What Are SOLID Principles? A Beginner-Friendly Guide to the 5 Core Object-Oriented Design Principles [With Python Examples]

As you develop software, a codebase that started out clean inevitably starts showing these symptoms:

• Fixing something in one place mysteriously breaks something elsewhere
• Adding new features becomes terrifying because it requires modifying existing code
• Code you wrote a few months ago is now unreadable
• A single class balloons to hundreds of lines, and nobody wants to touch it—the dreaded “God Class”

This isn’t a matter of individual skill—it’s a design problem. Without deliberate attention to code structure, projects inevitably grow complex and become unmaintainable.

The SOLID principles were formulated to systematically prevent these problems. SOLID is a set of five foundational object-oriented design principles, codified in the early 2000s by Robert C. Martin (a.k.a. Uncle Bob). Today, they serve as the design backbone across virtually every area of software development—web, AI/ML, gaming, embedded systems, and beyond.

This article explains each of the five SOLID principles with why it matters, bad-vs-good design comparisons, Python code examples, and real-world applications, all in a beginner-friendly format. While SOLID applies to any OOP language, all code examples use Python.

SOLID Principles at a Glance

In a nutshell, SOLID is “a set of design rules for writing code that is resilient to change, hard to break, and easy to extend.”

Why Are SOLID Principles Necessary?

To understand why SOLID matters, let’s first look at code with a broken design.

class UserManager:
    def register(self, name, email):
        # User registration
        pass

    def send_welcome_email(self, email):
        # Send email
        pass

    def save_to_database(self, user):
        # Save to DB
        pass

    def generate_monthly_report(self):
        # Generate report
        pass

    def validate_input(self, data):
        # Validate input
        pass

This class looks convenient at first, but it carries serious problems:

This is a design where “one change can break everything”—and it gets worse as the project grows. SOLID is the design philosophy that prevents this.

S: Single Responsibility Principle (SRP)

A class should have only one reason to change.

The most fundamental and arguably the most important SOLID principle. “Responsibility” can be read as “reason to change.” If a class has multiple reasons to change, it has too many responsibilities.

Bad Example: Mixed Responsibilities

class User:
    def __init__(self, name, email):
        self.name = name
        self.email = email

    def save(self):
        # Save to DB (persistence responsibility)
        pass

    def send_email(self, subject, body):
        # Send email (notification responsibility)
        pass

    def calculate_age(self, birthdate):
        # Calculate age (business logic responsibility)
        pass

Good Example: Separated Responsibilities

class User:
    def __init__(self, name, email):
        self.name = name
        self.email = email

class UserRepository:
    def save(self, user: User):
        # Save to DB
        pass

class EmailService:
    def send(self, to: str, subject: str, body: str):
        # Send email
        pass

class AgeCalculator:
    def calculate(self, birthdate) -> int:
        # Calculate age
        pass

O: Open/Closed Principle (OCP)

Software should be open for extension but closed for modification.

When adding new features, you should be able to extend without modifying existing code. Modifying existing code always risks introducing bugs. If you can extend without modification, the risk of breaking existing features drops to zero.

Bad Example: Extending via Conditionals

class DiscountCalculator:
    def calculate(self, customer_type: str, price: float) -> float:
        if customer_type == "normal":
            return price * 0.9
        elif customer_type == "vip":
            return price * 0.8
        elif customer_type == "super_vip":
            return price * 0.7
        # Must modify this method for every new customer type...

Good Example: Extending via Polymorphism

from abc import ABC, abstractmethod

class Discount(ABC):
    @abstractmethod
    def calculate(self, price: float) -> float:
        pass

class NormalDiscount(Discount):
    def calculate(self, price: float) -> float:
        return price * 0.9

class VipDiscount(Discount):
    def calculate(self, price: float) -> float:
        return price * 0.8

# Adding a new discount type (no existing code modified)
class SuperVipDiscount(Discount):
    def calculate(self, price: float) -> float:
        return price * 0.7

Adding a new discount type just means creating a new class. The existing NormalDiscount and VipDiscount are never touched.

L: Liskov Substitution Principle (LSP)

Subtypes must be substitutable for their base types without breaking correctness.

Inheritance should only be used when a true “is-a” relationship exists. If a subclass violates the contract (behavioral promise) of its parent, client code will break unexpectedly.

Bad Example: Contract-Breaking Inheritance

class Bird:
    def fly(self):
        return "Flying!"

class Penguin(Bird):
    def fly(self):
        raise Exception("Penguins can't fly!")

# Client code breaks
def make_bird_fly(bird: Bird):
    return bird.fly()  # Throws exception if Penguin is passed

Good Example: Proper Inheritance Hierarchy

class Bird:
    def eat(self):
        return "Eating!"

class FlyingBird(Bird):
    def fly(self):
        return "Flying!"

class Penguin(Bird):
    def swim(self):
        return "Swimming!"

class Eagle(FlyingBird):
    pass

# Safe: only FlyingBird is expected to fly
def make_bird_fly(bird: FlyingBird):
    return bird.fly()

I: Interface Segregation Principle (ISP)

Clients should not be forced to depend on methods they don’t use.

Instead of one large interface, split it into smaller interfaces that each client actually needs.

Bad Example: Fat Interface

from abc import ABC, abstractmethod

class Worker(ABC):
    @abstractmethod
    def work(self):
        pass

    @abstractmethod
    def eat(self):
        pass

    @abstractmethod
    def sleep(self):
        pass

class Robot(Worker):
    def work(self):
        return "Working!"

    def eat(self):
        raise NotImplementedError("Robots don't eat")

    def sleep(self):
        raise NotImplementedError("Robots don't sleep")

Good Example: Segregated Interfaces

from abc import ABC, abstractmethod

class Workable(ABC):
    @abstractmethod
    def work(self):
        pass

class Eatable(ABC):
    @abstractmethod
    def eat(self):
        pass

class Sleepable(ABC):
    @abstractmethod
    def sleep(self):
        pass

class Human(Workable, Eatable, Sleepable):
    def work(self):
        return "Working!"
    def eat(self):
        return "Eating!"
    def sleep(self):
        return "Sleeping!"

class Robot(Workable):
    def work(self):
        return "Working!"

D: Dependency Inversion Principle (DIP)

High-level modules should not depend on low-level modules. Both should depend on abstractions.

Rather than depending directly on concrete implementations (MySQL, SendGrid, etc.), depend on abstractions (interfaces) to make swapping implementations easy.

Bad Example: Direct Dependency on Concretions

class MySQLDatabase:
    def save(self, data):
        # Save to MySQL
        pass

class UserService:
    def __init__(self):
        self.db = MySQLDatabase()  # Directly depends on MySQL

    def create_user(self, name):
        self.db.save({"name": name})

Good Example: Depending on Abstractions + DI

from abc import ABC, abstractmethod

class Database(ABC):
    @abstractmethod
    def save(self, data):
        pass

class MySQLDatabase(Database):
    def save(self, data):
        # Save to MySQL
        pass

class PostgreSQLDatabase(Database):
    def save(self, data):
        # Save to PostgreSQL
        pass

class UserService:
    def __init__(self, db: Database):  # Depends on abstraction
        self.db = db

    def create_user(self, name):
        self.db.save({"name": name})

# Usage
service = UserService(MySQLDatabase())
# Easy to swap
service = UserService(PostgreSQLDatabase())

What Happens When You Follow SOLID — Before / After

SOLID in Practice

In Python Web framework-based API development, separating routing, business logic, and data access (SRP), adding features via middleware (OCP), and abstracting the DB for testability (DIP) are all SOLID in action. The design patterns in Python Security Implementation Patterns—separating input validation, authentication, and authorization—are SRP in practice.

Learning Priority for Beginners

Common Misconceptions

What to Learn After SOLID

FAQ

Q: Should beginners learn SOLID?

Yes—the earlier, the better. Design habits are extremely hard to fix later. Just being aware of “one reason to change” from the start makes a huge difference in long-term growth.

Q: Is SOLID needed for Python?

Absolutely. SOLID is a design philosophy, not language-specific. It applies to Python, Java, C++, TypeScript, Go, and any OOP-supporting language. Python’s dynamic typing arguably makes good design more important.

Q: Must I follow all five?

Start with SRP alone. Just that one principle dramatically improves code quality. The others will naturally become relevant as you gain experience.

Q: When should I think about SOLID?

When designing classes and modules. Especially when creating a new class, when an existing class grows too large, or when tests become hard to write.

Q: Is SOLID hard?

It may feel abstract at first, but it becomes natural as you practice. SRP and OCP in particular have many “aha” moments—you’ll soon write SOLID-compliant code without consciously thinking about it.

Summary

SOLID is a set of five design principles for writing code that is resilient to change, hard to break, and easy to extend.

• S (Single Responsibility): One class, one job. Only one reason to change
• O (Open/Closed): Extend without modifying existing code
• L (Liskov Substitution): Subtypes must honor their parent’s contract
• I (Interface Segregation): Don’t force unnecessary methods
• D (Dependency Inversion): Depend on abstractions, not concretions

SOLID is not something to memorize—it’s a design philosophy. Understand why it exists, and it will naturally reflect in your code. Start by focusing on the Single Responsibility Principle alone. That one change will dramatically improve your code quality.

Related articles: Python Getting Started Guide / 7 Python Error Handling Patterns / Python Web Framework Comparison / Python Security Implementation Patterns / Programming Language Comparison Guide