It started at midnight I had 24 hours, a free Replit subscription, and an idea: what if I could build something like Miro — but actually understand every line of code in it? The core problem I had to solve first Multiplayer sync sounds simple until you actually build it. The hard part isn't sending a canvas update — it's figuring out what to send. canvas.on('object:modified', (e) => { socket.emi
FutureMe has 15 million letters in its database. They've been there since 2002. Some of them will be there in 2050. Evengood will have zero. This week I shipped The Quiet Letter — a feature where you write to your future self today, we email it on a date you pick, and we hard-delete the row from our database within 24 hours of sending it. The email is the only artifact. We don't keep a copy. Every
The DataFrame class (from Pandas) is a work of art. Even if you never "do data", priceless lessons can be gleaned by studying this class. It starts simple enough. Usually you will create a DataFrame by ingesting from a CSV file or database table or something. But you can whip up a small one like this: import pandas as pd df = pd.DataFrame({ 'A': [-137, 22, -3, 4, 5], 'B': [10, 11,
It was around 1am and I had three feeds open. X on my phone, Reddit on one monitor, Hacker News on the other. I was reading about a plane crash, a new AI model, and a meme war about whether oat milk counts as milk. And I realised I had no idea what the internet was actually feeling about any of it. The feeds told me what was happening. They didn't tell me how it felt. That's when the idea hit me.
I write a lot of READMEs. I ship faster than I document. I work with AI agents that write code in seconds and READMEs in minutes, and somewhere between the first commit and the third refactor, the README I wrote on Tuesday stops matching the code I wrote on Friday. The install command says npm start. The package.json defines start:prod. Anyone copying that command would have failed instantly. I'd
When we talk about Data Visualization and Dashboards, enterprise tools like Tableau or PowerBI often dominate the conversation. However, for Data Scientists and Developers, these GUI-based tools can feel restrictive. What if you need complex machine learning integration, custom UI logic, or automated CI/CD deployments? Enter the holy trinity of Python visualization tools: Streamlit, Dash, and Boke
[05] When to Pull the Trigger on FIRE — Monte Carlo Says You're Already Free This is Part 5 of a 6-part series: Building Investment Systems with Python "You need 25x your annual expenses." That's the standard FIRE rule. For ¥9.6M annual expenses, that's ¥240M. Most people see that number and think: "I'll never get there." But the 25x rule assumes a fixed 4% withdrawal rate, zero income, zero ada