


Python GIL and performance optimization of multi-threaded programming
1. python Introduction to GIL
Python GIL (Global Interpreter Lock) is the core mechanism of the Python interpreter. It ensures that only one thread is executing Python bytecode at the same time. . This is because the Python interpreter is a single-threaded interpreter and it can only execute one instruction at a time. The role of GIL is to prevent multiple threads from executing Python bytecode at the same time, thereby avoiding data races and program crashes.
2. Common scenarios of GIL competitionIn
Multi-threadedProgramming, GIL contention occurs when multiple threads try to execute Python bytecode at the same time. This causes the thread to wait before acquiring the GIL, affecting program performance. Common GIL competition scenarios include:
- Multiple threads access shared data simultaneously.
- Multiple threads call GIL-sensitive library functions at the same time.
- Multiple threads perform computationally intensive tasks simultaneously.
GIL competition can have a significant impact on the performance of multi-threaded programming. In severe cases, GIL contention can even lead to program deadlock. Here are some of the performance impacts of GIL competition:
- The time the thread waits to obtain the GIL increases.
- The execution time of GIL-sensitive library functions increases.
- Execution time of compute-intensive tasks increases.
Optimize GIL Competition
In order to minimize GIL competition, the following optimization measures can be taken:
- Reduce access to shared data.
- Avoid calling GIL-sensitive library functions at the same time.
- Decompose computing-intensive tasks into multiple subtasks and execute them in parallel using multi-threads.
- Use other techniques to minimize GIL competition, such as using multiple processes, using coroutines, etc.
Multiple processes is a way to create new processes in Python. New processes are independent of the current process and have their own memory space and threads. Therefore, multiple processes can be used to avoid GIL contention. The following is a code example that demonstrates how to use multiple processes to optimize GIL competition:
import multiprocessing def task(n): # 计算密集型任务 result = 0 for i in range(n): result += i return result if __name__ == "__main__": # 创建多个进程 processes = [] for i in range(4): p = multiprocessing.Process(target=task, args=(10000000,)) processes.append(p) # 启动所有进程 for p in processes: p.start() # 等待所有进程完成 for p in processes: p.join()
6. Use coroutines to optimize GIL competition
Coroutines are a way to create new coroutines in Python. Coroutines are similar to threads in that they also have their own state and execution stack. But unlike threads, coroutines are lightweight and they do not occupy system resources. Therefore, coroutines can be used to avoid GIL contention. The following is a code example that demonstrates how to use coroutines to optimize GIL competition:
import asyncio async def task(n): # 计算密集型任务 result = 0 for i in range(n): result += i return result async def main(): # 创建多个协程 tasks = [] for i in range(4): task_ = asyncio.create_task(task(10000000)) tasks.append(task_) # 启动所有协程 await asyncio.gather(*tasks) if __name__ == "__main__": asyncio.run(main())
The above is the detailed content of Python GIL and performance optimization of multi-threaded programming. For more information, please follow other related articles on the PHP Chinese website!

Hot AI Tools

Undresser.AI Undress
AI-powered app for creating realistic nude photos

AI Clothes Remover
Online AI tool for removing clothes from photos.

Undress AI Tool
Undress images for free

Clothoff.io
AI clothes remover

AI Hentai Generator
Generate AI Hentai for free.

Hot Article

Hot Tools

Notepad++7.3.1
Easy-to-use and free code editor

SublimeText3 Chinese version
Chinese version, very easy to use

Zend Studio 13.0.1
Powerful PHP integrated development environment

Dreamweaver CS6
Visual web development tools

SublimeText3 Mac version
God-level code editing software (SublimeText3)

Hot Topics



PHP and Python have their own advantages and disadvantages, and the choice depends on project needs and personal preferences. 1.PHP is suitable for rapid development and maintenance of large-scale web applications. 2. Python dominates the field of data science and machine learning.

Python and JavaScript have their own advantages and disadvantages in terms of community, libraries and resources. 1) The Python community is friendly and suitable for beginners, but the front-end development resources are not as rich as JavaScript. 2) Python is powerful in data science and machine learning libraries, while JavaScript is better in front-end development libraries and frameworks. 3) Both have rich learning resources, but Python is suitable for starting with official documents, while JavaScript is better with MDNWebDocs. The choice should be based on project needs and personal interests.

Docker uses Linux kernel features to provide an efficient and isolated application running environment. Its working principle is as follows: 1. The mirror is used as a read-only template, which contains everything you need to run the application; 2. The Union File System (UnionFS) stacks multiple file systems, only storing the differences, saving space and speeding up; 3. The daemon manages the mirrors and containers, and the client uses them for interaction; 4. Namespaces and cgroups implement container isolation and resource limitations; 5. Multiple network modes support container interconnection. Only by understanding these core concepts can you better utilize Docker.

VS Code can be used to write Python and provides many features that make it an ideal tool for developing Python applications. It allows users to: install Python extensions to get functions such as code completion, syntax highlighting, and debugging. Use the debugger to track code step by step, find and fix errors. Integrate Git for version control. Use code formatting tools to maintain code consistency. Use the Linting tool to spot potential problems ahead of time.

In VS Code, you can run the program in the terminal through the following steps: Prepare the code and open the integrated terminal to ensure that the code directory is consistent with the terminal working directory. Select the run command according to the programming language (such as Python's python your_file_name.py) to check whether it runs successfully and resolve errors. Use the debugger to improve debugging efficiency.

VS Code can run on Windows 8, but the experience may not be great. First make sure the system has been updated to the latest patch, then download the VS Code installation package that matches the system architecture and install it as prompted. After installation, be aware that some extensions may be incompatible with Windows 8 and need to look for alternative extensions or use newer Windows systems in a virtual machine. Install the necessary extensions to check whether they work properly. Although VS Code is feasible on Windows 8, it is recommended to upgrade to a newer Windows system for a better development experience and security.

VS Code extensions pose malicious risks, such as hiding malicious code, exploiting vulnerabilities, and masturbating as legitimate extensions. Methods to identify malicious extensions include: checking publishers, reading comments, checking code, and installing with caution. Security measures also include: security awareness, good habits, regular updates and antivirus software.

Python excels in automation, scripting, and task management. 1) Automation: File backup is realized through standard libraries such as os and shutil. 2) Script writing: Use the psutil library to monitor system resources. 3) Task management: Use the schedule library to schedule tasks. Python's ease of use and rich library support makes it the preferred tool in these areas.
