QCoro 0.5.0 Release Announcement

After another few months I’m happy to announce a new release of QCoro, which brings several new features and a bunch of bugfixes.

  • .then() continuation for Task<T>
  • All asynchronous operations now return Task<T>
  • Timeouts for many operations
  • Support for QThread

.then() continuation for Task

Sometimes it’s not possible to co_await a coroutine - usually because you need to integrate with a 3rd party code that is not coroutine-ready. A good example might be implementing QAbstractItemModel, where none of the virtual methods are coroutines and thus it’s not possible to use co_await in them.

To still make it possible to all coroutines from such code, QCoro::Task<T> now has a new method: .then(), which allows attaching a continuation callback that will be invoked by QCoro when the coroutine represented by the Task finishes.

void notACoroutine() {
    someCoroutineReturningQString().then([](const QString &result) {
        // Will be invoked when the someCoroutine() finishes.
        // The result of the coroutine is passed as an argument to the continuation.

The continuation itself might be a coroutine, and the result of the .then() member function is again a Task<R> (where R is the return type of the continuation callback), so it is possible to chain multiple continuations as well as co_awaiting the entire chain.

All asynchronous operations now return Task<T>

Up until now each operation from the QCoro wrapper types returned a special awaitable - for example, QCoroIODevice::read() returned QCoro::detail::QCoroIODevice::ReadOperation. In most cases users of QCoro do not need to concern themselves with that type, since they can still directly co_await the returned awaitable.

However, it unnecessarily leaks implementation details of QCoro into public API and it makes it harded to return a coroutine from a non-coroutine function.

As of QCoro 0.5.0, all the operations now return Task<T>, which makes the API consistent. As a secondary effect, all the operations can have a chained continuation using the .then() continuation, as described above.

Timeout support for many operations

Qt doesn’t allow specifying timeout for many operations, because they are typically non-blocking. But the timeout makes sense in most QCoro cases, because they are combination of wait + the non-blocking operation. Let’s take QIODevice::read() for example: the Qt version doesn’t have any timeout, because the call will never block - if there’s nothing to read, it simply returns an empty QByteArray.

On the other hand, QCoroIODevice::read() is an asynchronous operation, because under to hood, it’s a coroutine that asynchronously calls a sequence of


Since QIODevice::waitForReadyRead() takes a timeout argument, it makes sense for QCoroIODevice::read() to also take (an optional) timeout argument. This and many other operations have gained support for timeout.

Support for QThread

It’s been a while since I added a new wrapper for a Qt class, so QCoro 0.5.0 adds wrapper for QThread. It’s now possible to co_await thread start and end:

std::unique_ptr<QThread> thread(QThread::create([]() {
ui->setLabel(tr("Starting thread...");
co_await qCoro(thread)->waitForStarted();
co_await qCoro(thread)->waitForFinished();

Full changelog

  • .then() continuation for Task<T> (#39)
  • Fixed namespace scoping (#45)
  • Fixed QCoro::waitFor() getting stuck when coroutine returns synchronously (#46)
  • Fixed -pthread usage in CMake (#47)
  • Produce QMake config files (.pri) for each module (commit e215616)
  • Fix build on platforms where -latomic must be linked explicitly (#52)
  • Return Task<T> from all operations (#54)
  • Add QCoro wrapper for QThread (commit 832d931)
  • Many documentation updates

Thanks to everyone who contributed to QCoro!


You can download QCoro 0.5.0 here or check the latest sources on QCoro GitHub.

More About QCoro

If you are interested in learning more about QCoro, go read the documentation, look at the first release announcement, which contains a nice explanation and example or watch recording of my talk about C++20 coroutines and QCoro this years’ Akademy.

QCoro 0.4.0 Release Announcement

It took a few months, but there’s a new release of QCoro with some new cool features. This change contains a breaking change in CMake, wich requires QCoro users to adjust their CMakeLists.txt. I sincerely hope this is the last breaking change for a very long time.

Major highlights in this release:

  • Co-installability of Qt5 and Qt6 builds of QCoro
  • Complete re-work of CMake configuration
  • Support for compiling QCoro with Clang against libstdc++

Co-installability of Qt5 and Qt6 builds of QCoro

This change mostly affects packagers of QCoro. It is now possible to install both Qt5 and Qt6 versions of QCoro alongside each other without conflicting files. The shared libraries now contain the Qt version number in their name (e.g. libQCoro6Core.so) and header files are also located in dedicated subdirectories (e.g. /usr/include/qcoro6/{qcoro,QCoro}). User of QCoro should not need to do any changes to their codebase.

Complete re-work of CMake configuration

This change affects users of QCoro, as they will need to adjust CMakeLists.txt of their projects. First, depending on whether they want to use Qt5 or Qt6 version of QCoro, a different package must be used. Additionally, list of QCoro components to use must be specified:

find_package(QCoro5 REQUIRED COMPONENTS Core Network DBus)

Finally, the target names to use in target_link_libraries have changed as well:

  • QCoro::Core
  • QCoro::Network
  • QCoro::DBus

The version-less QCoro namespace can be used regardless of whether using Qt5 or Qt6 build of QCoro. QCoro5 and QCoro6 namespaces are available as well, in case users need to combine both Qt5 and Qt6 versions in their codebase.

This change brings QCoro CMake configuration system to the same style and behavior as Qt itself, so it should now be easier to use QCoro, especially when supporting both Qt5 and Qt6.

Support for compiling QCoro with Clang against libstdc++

Until now, when the Clang compiler was detected, QCoro forced usage of LLVM’s libc++ standard library. Coroutine support requires tight co-operation between the compiler and standard library. Because Clang still considers their coroutine support experimental it expects all coroutine-related types in standard library to be located in std::experimental namespace. In GNU’s libstdc++, coroutines are fully supported and thus implemented in the std namespace. This requires a little bit of extra glue, which is now in place.

Full changelog

  • QCoro can now be built with Clang against libstdc++ (#38, #22)
  • Qt5 and Qt6 builds of QCoro are now co-installable (#36, #37)
  • Fixed early co_return not resuming the caller (#24, #35)
  • Fixed QProcess example (#34)
  • Test suite has been improved and extended (#29, #31)
  • Task move assignment operator checks for self-assignment (#27)
  • QCoro can now be built as a subdirectory inside another CMake project (#25)
  • Fixed QCoroCore/qcorocore.h header (#23)
  • DBus is disabled by default on Windows, Mac and Android (#21)

Thanks to everyone who contributed to QCoro!


You can download QCoro 0.4.0 here or check the latest sources on QCoro GitHub.

More About QCoro

If you are interested in learning more about QCoro, go read the documentation, look at the first release announcement, which contains a nice explanation and example or watch recording of my talk about C++20 coroutines and QCoro this years’ Akademy.

QCoro 0.2.0 Release Announcement

Just about a month after the first official release of QCoro, a library that provides C++ coroutine support for Qt, here’s 0.2.0 with some big changes. While the API is backwards compatible, users updating from 0.1.0 will have to adjust their #include statements when including QCoro headers.

QCoro 0.2.0 brings the following changes:

Library modularity

The code has been reorganized into three modules (and thus three standalone libraries): QCoroCore, QCoroDBus and QCoroNetwork. QCoroCore contains the elementary QCoro tools (QCoro::Task, qCoro() wrapper etc.) and coroutine support for some QtCore types. The QCoroDBus module contains coroutine support for types from the QtDBus module and equally the QCoroNetwork module contains coroutine support for types from the QtNetwork module. The latter two modules are also optional, the library can be built without them. It also means that an application that only uses let’s say QtNetwork and has no DBus dependency will no longer get QtDBus pulled in through QCoro, as long as it only links against libQCoroCore and libQCoroNetwork. The reorganization will also allow for future support of additional Qt modules.

Headers clean up

The include headers in QCoro we a bit of a mess and in 0.2.0 they all got a unified form. All public header files now start with qcoro (e.g. qcorotimer.h, qcoronetworkreply.h etc.), and QCoro also provides CamelCase headers now. Thus users should simply do #include <QCoroTimer> if they want coroutine support for QTimer.

The reorganization of headers makes QCoro 0.2.0 incompatible with previous versions and any users of QCoro will have to update their #include statements. I’m sorry about this extra hassle, but with this brings much needed sanity into the header organization and naming scheme.

Docs update

The documentation has been updated to reflect the reorganization as well as some internal changes. It should be easier to understand now and hopefully will make it easier for users to start with QCoro now.

Internal API cleanup and code de-duplication

Historically, certain types types which can be directly co_awaited with QCoro, for instance QTimer has their coroutine support implemented differently than types that have multiple asynchronous operations and thus have a coroutine-friendly wrapper classes (like QIODevice and it’s QCoroIODevice wrapper). In 0.2.0 I have unified the code so that even the coroutine support for simple types like QTimer are implemented through wrapper classes (so there’s QCoroTimer now)


You can download QCoro 0.2.0 here or check the latest sources on QCoro GitHub.

More About QCoro

If you are interested in learning more about QCoro, go read the documentation, look at the first release announcement, which contains a nice explanation and example or watch recording of my talk about C++20 coroutines and QCoro this years’ Akademy.

Initial release of QCoro

I’m happy to announce first release of QCoro, a library that provides C++ coroutine support for Qt.

You can download QCoro 0.1.0 here or check the latest sources on QCoro GitHub.

I have talked about QCoro (and C++ coroutines in general) recently at KDE Akademy, you can view the recording of my talk on YouTube.

In general, QCoro provides coroutine support for various asynchronous operations provided by Qt. Since Qt doesn’t support coroutines by default, QCoro provides the necessary “glue” between native Qt types and the C++ coroutine machinery, making it possible to use Qt types with coroutines easily.

QCoro provides coroutine support for asynchronous operations of QIODevice, QNetworkReply, QProcess, QDBusPendingReply, QTimer and more. Take a look at the documentation for detailed description and list of all currently supported Qt types.

A brief example from our documentation that demonstrates how using coroutines makes handling asynchronous operations in Qt simpler:

This is a (simplified) example of how we do network requests with Qt normally, using signals and slots:

QNetworkAccessManager *manager = new QNetworkAccessManager(this);
QNetworkReply *reply = manager->get(url);
connect(reply, &QNetworkReply::finished, this,
        [this, reply]() {
            const auto data = reply->readAll();

And this is the same code, written using C++ coroutines:

QNetworkAccessManager networkAccessManager;
QNetworkReply *reply = co_await networkAccessManager.get(url);
const auto data = reply->readAll();

The co_await keyword here is the key here: it asynchronously waits for the reply to finish. During the wait, the execution returns to the caller, which could be the Qt event loop, which means that even if this code looks synchronous, in fact it won’t block the event loop while keeping the code simple to read and understand.

Building RC LEGO with Arduino and Qt

Recently my 4 year-old stepson saw a kid with an RC racing car in a park. He really wanted his own, but with Christmas and his birthday still being a long way away, I decided to solve the “problem” by combining three things I’m really passionate about: LEGO, electronics and programming.

In this short series of blogs I’ll describe how to build one such car using LEGO, Arduino and a bit of C++ (and Qt, of course!).


Obviously, we will need some LEGO to build the car. Luckily, I bought LEGO Technic Mercedes Benz Arocs 3245 (40243) last year. It’s a big build with lots of cogs, one electric engine and bunch of pneumatics. I can absolutely recommend it - building the set was a lot of fun and thanks to the Power Functions it has a high play-value as well. There’s also fair amount of really good MOCs, especially the MOC 6060 - Mobile Crane by M_longer is really good. But I’m digressing here. :)

Mercedes Benz Arocs 3245 (40243) Mercedes Benz Arocs 3245 (40243)

The problem with Arocs is that it only has a single Power Functions engine (99499 Electric Power Functions Large Motor) and we will need at least two: one for driving and one for steering. So I bought a second one. I bought the same one, but a smaller one would probably do just fine for the steering.

LEGO Power Functions engine (99499)

I started by prototyping the car and the drive train, especially how to design the gear ratios to not overload the engine when accelerating while keeping the car moving at reasonable speed.

First prototype of engine-powered LEGO car

Turns out the 76244 Technic Gear 24 Tooth Clutch is really important as it prevents the gear teeth skipping when the engine stops suddenly, or when the car gets pushed around by hand.

76244 Technic Gear 24 Tooth Clutch

Initially I thought I would base the build of the car on some existing designs but in the end I just started building and I ended up with this skeleton:

Skelet of first version of the RC car

The two engines are in the middle - rear one powers the wheels, the front one handles the steering using the 61927b Technic Linear Actuator. I’m not entirely happy with the steering, so I might rework that in the future. I recently got Ford Mustang (10265) which has a really interesting steering mechanism and I think I’ll try to rebuild the steering this way.


58118 Eletric Power Functions Extension Wires

We will control the engines from Arduino. But how to connect the LEGO Power Functions to an Arduino? Well, you just need to buy a bunch of those 58118 Electric Power Functions Extension Wires, cut them and connect them with DuPont cables that can be connected to a breadboard. Make sure to buy the “with one Light Bluish Gray End” version - I accidentally bought cables which had both ends light bluish, but those can’t be connected to the 16511 Battery Box.

We will need 3 of those half-cut PF cables in total: two for the engines and one to connect to the battery box. You probably noticed that there are 4 connectors and 4 wires in each cable. Wires 1 and 4 are always GND and 9V, respectively, regardless of what position is the switch on the battery pack. Wires 2 and 3 are 0V and 9V or vice versa, depending on the position of the battery pack switch. This way we can control the engine rotation direction.

Schematics of PF wires

For the two cables that will control the engines we need all 4 wires connected to the DuPont cable. For the one cable that will be connected to the battery pack we only need the outter wires to be connected, since we will only use the battery pack to provide the power - we will control the engines using Arduino and an integrated circuit.

I used the glue gun to connect the PF wires and the DuPont cables, which works fairly well. You could use a solder if you have one, but the glue also works as an isolator to prevent the wires from short-circuiting.

LEGO PF cable connected to DuPont wires

This completes the LEGO part of this guide. Next comes the electronics :)


To remotely control the car we need some electronics on board. I used the following components:

  • Arduino UNO - to run the software, obviously
  • HC-06 Bluetooth module - for remote control
  • 400 pin bread board - to connect the wiring
  • L293D integrated circuit - to control the engines
  • 1 kΩ and 2 kΩ resistors - to reduce voltage between Arduino and BT module
  • 9V battery box - to power the Arduino board once on board the car
  • M-M DuPont cables - to wire everything together

The total price of those components is about €30, which is still less than what I paid for the LEGO engine and PF wires.

Let’s start with the Bluetooth module. There are some really nice guides online how to use them, I’ll try to describe it quickly here. The module has 4 pins: RX, TX, GND and VCC. GND can be connected directly to Arduino’s GND pin. VCC is power supply for the bluetooth module. You can connect it to the 5V pin on Arduino. Now for TX and RX pins. You could connect them to the RX and TX pins on the Arduino board, but that makes it hard to debug the program later, since all output from the program will go to the bluetooth module rather than our computer. Instead connect it to pins 2 and 3. Warning: you need to use a voltage divider for the RX pin, because Arduino operates on 5V, but the HC-06 module operates on 3.3V. You can do it by putting a 1kΩ resistor between Arduino pin 3 and HC-06 RX and 2kΩ resistor between Arduino GND and HC-06 RX pins.

Next comes up the L293D integrated circuit. This circuit will allow us to control the engines. While in theory we could hook up the engines directly to the Arduino board (there’s enough free pins), in practice it’s a bad idea. The engines need 9V to operate, which is a lot of power drain for the Arduino circuitry. Additionally, it would mean that the Arduino board and the engines would both be drawing power from the single 9V battery used to power the Arduino.

Instead, we use the L293D IC, where you connect external power source (the LEGO Battery pack in our case) to it as well as the engines and use only a low voltage signal from the Arduino to control the current from the external power source to the engines (very much like a transistor). The advantage of the L293D is that it can control up to 2 separate engines and it can also reverse the polarity, allowing to control direction of each engine.

Here’s schematics of the L293D:

L293D schematics

To sum it up, pin 1 (Enable 1,2) turns on the left half of the IC, pin 9 (Enable 3,4) turns on the right half of the IC. Hook it up to Arduino's 5V pin. Do the same with pin 16 (VCC1), which powers the overall integrated circuit. The external power source (the 9V from the LEGO Battery pack) is connected to pin 8 (VCC2). Pin 2 (Input 1) and pin 7 (Input 2) are connected to Arduino and are used to control the engines. Pin 3 (Output 1) and pin 6 (Output 2) are output pins that are connected to one of the LEGO engines. On the other side of the circuit, pin 10 (Input 3) and pin 15 (Input 4) are used to control the other LEGO engine, which is connected to pin 11 (Output 3) and pin 14 (Output 4). The remaining four pins in the middle (4, 5, 12 and 13 double as ground and heat sink, so connect them to GND (ideally both Arduino and the LEGO battery GND).

Since we have 9V LEGO Battery pack connected to VCC2, sending 5V from Arduino to Input 1 and 0V to Input 2 will cause 9V on Output 1 and 0V on Output 2 (the engine will spin clockwise). Sending 5V from Arduino to Input 2 and 0V to Input 1 will cause 9V to be on Output 2 and 0V on Output 1, making the engine rotate counterclockwise. Same goes for the other side of the IC. Simple!

Photo of all electronic components wired together Photo of all electronic components wired together


I also built a LEGO casing for the Arduino board and the breadboard to attach them to the car. With some effort I could probably rebuild the chassis to allow the casing to “sink” lower into the construction.

Photo of LEGO car with the electronics on board

The batterry packs (the LEGO Battery box and the 9V battery case for Arduino) are nicely hidden in the middle of the car on the sides next to the engines.

Photo of LEGO Battery Box Photo of Arduino 9V battery case

Now we are done with the hardware side - we have a LEGO car with two engines and all the electronics wired together and hooked up to the engines and battery. In the next part we will start writing software for the Arduino board so that we can control the LEGO engines programmatically. Stay tuned!

Taking a break

I’ve seen lots of posts like this in the past, never thought I’d be writing one myself.

I haven’t been very actively contributing to KDE for the past months. It’s been rather frustrating, because I felt like I have to contribute something, fix some bugs, finish some feature…but whenever I had the time to work on PIM, I just couldn’t bring myself to do anything. Instead I found myself running away to other projects or just playing games.

It took me a while to realize that the problem was that I was putting pressure on myself to contribute even though I did not feel like it. It turned from hobby and passion into a duty, and that’s wrong.

I think the main frustration comes from the feeling that I cannot innovate - I’m bound by various restrictions - libraries and languages I can use, APIs I must preserve/conform to, legacy behavior to not break anything for existing users… This has been taking away the fun. I have enough of this in my dayjob, thank you. So….

I decided to take a break from KDE PIM for a while. I’m sure I’ll be back at some point. But right now I feel like I gave it all I could and it’s still not where I’d like it to be and it’s no longer fun for me. What makes me very happy is the number of new contributors that have appeared over the past year or so.

Instead of hacking on KDE PIM I went back to some of my older projects - I improved Passilic, the Pass password manager frontend for Sailfish OS and revived my old Android app to sync Facebook events with Android calenar.

I also started playing with C++20 coroutines and how they could be used with Qt. The result is the QCoro library. I’ll blog about that soon and, hopefully, will talk about it in more depth in two months on Akademy (see, I’m not leaving completely 😉).

Finally, I spent the past week building a remote-controlled car using Lego, Arduino and a mobile app I wrote (with Qt, of course 😉). I’ll blog about that as well (spoiler alert: it’s fun!).

See y’all around!


Plasma Pass 1.2.0

Plasma Pass, a Plasma applet for the Pass password manager version 1.2.0 is out.

The applet now supports OTP codes (in the format supported by the pass OTP plugin). The ‘clock’ icon appears next to all passwords, even those that do not have OTP code. This is a limitation caused by the passwords being stored in files encrypted and being decrypted only when the user requests it - so the applet cannot know whether there’s an OTP code available in the password file until you click on it. There were also some small fixups and UI improvements.




SHA-256: 01f0b03b99e41c067295e7708d41bbe581c0d73e78d43b50bf86b4699969f780
SHA-1:   07a32d21b0c4dd38cad9c800d7b8f463f42c39c6


0ABDFA55A4E6BEA99A83EA974D69557AECB13683 Daniel Vrátil <dvratil@kde.org>

Feel free to report any issues or feature requests to KDE Bugzilla.

Static Code Analysis and GitLab CI

Few days ago I gave a talk on KDE Akademy about running static code analyzers in the KDE instance of GitLab. There I explained what static code analyzers are good for and why you want to use them. Then I showcased my progress implementing a GitLab CI jobs to automatically run clazy and clang-tidy on merge requests as well as individual git pushes to make it as easy for KDE developers as possible to add static analyzers to their projects.

Based on some feedback from the KDE sysadmins as well as the talk audience I have revamped the pipeline and the helper scripts, so let’s see how the pipeline works now and how you can add it to your project.

How It Works

The pipeline on GitLab CI can have multiple stages. Jobs in the same stage are executed in parallel and artifacts from the first stage are made available to jobs in the next stage. The default stage is the build stage where the project is, well, built to see if the code actually compiles. The entire “build” directory from this stage is than carried over to the static analysis job in the test stage. Thanks to that we no longer have to compile the project twice, once in the build job and once in the static analysis job.

Why do we need to make sure the project is built before applying static analysis? Because the static analyzers need the code to compile, so we need to make sure that all the generated include files (MOC files, UI header files, DBus adaptors etc.) exist - and so far I’ve been unable to find a better way to have those files generated than actually building the project.

There are two types of static analysis job: one for merge requests and one for regular pushes into the master branch and for manually triggered pipelines. The merge-request= job detects which C++ files have been changed in the branch and will only run the static analyzers for those jobs. This saves a lot of CPU time and makes the static analysis jobs to finish much faster than if we had to analyze the entire project every time.

The second job is used when someone just pushes directly into the master branch (the branch trigger can be customized, I’ll get to that later). The job only executes the static analyzers on files that have changed since the last push - again, no need to recheck the entire project over and over again. The only case when the static analyzers are ran for the entire project codebase is when the job is launched manually from the GitLab UI.

The job will run clazy and clang-tidy on each file, collect the output of the tools and convert them to codequality report which is then displayed in the GitLab merge request UI.

How To Enable It:

Create .gitlab-ci.yml file in the root of your git repository. Add the following content to it:

  - https://invent.kde.org/sysadmin/ci-tooling/raw/master/invent/ci-before.yml
  - https://invent.kde.org/sysadmin/ci-tooling/raw/master/invent/ci-<PRODUCT>-linux.yml
  - https://invent.kde.org/sysadmin/ci-tooling/raw/master/invent/ci-static-analysis.yml

Replace <PRODUCT> with applications, frameworks or extragear based on what “product” your project belongs to. If your project is not part of any of those group, you will need to experiment a bit more, or refer to the documentation on the wiki here [TODO]

Those includes will give you access to all the necessary job templates. The templates themselves do not create any jobs, you still need to define the jobs:

  extends: .static-analysis-linux-merge-request

  extends: .static-analysis-linux-commit

This creates two new jobs that inherit from the job templates. This is all you need to do. Once you commit and push, you should already see a new pipeline appear in GitLab. I recommend that you go and manually trigger a new pipeline to make sure you get an initial run with full check - it will probably throw a lot of warnings that you will want to fix, otherwise your future merge requests might fail on issues that are unrelated to the change itself.


The above is just a quick-start guideline. Go to the community wiki here to read in-depth documentation on how to configure and customize the static analysis jobs.

If you run into any issues with the integration, please let me know via email or try to catch me on IRC.

Happy analyzing! :)