This page is a collection of cool building blocks.
Fundamentally, debugging is an exercise in changing what a program does to match what it should do. It requires us to know what a program should do, which isn't captured in the code. Sometimes that's easy: What it does is crash, what it should do is not crash. Outside those trivial cases, discovering intent is harder.
This is probably what I care about most in programming: stream processing.
Stream Processing
https://medium.com/stream-processing/what-is-stream-processing-1eadfca11b97
https://iwringer.wordpress.com/2015/08/03/patterns-for-streaming-realtime-analytics/
How to be old in tech
Lazy Looping in Python
Emerging Tech
- https://pusher.com
- https://www.kinto-storage.org
- https://github.com/ryansolid/solid
- https://www.timc.dev/posts/future-of-server-side-swift
- https://www.integromat.com/en/
https://simplescraper.io
https://almad.blog/essays/no-bugs-just-todos/
https://github.com/grafana/loki/blob/master/README.md
HTML5 intro to semantic HTML
RabbitMQ in Depth
Kite - AI coding assistant
A bunch of tech things I have my eye on.
Deno - Run JavaScript more securely than with Node.js.
Apache Arrow and Apache Flight - Unify data structures across computer architectures. Avoid serialization penalty.
Parquet - columnar data formats are pretty smart
Common Crawl project.
Postgrest
https://thume.ca/2020/05/17/pipes-kill-productivity/
Static site generators: Publii and https://www.11ty.dev/
TypeScript type challenges https://github.com/type-challenges/type-challenges
Building distributed systems without imperative APIs
The OAuth Bible
Robust Client-Side JavaScript
Libraries.io (complement to npm with package scores)
Message Bus / Event Sourcing
NATS.io
The shortest way to suppress favicon 404s in your logs
On writing effective automated tests for bug-finding