An end-to-end example of Json Logic Scala

This example starts from typed JsonLogic data, then deserializes it into a Scala data structure. With json-logic-scala, it would be just as easy to perform the reverse process (starting from a Scala struture and serializing it as Typed JsonLogic).

1. Represent an expression as JsonLogic-typed

Consider the following expression.

\[\mathbf{price} \ge 20\ \&\ \mathbf{label}\neq\mathbf{label2}\]

You can represent this expression, along with possible values in a single Json data file:

 [
  {
    "and": [
      {
        ">=": [
          {
            "var": "price",
            "type": {
              "codename": "int"
            }
          },
          {
            "var": "price_threshold",
            "type": {
              "codename": "int"
            }
          }
        ]
      },
      {
        "!=": [
          {
            "var": "value",
            "type": {
              "codename": "string"
            }
          },
          {
            "var": "value_to_be_different",
            "type": {
              "codename": "string"
            }
          }
        ]
      }
    ]
  },
  {
    "price": 45,
    "price_threshold": 20,
    "value": "label456",
    "value_to_be_different": "label2"
  }
]

Note that, in this snippet, data and logic are separate objects.

Let’s assume this json is written in a json file named binary_expression.json.

2. Deserialize the Json as a Scala Data structure

Using Json Logic Scala, you can deserialize the preceding JSON snippet as a scala data structure. The expression and data looks like this:

import play.api.libs.json.Json

val jsonString: String = scala.io.Source.fromFile("binary_expression.json").mkString
implicit val deserializerConf: DeserializerConf = DeserializerConf.createConf()
val deserializer = new Deserializer()
val jsonLogicCore = deserializer.deserialize(jsonString)

the resulting jsonLogicCore structure is equivalent to

import com.celadari.jsonlogicscala.tree.types.DefaultTypes.{INT_CODENAME, STRING_CODENAME}

val tree = new ComposeLogic("and", Array(
  new ComposeLogic(">=", Array(
    ValueLogic(Some(45), typeOpt = Some(SimpleTypeValue(INT_CODENAME)), pathNameOpt = Some("price")),
    ValueLogic(Some(20), typeOpt = Some(SimpleTypeValue(INT_CODENAME)), pathNameOpt = Some("price_threshold"))
  )),
  new ComposeLogic("!=", Array(
    ValueLogic(Some("label456"), typeOpt = Some(SimpleTypeValue(STRING_CODENAME)), pathNameOpt = Some("value")),
    ValueLogic(Some("label2"), typeOpt = Some(SimpleTypeValue(STRING_CODENAME)), pathNameOpt = Some("value_to_be_different"))
  ))
))

3. Evaluate the expression

Finally, you can evaluate this Scala data structure.

val evaluator = new EvaluatorLogic
evaluator.eval(tree)
// false: Any

The price value is 45, and the tested threshold is 20. 45 is greater than 20, so the result will be false.

4. Serialize to TypedJson

Using Json Logic Scala, you can serialize the json-scala data structure to a JSON snippet. The expression and data looks like this:

import com.celadari.jsonlogicscala.tree.types.DefaultTypes.{INT_CODENAME, STRING_CODENAME}

val tree = new ComposeLogic("and", Array(
  new ComposeLogic(">=", Array(
    ValueLogic(Some(45), typeOpt = Some(SimpleTypeValue(INT_CODENAME)), pathNameOpt = Some("price")),
    ValueLogic(Some(20), typeOpt = Some(SimpleTypeValue(INT_CODENAME)), pathNameOpt = Some("price_threshold"))
  )),
  new ComposeLogic("!=", Array(
    ValueLogic(Some("label456"), typeOpt = Some(SimpleTypeValue(STRING_CODENAME)), pathNameOpt = Some("value")),
    ValueLogic(Some("label2"), typeOpt = Some(SimpleTypeValue(STRING_CODENAME)), pathNameOpt = Some("value_to_be_different"))
  ))
))

import play.api.libs.json.Json

implicit val serializerConf: SerializerConf = SerializerConf.createConf()
val serializer = new Serializer()
val jsonLogicCore = serializer.serialize(tree)