Python ThreadPool
A thread pool is a collection of threads that are created in advance and can be reused to execute multiple tasks. The concurrent.futures module in Python provides a ThreadPoolExecutor class that makes it easy to create and manage a thread pool.
In this example, we define a function worker that will run in a thread. We create a ThreadPoolExecutor with a maximum of 2 worker threads. We then submit two tasks to the pool using the submit method. The pool manages the execution of the tasks in its worker threads. We use the shutdown method to wait for all tasks to complete before the main thread continues.
Multithreading can help you make your programs more efficient and responsive. However, it’s important to be careful when working with threads to avoid issues such as race conditions and deadlocks.
This code uses a thread pool created with concurrent.futures.ThreadPoolExecutor to run two worker tasks concurrently. The main thread waits for the worker threads to finish using pool.shutdown(wait=True). This allows for efficient parallel processing of tasks in a multi-threaded environment.
Python3
import concurrent.futuresdef worker(): print("Worker thread running")pool = concurrent.futures.ThreadPoolExecutor(max_workers=2)pool.submit(worker)pool.submit(worker)pool.shutdown(wait=True)print("Main thread continuing to run") |
Worker thread running Worker thread running Main thread continuing to run
Multithreading in Python
This article covers the basics of multithreading in Python programming language. Just like multiprocessing, multithreading is a way of achieving multitasking. In multithreading, the concept of threads is used. Let us first understand the concept of thread in computer architecture.
Contact Us