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,
The problem: too many clients, too few discovery hooks We expose Supabase Edge Functions as MCP (Model Context Protocol) servers. The clients that hit them are heterogeneous — Claude Desktop, Codex CLI, Cursor, VS Code Continue, a couple of in-house browser extensions. None of them ship with a hard-coded "use WorkOS AuthKit, scope is tool:ai_chat, audience must contain urn:jibun:tool:<tool>" rec
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
A Fully Native, Dependency‑Free Web5 Case Study TL;DR: This case study demonstrates how the Ascoos OS Kernel 1.0.0 performs OAuth2 authentication, event‑driven processing, torrent file creation, and secure P2P upload using raw sockets — all without frameworks, external libraries, or middleware. 🔗 Full source code: https://github.com/ascoos/oauth2-torrent-upload Modern decentralized systems