json-deserialize.md

title	type	description	num	previous-page	next-page
How to deserialize JSON to an object?	section	Parsing JSON to a custom data type	19	json-modify	json-serialize

{% include markdown.html path="_markdown/install-upickle.md" %}

Parsing vs. deserialization

Parsing with uJson only accepts valid JSON, but it does not validate that the names and types of fields are as expected.

Deserialization, on the other hand, transforms a JSON string to some user-specified Scala data type, if required fields are present and have the correct types.

In this tutorial, we show how to deserialize to a Map and also to a custom case class.

Deserializing JSON to a Map

For a type T, uPickle can deserialize JSON to a Map[String, T], checking that all fields conform to T.

We can for instance, deserialize to a Map[String, List[Int]]:

{% tabs 'parsemap' %} {% tab 'Scala 2 and 3' %}

valjson="""{"primes": [2, 3, 5], "evens": [2, 4, 6]} """valmap:Map[String, List[Int]] = upickle.default.read[Map[String, List[Int]]](json) println(map("primes")) // prints: List(2, 3, 5)

{% endtab %} {% endtabs %}

If a value is the wrong type, uPickle throws a upickle.core.AbortException.

{% tabs 'parsemap-error' %} {% tab 'Scala 2 and 3' %}

valjson="""{"name": "Peter"} """ upickle.default.read[Map[String, List[Int]]](json) // throws: upickle.core.AbortException: expected sequence got string at index 9

{% endtab %} {% endtabs %}

Deserializing JSON to a custom data type

In Scala, you can use a case class to define your own data type. For example, to represent a pet owner, you might:

caseclassPetOwner(name: String, pets: List[String])

To read a PetOwner from JSON, we must provide a ReadWriter[PetOwner]. uPickle can do that automatically:

{% tabs 'given' class=tabs-scala-version %} {% tab 'Scala 2' %}

importupickle.default._implicitvalownerRw:ReadWriter[PetOwner] = macroRW[PetOwner]

Some explanations:

• An implicit val is a value that can be automatically provided as an argument to a method or function call, without having to explicitly pass it.
• macroRW is a method provided by uPickle that can generate a instances of ReadWriter for case classes, using the information about its fields. {% endtab %} {% tab 'Scala 3' %}

importupickle.default.*caseclassPetOwner(name: String, pets: List[String]) derivesReadWriter

The derives keyword is used to automatically generate given instances. Using the compiler's knowledge of the fields in PetOwner, it generates a ReadWriter[PetOwner]. {% endtab %} {% endtabs %}

This means that you can now read (and write) PetOwner objects from JSON with upickle.default.read(petOwner).

Notice that you do not need to pass the instance of ReadWriter[PetOwner] explicitly to the read method. But it does, nevertheless, get it from the context, as "given" value. You may find more information about contextual abstractions in the Scala 3 Book.

Putting everything together you should get:

{% tabs 'full' class=tabs-scala-version %} {% tab 'Scala 2' %}

importupickle.default._caseclassPetOwner(name: String, pets: List[String]) implicitvalownerRw:ReadWriter[PetOwner] = macroRW valjson="""{"name": "Peter", "pets": ["Toolkitty", "Scaniel"]}"""valpetOwner:PetOwner= read[PetOwner](json) valfirstPet= petOwner.pets.head println(s"${petOwner.name} has a pet called $firstPet") // prints: Peter has a pet called Toolkitty

{% endtab %} {% tab 'Scala 3' %}

importupickle.default.*caseclassPetOwner(name: String, pets: List[String]) derivesReadWritervaljson="""{"name": "Peter", "pets": ["Toolkitty", "Scaniel"]}"""valpetOwner:PetOwner= read[PetOwner](json) valfirstPet= petOwner.pets.head println(s"${petOwner.name} has a pet called $firstPet") // prints: Peter has a pet called Toolkitty

{% endtab %} {% endtabs %}