TLDR WEB DEV 2023-10-20

ANALYZING MULTI-GIGABYTE JSON FILES LOCALLY

Working with large JSON files can be time-consuming, especially when analyzing them. There are two efficient solutions for local processing: one involves parallelizing JQ commands using GNU parallel and the other is based on Jupyter and the Dask library, which allows for distributed processing of large JSON files. This article discusses strategies for efficiently analyzing multi-gigabyte JSON files in a project context. It demonstrates the advantages of Dask for interactive data analysis, which enables the creation of pipelines that preprocess and analyze large JSON files without loading everything into memory.

SCROLL-DRIVEN STATE TRANSFER

SOLID.JS CREATOR OUTLINES OPTIONS TO REDUCE JAVASCRIPT CODE

RANDOM THOUGHTS 15 YEARS INTO SOFTWARE ENGINEERING

FROM INDIVIDUAL CONTRIBUTOR TO ENGINEERING DIRECTOR

ANNOUNCING TANSTACK QUERY V5

The query-led state management library TanStack Query hits its latest milestone release with an improved and more consistent API, simpler optimistic updates, sharable mutation state, non-experimental Suspense support, new devtools, and more. It’s available to use with React, Vue, Svelte, Solid, and other frameworks.

SYSTEM DESIGN 101

APPLE’S USE OF SWIFT AND SWIFTUI IN IOS 17

NETWORKING AS AN INTROVERT CTO

SOME NOTES ON LOCAL FIRST DEVELOPMENT

HTML TAGS MEMORY TEST

A quiz to see how many of the 114 HTML div elements you can remember.

IN-MEMORY DATABASE REDIS WANTS TO DABBLE IN DISK

HOW THE MICROSERVICE VS. MONOLITH DEBATE BECAME MEANINGLESS