How to Structure Large-Scale Python Projects Like a Senior Engineer

The difference between junior and senior Python code isn’t syntax — it’s structure.

How to Structure Large-Scale Python Projects Like a Senior Engineer

If you’ve ever found yourself knee-deep in a spaghetti mess of Python files, struggling to remember which function lives where — you’re not alone.

As projects grow in complexity, the need for proper structure becomes non-negotiable.

Junior developers often start with a few scripts, maybe some helper modules, and hope for the best. But senior engineers?

They think in terms of maintainability, scalability, readability, and testability — long before the first line of code is even written.

In this article, you’ll learn how to structure large-scale Python projects like a senior engineer — so your codebase doesn’t just work, it thrives.

1. Think in Layers, Not Files

Instead of dumping code into a utils.py file or keeping everything in main.py, senior engineers split responsibilities by layers:

• Presentation Layer → Handles I/O (e.g., CLI, REST APIs, Web UI)
• Service Layer → Contains business logic
• Data Layer → Deals with storage, databases, APIs, etc.

Example structure:

project/ 
├── app/ 
│   ├── __init__.py 
│   ├── api/               # Presentation Layer 
│   ├── services/          # Business Logic Layer 
│   └── repositories/      # Data Access Layer 
├── tests/ 
├── scripts/ 
├── config/ 
└── main.py

This separation makes your code easier to test, debug, and refactor over time.

2. Use a Package, Not a Pile of Scripts

A senior dev treats their project like a distributable package, even if it’s just internal.

Why?

• Cleaner imports
• Easier testing
• Future-ready for deployment or packaging

Set up your package like this:

project/ 
├── my_project/ 
│   ├── __init__.py 
│   ├── core/ 
│   ├── utils/ 
│   └── ... 
├── setup.py 
└── pyproject.toml

With this structure, you can do:

from my_project.core.service import BusinessLogic

Much cleaner than relative imports from random scripts.

3. Structure Tests to Mirror the App

Tests aren’t an afterthought — they’re a first-class citizen.

Mirror your app’s structure:

tests/ 
├── api/ 
├── services/ 
└── repositories/

Each test module should correspond to a source module. It makes it easier to locate and maintain.

Use pytest and make testing a habit, not a headache.

4. Configuration Should Be Environment-Agnostic

Avoid hardcoding configuration in your code.

Use a central config module that pulls from:

• .env files using python-dotenv
• environment variables
• config files (like YAML, TOML, or JSON)

Example:

# config/settings.py 
import os 
 
DATABASE_URL = os.getenv("DATABASE_URL", "sqlite:///local.db") 
DEBUG = os.getenv("DEBUG", "false").lower() == "true"

Pro tip: Also add config/__init__.py and expose the config cleanly.

5. Dependency Injection > Global Imports

Senior engineers avoid tight coupling by injecting dependencies.

Instead of:

from database import db 
user = db.get_user()

Prefer:

def get_user_service(db_client): 
    return db_client.get_user()

This improves testability and keeps your logic decoupled from specific tools or frameworks.

6. CLI or Entry Points Belong in main.py

Your app should have a single clear entry point — either a main.py file or a CLI app using argparse or typer.

Example:

# main.py 
from app.api.server import start_server 
 
if __name__ == "__main__": 
    start_server()

This keeps your app bootstrapping logic separate from your core logic.

7. Use __init__.py Wisely

Don’t clutter every __init__.py with logic or wildcard imports. Instead:

• Keep it clean
• Use it for exposing clean module APIs
• Only import what’s meant to be publicly accessible

Bad:

# my_project/__init__.py 
from .module1 import * 
from .module2 import *

Good:

# my_project/__init__.py 
from .module1 import ClassA, func_b

8. Add Tooling from Day 1

Senior engineers bake tooling into the project early:

• Formatters: black, isort or ruff
• Linters: flake8, pylint
• Type Checkers: mypy, pyright
• Pre-commit hooks: Automate checks before pushing

Add a pyproject.toml to centralize config where possible.

9. Don’t Be Afraid to Refactor

Your first structure won’t be perfect. That’s okay.

But senior engineers refactor relentlessly. They create README.md files in each submodule, document decisions, and prune unused code ruthlessly.

Use tools like:

• poetry for dependency management
• coverage to track test coverage
• mkdocs or Sphinx for documentation

Final Thoughts

Structuring large-scale Python projects like a senior engineer isn’t about using big words or complex tools. It’s about clarity, consistency, and foresight.

The best structures:

• Scale with teams and complexity
• Make onboarding new devs painless
• Reduce bugs and technical debt
• Let your logic shine through the structure

Whether you’re building the next AI-powered SaaS app or an internal automation tool, structure matters.

Write code your future self — and your team — will thank you for.

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