最近遇到一个问题,是指定参数来运行某个特定的进程,这很类似Linux中一些命令的参数了,比如ls -a,为什么加上-a选项会响应。optparse模块实现的也是类似的功能,它是为脚本传递命令参数。
使用此模块前,首先需要导入模块中的类OptionParser,然后创建它的一个实例(对象):
from optparse import OptionParser
parser = OptionParser() #这里也可以定义类的参数,后续有
接着就可以添加选项了,基本语法:
parser.add_option(opt_str, ...,
attr=value, ...)
每个opt_str可以有多个选项字符串,比如-f 和--file(就行Linux命令行中ls -a和ls --all效果一样),只要定义了这些选项,则在命令行输入的时候这些选项就会被识别,否则报错。opt_str的定义可以如下:
parser.add_option("-f", "--file", ...) #-f 和 --file 是作为调用时的参数的标签,会被识别
当选项被定义好后,则可以调用parse_args()函数来获取我们定义的选项和参数
(options, args) = parser.parse_args() #parse_args可以有参数,不定义的话使用默认的sys.argv[1:]
parse_args()返回两个值,一个是选项options(如:-f),另一个是参数args,即除选项options以外的值(如:test.txt)
add_option中最重要的四个option的属性是:action,type,dest(destination),help。这四个中action又是最基础的。
action参数(附带介绍了type、dest):
action参数告诉optparse该做什么当它在命令行中遇到选项时。action有三种存储方式:store、store_false、store_true。如果不指定action的值,默认的是store,它告诉optparse将继续读取下一个参数(type),保证类型的正确性,并将它将值存储在一个变量(dest)中,即将命令行中输入的字符串将它存为options的属性,这样可以直接调用。啰嗦了一大堆,我自己都被搞晕了~~~~,先看个例子吧!
>>> parser.add_option("-f", "--file",action="store", type="string", dest="filename")

Python and C each have their own advantages, and the choice should be based on project requirements. 1) Python is suitable for rapid development and data processing due to its concise syntax and dynamic typing. 2)C is suitable for high performance and system programming due to its static typing and manual memory management.

Choosing Python or C depends on project requirements: 1) If you need rapid development, data processing and prototype design, choose Python; 2) If you need high performance, low latency and close hardware control, choose C.

By investing 2 hours of Python learning every day, you can effectively improve your programming skills. 1. Learn new knowledge: read documents or watch tutorials. 2. Practice: Write code and complete exercises. 3. Review: Consolidate the content you have learned. 4. Project practice: Apply what you have learned in actual projects. Such a structured learning plan can help you systematically master Python and achieve career goals.

Methods to learn Python efficiently within two hours include: 1. Review the basic knowledge and ensure that you are familiar with Python installation and basic syntax; 2. Understand the core concepts of Python, such as variables, lists, functions, etc.; 3. Master basic and advanced usage by using examples; 4. Learn common errors and debugging techniques; 5. Apply performance optimization and best practices, such as using list comprehensions and following the PEP8 style guide.

Python is suitable for beginners and data science, and C is suitable for system programming and game development. 1. Python is simple and easy to use, suitable for data science and web development. 2.C provides high performance and control, suitable for game development and system programming. The choice should be based on project needs and personal interests.

Python is more suitable for data science and rapid development, while C is more suitable for high performance and system programming. 1. Python syntax is concise and easy to learn, suitable for data processing and scientific computing. 2.C has complex syntax but excellent performance and is often used in game development and system programming.

It is feasible to invest two hours a day to learn Python. 1. Learn new knowledge: Learn new concepts in one hour, such as lists and dictionaries. 2. Practice and exercises: Use one hour to perform programming exercises, such as writing small programs. Through reasonable planning and perseverance, you can master the core concepts of Python in a short time.

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.


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

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

Hot Article

Hot Tools

MantisBT
Mantis is an easy-to-deploy web-based defect tracking tool designed to aid in product defect tracking. It requires PHP, MySQL and a web server. Check out our demo and hosting services.

Dreamweaver Mac version
Visual web development tools

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

PhpStorm Mac version
The latest (2018.2.1) professional PHP integrated development tool

WebStorm Mac version
Useful JavaScript development tools