8BiTs 매일 코딩 홈페이지. (Qt) Cross Thread Signal and Slots - 2 Get Code. Some times you see a signal is emitted in sender thread but connected slot doesn't called (in other words it doesn't receive signal), you have asked about it and finaly got that the connection type Qt::DirectConnection would fix it, so the problem found and everything is ok.

What Are Threads?

Threads are about doing things in parallel, just like processes. So how do threads differ from processes? While you are making calculations on a spreadsheet, there may also be a media player running on the same desktop playing your favorite song. Here is an example of two processes working in parallel: one running the spreadsheet program; one running a media player. Multitasking is a well known term for this. A closer look at the media player reveals that there are again things going on in parallel within one single process. While the media player is sending music to the audio driver, the user interface with all its bells and whistles is being constantly updated. This is what threads are for — concurrency within one single process.

So how is concurrency implemented? Parallel work on single core CPUs is an illusion which is somewhat similar to the illusion of moving images in cinema. For processes, the illusion is produced by interrupting the processor's work on one process after a very short time. Then the processor moves on to the next process. In order to switch between processes, the current program counter is saved and the next processor's program counter is loaded. This is not sufficient because the same needs to be done with registers and certain architecture and OS specific data.

Just as one CPU can power two or more processes, it is also possible to let the CPU run on two different code segments of one single process. When a process starts, it always executes one code segment and therefore the process is said to have one thread. However, the program may decide to start a second thread. Then, two different code sequences are processed simultaneously inside one process. Concurrency is achieved on single core CPUs by repeatedly saving program counters and registers then loading the next thread's program counters and registers. No cooperation from the program is required to cycle between the active threads. A thread may be in any state when the switch to the next thread occurs.

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The current trend in CPU design is to have several cores. A typical single-threaded application can make use of only one core. However, a program with multiple threads can be assigned to multiple cores, making things happen in a truly concurrent way. As a result, distributing work to more than one thread can make a program run much faster on multicore CPUs because additional cores can be used.

GUI Thread and Worker Thread

As mentioned, each program has one thread when it is started. This thread is called the 'main thread' (also known as the 'GUI thread' in Qt applications). The Qt GUI must run in this thread. All widgets and several related classes, for example QPixmap, don't work in secondary threads. A secondary thread is commonly referred to as a 'worker thread' because it is used to offload processing work from the main thread.

Simultaneous Access to Data

Each thread has its own stack, which means each thread has its own call history and local variables. Unlike processes, threads share the same address space. The following diagram shows how the building blocks of threads are located in memory. Program counter and registers of inactive threads are typically kept in kernel space. There is a shared copy of the code and a separate stack for each thread.

If two threads have a pointer to the same object, it is possible that both threads will access that object at the same time and this can potentially destroy the object's integrity. It's easy to imagine the many things that can go wrong when two methods of the same object are executed simultaneously.

Sometimes it is necessary to access one object from different threads; for example, when objects living in different threads need to communicate. Since threads use the same address space, it is easier and faster for threads to exchange data than it is for processes. Data does not have to be serialized and copied. Passing pointers is possible, but there must be a strict coordination of what thread touches which object. Simultaneous execution of operations on one object must be prevented. There are several ways of achieving this and some of them are described below. Casino buffets in mississippi.

So what can be done safely? All objects created in a thread can be used safely within that thread provided that other threads don't have references to them and objects don't have implicit coupling with other threads. Such implicit coupling may happen when data is shared between instances as with static members, singletons or global data. Familiarize yourself with the concept of thread safe and reentrant classes and functions.

Using Threads

There are basically two use cases for threads:

Make processing faster by making use of multicore processors.
Keep the GUI thread or other time critical threads responsive by offloading long lasting processing or blocking calls to other threads.

When to Use Alternatives to Threads

Developers need to be very careful with threads. It is easy to start other threads, but very hard to ensure that all shared data remains consistent. Problems are often hard to find because they may only show up once in a while or only on specific hardware configurations. Before creating threads to solve certain problems, possible alternatives should be considered.

Alternative	Comment
QEventLoop::processEvents()	Calling QEventLoop::processEvents() repeatedly during a time-consuming calculation prevents GUI blocking. However, this solution doesn't scale well because the call to processEvents() may occur too often, or not often enough, depending on hardware.
QTimer	Background processing can sometimes be done conveniently using a timer to schedule execution of a slot at some point in the future. A timer with an interval of 0 will time out as soon as there are no more events to process.
QSocketNotifierQNetworkAccessManagerQIODevice::readyRead()	This is an alternative to having one or multiple threads, each with a blocking read on a slow network connection. As long as the calculation in response to a chunk of network data can be executed quickly, this reactive design is better than synchronous waiting in threads. Reactive design is less error prone and energy efficient than threading. In many cases there are also performance benefits.

Qt Signal Slot Thread Safe

In general, it is recommended to only use safe and tested paths and to avoid introducing ad-hoc threading concepts. QtConcurrent provides an easy interface for distributing work to all of the processor's cores. The threading code is completely hidden in the QtConcurrent framework, so you don't have to take care of the details. However, QtConcurrent can't be used when communication with the running thread is needed, and it shouldn't be used to handle blocking operations.

Which Qt Thread Technology Should You Use?

Sometimes you want to do more than just running a method in the context of another thread. You may want to have an object which lives in another thread that provides a service to the GUI thread. Maybe you want another thread to stay alive forever to poll hardware ports and send a signal to the GUI thread when something noteworthy has happened. Qt provides different solutions for developing threaded applications. The right solution depends on the purpose of the new thread as well as on the thread's lifetime.

Lifetime of thread	Development task	Solution
One call	Run one method within another thread and quit the thread when the method is finished.	Qt provides different solutions: Write a function and run it with QtConcurrent::run() Derive a class from QRunnable and run it in the global thread pool with QThreadPool::globalInstance()->start() Derive a class from QThread, reimplement the QThread::run() method and use QThread::start() to run it.
One call	Operations are to be performed on all items of a container. Processing should be performed using all available cores. A common example is to produce thumbnails from a list of images.