Although Python has advantages in Function Programming that other languages cannot match, we should not forget that Python is also an OO language. Therefore, while we pay attention to Python's advantages in FP, we also need to understand Python's OO characteristics.
To discuss the OO features of Python, understanding Class in Python is naturally the first thing to do. Defining classes and creating object instances in Python is very simple. The specific code is as follows:
class GrandPa: def __init__(self): print('I\'m GrandPa') class Father(GrandPa): def __init__(self): print('I\'m Father!') class Son(Father): """A simple example class""" i = 12345 def __init__(self): print('这是构造函数,son') def sayHello(self): return 'hello world' if __name__ == '__main__': son = Son() # 类型帮助信息 print('类型帮助信息: ',Son.__doc__) #类型名称 print('类型名称:',Son.__name__) #类型所继承的基类 print('类型所继承的基类:',Son.__bases__) #类型字典 print('类型字典:',Son.__dict__) #类型所在模块 print('类型所在模块:',Son.__module__) #实例类型 print('实例类型:',Son().__class__)
Running status:
Python 3.3.2 (v3.3.2:d047928ae3f6, May 16 2013, 00:03:43) [MSC v. 1600 32 bit (Intel)] on win32
Type "copyright", "credits" or "license()" for more information.
>>> ================ ================ RESTART ================================
>>>>
This is the constructor, son
type help information: A simple example class
Type name: The base class inherited by the Son
type: (
Type dictionary: {'__module__' : '__main__', 'sayHello':
The module where the type is located: __main__
This is the constructor, son
Instance type:
>>>>
#Python supports multiple inheritance
First of all, you will find that there is a bracket in the definition of Class, which is where inheritance is reflected. Java uses extends, C# and C++ use colons (:), and Python uses parentheses. There are two values contained in the brackets. If you are smart, you will definitely find out: Python supports multiple inheritance;
#__init__ is the constructor in Class
Second point, __init__ is the constructor in Class, two different The form of constructor reflects Python's support for function overloading. In the constructor, there is a special parameter self, whose meaning is the same as this common in Java and C#. One thing needs to be emphasized here: the method defined in Class is essentially a function, but the self parameter must be included when the method is defined, and the self parameter must be placed first;
#python member variable
Three points. In Python, you do not need to explicitly declare the Data Members of the Class. Instead, when assigning a value, the assigned variable becomes the Data Members of the Class, just like x and y in the code. Not only do you not need to explicitly declare Data Members, but even more special, you can even delete the Data Members in the Class through the del method. When I first saw such a feature, I was really surprised. After all, the first point of OO is encapsulation, but does this feature destroy the characteristics of encapsulation?
#python method ambiguity problem
The fourth point is that because Python supports multiple inheritance, method ambiguity problems may occur [1]. However, because Python follows the depth-first search rule, it avoids the problem of method ambiguity. For example, in the above code, MyClass inherits from both BaseClassA and BaseClassB. Assume that MyClass calls a method called derivedMethod. DeriveMethod is defined in both BaseClassA and BaseClassB, and the Signature is exactly the same, then the method in BaseClassA will be called. If derivedMethod is not defined in BaseClassA, but the parent class of BaseClassA defines this method, derivedMethod in the parent class of BaseClassA will be called. In short, the inheritance method search path is from left to right. After selecting a BaseClass, the search will be carried out along the inheritance structure of the BaseClass until the top, and then to another BaseClass.
That’s all for now. The OO features in Python will be further described in future posts.
[1] Method ambiguity: Since a class inherits from two or more parent classes at the same time, and there are methods with exactly the same signature in these parent classes, the compiler will not be able to determine which parent the subclass will inherit. Methods in classes, leading to method ambiguity

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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