An Introduction to Typescript for Pythonistas | Issue #42


Hi there,

If you’ve ever looked at TypeScript code and thought, “Hey, that kinda looks like Python!”, you’re not wrong. But under the hood, these two languages couldn’t be more different.

Python was designed for simplicity and readability. It’s dynamically typed, making development easy but deployment tricky.

TypeScript, on the other hand, adds strict static typing to JavaScript, helping with large-scale applications but making setup and debugging more complex. So, which one should you use? 🤔

In this week’s video, I break it all down:

✅ The key differences in typing, syntax, and philosophy

✅ When to choose TypeScript over Python (and vice versa)

✅ Some of the strangest quirks in JavaScript’s type system (yes, I talk about true + true === 2 😆)

If you’ve ever been curious about how Python and TypeScript compare, this is the video for you!

Cheers,

Arjan

# News

🎉 10 Years in Tech – What Really Matters?

Chris Kiehl reflects on a decade in software development, sharing hard-earned lessons about career growth, skills that truly matter, and the things he wishes he had known earlier.

If you’ve ever wondered what long-term success in tech actually looks like, this is a must-read. Check it out here.

Level Up Your CLI Skills! 🛠️

Real Python’s latest course teaches you how to build a command-line to-do app using Typer! 📝⚡ Learn to handle commands, arguments, and options while adding a solid project to your portfolio. Plus, you’ll test it like a pro with CliRunner & pytest! 🧪✅

Check it out here.

# Community

If you’re interested in how modern CPUs actually work under the hood, there’s a fantastic video series by Matt Godbolt in collaboration with Computerphile. 🖥️⚡

Dale shared a great thread in our community, linking to a playlist covering topics like:

✅ The basics of machine code

✅ How computer arithmetic works

✅ CPU pipelines

✅ Branch prediction

Matt Godbolt has a knack for explaining complex low-level details in an approachable way, making this an excellent resource whether you’re just starting out or looking to deepen your understanding. 🔗 Click here to join the thread and open Dale’s handy playlist.


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...