

Understand the language, stay close to the language

Python has matured massively in the last years, and I like to stay on top of the language and standard library release notes for each release.

I like how what used to be dirty hacks have now found a clean way into the language:

• what one would implement with metaclass magic one can now mostly do with descriptors, and get language support for it, including static type checking.
• understanding the inheritance system and method resolution order allows to write type checkable mixins
• runtime-accessible docstrings help a lot with autogenerating documentation
• os.scandir and os functions that accept directory file descriptors make filesystem exploration pleasantly fast, for an interpreted language!

In theory I wanted to announce the release of staticsite 2.0, but then I found bugs that prevented me from writing this post, so I'm also releasing 2.1 2.2 2.3 :grin:

staticsite is the static site generator that I ended up writing after giving other generators a try.

I did a big round of cleanup of the code, which among other things allowed me to implement incremental builds.

It turned out that staticsite is fast enough that incremental builds are not really needed, however, a bug in caching rendered markdown made me forget about that. Now I fixed that bug, too, and I can choose between running staticsite fast, and ridiculously fast.

My favourite bit of this work is the internal cleanup: I found a way to simplify the core design massively, and now the core and plugin system is simple enough that I can explain it, and I'll probably write a blog post or two about it in the next days.

On top of that, staticsite is basically clean with mypy running in strict mode! Getting there was a great ride which prompted a lot of thinking about designing code properly, as mypy is pretty good at flagging clumsy hacks.

If you want to give it a try, check out the small tutorial A new blog in under one minute.

Python: typing.overload

typing.overload makes it easier to type functions with behaviour that depends on input types. Functions marked with @overload are ignored by Python and only used by the type checker:

@overload
def process(response: None) -> None:
    ...
@overload
def process(response: int) -> tuple[int, str]:
    ...
@overload
def process(response: bytes) -> str:
    ...
def process(response):
    # <actual implementation>

Python's multiprocessing and deadlocks

Python's multiprocessing is prone to deadlocks in a number of conditions. In my case, the running program was a standard single-process, non-threaded script, but it used complex native libraries which might have been the triggers for the deadlocks.

The suggested workaround is using set_start_method("spawn"), but when we tried it we hit serious performance penalties.

Lesson learnt: multiprocessing is good for prototypes, and may end up being too hacky for production.

In my case, I was already generating small python scripts corresponding to worker tasks, which were useful for reproducing and debugging Magics issues, so I switched to running those as the actual workers. In the future, this may come in handy for dispatching work to HPC nodes, too.

Here's a parallel execution scheduler based on asyncio that I wrote to run them, which may always come in handy on other projects.

Debian:

• You can Build-Depend on debhelper-compat (=version) and get rid of debhelper as a build-dependency, and of debian/compat (details)
• You can Build-Depend on dh-sequence-foo and get rid of the corresponding dh-foo build-dependency, and of the need to add --with foo in debian/rules (details)
• You can (and should) get rid of dh-buildinfo, which is now handled automatically
• In salsa.debian.org there is a default CI pipeline for Debian packages that works beautifully without needing to add any .gitlab-ci.yml to a repository
• Add Testsuite: autopkgtest-pkg-python to debian/control, and you get a free autopkgtest that verifies that your packaged Python module can be imported. The default CI pipeline in salsa will automatically run the tests. (specification, details)

Python:

• From Python 3.8, you can use = in format strings to make it easier to debug variables and expressions (details):

>>> name="test"
>>> print(f"{name=}")
name='test'
>>> print(f"{3*8=}")
3*8=24

Leaflet:

• [abc].tile.openstreetmap.org links need to be replaced with tile.openstreetmap.org (details)