Python Multithreading Concepts: Threading Module, Priority Queue and Synchronizing Threads

Multithreading is a concept of processing multiple tasks simultaneously. The simple Thread concept is used to perform multithreading. A process and thread are not the same. A process is a set of programs that execute one by one. A thread is a flow of execution that can be scheduled as per the programmer’s requirement. In the operating system, the thread is the smallest unit of processing. A thread basically has some characteristics that stored I Thread Control Back or TCB.

• Thread Identifier is used to create a unique id for every new thread.
• The Stack pointer points the stack of thread in the process.
• The program counter is nothing but a register that is used to store the address of the currently executing thread.
• Thread state defines the state of a thread that it can be running, ready, waiting, start, or done state.
• Thread register is used to store computations of thread.
• The parent process pointer is a pointer that is used to process the process control block of the process.

Multithread:  Multithread is a way in which a processor can execute multiple threads concurrently. Every program has a main thread. In the process, multiple threads share the same memory space. For this reason, one thread can interact with other threads very efficiently. A thread does not require more memory spaces that is why it is known as light weighted in nature. 

The Threading Module:

The new thread module is introduced in Python which makes the multithreading process much easier and efficient. A thread class is implemented in this module that is used to create a new thread. There different types of methods are provided by Thread class and some of them are discussed below.

• The run() method is used as the entry point for a new thread in the threading process.
• The start() method is used to start a thread by calling the run( ) method.
• The join([time]) method is used to wait for threads to terminate.
• The isAlive() method is used to check whether a thread is still executing or the thread has done its execution and gone to the dead state.
• The getName() method is used to return the name of the currently executing thread.
• The setName() method is used to set the name of the currently executing thread.

Multithreaded Priority Queue:

In Python, the Queue module is also included for processing threads. There are some methods provided by the Queue module and they are discussed below.

• The get() is used to remove the currently executing item from the process queue and return it back.
• The put() method is used to add the item to a process queue.
• The qsize() method is used to return the number of items that are currently executing in the process queue.
• The empty() method is used to return the Boolean value. It returns True if the process queue is empty otherwise it returns False.
• The full() is also used to return the Boolean value. It returns True if the process queue is full otherwise it returns False.

Synchronizing Threads:

 In the multithreading concept, synchronization is used to ensure that two or more concurrent threads cannot execute simultaneously. This synchronization is used to avoid a critical situation that is occurred due to the same resource is accessed by the two or more threads. A simple locking mechanism is provided by the Thread module to perform synchronization. The acquire() method is used to run thread synchronously. The release() is used to release the locks of threads when it is no longer required.