Why You Should Switch to SQLModel for FastAPI Projects | Issue #27


Hi there,

Tired of writing the same code over and over when building APIs? With SQLModel, you can define your database schema and your API models in a single place, saving tons of time and reducing errors. ⚡️ But beware—it’s important to avoid exposing sensitive data.

In this week’s video, I break down exactly how to use SQLModel with FastAPI, and share a few key lessons on how to do it right. Watch the full video to level up your API game! 🎥

Enjoy the video and happy coding!

Cheers,

Arjan

# News

Simplify Cross-Platform UI Testing with Squish 🚀

Are you looking to streamline your UI testing process? Today’s sponsor, Squish, makes it easier than ever to automate tests across all major platforms, including desktop, web, mobile, and more! Say goodbye to manual testing bottlenecks and hello to smoother, faster releases.

🖥️ Cross-platform support

⚙️ CI/CD pipeline integration

🚀 Boost productivity with automation

Click here to learn how Squish can transform your testing strategy and increase your team’s efficiency.

Analyzing Data 170,000x Faster with Python

I just came across an awesome article on optimizing correlation set calculations in Python, where the author achieved a massive 814x speedup! 🚀

The improvements came from smart techniques like switching from Pandas operations to dictionary lookups, using np.corrcoef for faster correlations, and replacing set intersections with np.logical_and.reduce, which drastically improved performance when handling large datasets.

If you’re looking to make your Python data processing faster, this is a must-read. Check out all the optimizations here.

Under the Hood | Manim

Ever heard of Manim? It’s a powerful Python-based engine for creating stunning mathematical animations, crafted by the genius behind the 3blue1brown YouTube channel.

Last week, I hosted another “Under the Hood” livestream, where we dove straight into Manim’s codebase—no prior look, no prep, just pure exploration of this open-source library. Together, we uncovered how it all works!

Missed it? No worries! You can still watch the livestream and discover the inner workings of this cool tool! 🔍

# Community

There was an interesting discussion recently on ArjanCodes’ Discord server where members unpacked the best practices for managing Python installations using pipx, Poetry, and pyenv. The debate got particularly heated around whether pipx should be installed globally or in its own virtual environment.

They also explored the right way to handle Poetry’s installation now that it no longer recommends the shell script. Oh, and if you haven’t tried uv yet as an alternative, it’s promising—but comes with a few quirks to watch out for! ⚙️

Want to hear all the tips and insights? Check out the full thread and join the conversation!


Do you enjoy my content on YouTube and would you like to dive in deeper? Check out my online courses below. They've helped thousands of developers take the next step in their careers.

🚀 The Mindset Online Course Series

The goal of this series is to help junior developers grow their skills to become senior developers faster.

💥 Other Courses

💡 If you’re part of a development team at a company, I offer special packages for companies that give your team the tools to consistently write high-quality code and dramatically increase your team's productivity.

Unsubscribe | Send by ArjanCodes

Wolvenplein 25, Utrecht, UT 3512 CK

The Friday Loop

Every Friday, you'll get a recap of the most important and exciting Python and coding news. The Friday Loop also keeps everyone posted on new ArjanCodes courses and any limited offers coming up.

Read more from The Friday Loop

Hi there, You’ve probably noticed this by now: LLM prototypes are easy to build. But as soon as you try to turn them into actual production LLM systems… a lot more goes into it. In this week’s video, I walk through how to structure AI agents in Python using design patterns like Chain of Responsibility, Observer, and Strategy. I’ll build a fully functional travel assistant using Pydantic AI and explore how to make your agent pipelines more maintainable, testable, and modular. Hope you enjoy...

Hi there, I have to admit, I often forget how powerful the Python standard library is. Whenever I'm working on some project, I have to remind myself to consider whether something I need is already there, ready for me to use. So, in this week’s video, I’m looking at 10 of the most useful and underrated modules in Python’s standard library, including pathlib, heapq, graphlib, and more. These tools can help you write cleaner, faster, and more maintainable code without adding a single dependency....

Hi there, If you’ve been experimenting with trying to integrate AI into your code, you’ve probably run into the same problem I have: unstructured, unpredictable output. And the other way around: how do you let AI agents interact with your own code? That’s where Pydantic AI comes in. In this week's video, I show how to use Pydantic AI to embed an LLM agent directly into your Python app: with structured input, validated output, and access to real business logic. What I love about this approach...