In the previous chapter, we learned some basic methods of Python multi-process programming: Using the process, Pool, Queue, Lock, pipe, and other classes provided by the cross-platform multi-process module multiprocessing, to achieve child process creation, Process pools (batch creation of child processes and managing the maximum number of child processes) and interprocess communication. This chapter learns the multithreaded programming approach under Python. The threading thread is the smallest unit on which the operating system performs tasks. The threading module is available in the Python standard library and provides easy support for multithreaded programming. Here is the code to implement multithreading using threading: 1 #!/usr/bin/python 2 #-*-Coding:utf-8-* 3 author = ' Zni.feng ' 4 import&
1. Summarize multi-process module instances
Introduction: In the previous chapter, we learned some basic methods of Python multi-process programming: Using the process, Pool, Queue, Lock, pipe and other classes provided by the cross-platform multi-process module multiprocessing, we realized the child process creation, Process pools (batch creation of child processes and managing the maximum number of child processes) and interprocess communication. This chapter learns the multithreaded programming approach under Python. The threading thread is the smallest unit on which the operating system performs tasks. Threading modules are available in the Python standard library ...
2. Python multi-process and multithreaded instances (ii) Programming methods
Introduction: In the previous chapter, we learned some basic methods of Python multi-process programming: Using the process, Pool, Queue, Lock, pipe and other classes provided by the cross-platform multi-process module multiprocessing, we realized the child process creation, Process pools (batch creation of child processes and managing the maximum number of child processes) and interprocess communication. This chapter learns the multithreaded programming approach under Python.
3. Python thread pool/process pool for concurrent programming
Introduction: Introduction The Python standard library provides us with the threading and multiprocessing modules to write the corresponding multithreaded/multi-process code, but when the project reaches a certain scale, frequent creation/destruction of processes or threads is very resource-intensive, At this point we are going to write our own pool of threads/processes to change the time in space. But starting with Python3.2, the standard library provides us with the Concurrent.futures module
4. Python thread pool/process pool for concurrent programming
Introduction: Introduction The Python standard library provides us with the threading and multiprocessing modules to write the corresponding multithreaded/multi-process code, but when the project reaches a certain scale, frequent creation/destruction of processes or threads is very resource-intensive, At this point we are going to write our own pool of threads/processes to change the time in space. But starting with Python3.2, the standard library provides us with the Concurrent.futures module, which provides Threadpoolexecutor and processpoolexecutor two classes for THR.
5. Detailed description of the thread pool/process pool for Python concurrent programming
Introduction: Introduction The Python standard library provides us with the threading and multiprocessing modules to write the corresponding multithreaded/multi-process code, but when the project reaches a certain scale, frequent creation/destruction of processes or threads is very resource-intensive, At this point we are going to write our own pool of threads/processes to change the time in space. But starting with Python3.2, the standard library provides us with the Concurrent.futures module, which provides Threadpoolexecutor and processpoolexecutor two classes for THR.
6. Python Custom Process Pool instance analysis "producer, consumer model issues"
Introduction: This article mainly introduces the Python custom process pool, combined with an example of Python using a custom process pool implementation of the producer, consumer model problems, the need for friends can refer to the following
7. Nginx-How to configure multiple php-cgi process pools
Introduction: Assuming Nginx has 6 subdomains, does that mean I have to open 6 phpcgi process pool? Like 127.0.0.1:9005.
8. The path of PHP concurrent IO programming
Introduction:: PHP Concurrent IO Programming Path: Original link: http://rango.swoole.com/archives/508 First, the introduction concurrent IO problem has been a technical problem in server-side programming, from the earliest synchronization to block the direct fork process, to the worker process pool /thread pool, to the present asynchronous Io, the coprocessor. PHP programmer because there is a strong lamp framework, the knowledge of this kind of low-level information is very little, the purpose of this article is to introduce PHP for concurrent IO programming of various attempts, and finally introduce the use of Swoole, in a comprehensive analysis of the concurrent IO Q
9. A hodgepodge of PHP optimizations
Summary: PHP optimization of the PHP optimization of the article is often to teach you how to write efficient code, this article intends to discuss the issue from another perspective, teach you how to configure an efficient environment, so the same can achieve the goal of optimization. A frustrating news for pool is that the vast majority of PHP programmers ignore the value of pools. The pool mentioned here is not a database connection pool, but a process pool, PHP allows multiple pools to be started at the same time, and each pool uses a different configuration
Introduction to the multi-process (multiprocessing package) of the Python standard library
Introduction: This article mainly introduces the Python standard library multi-process (multiprocessing package) Introduction, this article explains the process pool, shared resources, shared memory, manager and other content, the need for friends can refer to the following
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