Rapture JSON

Rapture JSON is a comprehensive library providing support for working with JSON in Scala. Rapture JSON is part of the Rapture project.

Features

• Clean, intuitive, unintrusive, boilerplate-free Scala API
• Trivial extraction and serialization to/from primitives, collections and case classes
• Consistent and typesafe type-class-based interfaces
• Works with a choice of JSON parsers and backends
• Simple, efficient conversion between different backends
• Support for both immutable and mutable JSON
• Flexible choice of error handling strategies using modes

Availability

Rapture JSON 1.0.6 is available under the Apache 2.0 License from Maven Central with group ID com.propensive and artifact ID rapture-json_2.10.

SBT

You can include Rapture JSON as a dependency in your own project by adding the following library dependency to your build file:

libraryDependencies ++= Seq("com.propensive" %% "rapture-json-[backend]" % "1.0.6")

where [backend] is one of the following JSON backends:

• Argonaut (argonaut)
• Jackson (jackson)
• Jawn (jawn)
• JSON4S (json4s)
• Lift JSON (lift -- Scala 2.10 only)
• Spray (spray)

You can also use Rapture JSON with the JSON parser built into Scala 2.10 with the following dependency, though this is not recommended due to the poor performance characteristics of this parser.

libraryDependencies ++= Seq("com.propensive" %% "rapture-json" % "1.0.6")

Maven

If you use Maven, include the following dependency:

<dependency>
  <groupId>com.propensive</groupId>
  <artifactId>rapture-json-[backend]_2.10</artifactId>
  <version>1.0.6<version>
</dependency>

where [backend] is one of the backends listed above.

Building from source with SBT

To build Rapture JSON from source, follow these steps:

git clone git@github.com:propensive/rapture-json.git
cd rapture-json
sbt package

If the compilation is successful, the compiled JAR file should be found in the directory for the appropriate Scala version in the target directory.

Status

Rapture JSON is now stable. This means that the API represents a useful set of features, and is unlikely to change significantly in subsequent releases. All API changes will be documented with instructions on how to upgrade.

Contributing

Rapture JSON -- like all the Rapture projects -- openly welcomes contributions! We would love to receive pull requests of bugfixes and enhancements from other developers. To avoid potential wasted effort, bugs should first be reported on the Github issue tracker, and it's normally a good idea to talk about enhancements on the Rapture mailing list before embarking on any development. Alternatively, just send Jon Pretty (@propensive) a tweet to start a conversation.

Using Rapture JSON

JSON Representation

Rapture JSON is designed to be agnostic about the JSON parser and choice of AST representation used throughout the library. This means that a choice of JSON backend must be made in order to use Rapture JSON. Whilst different backend libraries provide different features, all features of Rapture JSON are available with every backend (with the exception of Jackson, which does not yet support mutable JSON operations).

The choice of backend should therefore depend on other characteristics such as performance, memory usage, required dependencies, integration with existing libraries, licensing and policy choices.

The following backends are available:

• Argonaut (argonaut)
• Jackson (jackson)
• Jawn (jawn)
• JSON4S (json4s)
• Lift (lift -- Scala 2.10 only)
• Scala standard library JSON (scalaJson)
• Spray (spray)

Work is ongoing to make Play JSON available too. It is also possible to integrate with other JSON backends, though this is not covered by this document. Anyone interested should look at the existing integration type classes, and contact the Rapture mailing list.

In the source code, you should import rapture.json.jsonBackends.<backend>._.

The Json type

A JSON value, whether an array, object, boolean, number or string, is represented by an instance of type Json. As JSON is inherently dynamically-typed, the Json type is used to provide a safe and immutable wrapper around the JSON tree, whose type is not known at compile time.

Instances of Json consist of three things:

• a reference to the root of a dynamically-typed JSON tree
• a path into a node within the JSON tree
• a reference to the parser used to create, modify and read the JSON tree

Although using Json objects should seem very intuitive, it is important to understand the purpose of this state.

{
  "fruits": [
    {
      "name": "apple",
      "color": "red"
    },
    {
      "name": "banana",
      "color": "yellow"
    }
  ]
}

If we were to parse the above JSON source, we should get a tree consisting of an object containing an array under the key "fruits", with two elements, each of which is an object containing two fields, "name" and "color", both of which are strings. Given this tree, we can refer to an element within with a path of strings for indexing JSON objects, and integers for indexing JSON arrays, for example, fruits / 0 / name, which would refer to the string "apple".

We could also look into the same tree with the path fruits / 3 / mass, though this wouldn't exist on account of there being only two elements in the fruits list, but we would not know this until we attempted it at runtime.

A Json instance represents both the JSON tree, and a lazily-evaluated path into that tree, which may or may not point to a value. If we assume the full JSON tree is a starting point (most likely originating from being parsed from source), Json instances can be created which hold the same reference to the original tree, but point -- by means of a path -- to any subtree of the original, without the performance cost of navigating the tree, or the requirement to safely handle missing-value or type-mismatch errors which arise because the path attempts to access a value which isn't available.

At some later point, if the JSON is to yield some useful data which we can do interesting things with, we will need to perform the access, and assign a Scala type to it, as it passes from the dynamic to the static world. It is at this point that all access failures will arise, so by deferring them to a single point, they can be handled just once.

Additionally, every Json instance stores a reference to the backend which was used to create it, and which will be used to access it. As Rapture JSON permits multiple different parsers to be used alongside each other, it is important that the AST within each Json instance is always handled using the right backend.

Accessing JSON values

Json instances implement Scala's Dynamic trait, providing a very natural way to refer to object fields within a Json value just by calling that field name as if it were a method on the Json instance. Additionally, integers may be applied to index into arrays.

For example, using the example JSON above, we can create a new Json instance pointing to the string "yellow" as follows:

json.fruits(1).color

Remember, this is just creating a pointer into the "yellow" value; it's not been accessed yet. To extract a value from a Json value, the as method is used. as takes a single type parameter, and is the single point at which a JSON type-mismatch or missing-value exception can occur.

json.fruits(1).color.as[String]

Rapture JSON uses Rapture Core's modes on the as method, thus allowing failure cases to be handled using the preferred exception-handling strategy, for example by throwing an exception or returning a Try. See the section on error messages below.

Note that calling toString, as happens automatically after every evaluation in the Scala REPL, will cause the AST to be accessed, but any errors will be suppressed, and the toString method will return the string "undefined".

A variety of types may be extracted from a Json value, including the following:

• Primitive types, such as String, Int, Double and Boolean
• Scala collections of other extractable types, e.g. List[Int] or Set[Int]
• Case classes, extracted by the names of their parameters, provided the type of every parameter is extractable
• Options, where None will be extracted if the element is missing or the wrong type
• Json types -- the no-op extractor
• Any other type for which an implicit Extractor exists in scope

These types compose, so it is possible to extract values of complex types like Option[Vector[MyCaseClass]].

Creating JSON values

JSON values can be created in a number of different ways. If starting with a JSON source, which will often be a String (but may be another type -- the Jawn backend can parse directly from ByteBuffers, for example), we can call Json.parse(src) to attempt to parse the source src.

Json values can also be created directly in code, using the json string context, like so:

json"""{
  "fruit": "apple",
  "variants": ["cox", "braeburn"]
}"""

Much lake an interpolated string, Scala expressions may be substituted into a json string context, provided the expressions evaluate to a type which is serializable to Json. Generally speaking, all types which can be extracted from a Json value (primitives, collections, case classes, Json) can also be serialized, like so:

val f = "apple"
json"""{
  "fruit": $f,
  "variants": ${List("cox", "braeburn")}
}"""

Any serializable type can also be converted to Json by applying it to the Json object, for example this,

case class Fruit(name: String, variants: Set[String])
Json(Fruit("apple", Set("cox", "braeburn")))

will produce the same JSON as the previous examples.

An instructive compile error will be displayed in the event of an attempt to serialize a type which cannot be serialized to Json.

Pattern matching on JSON

An alternative way of extracting values from Json types in to use pattern matching. A Json value can be pattern matched against JSON literals defined inline in the case clause, like this:

val json: Json = Json.parse(src)
json match {
  case json""" { "fruit": $name }""" =>
    name.as[String]
  case json""" { "vegetable": $name }""" =>
    name.as[String]
}

This will first attempt to match any JSON object which contains a key called fruit, and bind the value to the identifier name. If that match fails, it will attempt to match any JSON object which contains a key called vegetable, and likewise bind its value to name. In each case, we return the name as a String. The call to .as[String] is necessary because, as before, the compiler will no know nothing about the nature of the type at compile time, so it must be explicitly specified.

Literal match values may also be explicitly specified, for example:

val json: Json = Json.parse(src)
json match {
  case json""" { "fruit": "apple", "variety": $vs }""" =>
    vs.as[Set[String]]
  case json""" { "fruit": "lemon" }""" =>
    Set()
}

Multiple values may be extracted, and the pattern match expression may involve arbitrarily-deep object and array nesting.

The examples above use the default configuration for structural pattern matching, however three configuration explicits control the strictness of structural pattern matching.

• patternMatching.exactObjects
• patternMatching.exactArrays
• patternMatching.exact

If it is required that pattern matching on JSON objects should match the entire object, i.e. the existence of any keys in the object which are not specified in the pattern should result in failure to match, then include the following import somewhere within the scope of the pattern match:

import patternMatching.exactObjects

By default, array elements specified in a pattern are matched positionally, and superfluous array elements in the tail of the array are ignored, and the match will be successful. If strict array matching is required, include:

import patternMatching.exactArrays

If exact matching of both arrays and objects is required, then it is sufficient to import

import patternMatching.exact

Modifying Json

Whatever underlying backend is used, the Json type is immutable. A small number of methods are provided to create new Json values from existing values. Given a Json value, a new key may be added using the following syntax:

val j = json"""{ "fruit": "plum" }"""
j + (_.color, "purple")

This syntax is designed to resemble the syntax for adding a value to a scala.collection.Map, whereby the tuple passed to the + operator contains a key and a value, resulting in the addition of this value to the map. However, with Json types, the "key" is a path into the Json structure, and the "value" is the value to be serialized to JSON and stored at that position in the JSON tree.

The ++ operator can be used to combine two JSON structures, like so:

val j1 = json"""{ "fruit": { "name": "grape" } }"""
val j2 = json"""{ "fruit": { "color": "white" } }"""
val json = j1 ++ j2

The resultant json value would be

{
  "fruit": {
    "name": "grape",
    "color": "white"
  }
}

Currently, when merging, object keys from both sides will be merged, favoring the right side in the event of a clash, and arrays will be concatenated. If the types of corresponding values do not match, the value from the right side will clobber that from the left. In a later version of Rapture JSON, more control over mechanisms for combining and merging Json values may be provided through configuration implicits.

Error messages

By default, failures in Rapture JSON operations will result in an exception being thrown, however, alternative exception handling methods can be used with a simple import from the Rapture Core project which will determine the return type of all fallible methods such as Json.parse and as. For example,

import rapture.core._
import modes.returnTry
Json.parse(src)

will result in the return type of Json.parse changing from Json to Try[Json], safely capturing any failures which may result from the operation.

All Rapture JSON methods will throw a limited set of possible exceptions, which are implemented as case classes inheriting from a sealed trait. If choosing to use the captureExceptions mode, or another mode which captures the exception and tracks the exception type in its signature, this allows exhaustivity checking to be performed on errors, for example:

import modes.captureExceptions
json.fruit.as[String] match {
  case Right(f) =>
    s"Found fruit $f"
  case Left(TypeMismatchException(found, _, _)) =>
    s"Fruit was the wrong type: $found)
  case Left(MissingValueException(path)) =>
    s"Fruit value was missing at path $path"
}

If either of the final two case clauses were omitted from this pattern match, the compiler will issue a warning that the match may not be exhaustive.

Mutable JSON

In the same way that the List type from the Scala collections library has a corresponding mutable ListBuffer type, the Json type has a corresponding JsonBuffer type, which supports mutability in addition to the operations described above. The functionality of JsonBuffer is a strict superset of the functionality of Json.

An empty JsonBuffer may be created with

val jb = JsonBuffer.empty

and can be mutated with instructions such as

jb.fruit.name = "apple"
jb.fruit.color = "green"
jb.fruit.varieties = List("cox")

resulting in

{
  "fruit": {
    "name": "apple",
    "color": "green",
    "varieties": ["cox"]
  }
}

Note that the top-level fruit object gets automatically created by the first instruction, and that the right-hand side of the assignment is serialized to JSON using Rapture's standard serialization scheme, causing a compile-time error if the type cannot be serialized.

It is additionally possible to append items to the end of an array using the += operator, like this:

jb.fruit.varieties += "braeburn"

Mutable JSON is not yet available for all backends, though this work is in progress. Note that the underlying JSON backend does not need to be inherently mutable to support mutable JSON. If a backend which uses an immutable AST is used, Rapture JSON will efficiently perform the necessary tree manipulations, updating references as necessary to give the impression of a mutable data structure. However, using a backend which uses a mutable JSON representation will likely result in better performance.

Converting JSON

Depending on how a JSON value is created, the same Scala type is used, regardless of the JSON backend that was used to create it.

Outputting JSON

Often, the easiest way to output JSON from the Json type is to call .toString on the Json value. Although simple, this has the disadvantages that it does not offer any flexibility in how the JSON is formatted, and it always returns a String whereas other types, such as an input stream may be more appropriate for some applications.

The more general method is to use the Json.format method, with an appropriate implicit Formatter in scope. Two formatters are provided as standard:

• formatters.humanReadable, which formats the JSON with newlines and indentation, attempting to make it as readable as possible,
• formatters.compact, which includes no unnecessary whitespace

Both formatters return Strings, though it is possible for other backends to provide their own formatters for outputting to other types.

For example,

import formatters.compact
val out = Json.format(json)