search
HomeBackend DevelopmentPython TutorialWhat does the stack in python refer to?

What does the stack in python refer to?

A stack is an ordered collection of items, where adding and removing new items always occurs at the same end. This end is often called the "top." The end corresponding to the top is called the "bottom".

What does the stack in python refer to?

As described in the picture, stack s=(a1,a2,…an-1,an). The last one pushed onto the stack is an, and the first one popped off the stack is also an. So the stack complies with the LIFO principle.

LIFO

LIFO, that is, the last-in-first-out sorting principle. It sorts based on the length of time within the collection. Newer items are near the top and older items are near the bottom. The bottom of the stack is important because items near the bottom of the stack are stored the longest. Recently added items are the first to be removed.

The reason why the stack is important is that it can reverse the order of items. Insertion and deletion are in reverse order.

The most typical example is that every web browser has a back button. When you browse the web, the web pages are placed in a stack (actually the URL of the web page). The page you are viewing now is at the top, and the page you were first viewing is at the bottom. If you press the 'Back' button, you will browse the previous pages in reverse order.

Python implementation stack

# 创建一个空的新栈。 它不需要参数,并返回一个空栈。
class Stack:
    def __init__(self):
        self.items = []
        
    # 测试栈是否为空。不需要参数,并返回布尔值。
    def isEmpty(self):
        return self.items == []
    
    # 将一个新项添加到栈的顶部。它需要 item 做参数并不返回任何内容。
    def push(self, item):
        self.items.append(item)
        
    # 从栈中删除顶部项。它不需要参数并返回 item 。栈被修改。
    def pop(self):
        return self.items.pop()
    
    # 从栈返回顶部项,但不会删除它。不需要参数。 不修改栈。
    def peek(self):
        return self.items[len(self.items)-1]
    
    # 返回栈中的 item 数量。不需要参数,并返回一个整数。
    def size(self):
        return len(self.items)

Convert decimal number to arbitrary base number

I know the stack Just do a small project to practice the basic operation. Convert a decimal number to any base number. In fact, the highest number is hexadecimal (are there any higher bases?).

def baseConverter(n, base):
    
    # n是输入的十进制数字,base为要转化的进制数
    digits = '0123456789ABCDEF'
    
    #创建一个新栈
    s= Stack()
    
    # 将每次计算所得的余数添加进栈
    while n> 0:
        rem = n % base
        s.push(rem)
        n = n // base
    
    # 将余数倒序排列至新字符串    
    newString = ''
    while not remstack.isEmpty():
        newString = newString + digits[remstack.pop()]
        
    return newString

Related recommendations: "Python Tutorial"

The above is the detailed content of What does the stack in python refer to?. For more information, please follow other related articles on the PHP Chinese website!

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