XML validation and binding library.
- Validate XML structure
- Assertions on nodes and node collections
- Decode XML
- As nested HLists (default)
- As arbitrary data types by using custom decoders
- Using effects (decoders can target an arbitrary monad)
- Encode XML
- Modular schemas
- No support for namespaces
- No support for validating the order of nodes
- No support for individual text nodes (only
Elem.text
is supported)
- Test case to demonstrate usage:
Supported cardinalities for node collections:
… → A
optional(…) → Option[A]
oneOrMore(…) → NonEmptyList[A]
zeroOrMore(…) → List[A]
elem1("name", child)
elem2("name", child1, child2)
…
Attributes, text and child elements are declared as children:
elem3("name",
attr(…),
elem1("child", …),
text
)
attribute("name")
Mandatory/optional attributes:
attr("name") → String
optional(attr("name")) → Option[String]
There are two flavours of handling text:
By combining nonEmptyText
with the one
and optional
cardinalities. In this case it is assured that no empty text values are emitted:
nonEmptyText → String
optional(nonEmptyText) → Option[String]
By using text
directly. In this case an empty text value are emitted if the parent element doesn't contain any text:
text → String
The schema nonEmptyText
is equivalent to text.ensure(nonEmpty)
.
Assertions can be made using ensure
:
attr("name").ensure(nonEmpty)
attr("name").ensure(mustEqual("Sam"))
Assertions can be applied to collections:
oneOrMore(elem1("employee",
zeroOrMore(
elem1("tool", text)
).ensure(check(_.size < 3, _ => "Only 2 tools allowed"))
))
Custom assertions can be implemented in this fashion.
It is possible to use an effect F
; see section on codecs for details.
def nonEmpty[F[_]:Applicative]: Ensure[F, String] =
_.isEmpty.option("String must not be empty").point[F]
When using the schema builder DSL, you have to decide what you want to use your schema for: encoding, decoding, or both. This is done by importing the corresponding variant of the DSL:
import Dsl.simple.decode._
import Dsl.simple.encode._
import Dsl.simple.codec._
For decode/encode schemas, only decoders/encoders for the involved types need to be provided. For codec schemas, both decoders and encoders are required.
This approach allows the compiler to show an error when a decoder/encoder is missing in a specific location. The alternative would be using mode-agnostic schemas and assembling the decoder/encoder implicitly when it is required, but this would lead to incomprehensible implicit-not-found error messages.
In this example we use the simple schema which targets the cats.Id
monad:
// Get access to the schema builder API
import Dsl.simple.codec._
final case class Foo(a: String, b: Option[String], bars: List[Bar])
final case class Bar(c: String, d: Option[String])
val schema =
elem3("foo",
attr("a"),
optional(attr("b")),
zeroOrMore(elem2("bar",
attr("c"),
optional(attr("d"))
))
)
val result: NonEmptyList[String] \/ Foo =
schema.decode(<foo>…</foo>)
.map {
case a :: b :: barElems :: HNil =>
val bars = barElems map {
case c :: d :: HNil => Bar(c, d)
}
Foo(a, b, bars)
}
Schemas can be composed by including other schemas. A codec schema can be included in decoder and encoder schemas, but not the other way around.
import Dsl.simple.codec._
final case class Foo(a: String, b: Option[String], bars: List[Bar])
final case class Bar(c: String, d: Option[String])
val barElem =
elem2("bar",
attr("c"),
optional(attr("d"))
).as[Bar]
val fooElem =
elem3("foo",
attr("a"),
optional(attr("b")),
zeroOrMore(barElem) // Include other schema
).as[Foo]
val result: NonEmptyList[String] \/ Foo = fooElem.decode(<foo></foo>)
Text nodes, attributes, elements and collections thereof can be decoded/encoded to/from custom types. Any error messages generated during decoding are prepended with the XML path, which makes it easier to locate the source of the error.
Pass a codec implicitly:
attr("name").as[A]
Pass a codec explicitly:
attr("name") ~ codecForA
Codecs can be chained:
attr("foo")
.as[LocalDate] // decode to LocalDate
.as[LocalDate @@ StartDate] // apply tag
If the target type of a schema is a HList
that is the generic representation of a certain type (e.g. case class) A
, a codec for A
is provided out of the box, courtesy of shapeless:
final case class Bar(c: String, d: Option[String])
val barElem = elem2("bar", attr("c"), optional(attr("d"))).as[Bar]
A codec targets an effect monad F
, which makes it usable only in schemas supporting this effect type.
implicit def myCodec[F[_]]: Codec[F, String, Foo] =
Codec.from(
Decoder.fromDisjunction(x => if (canDecode(x)) \/-(…) else -\/(NonEmptyList("An error occurred"))),
Encoder.fromFunction(_.unwrap)
)
Example for a decoder targeting a cats.data.Reader
:
type EnvReader[A] = Reader[Env, A]
def findVideoFormat(env: Env, name: String): Option[VideoFormat] = ???
def getVideoFormatName(env: Env, videoFormat: VideoFormat): String = ???
implicit def videoFormatCodec: Codec[EnvReader, String, VideoFormat] =
Codec.from(
Decoder.fromEitherT(name => EitherT(Reader { env =>
val videoFormat: Option[VideoFormat] = findVideoFormat(env, name)
videoFormat.\/>(s"Video format $name not found")
})),
Encoder.fromEffect(f => Reader(env => getVideoFormatName(env, f)))
)
Usage:
attr("name").as[VideoFormat]
Decoding XML targeting the EnvReader
effect monad:
// Create a schema
val mySchema = new ch.srg.xml.Schema[EnvReader]
// Get access to the schema builder API
import mySchema.codec._
val schema = …
schema
.decode(xml)
.run(env) // Execute the effect