This approach does not scale that well, however. The serialization of this object won’t contain the age, but it is available in our code. I have a User entity with two fields that I want to convert to JSON and back.ĭata class User ( val id : String = "", (access = JsonProperty. You can use an ObjectMapper to do the parsing, although you can configure SpringBoot to do it mostly automatically, which I will show later. They are immutable (yay!) and have convenience methods like equals and toString out of the box. They are the equivalent of using the annotation in Lombok, with first-class support from the language. We will be using data classes to represent the entities that will get converted to a from JSON. ![]() In this case, I will be using SpringBoot. I have a bunch of examples showing how to parse different classes, plus some code to integrate it into your workflow. Jackson is a mighty library, but you can get lost easily. Nowadays, using Kotlin and Jackson you can deal with JSON with minimal effort. Things have changed a lot (for the better!) since then. That is what initially led me to use Ruby. ![]() I remember that dealing with JSON in Java used to be pretty painful back in the day, as you had to write a ton of code to map objects. I want to talk about my experience using Kotlin and Jackson for this. Having the right tools to parse and produce JSON can thus make a big impact in keeping the code tidy and compact. It is especially true if you are trying to keep those backends as simple as possible ( Microservices anyone?). It seems that many backends that provide a REST API end up being glorified proxies that move JSON from one place to another. ![]() Painless JSON with Kotlin and jackson 6 Kotlin JSON Jackson REST SpringBoot
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