Posts

Picture this: you’re building a doghouse. You wouldn’t call an architect, 3D-print titanium joints, or create separate teams for roof-tiling and tail-wagging detection systems. Yet in software, we often reach for microservices when a simple shed would do. Let’s explore when your project might actually yearn for the cozy simplicity of a monolith. The Monolith’s Sweet Spot: Green Light Scenarios Scenario 1: You’re building the digital equivalent of a lemonade stand...

Picture this: you’re sipping coffee while Jupyter Notebook obediently types your Python variables into Shakespearean sonnets. That’s the power of extensions - and today we’ll make one that actually does something useful (though iambic pentameter support might come in v2). Buckle up for a code-packed journey through Jupyter’s extension system! Laying the Groundwork Before we make magic happen, let’s set up our wizard’s workshop: # Create extension scaffolding npx create-jupyterlab-extension jupyterlab_stonks cd jupyterlab_stonks jlpm install This creates a TypeScript project (JavaScript’s type-aware cousin)....

Let’s start with a uncomfortable truth: that innocent-looking ChatGPT query box has a bigger appetite than a caffeinated grad student during finals week. While you’re asking it to explain quantum physics or generate cat memes, somewhere a server farm is guzzling energy like a Hummer at a gas station. But how bad is it really? Let’s crunch numbers like a climate-conscious accountant: def calculate_ai_footprint(queries_per_day: int): co2_per_query = 4.32 # grams daily_emissions = queries_per_day * co2_per_query print(f"Daily CO₂: {daily_emissions}g (That's {daily_emissions/1000}kg)") print(f"Annual CO₂: {(daily_emissions * 365)/1000}kg") calculate_ai_footprint(50) # Average user estimate Daily CO₂: 216....

Picture this: you’re trying to find a socks pair in a teenager’s bedroom. That’s imperative programming. Now imagine Marie Kondo organizing your codebase - that’s functional programming. Let’s explore why this paradigm turns chaotic kitchens into Michelin-starred code restaurants. From Spaghetti Code to Lasagna Layers Functional programming (FP) isn’t new - it’s been around since the 1930s. But like avocado toast, it needed millennia to become mainstream. Here’s why it’s perfect for modern development:...

Picture this: you’re assembling your dream engineering team and stumble upon a LinkedIn profile that reads “10x Full Stack Developer - I output 12,000 lines of bug-free Rust code before breakfast (and yes, I actually like async programming)”. Your inner tech lead starts drooling. But before you max out your AWS budget trying to hire this coding demigod, let’s talk about why the 10x developer myth is more dangerous than a sudo rm -rf /* in your production environment....