Principles of Python Programming
Python adheres to a set of guiding principles that contribute to its readability, efficiency, and maintainability. These principles are collectively known as the «Zen of Python.»

The Zen of Python
To access the Zen of Python in your Python interpreter, simply type import this. You'll see a collection of aphorisms that influence Python's design.

Python
import this
Use code with caution.

Here are some key principles:

Readability Counts: Python emphasizes clear and concise code.
Simple is Better Than Complex: Avoid unnecessary complexity.
Errors Should Never Pass Silently: Python's error handling mechanisms are designed to prevent silent failures.
Practicality Beats Purity: While Python promotes clean code, it also acknowledges that practical considerations sometimes outweigh theoretical purity.
Object-Oriented Programming (OOP) Principles in Python
Python supports OOP concepts, which are essential for building complex applications:

Encapsulation: Bundling data (attributes) and methods (functions) that operate on the data into a single unit (class).
Abstraction: Hiding implementation details and providing a simplified interface.
Inheritance: Creating new classes (subclasses) that inherit attributes and methods from existing classes (superclasses).
Polymorphism: Using a single interface to represent different types of objects.
SOLID Principles (Python Classes in Ahmednagar)
The SOLID principles are design principles for creating maintainable and extensible software. While not strictly enforced in Python, they provide valuable guidance for writing clean and well-structured code:

Single Responsibility Principle (SRP): A class or function should have only one reason to change.
Open-Closed Principle (OCP): Software entities should be open for extension but closed for modification.
Liskov Substitution Principle (LSP): Objects in a program should be replaceable with instances of their subtypes withoutaltering the program's correctness.   (Python Course in Ahmednagar)
Interface Segregation Principle (ISP): Clients should not be forced to depend on interfaces they do not use.
Dependency Inversion Principle (DIP): High-level modules should not depend on low-level modules. Both should depend on abstractions.  
By following these principles, you can write Python code that is well-structured, maintainable, and scalable.