search
HomeBackend DevelopmentPython Tutorial简单讲解Python中的字符串与字符串的输入输出

字符串
字符串用''或者""括起来,如果字符串内部有‘或者",需要使用\进行转义

>>> print 'I\'m ok.'
I'm ok.

转义字符\可以转义很多字符,比如\n表示换行,\t表示制表符,字符\本身也要转义,所以\\表示的字符就是\。当然如果不需要转义,可以使用r'':

>>> print '\\\t\\'
\  \
>>> print r'\\\t\\'
\\\t\\

如果字符串内部有很多换行,用\n写在一行里不好阅读,为了简化,Python允许用'''…'''的格式表示多行内容:

>>> print '''line1
... line2
... line3'''
line1
line2
line3

如果写成程序,就是:

print '''line1
line2
line3'''


可能出现的问题
中文编码问题

# coding = utf-8

结果报错:

SyntaxError: Non-ASCII character ‘/xe6'

所以最后改成了

# coding=utf-8

唉....

Unicode编码问题

Python 2.7.6 (default, Mar 22 2014, 22:59:56) 
[GCC 4.8.2] on linux2
Type "help", "copyright", "credits" or "license" for more information.
>>> len('中文')
6
>>> len(u'中文')
2
>>>

注意: 这个问题是由python编码导致的,详细的编码问题详见字符串和编码,但是在python 3.x中这个编码问题就不存在了:

Python 3.4.0 (default, Jun 19 2015, 14:20:21) 
[GCC 4.8.2] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> len('中文')
2
>>> len(u'中文')
2
>>>
 

输出

>>> print 'hello, world'
hello, world

>>> print 'The quick brown fox', 'jumps over', 'the lazy dog'
The quick brown fox jumps over the lazy dog

>>> print '100 + 200 =', 100 + 200
100 + 200 = 300

输入

>>> name = raw_input()
Michael

>>> name
'Michael'

>>> print name
Michael

>>> name = raw_input('please enter your name: ')
please enter your name:

注意: raw_input返回的永远是字符串,也就是说你输入一个int型,返回的是一个数字字符串,你需要进行转换:

>>> number = raw_input("输入一个整数:")
输入一个整数:123
>>> number
'123'
>>> number = int(raw_input("输入一个整数:"))
输入一个整数:123
>>> number
123

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

AI Hentai Generator

AI Hentai Generator

Generate AI Hentai for free.

Hot Tools

Notepad++7.3.1

Notepad++7.3.1

Easy-to-use and free code editor

SublimeText3 Mac version

SublimeText3 Mac version

God-level code editing software (SublimeText3)

Dreamweaver Mac version

Dreamweaver Mac version

Visual web development tools

WebStorm Mac version

WebStorm Mac version

Useful JavaScript development tools

Zend Studio 13.0.1

Zend Studio 13.0.1

Powerful PHP integrated development environment