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Python Object-Oriented & Functional Programming

Learn Python's object-oriented programming, functional programming features, and decorators from a JavaScript developer's perspective.

1. Introduction

Why Learn Object-Oriented and Functional Programming?

As a JavaScript developer, you are likely familiar with ES6 class syntax and functional programming concepts. Python has its own unique implementations of these paradigms. Mastering these features will enable you to:

  • Write more elegant and maintainable code
  • Understand Python's design philosophy
  • Leverage Python's powerful metaprogramming capabilities
  • Build more complex applications

💡 Learning Strategy: Think of Python's OOP and functional features as "enhanced versions" of JavaScript concepts.

2. Object-Oriented Programming (OOP)

2.1 Basic Class Concepts

Python's class system has many similarities to JavaScript's, but also some important differences.

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2.2 Class Variables vs. Instance Variables

The concepts of class variables and instance variables in Python are similar to static properties and instance properties in JavaScript.

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2.3 Inheritance and Polymorphism

Python's inheritance system is more intuitive and powerful than JavaScript's.

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2.4 Special Methods (Magic Methods)

Python's special methods are a powerful feature of its object-oriented programming, similar to Symbol methods in JavaScript.

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3. Functional Programming Features

3.1 Higher-Order Functions

Python supports higher-order functions, similar to functional programming concepts in JavaScript.

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3.2 Lambda Functions

Python's lambda functions are similar to JavaScript's arrow functions, but more limited in functionality.

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3.3 List Comprehensions

List comprehensions are a feature of Python, similar to a combination of map and filter in JavaScript.

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4. Decorators

Decorators are a unique feature of Python, similar to higher-order components or middleware in JavaScript.

4.1 Basic Decorators

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4.2 Decorators with Arguments

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4.3 Class Decorators

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5. Practical Project Example

5.1 Data Validator

Let's create a data validator that combines object-oriented and functional programming.

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5.2 Cache Decorator

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6. Exercises

Exercise 1: Create a Student Management System

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Exercise 2: Functional Programming Exercise

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7. Summary

Key Concept Review

  1. Object-Oriented Programming

    • Class definition and instantiation
    • Inheritance and polymorphism
    • Special methods (magic methods)
    • Class variables and instance variables
  2. Functional Programming

    • Higher-order functions (map, filter, reduce)
    • Lambda functions
    • List comprehensions
    • Functions as arguments and return values
  3. Decorators

    • Basic decorators
    • Decorators with arguments
    • Class decorators
    • Practical use cases

JavaScript vs. Python Comparison Summary

ConceptJavaScriptPythonDescription
Class Definitionclass ClassNameclass ClassName:Python uses a colon.
Constructorconstructor()__init__(self)Python requires the self parameter.
Inheritanceextends(ParentClass)Python uses parenthesis syntax.
Special MethodsSymbol methods__method__Python has more extensive special methods.
Higher-Order FunctionsBuilt-in methodsmap, filter, reduceSame concept, different syntax.
Anonymous FunctionsArrow functionslambdaPython's lambda is more limited.
DecoratorsHigher-order functions@decoratorPython has syntax sugar support.

Best Practices

  1. Object-Oriented Programming

    • Use @dataclass to simplify data classes
    • Use inheritance and composition appropriately
    • Implement appropriate special methods
    • Follow the single responsibility principle
  2. Functional Programming

    • Prefer list comprehensions
    • Use lambda functions appropriately
    • Avoid excessive nesting
    • Maintain function purity
  3. Decorators

    • Use @wraps to preserve function metadata
    • Design decorator arguments appropriately
    • Be aware of the execution order of decorators
    • Avoid overusing decorators

Next Steps

In the next module, we will learn about:

  • Python asynchronous programming (async/await)
  • Event loop mechanism
  • Asynchronous web development
  • Basics of concurrent programming

These concepts will help you build high-performance Python applications, especially in web development and data processing.