A Practical Guide to MVC:

Structuring Your Python Projects for Readability, Maintainability, and Scalability

Someone asked me the other day how they should approach a larger project they were planning on working on and this brought back some memories of years ago. I figured I’d summarize the conversation we had in a post!

When working on software projects involving multiple technologies—such as Heroku, AWS, Salesforce, Raspberry Pi, or embedded devices like ESP32—it’s crucial to structure your Python codebase clearly and efficiently.

This fairly high level overview provides step-by-step guidance and a concrete example leveraging the MVC (Model-View-Controller) framework to help you build maintainable and scalable Python projects.

Step 1: Fundamental Principles for Maintainable Python Code

Follow these core principles:

• Clear naming conventions: Use descriptive and intuitive names.
• Single responsibility: Each function, class, and module should handle a single task or functionality.
• Adhere to PEP 8 standards: Python’s official style guide ensures consistency.
• Use linting and formatting tools: Employ tools like flake8 and black for automation.

Step 2: Choosing the MVC Pattern

The MVC pattern divides the codebase into three interconnected components:

• Model: Handles data and business logic.
• View: Manages presentation to the user.
• Controller: Interacts with the Model and View based on user input.

MVC enhances clarity by separating concerns, simplifies debugging, and scales easily with larger projects.

Step 3: Structuring Your Project

A clear, logical directory structure improves readability and maintenance:

my_python_project/
├── .github/
│   └── workflows/
│       └── ci.yml
├── docs/
│   └── architecture.md
├── src/
│   ├── controllers/
│   ├── models/
│   ├── views/
│   ├── utils/
│   └── main.py
├── tests/
│   └── test_controllers.py
├── requirements.txt
└── README.md

Step 4: Implementing MVC Components

Example implementations:

• Model (models/customer.py):

class Customer:
    def __init__(self, customer_id: int, name: str, email: str):
        self.customer_id = customer_id
        self.name = name
        self.email = email

    def to_dict(self):
        return {"id": self.customer_id, "name": self.name, "email": self.email}

• Controller (controllers/customer_controller.py):

from models.customer import Customer

CUSTOMER_DB = {
    1: Customer(1, "Alice", "alice@example.com"),
    2: Customer(2, "Bob", "bob@example.com"),
}

def get_customer_by_id(customer_id: int):
    return CUSTOMER_DB.get(customer_id)

def add_customer(customer_id: int, name: str, email: str):
    customer = Customer(customer_id, name, email)
    CUSTOMER_DB[customer_id] = customer
    return customer

• View (views/customer_view.py):

from flask import Blueprint, jsonify, request
from controllers.customer_controller import get_customer_by_id, add_customer

customer_bp = Blueprint("customer", __name__, url_prefix="/customer")

@customer_bp.route("/<int:customer_id>", methods=["GET"])
def get_customer(customer_id):
    customer = get_customer_by_id(customer_id)
    if customer:
        return jsonify(customer.to_dict()), 200
    return jsonify({"error": "Customer not found"}), 404

@customer_bp.route("/", methods=["POST"])
def create_customer():
    data = request.get_json()
    customer = add_customer(data["id"], data["name"], data["email"])
    return jsonify(customer.to_dict()), 201

Step 5: Main Application Entry Point (main.py)

from flask import Flask
from views.customer_view import customer_bp

def create_app():
    app = Flask(__name__)
    app.register_blueprint(customer_bp)
    return app

if __name__ == "__main__":
    app = create_app()
    app.run(debug=True)

Step 6: Automating Tests and CI/CD

Automate tests and continuous integration to maintain quality:

• Testing (tests/test_controllers.py):

import pytest
from controllers.customer_controller import get_customer_by_id, add_customer

def test_get_customer_by_id():
    customer = get_customer_by_id(1)
    assert customer is not None
    assert customer.name == "Alice"

def test_add_customer():
    customer = add_customer(3, "Charlie", "charlie@example.com")
    assert customer.customer_id == 3

• CI/CD (.github/workflows/ci.yml):

name: Python CI
on:
  push:
    branches: [main, develop]
  pull_request:
    branches: [main]
jobs:
  test:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
      - uses: actions/setup-python@v5
        with:
          python-version: "3.13"
      - run: pip install -r requirements.txt
      - run: flake8 src/
      - run: black --check src/
      - run: pytest tests/

Step 7: Documentation and Version Control

• Documentation (README.md):

Clearly document how to set up and run your project:

# My Python Project

## Setup

Clone the repo, install dependencies, and run the application:

bash
pip install -r requirements.txt
python src/main.py

## Running Tests

bash
pytest tests/

• Git Best Practices:

Use feature branches, pull requests, and regular code reviews to maintain high-quality code.

Following these steps will help you create Python projects that are readable, maintainable, and scalable. This template serves as a solid foundation for integrating diverse technologies smoothly and efficiently.