本文以实例形式展示了Python算法中栈(stack)的实现,对于学习数据结构域算法有一定的参考借鉴价值。具体内容如下:
1.栈stack通常的操作:
Stack() 建立一个空的栈对象
push() 把一个元素添加到栈的最顶层
pop() 删除栈最顶层的元素,并返回这个元素
peek() 返回最顶层的元素,并不删除它
isEmpty() 判断栈是否为空
size() 返回栈中元素的个数
2.简单案例以及操作结果:
Stack Operation Stack Contents Return Value s.isEmpty() [] True s.push(4) [4] s.push('dog') [4,'dog'] s.peek() [4,'dog'] 'dog' s.push(True) [4,'dog',True] s.size() [4,'dog',True] 3 s.isEmpty() [4,'dog',True] False s.push(8.4) [4,'dog',True,8.4] s.pop() [4,'dog',True] 8.4 s.pop() [4,'dog'] True s.size() [4,'dog'] 2
这里使用python的list对象模拟栈的实现,具体代码如下:
#coding:utf8 class Stack: """模拟栈""" def __init__(self): self.items = [] def isEmpty(self): return len(self.items)==0 def push(self, item): self.items.append(item) def pop(self): return self.items.pop() def peek(self): if not self.isEmpty(): return self.items[len(self.items)-1] def size(self): return len(self.items) s=Stack() print(s.isEmpty()) s.push(4) s.push('dog') print(s.peek()) s.push(True) print(s.size()) print(s.isEmpty()) s.push(8.4) print(s.pop()) print(s.pop()) print(s.size())
感兴趣的读者可以动手测试一下本文所述实例代码,相信会对大家学习Python能有一定的收获。

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.


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