Does Python Support Multithreading Despite the Limitations of the GIL?-Python Tutorial-php.cn

Home

Backend Development

Python Tutorial

Does Python Support Multithreading Despite the Limitations of the GIL?

Barbara Streisand

Oct 19, 2024 pm 09:30 PM

Does Python Support Multithreading Despite the Limitations of the GIL?

Multithreading in Python: Unraveling Performance and the Role of the GIL

Multithreading is a technique that allows multiple processes to execute concurrently within a single program. For a programming language like Python, the question arises whether multithreading is supported and if it can enhance execution speed.

Multithreading in Python: A Paradoxical Situation

Contrary to common belief, Python does indeed support multithreading through its threading module. However, a persistent question lingers: why do many claim that Python is locked by the Global Interpreter Lock (GIL) and that only one thread can run at a time?

The answer lies in the nature of the GIL. The GIL is a lock that prevents multiple Python threads from executing Python code simultaneously. However, the GIL does not restrict threads from executing non-Python code, such as I/O operations or code in C extensions.

GIL's Effect on Performance: Unmasking the Truth

The GIL significantly impacts multithreading performance for computationally intensive Python operations. Because only one thread can execute Python code at a time, parallelizing such operations using multithreading will not yield speed improvements.

When Multithreading Shines: Practical Applications

Despite the limitations imposed by the GIL, multithreading offers advantages in scenarios where Python code interacts with I/O or external libraries. For instance, multithreading can significantly improve responsiveness in GUI applications and optimize web servers to handle concurrent client requests.

Conclusion: Unleashing Enhanced Performance with Discernment

While multithreading in Python has limitations due to the GIL, it remains a valuable tool for optimizing performance in appropriate contexts. By leveraging I/O operations and C extensions, programmers can harness the benefits of multithreading to expedite certain computational tasks.

The above is the detailed content of Does Python Support Multithreading Despite the Limitations of the GIL?. For more information, please follow other related articles on the PHP Chinese website!

Statement

The content of this article is voluntarily contributed by netizens, and the copyright belongs to the original author. This site does not assume corresponding legal responsibility. If you find any content suspected of plagiarism or infringement, please contact admin@php.cn

How to Use Python to Find the Zipf Distribution of a Text FileMar 05, 2025 am 09:58 AM

This tutorial demonstrates how to use Python to process the statistical concept of Zipf's law and demonstrates the efficiency of Python's reading and sorting large text files when processing the law. You may be wondering what the term Zipf distribution means. To understand this term, we first need to define Zipf's law. Don't worry, I'll try to simplify the instructions. Zipf's Law Zipf's law simply means: in a large natural language corpus, the most frequently occurring words appear about twice as frequently as the second frequent words, three times as the third frequent words, four times as the fourth frequent words, and so on. Let's look at an example. If you look at the Brown corpus in American English, you will notice that the most frequent word is "th

How Do I Use Beautiful Soup to Parse HTML?Mar 10, 2025 pm 06:54 PM

This article explains how to use Beautiful Soup, a Python library, to parse HTML. It details common methods like find(), find_all(), select(), and get_text() for data extraction, handling of diverse HTML structures and errors, and alternatives (Sel

How to Perform Deep Learning with TensorFlow or PyTorch?Mar 10, 2025 pm 06:52 PM

This article compares TensorFlow and PyTorch for deep learning. It details the steps involved: data preparation, model building, training, evaluation, and deployment. Key differences between the frameworks, particularly regarding computational grap

Serialization and Deserialization of Python Objects: Part 1Mar 08, 2025 am 09:39 AM

Serialization and deserialization of Python objects are key aspects of any non-trivial program. If you save something to a Python file, you do object serialization and deserialization if you read the configuration file, or if you respond to an HTTP request. In a sense, serialization and deserialization are the most boring things in the world. Who cares about all these formats and protocols? You want to persist or stream some Python objects and retrieve them in full at a later time. This is a great way to see the world on a conceptual level. However, on a practical level, the serialization scheme, format or protocol you choose may determine the speed, security, freedom of maintenance status, and other aspects of the program

Mathematical Modules in Python: StatisticsMar 09, 2025 am 11:40 AM

Python's statistics module provides powerful data statistical analysis capabilities to help us quickly understand the overall characteristics of data, such as biostatistics and business analysis. Instead of looking at data points one by one, just look at statistics such as mean or variance to discover trends and features in the original data that may be ignored, and compare large datasets more easily and effectively. This tutorial will explain how to calculate the mean and measure the degree of dispersion of the dataset. Unless otherwise stated, all functions in this module support the calculation of the mean() function instead of simply summing the average. Floating point numbers can also be used. import random import statistics from fracti

What are some popular Python libraries and their uses?Mar 21, 2025 pm 06:46 PM

The article discusses popular Python libraries like NumPy, Pandas, Matplotlib, Scikit-learn, TensorFlow, Django, Flask, and Requests, detailing their uses in scientific computing, data analysis, visualization, machine learning, web development, and H

Scraping Webpages in Python With Beautiful Soup: Search and DOM ModificationMar 08, 2025 am 10:36 AM

This tutorial builds upon the previous introduction to Beautiful Soup, focusing on DOM manipulation beyond simple tree navigation. We'll explore efficient search methods and techniques for modifying HTML structure. One common DOM search method is ex

How to Create Command-Line Interfaces (CLIs) with Python?Mar 10, 2025 pm 06:48 PM

This article guides Python developers on building command-line interfaces (CLIs). It details using libraries like typer, click, and argparse, emphasizing input/output handling, and promoting user-friendly design patterns for improved CLI usability.

See all articles