Python - Multithreaded Programming
Categories: Python
Running several threads is similar to running several different programs concurrently, but with the following benefits −
Multiple threads within a process share the same data space with the main thread and can therefore share information or communicate with each other more easily than if they were separate processes.
Threads sometimes called light-weight processes and they do not require much memory overhead; they are cheaper than processes.
A thread has a beginning, an execution sequence, and a conclusion. It has an instruction pointer that keeps track of where within its context it is currently running.
It can be pre-empted (interrupted)
It can temporarily be put on hold (also known as sleeping) while other threads are running - this is called yielding.
Starting a New Thread
To spawn another thread, you need to call following method available in thread module −
thread.start_new_thread ( function, args[, kwargs] )
This method call enables a fast and efficient way to create new threads in both Linux and Windows.
The method call returns immediately and the child thread starts and calls function with the passed list of args. When function returns, the thread terminates.
The Threading Module
The newer threading module included with Python 2.4 provides much more powerful, high-level support for threads than the thread module discussed in the previous section.
The threading module exposes all the methods of the thread module and provides some additional methods −
threading.activeCount() − Returns the number of thread objects that are active.
threading.currentThread() − Returns the number of thread objects in the caller's thread control.
threading.enumerate() − Returns a list of all thread objects that are currently active.