The second trick is related to mandatory fields of primitive types. While this implementation is pretty naive and can be improved in different ways, it shows the idea.īy the way, you can also check here that values are invalid range within the type, like positive integers or non-empty strings. If (id = null) throw JsonParseException(''id' is null!') It can be done in different ways, the most straightforward of them is just a validate() method like this data class User(

In order to make sure that there are no nulls in non-nullable fields, we have to validate them after parsing. Would produce an NPE at the last line, as Gson would set null into the non-nullable field via reflection.

Val user: User = Gson().fromJson(invalidResponse, User::class.java) Suppose we have the following response: ''' I will use JSON and GSON as an example, but the idea remains the same regardless of the format and deserialization method. One of the most common use cases is network communication. There are many use-cases of Java-interop and just as many ways to increase the level of safety when dealing with it. While this works perfectly in pure Kotlin code, null-safety cannot be guaranteed when Java interoperation begins. It gives us compile-time knowledge of where null can be and where not. One of Kotlin’s best features is null safety.

Null safe kotlin