


Fallout from the GIL: Unintended consequences in concurrent Python
Mar 02, 2024 pm 04:28 PMpython is a powerful and versatile programming language with extensive libraries and frameworks that make it Becoming a popular choice for data science, machine learning, and other compute-intensive tasks. However, Python's parallel processing capabilities are limited by the Global Interpreter Lock (GIL), which can lead to unintended consequences in some cases.
The role of GIL
GIL is a lightweight locking mechanism that ensures that the Python interpreter can only execute onethread at the same time. This means that multiple threads cannot execute Python bytecode at the same time, thus avoiding race conditions in which shared data is modified at the same time. The GIL is critical to the stability of the interpreter and data integrity.
Unintended Consequences of Concurrency
Although the GIL is important to ensuresecurity, it can also have a negative impact on concurrency performance. When multiple threads compete on the GIL, they may experience blocking and delays. This is especially problematic for computationally intensive tasks where a large number of parallel tasks are performed simultaneously.
Sample code
The following code demonstrates how using the GIL in Python can lead to unintended consequences:
import threading def increment_counter(counter): for _ in range(1000000): counter += 1 def main(): counter = 0 threads = [] # 创建并启动 10 个线程 for _ in range(10): threads.append(threading.Thread(target=increment_counter, args=(counter,))) threads[-1].start() # 等待所有线程完成 for thread in threads: thread.join() print(counter) if __name__ == "__main__": main()
Avoid GIL
For applications that requirehigh concurrency , the GIL can be circumvented by the following methods:
- Using multi-process: Multi-process allows independent processes to be run in parallel, each with its own GIL.
- Using Cython: Cython can compile Python code to C or c code, thereby removing the limitations of the GIL.
- Using coroutines: Coroutines allow function execution to be paused and resumed within a single thread without the need for the GIL.
in conclusion
GIL is an important mechanism to ensure thread safety in Python. However, it can also have unintended consequences on concurrency performance.Programmers should understand the limitations of the GIL and choose an appropriate concurrency strategy based on application needs. By using multi-processing, Cython, or coroutines, you can circumvent the limitations of the GIL and take full advantage of Python's parallel processing capabilities.
The above is the detailed content of Fallout from the GIL: Unintended consequences in concurrent Python. For more information, please follow other related articles on the PHP Chinese website!

Hot Article

Hot tools Tags

Hot Article

Hot Article Tags

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

What are the advantages and disadvantages of templating?

Google AI announces Gemini 1.5 Pro and Gemma 2 for developers

What language is the browser plug-in written in?
