search
HomeBackend DevelopmentPython TutorialPython进程通信之匿名管道实例讲解

匿名管道

管道是一个单向通道,有点类似共享内存缓存.管道有两端,包括输入端和输出端.对于一个进程的而言,它只能看到管道一端,即要么是输入端要么是输出端.

os.pipe()返回2个文件描述符(r, w),表示可读的和可写的.示例代码如下:

代码如下:


#!/usr/bin/python
import time
import os

def child(wpipe):
    print('hello from child', os.getpid())
    while True:
        msg = 'how are you\n'.encode()
        os.write(wpipe, msg)
        time.sleep(1)

def parent():
    rpipe, wpipe = os.pipe()
    pid = os.fork()
    if pid == 0:
        child(wpipe)
        assert False, 'fork child process error!'
    else:
        os.close(wpipe)
        print('hello from parent', os.getpid(), pid)
        fobj = os.fdopen(rpipe, 'r')
        while True:
            recv = os.read(rpipe, 32)
            print recv

parent()


输出如下:

代码如下:


('hello from parent', 5053, 5054)
('hello from child', 5054)
how are you

how are you

how are you

how are you

我们也可以改进代码,不用os.read()从管道中读取二进制字节,而是从文件对象中读取字符串.这时需要用到os.fdopen()把底层的文件描述符(管道)包装成文件对象,然后再用文件对象中的readline()方法读取.这里请注意文件对象的readline()方法总是读取有换行符'\n'的一行,而且连换行符也读取出来.还有一点要改进的地方是,把父进程和子进程的管道中不用的一端关闭掉.

代码如下:


#!/usr/bin/python
import time
import os

def child(wpipe):
    print('hello from child', os.getpid())
    while True:
        msg = 'how are you\n'.encode()
        os.write(wpipe, msg)
        time.sleep(1)

def parent():
    rpipe, wpipe = os.pipe()
    pid = os.fork()
    if pid == 0:
        os.close(rpipe)
        child(wpipe)
        assert False, 'fork child process error!'
    else:
        os.close(wpipe)
        print('hello from parent', os.getpid(), pid)
        fobj = os.fdopen(rpipe, 'r')
        while True:
            recv = fobj.readline()[:-1]
            print recv

parent()

输出如下:

代码如下:


('hello from parent', 5108, 5109)
('hello from child', 5109)
how are you
how are you
how are you


如果要与子进程进行双向通信,只有一个pipe管道是不够的,需要2个pipe管道才行.以下示例在父进程新建了2个管道,然后再fork子进程.os.dup2()实现输出和输入的重定向.spawn功能类似于subprocess.Popen(),既能发送消息给子进程,由能从子子进程获取返回数据.

代码如下:


#!/usr/bin/python
#coding=utf-8
import os, sys

def spawn(prog, *args):
    stdinFd = sys.stdin.fileno()
    stdoutFd = sys.stdout.fileno()

    parentStdin, childStdout = os.pipe()
    childStdin, parentStdout= os.pipe()

    pid = os.fork()
    if pid:
        os.close(childStdin)
        os.close(childStdout)
        os.dup2(parentStdin, stdinFd)#输入流绑定到管道,将输入重定向到管道一端parentStdin
        os.dup2(parentStdout, stdoutFd)#输出流绑定到管道,发送到子进程childStdin
    else:
        os.close(parentStdin)
        os.close(parentStdout)
        os.dup2(childStdin, stdinFd)#输入流绑定到管道
        os.dup2(childStdout, stdoutFd)
        args = (prog, ) + args
        os.execvp(prog, args)
        assert False, 'execvp failed!'

if __name__ == '__main__':
    mypid = os.getpid()
    spawn('python', 'pipetest.py', 'spam')

    print 'Hello 1 from parent', mypid #打印到输出流parentStdout, 经管道发送到子进程childStdin
    sys.stdout.flush()
    reply = raw_input()
    sys.stderr.write('Parent got: "%s"\n' % reply)#stderr没有绑定到管道上

    print 'Hello 2 from parent', mypid
    sys.stdout.flush()
    reply = sys.stdin.readline()#另外一种方式获得子进程返回信息
    sys.stderr.write('Parent got: "%s"\n' % reply[:-1])

pipetest.py代码如下:

代码如下:


#coding=utf-8
import os, time, sys

mypid = os.getpid()
parentpid = os.getppid()
sys.stderr.write('child %d of %d got arg: "%s"\n' %(mypid, parentpid, sys.argv[1]))

for i in range(2):
    time.sleep(3)
    recv = raw_input()#从管道获取数据,来源于父经常stdout
    time.sleep(3)
    send = 'Child %d got: [%s]' % (mypid, recv)
    print(send)#stdout绑定到管道上,发送到父进程stdin
    sys.stdout.flush()

输出:

代码如下:


child 7265 of 7264 got arg: "spam"
Parent got: "Child 7265 got: [Hello 1 from parent 7264]"
Parent got: "Child 7265 got: [Hello 2 from parent 7264]"

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
Python vs. C  : Learning Curves and Ease of UsePython vs. C : Learning Curves and Ease of UseApr 19, 2025 am 12:20 AM

Python is easier to learn and use, while C is more powerful but complex. 1. Python syntax is concise and suitable for beginners. Dynamic typing and automatic memory management make it easy to use, but may cause runtime errors. 2.C provides low-level control and advanced features, suitable for high-performance applications, but has a high learning threshold and requires manual memory and type safety management.

Python vs. C  : Memory Management and ControlPython vs. C : Memory Management and ControlApr 19, 2025 am 12:17 AM

Python and C have significant differences in memory management and control. 1. Python uses automatic memory management, based on reference counting and garbage collection, simplifying the work of programmers. 2.C requires manual management of memory, providing more control but increasing complexity and error risk. Which language to choose should be based on project requirements and team technology stack.

Python for Scientific Computing: A Detailed LookPython for Scientific Computing: A Detailed LookApr 19, 2025 am 12:15 AM

Python's applications in scientific computing include data analysis, machine learning, numerical simulation and visualization. 1.Numpy provides efficient multi-dimensional arrays and mathematical functions. 2. SciPy extends Numpy functionality and provides optimization and linear algebra tools. 3. Pandas is used for data processing and analysis. 4.Matplotlib is used to generate various graphs and visual results.

Python and C  : Finding the Right ToolPython and C : Finding the Right ToolApr 19, 2025 am 12:04 AM

Whether to choose Python or C depends on project requirements: 1) Python is suitable for rapid development, data science, and scripting because of its concise syntax and rich libraries; 2) C is suitable for scenarios that require high performance and underlying control, such as system programming and game development, because of its compilation and manual memory management.

Python for Data Science and Machine LearningPython for Data Science and Machine LearningApr 19, 2025 am 12:02 AM

Python is widely used in data science and machine learning, mainly relying on its simplicity and a powerful library ecosystem. 1) Pandas is used for data processing and analysis, 2) Numpy provides efficient numerical calculations, and 3) Scikit-learn is used for machine learning model construction and optimization, these libraries make Python an ideal tool for data science and machine learning.

Learning Python: Is 2 Hours of Daily Study Sufficient?Learning Python: Is 2 Hours of Daily Study Sufficient?Apr 18, 2025 am 12:22 AM

Is it enough to learn Python for two hours a day? It depends on your goals and learning methods. 1) Develop a clear learning plan, 2) Select appropriate learning resources and methods, 3) Practice and review and consolidate hands-on practice and review and consolidate, and you can gradually master the basic knowledge and advanced functions of Python during this period.

Python for Web Development: Key ApplicationsPython for Web Development: Key ApplicationsApr 18, 2025 am 12:20 AM

Key applications of Python in web development include the use of Django and Flask frameworks, API development, data analysis and visualization, machine learning and AI, and performance optimization. 1. Django and Flask framework: Django is suitable for rapid development of complex applications, and Flask is suitable for small or highly customized projects. 2. API development: Use Flask or DjangoRESTFramework to build RESTfulAPI. 3. Data analysis and visualization: Use Python to process data and display it through the web interface. 4. Machine Learning and AI: Python is used to build intelligent web applications. 5. Performance optimization: optimized through asynchronous programming, caching and code

Python vs. C  : Exploring Performance and EfficiencyPython vs. C : Exploring Performance and EfficiencyApr 18, 2025 am 12:20 AM

Python is better than C in development efficiency, but C is higher in execution performance. 1. Python's concise syntax and rich libraries improve development efficiency. 2.C's compilation-type characteristics and hardware control improve execution performance. When making a choice, you need to weigh the development speed and execution efficiency based on project needs.

See all articles

Hot AI Tools

Undresser.AI Undress

Undresser.AI Undress

AI-powered app for creating realistic nude photos

AI Clothes Remover

AI Clothes Remover

Online AI tool for removing clothes from photos.

Undress AI Tool

Undress AI Tool

Undress images for free

Clothoff.io

Clothoff.io

AI clothes remover

Video Face Swap

Video Face Swap

Swap faces in any video effortlessly with our completely free AI face swap tool!

Hot Tools

SublimeText3 Linux new version

SublimeText3 Linux new version

SublimeText3 Linux latest version

Dreamweaver Mac version

Dreamweaver Mac version

Visual web development tools

ZendStudio 13.5.1 Mac

ZendStudio 13.5.1 Mac

Powerful PHP integrated development environment

SecLists

SecLists

SecLists is the ultimate security tester's companion. It is a collection of various types of lists that are frequently used during security assessments, all in one place. SecLists helps make security testing more efficient and productive by conveniently providing all the lists a security tester might need. List types include usernames, passwords, URLs, fuzzing payloads, sensitive data patterns, web shells, and more. The tester can simply pull this repository onto a new test machine and he will have access to every type of list he needs.

SublimeText3 Mac version

SublimeText3 Mac version

God-level code editing software (SublimeText3)