Multithreaded Programming In Python
What is Threading?
A thread of execution represents the most diminutive sequence of programmed instructions, capable of autonomous management by a scheduler, often integrated within the operating system. In the previous chapter, you can study in detail about... Threading in Python
What is Multithreading ?
Multithreading constitutes a fundamental concept within software programming, widely embraced by various high-level programming languages. Multithreaded programs bear resemblance to their single-threaded counterparts, differing primarily in their capacity to accommodate multiple concurrent threads of execution. These threads share process resources while retaining the ability to operate autonomously.
This architecture enables a single process to concurrently manage diverse "functions," optimizing hardware utilization, especially across multiple cores or processors. For instance, within a multithreaded operating system, simultaneous tasks like logging file modifications, data indexing, and window management can be efficiently executed.
Basic Multithreading Example
In this example, two threads are created using the threading.Thread class. Each thread runs a separate function, print_numbers() and print_letters(), and a delay is introduced using time.sleep(1) to visualize concurrency.
Thread Synchronization with Locks
Threads often share resources like variables or data. To avoid conflicts, locks are employed. Here's a simple counter example:
The counter_lock ensures that only one thread can increment the counter at a time, avoiding race conditions.
ThreadPoolExecutor for Concurrent Execution
Python's concurrent.futures module simplifies thread management. The ThreadPoolExecutor class allows executing functions concurrently.
Here, the ThreadPoolExecutor manages concurrent execution of the process_data() function over the provided data list.
Downloads images from the web | Multithreading in Python
Here is an example of a multithreaded program that downloads images from the web. The program uses three threads to download the images in parallel.
This program will download the three images in parallel. The download_image() function is executed in a separate thread for each image. The main() function starts the three threads and then waits for them to finish.
This program will be faster than a single-threaded program that downloads the images one at a time. The amount of speedup will depend on the number of cores on your CPU.
Multithreading in Python is a powerful technique to achieve parallelism and improve performance, particularly for tasks involving I/O-bound operations. However, it's essential to manage shared resources carefully to avoid issues like race conditions.