


What are some common design patterns (e.g., Singleton, Factory, Observer) and how can they be implemented in Python?
Singleton, Factory and Observer are three commonly used design patterns in Python, which are used to solve the problems of object instantiation, creation of abstraction and dependency notification. 1. Singleton coordinates system operations by ensuring that a class has only one instance and provides global access points, such as configuration management; 2. Factory encapsulates object creation logic to make the code more flexible, making it easier to extend the creation of different types of objects; 3. Observer allows objects to automatically notify dependent objects when their state changes, and is suitable for event-driven systems such as GUI updates or logging systems. These patterns help improve the maintainability and scalability of your code.
When people start learning about software design patterns, they often hear terms like Singleton, Factory, and Observer. These are some of the most commonly used design patterns in Python (and other object-oriented languages), and each solves a specific kind of problem. Let's break down what they are and how to implement them in Python.
What is the Singleton pattern and when should you use it?
The Singleton pattern ensures that a class has only one instance and provides a global point of access to it. This is useful when exactly one object is needed to coordinate actions across a system — for example, a configuration manager or a logging service.
How to implement it in Python:
One simple way is by using a module-level variable since modules are only loaded once. But if you want to stick with classes, here's a basic implementation:
class Singleton: _instance = None def __new__(cls): if cls._instance is None: cls._instance = super().__new__(cls) return cls._instance
Now, every time you create an instance of Singleton
, it will return the same object.
Note: This is a minimum version. In real-world applications, you might need to handle edge cases like thread safety or subclassing.
How does the Factory pattern help with object creation?
The Factory pattern abstracts the object creation process. Instead of calling a constructor directly, you call a method that returns an instance of a class — possibly based on input parameters. This makes your code more flexible and easier to extend.
Example scenario: You have different types of users (AdminUser, GuestUser), and you want to create the correct user type based on a string input.
class AdminUser: def greet(self): return "Hello Admin!" class GuestUser: def greet(self): return "Hello Guest!" def user_factory(user_type): if user_type == "admin": return AdminUser() elif user_type == "guest": return GuestUser()
Now, you can create users like this:
user = user_factory("admin") print(user.greet()) # Output: Hello Admin!
This keeps object creation logic centralized and clean.
Some benefits:
- Decouples your code from concrete classes.
- Makes adding new types easier without modifying existing code.
Why use the Observer pattern and how does it work?
The Observer pattern allows an object (called the subject) to maintain a list of dependents (observers) and notify them automatically of any state changes. It's especially useful in event-driven systems like GUIs or message queues.
How to implement it in Python:
Here's a simple version:
class Subject: def __init__(self): self._observers = [] def attach(self, observer): self._observers.append(observer) def detach(self, observer): self._observers.remove(observer) def notify(self): for observer in self._observers: observer.update(self) class Observer: def update(self, subject): print("Observer got notified!") # Usage subject = Subject() observer1 = Observer() observer2 = Observer() subject.attach(observer1) subject.attach(observer2) subject.notify() # Output: # Observer got notified! # Observer got notified!
This structure lets you plug in various behaviors that react to changes in the subject.
Use cases include:
- UI updates triggered by data changes.
- Event listeners in frameworks.
- Logging or auditing systems.
Summary
Design patterns like Singleton, Factory, and Observer provides reusable solutions to common problems in object-oriented programming. Using them appropriately can make your code cleaner, more scalable, and easier to maintain.
Each pattern serves a different purpose:
- Singleton : Ensures one instance exists.
- Factory : Abstracts object creation.
- Observer : Enables one-to-many dependency relationships.
They're not overly complex, but knowing when and how to apply them makes a big difference.
The above is the detailed content of What are some common design patterns (e.g., Singleton, Factory, Observer) and how can they be implemented in Python?. For more information, please follow other related articles on the PHP Chinese website!

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