This section contains snippets that were automatically translated from C++ to Python and may contain errors.
Demonstrates multi-thread programming using Qt.
The Semaphores example shows how to use
QSemaphore to control access to a circular buffer shared by a producer thread and a consumer thread.
The producer writes data to the buffer until it reaches the end of the buffer, at which point it restarts from the beginning, overwriting existing data. The consumer thread reads the data as it is produced and writes it to standard error.
Semaphores make it possible to have a higher level of concurrency than mutexes. If accesses to the buffer were guarded by a
QMutex , the consumer thread couldn’t access the buffer at the same time as the producer thread. Yet, there is no harm in having both threads working on different parts of the buffer at the same time.
The example comprises two classes:
Consumer. Both inherit from
QThread . The circular buffer used for communicating between these two classes and the semaphores that protect it are global variables.
An alternative to using
QSemaphore to solve the producer-consumer problem is to use
QMutex . This is what the Wait Conditions Example does.
Let’s start by reviewing the circular buffer and the associated semaphores:
DataSize = 100000 BufferSize = 8192 buffer[BufferSize] = char() freeBytes = QSemaphore(BufferSize) usedBytes = QSemaphore()
DataSize is the amount of data that the producer will generate. To keep the example as simple as possible, we make it a constant.
BufferSize is the size of the circular buffer. It is less than
DataSize, meaning that at some point the producer will reach the end of the buffer and restart from the beginning.
To synchronize the producer and the consumer, we need two semaphores. The
freeBytes semaphore controls the “free” area of the buffer (the area that the producer hasn’t filled with data yet or that the consumer has already read). The
usedBytes semaphore controls the “used” area of the buffer (the area that the producer has filled but that the consumer hasn’t read yet).
Together, the semaphores ensure that the producer is never more than
BufferSize bytes ahead of the consumer, and that the consumer never reads data that the producer hasn’t generated yet.
freeBytes semaphore is initialized with
BufferSize, because initially the entire buffer is empty. The
usedBytes semaphore is initialized to 0 (the default value if none is specified).
Let’s review the code for the
The producer generates
DataSize bytes of data. Before it writes a byte to the circular buffer, it must acquire a “free” byte using the
freeBytes semaphore. The
acquire() call might block if the consumer hasn’t kept up the pace with the producer.
At the end, the producer releases a byte using the
usedBytes semaphore. The “free” byte has successfully been transformed into a “used” byte, ready to be read by the consumer.
Let’s now turn to the
The code is very similar to the producer, except that this time we acquire a “used” byte and release a “free” byte, instead of the opposite.
The main() Function#
main(), we create the two threads and call
wait() to ensure that both threads get time to finish before we exit:
if __name__ == "__main__":
So what happens when we run the program? Initially, the producer thread is the only one that can do anything; the consumer is blocked waiting for the
usedBytes semaphore to be released (its initial
available() count is 0). Once the producer has put one byte in the buffer,
BufferSize - 1 and
usedBytes.available() is 1. At that point, two things can happen: Either the consumer thread takes over and reads that byte, or the producer thread gets to produce a second byte.
The producer-consumer model presented in this example makes it possible to write highly concurrent multithreaded applications. On a multiprocessor machine, the program is potentially up to twice as fast as the equivalent mutex-based program, since the two threads can be active at the same time on different parts of the buffer.
Be aware though that these benefits aren’t always realized. Acquiring and releasing a
QSemaphore has a cost. In practice, it would probably be worthwhile to divide the buffer into chunks and to operate on chunks instead of individual bytes. The buffer size is also a parameter that must be selected carefully, based on experimentation.