3 Mistakes You Should Never Make When Starting a New Python Project

Alex | Python DevTools — Sun, 19 Jul 2026 21:17:14 +0000

"I'll figure out the structure later."

We've all been there. You wake up with a new project idea, grab a coffee, open VS Code, and... stare at the blank screen.

Then comes the "setup phase." You spend the first hour manually creating folders, hunting for a .gitignore file, and trying to remember how to configure basic logging. By the time you're ready to actually write code, your energy is drained.

If you are doing this, you are losing the battle before you even start. Here are the 3 mistakes you should never make when starting a new Python project.

The "Spaghetti Folder" Trap Starting a project without a modular structure is a recipe for disaster. As your codebase grows, simple features become tangled, and maintaining code becomes a nightmare.

The fix: Always start with a modular architecture. It doesn't have to be complex, but separating your logic, config, and utilities from day one saves you hundreds of hours later.

Ignoring .gitignore There is nothing more painful than seeing pycache folders, .env files, or your entire virtual environment accidentally pushed to your repository. It makes your repo look messy and, worse, exposes secrets.

The fix: A clean repo is a professional repo. Start with a solid .gitignore template that keeps the clutter out of your version control.

Putting Off Logging "I'll add logging once the code is actually running."

This is the most dangerous sentence in development. When your code crashes in production, you don't want to be guessing what happened. You want to see exactly where it broke.

The fix: Integrate a basic logger setup immediately. It takes 30 seconds to set up, but it saves you hours of debugging when things go wrong.

How to Automate Your Setup
I got tired of repeating these manual steps for every single project. So, I built a solution to get from "idea" to "coding" in under 5 minutes.

I created the Modular Python Starter Kit (Lite). It includes:

✅ A clean, professional folder structure.

✅ A ready-to-go .gitignore & requirements.txt.

✅ A basic, functional logger setup.

You can grab it for free here: https://alexdevtools.gumroad.com/l/python-starter-lite

Stop wasting time on plumbing and start building what matters.

What about you? What is that one "must-have" rule you apply to every new Python project? Let me know in the comments!

I Stopped Reinventing the Wheel: Building Modular Python Foundations

Alex | Python DevTools — Sun, 19 Jul 2026 19:34:56 +0000

Hi everyone! 👋

I'm Alex, and like many of you, I've spent countless hours in "setup hell."

Every time I started a new Python project, I found myself doing the exact same boring things: configuring SQLite connections, setting up logging, wrestling with directory structures, and manually wiring up authentication.

I realized I was building the same "skeleton" over and over again instead of focusing on the actual business logic.

So, I decided to switch the script.

I’ve spent the last few weeks modularizing my workflow. I built a set of production-ready foundations designed to help solo developers skip the repetitive setup and start shipping faster.

What I’m working on:

I'm currently focusing on Modular Monolith patterns. My goal is to make professional, clean-code architecture accessible without the overhead of complexity.

Here is what I’ve just made public:

1. Modular Architecture Boilerplate

A highly scalable foundation with built-in logging, plugin support, and clean architecture principles.

2. Clean Architecture Boilerplate

The perfect skeleton for building robust, professional Python applications with SOLID principles.

3. JWT Authentication Plugin

A drop-in, secure authentication layer designed to integrate seamlessly into modular systems.

Why am I sharing this?

I believe that 80% of development time shouldn't be spent on infrastructure. If we want to ship better products, we need better starting points.

I’m building these tools in public. You can find the source code on my GitHub, and if you find them useful for your production projects, I have premium versions available for those who want to support the development.

I’m currently looking for feedback on these architectures. Does this modular approach resonate with your workflow, or do you prefer building from scratch? Let me know in the comments!

Happy coding!