Common Design Patterns in Python

1. Singleton Pattern: ensures a class has only one instance and provides a global access point.

2. Factory Pattern: uses factory methods to create objects instead of direct instantiation, determining the type based on parameters.

3. Abstract Factory Pattern: provides an interface or abstract class to create families of related objects without specifying concrete classes.

4. Builder Pattern: constructs complex objects step by step, separating construction from representation, allowing the same process to create different representations.

5. Prototype Pattern: creates new objects by copying existing ones rather than instantiating new classes.

6. Adapter Pattern: converts one class's interface into another that clients expect, enabling incompatible interfaces to work together.

7. Decorator Pattern: dynamically adds additional responsibilities to an object without modifying its interface.

8. Proxy Pattern: provides a surrogate for another object to control access and add pre/post-processing.

9. Observer Pattern: defines a one-to-many dependency so that when one object changes state, all its dependents are notified and updated automatically.

10. Strategy Pattern: defines a family of algorithms, encapsulates each one, and makes them interchangeable, allowing algorithm variations independent of clients.

11. Template Method Pattern: defines the skeleton of an algorithm, leaving some steps to be implemented by subclasses.

12. Iterator Pattern: provides a way to access elements of an aggregate object sequentially without exposing its underlying representation.

13. Chain of Responsibility Pattern: decouples sender and receiver by passing a request along a chain of handlers until one handles it.

14. Command Pattern: encapsulates a request as an object, allowing parameterization of clients with different requests.

15. State Pattern: allows an object to alter its behavior when its internal state changes, appearing as if it changed its class.