Changelog

This is an excellent post with some immediately useful takeaways (and some open source, to boot). Chris starts it with a compelling description of JSON API's value proposition: how to use JSON API as an "anti-bikeshedding weapon" Building Restful APIs requires hundreds of tiny decisions, which is like having a bike shed on every corner. Outsource the little stuff!

Transforms JSON into discrete assignments to make it easier to grep for what you want and see the absolute 'path' to it. It eases the exploration of APIs that return large blobs of JSON but have terrible documentation. Also works in reverse, so you can turn your filtered data back in to JSON.

To display a tweet properly, it needs to be well formatted. This means identifying and linking entities like usernames, hashtags and URLs. In simple terms, it is converting a typical tweet object like this... It is dizzying how complex the tweet data structure has become over the years. We've come a long way from 140 characters of unicode.

It's unfortunate that this only works with iTerm2. Anybody up for a port? 😏

Pipe some JSON to the quicktype CLI and it will spit out types and code to read/write/validate the data in your language of choice. Currently supports 10 target languages. There's also a web-based version so you can kick the tires.

Chris McCord with a great round-up of advancements to the popular Elixir web framework. Highlights include H2 support, faster dev compilation, and a harder/better/faster/stronger JSON encoding library.

Imagine a JavaScript app that keeps all of its state in model objects. Now imagine that those objects are automatically synced and merged across network-attached devices. That's Automerge in a nutshell. It works a lot like Git, really, except for one big difference... no merge conflicts to resolve!

The Netflix team managed to squeeze out some huge performance improvements over Active Model Serializers: We want to ensure that with every change on this library, serialization time is at least 25 times faster than Active Model Serializers on up to current benchmark of 1000 records. At first glance I thought this was a drop-in replacement for AMS, which would've been epic, but it has its own API. That being said, its API is pretty similar and looks easy to use. Exactly how much faster is this library? It can serialize 250 records in 3.01 ms vs AMS's 138.71 ms!