QML

This package provides an interface to Qt5 QML. It uses the CxxWrap package to expose C++ classes. Current functionality allows interaction between QML and Julia using Observables, ListModels and function calling. There is also a generic Julia display, as well as specialized integration for image drawing, GR plots and Makie.

Installation

Installation on Linux, Mac and Windows should be as easy as: (in pkg mode, hit ] in the Julia REPL):

add QML

Documentation

See https://barche.github.io/QML.jl/dev

Basic usage

Running examples

To run the included examples, execute:

include(joinpath(dirname(pathof(QML)), "..", "example", "runexamples.jl"))

The examples require some additional packages to be described by the manifest and project files in the examples directory, so from the examples directory you should start Julia with julia --project and then run instantiate from the pkg shell.

Loading a QML file

We support three methods of loading a QML file: QQmlApplicationEngine, QQuickView and QQmlComponent. These behave equivalently to the corresponding Qt classes.

QQmlApplicationEngine

The easiest way to run the QML file main.qml from the current directory is using the load function, which will create and return a QQmlApplicationEngine and load the supplied QML file:

using QML
load("main.qml")
exec()

The lifetime of the QQmlApplicationEngine is managed from C++ and it gets cleaned up when the application quits. This means it is not necessary to keep a reference to the engine to prevent it from being garbage collected prematurely.

QQuickView

The QQuickView creates a window, so it's not necessary to wrap the QML in ApplicationWindow. A QML file is loaded as follows:

qview = init_qquickview()
set_source(qview, "main.qml")
QML.show(qview)
exec()

QQmlComponent

Using QQmlComponent the QML code can be set from a Julia string wrapped in QByteArray:

qml_data = QByteArray("""
import ...

ApplicationWindow {
  ...
}
""")

qengine = init_qmlengine()
qcomp = QQmlComponent(qengine)
set_data(qcomp, qml_data, "")
create(qcomp, qmlcontext());

# Run the application
exec()

Interacting with Julia

Interaction with Julia happens through the following mechanisms:

Call Julia functions from QML
Read and set context properties from Julia and QML
Emit signals from Julia to QML
Use data models

Note that Julia slots appear missing, but they are not needed since it is possible to directly connect a Julia function to a QML signal in the QML code (see the QTimer example below).

Calling Julia functions

In Julia, functions are registered using the qmlfunction function:

my_function() = "Hello from Julia"
my_other_function(a, b) = "Hi from Julia"

qmlfunction("my_function", my_function)
qmlfunction("my_other_function", my_other_function)

For convenience, there is also a macro that registers any number of functions that are in scope and will have the same name in QML as in Julia:

@qmlfunction my_function my_other_function

However, the macro cannot be used in the case of non-exported functions from a different module or in case the function contains a ! character.

In QML, include the Julia API:

import org.julialang 1.0

Then call a Julia function in QML using:

Julia.my_function()
Julia.my_other_function(arg1, arg2)

Context properties

Context properties are set using the context object method. To dynamically add properties from Julia, a QQmlPropertyMap is used, setting e.g. a property named a:

propmap = QML.QQmlPropertyMap()
propmap["a"] = 1

This sets the QML context property named property_name to value julia_value.

The value of a property can be queried from Julia like this:

@test propmap["a"] == 1

To pass these properties to the QML side, the property map can be the second argument to load:

load(qml_file, propmap)

There is also a shorthand notation using keywords:

load(qml_file, a=1, b=2)

This will create context properties a and b, initialized to 1 and 2.

Observable properties

When an Observable is set in a QQmlPropertyMap, bi-directional change notification is enabled. For example, using the Julia code:

using QML
using Qt5QuickControls_jll
using Observables

const qml_file = "observable.qml"
const input = Observable(1.0)
const output = Observable(0.0)

on(output) do x
  println("Output changed to ", x)
end

load(qml_file, input=input, output=output)
exec_async() # run from REPL for async execution

In QML we add a slider for the input and display the output, which is twice the input (computed in QML here):

import QtQuick 2.0
import QtQuick.Controls 1.0
import QtQuick.Layouts 1.0

ApplicationWindow {
  id: root
  title: "Observables"
  width: 512
  height: 200
  visible: true

  ColumnLayout {
    spacing: 6
    anchors.fill: parent

    Slider {
      value: input
      Layout.alignment: Qt.AlignCenter
      Layout.fillWidth: true
      minimumValue: 0.0
      maximumValue: 100.0
      stepSize: 1.0
      tickmarksEnabled: true
      onValueChanged: {
        input = value;
        output = 2*input;
      }
    }

    Text {
      Layout.alignment: Qt.AlignCenter
      text: output
      font.pixelSize: 0.1*root.height
    }
  }

}

Moving the slider will print the output on Julia. The input can also be set from the REPL using e.g. input[] = 3.0, and the slider will move accordingly and call QML to compute the output, which can be queried using output[].

Type conversion

Most fundamental types are converted implicitly. Mind that the default integer type in QML corresponds to Int32 in Julia.

We also convert QVariantMap, exposing the indexing operator [] to access element by a string key. This mostly to deal with arguments passed to the QML append function in list models.

Emitting signals from Julia

Defining signals must be done in QML in the JuliaSignals block, following the instructions from the QML manual. Example signal with connection:

JuliaSignals {
  signal fizzBuzzFound(int fizzbuzzvalue)
  onFizzBuzzFound: lastFizzBuzz.text = fizzbuzzvalue
}

The above signal is emitted from Julia using simply:

@emit fizzBuzzFound(i)

There must never be more than one JuliaSignals block in QML

Using data models

ListModel

The ListModel type allows using data in QML views such as ListView and Repeater, providing a two-way synchronization of the data. The dynamiclist example from Qt has been translated to Julia in example/dynamiclist.jl. As can be seen from this commit, the only required change was moving the model data from QML to Julia, otherwise the Qt-provided QML file is left unchanged.

A ListModel is constructed from a 1D Julia array. In Qt, each of the elements of a model has a series of roles, available as properties in the delegate that is used to display each item. The roles can be added using the addrole function, for example:

julia_array = ["A", 1, 2.2]
myrole(x::AbstractString) = lowercase(x)
myrole(x::Number) = Int(round(x))

array_model = ListModel(julia_array)
addrole(array_model, "myrole", myrole, setindex!)

adds the role named myrole to array_model, using the function myrole to access the value. The setindex! argument is a function used to set the value for that role from QML. This argument is optional, if it is not provided the role will be read-only. The arguments of this setter are collection, new_value, key as in the standard setindex! function.

To use the model from QML, it can be exposed as a context attribute, e.g:

load(qml_file, array_model=array_model)

And then in QML:

ListView {
  width: 200
  height: 125
  model: array_model
  delegate: Text { text: myrole }
}

If no roles are added, one default role named string is exposed, calling the Julia function string to convert whatever value in the array to a string.

If new elements need to be constructed from QML, a constructor can also be provided, using the setconstructor method, taking a ListModel and a Julia function as arguments, e.g. just setting identity to return the constructor argument:

setconstructor(array_model, identity)

In the dynamiclist example, the entries in the model are all "fruits", having the roles name, cost and attributes. In Julia, this can be encapsulated in a composite type:

mutable struct Fruit
  name::String
  cost::Float64
  attributes::ListModel
end

When an array composed only of Fruit elements is passed to a listmodel, setters and getters for the roles and the constructor are all passed to QML automatically, i.e. this will automatically expose the roles name, cost and attributes:

# Our initial data
fruitlist = [
  Fruit("Apple", 2.45, ListModel([Attribute("Core"), Attribute("Deciduous")])),
  Fruit("Banana", 1.95, ListModel([Attribute("Tropical"), Attribute("Seedless")])),
  Fruit("Cumquat", 3.25, ListModel([Attribute("Citrus")])),
  Fruit("Durian", 9.95, ListModel([Attribute("Tropical"), Attribute("Smelly")]))]

# Set a context property with our listmodel
propmap["fruitModel"] = ListModel(fruitlist)

See the full example for more details, including the addition of an extra constructor to deal with the nested ListModel for the attributes.

Using QTimer

QTimer can be used to simulate running Julia code in the background. Excerpts from test/gui.jl:

const bg_counter = Observable(0)

function counter_slot()
  global bg_counter
  bg_counter[] += 1
end

@qmlfunction counter_slot

load(qml_file, timer=QTimer(), bg_counter=bg_counter)

Use in QML like this:

import QtQuick 2.0
import QtQuick.Controls 1.0
import QtQuick.Layouts 1.0
import org.julialang 1.0

ApplicationWindow {
    title: "My Application"
    width: 480
    height: 640
    visible: true

    Connections {
      target: timer
      onTimeout: Julia.counter_slot()
    }

    ColumnLayout {
      spacing: 6
      anchors.centerIn: parent

      Button {
          Layout.alignment: Qt.AlignCenter
          text: "Start counting"
          onClicked: timer.start()
      }

      Text {
          Layout.alignment: Qt.AlignCenter
          text: bg_counter.toString()
      }

      Button {
          Layout.alignment: Qt.AlignCenter
          text: "Stop counting"
          onClicked: timer.stop()
      }
  }
}

Note that QML provides the infrastructure to connect to the QTimer signal through the Connections item.

JuliaDisplay

QML.jl provides a custom QML type named JuliaDisplay that acts as a standard Julia multimedia Display. Currently, only the image/png mime type is supported. Example use in QML from the plot example:

JuliaDisplay {
  id: jdisp
  Layout.fillWidth: true
  Layout.fillHeight: true
  onHeightChanged: root.do_plot()
  onWidthChanged: root.do_plot()
}

The function do_plot is defined in the parent QML component and calls the Julia plotting routine, passing the display as an argument:

function do_plot()
{
  if(jdisp === null)
    return;

  Julia.plotsin(jdisp, jdisp.width, jdisp.height, amplitude.value, frequency.value);
}

Of course the display can also be added using pushdisplay!, but passing by value can be more convenient when defining multiple displays in QML.

JuliaCanvas

QML.jl provides a custom QML type named JuliaCanvas which presents a canvas to be painted via a julia callback function. This approach avoids the MIME content encoding overhead of the JuliaDisplay approach.

Example use in QML from the canvas example:

JuliaCanvas {
  id: circle_canvas
  paintFunction: paint_cfunction
  Layout.fillWidth: true
  Layout.fillHeight: true
  Layout.minimumWidth: 100
  Layout.minimumHeight: 100
}

The callback function paint_cfunction is defined in julia:

# fix callback arguments (TODO: macro this?)
function paint_circle(buffer::Array{UInt32, 1},
                      width32::Int32,
                      height32::Int32)
   width::Int = width32
   height::Int = height32
   buffer = reshape(buffer, width, height)
   buffer = reinterpret(ARGB32, buffer)
   paint_circle(buffer)
end

# callback to paint circle
function paint_circle(buffer)
   width, height = size(buffer)
   for x in 1:width
       for y in 1:height
           # paint here..., e.g.
           buffer[x,y] = ARGB32(1, 0, 0, 1) #red
       end
   end
end

load(qmlfile,
     #...
     paint_cfunction = CxxWrap.@safe_cfunction(paint_circle, Cvoid, (Array{UInt32,1}, Int32, Int32))
)

Note that the canvas buffer is allocated (and freed) in the C++ code. A new unitialized buffer is allocated for each frame (this could change).

At the moment, only the 32-bit QImage::Format_RGB32 (alpha, red, green, blue) image format is supported.

See the example for details on emitting an update signal from julia to force redrawing the JuliaCanvas.

NOTE

Set

ENV["QSG_RENDER_LOOP"] = "basic"

at the top of your Julia file to avoid crashes or infinite loops when using JuliaCanvas.

Combination with the REPL

When launching the application using exec, execution in the REPL will block until the GUI is closed. If you want to continue using the REPL with an active QML gui, exec_async provides an alternative. This method keeps the REPL active and polls the QML interface periodically for events, using a timer in the Julia event loop. An example (requiring packages Plots.jl and PyPlot.jl) can be found in example/repl-background.jl, to be used as:

include("example/repl-background.jl")
plot([1,2],[3,4])

This should display the result of the plotting command in the QML window.

For further examples, see the documentation.

Breaking changes

Upgrade from v0.6 to v0.7

Julia 1.6 minimal requirement
Need to specifically add and load Julia packages for Controls and Controls 2, i.e. Qt5QuickControls_jll and Qt5QuickControls2_jll

Upgrade from v0.4 to v0.6

Signals in JuliaSignals must have arguments of type var
Role indices are 1-based now on the Julia side
The interface of some functions has changed because of the way CxxWrap handles references and pointers more strictly now
No more automatic conversion from String to QUrl, use the QUrl("mystring") constructor
Setting a QQmlPropertyMap as context object is not supported as of Qt 5.12

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