Python 条件语句
Python条件语句是通过一条或多条语句的执行结果(True或者False)来决定执行的代码块。
可以通过下图来简单了解条件语句的执行过程:
Python程序语言指定任何非0和非空(null)值为true,0 或者 null为false。
Python 编程中 if 语句用于控制程序的执行,基本形式为:
if 判断条件: 执行语句…… else: 执行语句……
其中"判断条件"成立时(非零),则执行后面的语句,而执行内容可以多行,以缩进来区分表示同一范围。
else 为可选语句,当需要在条件不成立时执行内容则可以执行相关语句,具体例子如下:
#!/usr/bin/python # -*- coding: UTF-8 -*- # 例1:if 基本用法 flag = False name = 'luren' if name == 'python': # 判断变量否为'python' flag = True # 条件成立时设置标志为真 print 'welcome boss' # 并输出欢迎信息 else: print name # 条件不成立时输出变量名称
输出结果为:
>>> luren # 输出结果
if 语句的判断条件可以用>(大于)、=(大于等于)、
当判断条件为多个值是,可以使用以下形式:
if 判断条件1: 执行语句1…… elif 判断条件2: 执行语句2…… elif 判断条件3: 执行语句3…… else: 执行语句4……
实例如下:
#!/usr/bin/python # -*- coding: UTF-8 -*- # 例2:elif用法 num = 5 if num == 3: # 判断num的值 print 'boss' elif num == 2: print 'user' elif num == 1: print 'worker' elif num < 0: # 值小于零时输出 print 'error' else: print 'roadman' # 条件均不成立时输出
输出结果为:
>>> roadman # 输出结果
由于 python 并不支持 switch 语句,所以多个条件判断,只能用 elif 来实现,如果判断需要多个条件需同时判断时,可以使用 or (或),表示两个条件有一个成立时判断条件成功;使用 and (与)时,表示只有两个条件同时成立的情况下,判断条件才成功。
#!/usr/bin/python # -*- coding: UTF-8 -*- # 例3:if语句多个条件 num = 9 if num >= 0 and num <= 10: # 判断值是否在0~10之间 print 'hello' >>> hello # 输出结果 num = 10 if num < 0 or num > 10: # 判断值是否在小于0或大于10 print 'hello' else: print 'undefine' >>> undefine # 输出结果 num = 8 # 判断值是否在0~5或者10~15之间 if (num >= 0 and num <= 5) or (num >= 10 and num <= 15): print 'hello' else: print 'undefine' >>> undefine # 输出结果
当if有多个条件时可使用括号来区分判断的先后顺序,括号中的判断优先执行,此外 and 和 or 的优先级低于>(大于)、
简单的语句组
你也可以在同一行的位置上使用if条件判断语句,如下实例:
#!/usr/bin/python # -*- coding: UTF-8 -*- var = 100 if ( var == 100 ) : print "变量 var 的值为100" print "Good bye!"
以上代码执行输出结果如下:
变量 var 的值为100 Good bye!
Python运算符优先级
以下表格列出了从最高到最低优先级的所有运算符:
以下实例演示了Python所有运算符优先级的操作:
#!/usr/bin/python a = 20 b = 10 c = 15 d = 5 e = 0 e = (a + b) * c / d #( 30 * 15 ) / 5 print "Value of (a + b) * c / d is ", e e = ((a + b) * c) / d # (30 * 15 ) / 5 print "Value of ((a + b) * c) / d is ", e e = (a + b) * (c / d); # (30) * (15/5) print "Value of (a + b) * (c / d) is ", e e = a + (b * c) / d; # 20 + (150/5) print "Value of a + (b * c) / d is ", e
以上实例输出结果:
Value of (a + b) * c / d is 90 Value of ((a + b) * c) / d is 90 Value of (a + b) * (c / d) is 90 Value of a + (b * c) / d is 50

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 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'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.

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 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.

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.

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 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.


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

SublimeText3 Chinese version
Chinese version, very easy to use

MinGW - Minimalist GNU for Windows
This project is in the process of being migrated to osdn.net/projects/mingw, you can continue to follow us there. MinGW: A native Windows port of the GNU Compiler Collection (GCC), freely distributable import libraries and header files for building native Windows applications; includes extensions to the MSVC runtime to support C99 functionality. All MinGW software can run on 64-bit Windows platforms.

Dreamweaver CS6
Visual web development tools

mPDF
mPDF is a PHP library that can generate PDF files from UTF-8 encoded HTML. The original author, Ian Back, wrote mPDF to output PDF files "on the fly" from his website and handle different languages. It is slower than original scripts like HTML2FPDF and produces larger files when using Unicode fonts, but supports CSS styles etc. and has a lot of enhancements. Supports almost all languages, including RTL (Arabic and Hebrew) and CJK (Chinese, Japanese and Korean). Supports nested block-level elements (such as P, DIV),

Zend Studio 13.0.1
Powerful PHP integrated development environment