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.
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.
2.3 Inheritance and Polymorphism
Python's inheritance system is more intuitive and powerful than JavaScript's.
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.
3. Functional Programming Features
3.1 Higher-Order Functions
Python supports higher-order functions, similar to functional programming concepts in JavaScript.
3.2 Lambda Functions
Python's lambda functions are similar to JavaScript's arrow functions, but more limited in functionality.
3.3 List Comprehensions
List comprehensions are a feature of Python, similar to a combination of map and filter in JavaScript.
4. Decorators
Decorators are a unique feature of Python, similar to higher-order components or middleware in JavaScript.
4.1 Basic Decorators
4.2 Decorators with Arguments
4.3 Class Decorators
5. Practical Project Example
5.1 Data Validator
Let's create a data validator that combines object-oriented and functional programming.
5.2 Cache Decorator
6. Exercises
Exercise 1: Create a Student Management System
Exercise 2: Functional Programming Exercise
7. Summary
Key Concept Review
-
Object-Oriented Programming
- Class definition and instantiation
- Inheritance and polymorphism
- Special methods (magic methods)
- Class variables and instance variables
-
Functional Programming
- Higher-order functions (map, filter, reduce)
- Lambda functions
- List comprehensions
- Functions as arguments and return values
-
Decorators
- Basic decorators
- Decorators with arguments
- Class decorators
- Practical use cases
JavaScript vs. Python Comparison Summary
Concept | JavaScript | Python | Description |
---|---|---|---|
Class Definition | class ClassName | class ClassName: | Python uses a colon. |
Constructor | constructor() | __init__(self) | Python requires the self parameter. |
Inheritance | extends | (ParentClass) | Python uses parenthesis syntax. |
Special Methods | Symbol methods | __method__ | Python has more extensive special methods. |
Higher-Order Functions | Built-in methods | map , filter , reduce | Same concept, different syntax. |
Anonymous Functions | Arrow functions | lambda | Python's lambda is more limited. |
Decorators | Higher-order functions | @decorator | Python has syntax sugar support. |
Best Practices
-
Object-Oriented Programming
- Use
@dataclass
to simplify data classes - Use inheritance and composition appropriately
- Implement appropriate special methods
- Follow the single responsibility principle
- Use
-
Functional Programming
- Prefer list comprehensions
- Use lambda functions appropriately
- Avoid excessive nesting
- Maintain function purity
-
Decorators
- Use
@wraps
to preserve function metadata - Design decorator arguments appropriately
- Be aware of the execution order of decorators
- Avoid overusing decorators
- Use
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.
Python Module System and Project Organization
Learn Python's module system, package management, and project organization best practices from a JavaScript developer's perspective.
Python Asynchronous Programming
Learn Python's async programming, event loop, and async web development from a JavaScript developer's perspective.