How to optimize Python code with profiling, generators and itertools: find bottlenecks, understand memory costs and measure whether a change helps.
Python Code Optimization — Profiling, Memory and Performance Read Post »
MCP architecture, tools, resources, transports and authorization, with a FastMCP SDK 1.x example clearly separated from protocol revision 2026-07-28.
Building an MCP Server in Python — Architecture, FastMCP and Deployment Pitfalls Read Post »
epoll reports readiness; io_uring returns operation results. Comparing I/O models, batching, SQPOLL and deployment constraints without universal RPS thresholds.
epoll vs io_uring — When the Event Loop Isn’t Enough Read Post »
DRY is about knowledge, not similar lines. Distinguishing shared rules from incidental duplication and recognizing the cost of premature abstraction.
The DRY Myth — When Code Duplication Is the Correct Architecture Read Post »