Adam Stankiewicz sheerun

Frontend Development

Attention: the list was moved to

https://github.com/dypsilon/frontend-dev-bookmarks

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Better local require() paths for Node.js

Problem

When the directory structure of your Node.js application (not library!) has some depth, you end up with a lot of annoying relative paths in your require calls like:

const Article = require('../../../../app/models/article');

Those suck for maintenance and they're ugly.

Possible solutions

THIS GIST WAS MOVED TO TERMSTANDARD/COLORS REPOSITORY.

PLEASE ASK YOUR QUESTIONS OR ADD ANY SUGGESTIONS AS A REPOSITORY ISSUES OR PULL REQUESTS INSTEAD!

Experimental Relay Implementation

Features:

Relay.fetch(graphqlQuery) returns subscribtion that could change over time by mutation queries.
Relay.update(m: UpdateMutation) optimistically updates resource in all previous queries that contains updated resource.
Relay.update(m: DeleteMutation) optimistically deletes resource from all previous queries that contains deleted resource.
Relay.update(m: CreateMutation) pessimistically creates resource and executes again all previous queries.
All objects with id key in graphql response explained as resources. Arrays, objects without id and scalars explained as static properties.

These links no longer work. Springer have pulled the free plug.

Graduate texts in mathematics

duplicates = multiple editions

A Classical Introduction to Modern Number Theory, Kenneth Ireland Michael Rosen

Setting Up and Calibrating Sensorless XY Homing

When using the TMC2130 / TMC2209 / TMC2660 / TMC5160 drivers, the StallGuard feature makes it possible to set up sensorless homing on the X and Y axes for CoreXY machines. The Klipper project has a page with documentation and recommendations on getting it working.

Following are some more detailed instructions and suggestions to supplement the Klipper documentation specifically for Vorons.

Hardware Setup

Extracting financial disclosure reports and police blotter narratives using OpenAI's Structured Output

tl;dr this demo shows how to call OpenAI's gpt-4o-mini model, provide it with URL of a screenshot of a document, and extract data that follows a schema you define. The results are pretty solid even with little effort in defining the data — and no effort doing data prep. OpenAI's API could be a cost-efficient tool for large scale data gathering projects involving public documents.

OpenAI announced Structured Outputs for its API, a feature that allows users to specify the fields and schema of extracted data, and guarantees that the JSON output will follow that specification.

For example, given a Congressional financial disclosure report, with assets defined in a table like this:

	source "https://rubygems.org/"

	gem "neo4j"
	gem "pry"
	gem "minitest"
	gem "jbundler"

	import { Component } from "React";

	export var Enhance = ComposedComponent => class extends Component {
	constructor() {
	this.state = { data: null };
	}
	componentDidMount() {
	this.setState({ data: 'Hello' });
	}
	render() {