Product types are disambiguated by a {"key":"value",...}.
Product types are disambiguated by a {"key":"value",...}. Of
course, this will fail if the product type has a field with the
same name as the key. The default key is the word "type" which
is a keyword in Scala so unlikely to collide with too many case
classes.
This variant is most common in JSON serialisation schemes and well supported by other frameworks.
Sometimes the wire format needs to match an existing format and
JsNull behaviour needs to be customised.
Sometimes the wire format needs to match an existing format and
JsNull behaviour needs to be customised. This allows null
behaviour to be defined at the product level. Field level control
is only possible with a user-defined RootJsonFormat.
Product types are disambiguated by an extra JSON map layer containing a single key which is the name of the type of product contained in the value.
Product types are disambiguated by an extra JSON map layer
containing a single key which is the name of the type of product
contained in the value. e.g. {"MyType":{...}}
This variant may be more appropriate for non-polymorphic schemas such as MongoDB and Mongoose (consider using the above format on your endpoints, and this format when persisting).
a JsonFormat[HList] or JsonFormat[Coproduct] would not retain the
type information for the full generic that it is serialising.
a JsonFormat[HList] or JsonFormat[Coproduct] would not retain the
type information for the full generic that it is serialising.
This allows us to pass the wrapped type, achieving: 1) custom
CoproductHints on a per-trait level 2) configurable null behaviour
on a per product level 3) clearer error messages.
This is intentionally not part of the JsonFormat hierarchy to
avoid ambiguous implicit errors.
All values serialising to JsNull will be included in the wire format.
All values serialising to JsNull will be included in the wire format. Ambiguous.
Option values of None are omitted, but Some values of JsNull are retained.
Option values of None are omitted, but Some values of JsNull are retained. Default.
No values serialising to JsNull will be included in the wire format.
No values serialising to JsNull will be included in the wire format. Ambiguous.
Format for LabelledGenerics that uses the HList or Coproduct
marshaller above.
Format for LabelledGenerics that uses the HList or Coproduct
marshaller above.
Blah.Aux[T, Repr] is a trick to work around scala compiler
constraints. We'd really like to have only one type parameter
(T) implicit list g: LabelledGeneric[T], f:
Cached[Strict[JsonFormat[T.Repr]]] but that's not possible.
Automatically create product/coproduct marshallers (i.e. families of sealed traits and case classes/objects) for spray-json.
Shapeless allows us to view sealed traits as "co-products" (aka
Coproducts) and to view case classes / objects as "products" (akaHLists).Here we write marshallers for
HLists andCoproducts and a converter to/from the generic form.Customisation
Users may provide an implicit
CoproductHint[T]for their sealed traits, allowing the disambiguation scheme to be customised. Some variants are provided to cater for common needs.Users may also provide an implicit
ProductHint[T]for their case classes, allowing wire format field names to be customised and to specialise the handling ofJsNullentries. By default,Noneoptional parameters are omitted and any formatter that outputsJsNullwill be respected.Performance
TL;DR these things are bloody fast, don't even think about runtime performance concerns unless you have hard proof that these serialisers are a bottleneck.
However, **compilation times** may be negatively impacted. Many of the problems are fundamental performance issues in the Scala compiler. In particular, compile times appear to be quadratic with respect to the number of case classes/objects in a sealed family, with compile times becoming unbearable for 30+ implementations of a sealed trait. It may be wise to use encapsulation to reduce the number of implementations of a sealed trait if this becomes a problem. For more information see https://github.com/milessabin/shapeless/issues/381
Benchmarking has shown that these formats are within 5% of the performance of hand-crafted spray-json family format serialisers. The extra overhead can be explained by the conversion to/from
LabelledGeneric, and administration around custom type hinting. These are all just churn of small objects - not computational - and is nothing compared to the performance bottleneck introduced by using anEither(which uses exception throwing for control flow), e.g. https://github.com/spray/spray-json/issues/133 or howOptionfields used to be handled https://github.com/spray/spray-json/pull/136The best performance is obtained by constructing an "explicit implicit" (see the tests for examples) for anything that you specifically wish to convert to / from (e.g. the top level family, if it is on a popular endpoint) because it will reuse the formatters at all stages in the hierarchy. However, the overhead for not defining the
implicit valis less that you might expect (it only accounts for another 5%) whereas eagerly definingimplicit vals for everything in the hierarchy can (counterintuitively) slow things down by 50%.Logging at the
tracelevel is enabled to allow visibility of when formatters are being instantiated.Caveats
If shapeless fails to derive a family format for you, it won't tell you what was missing in your tree. e.g. if you have a
UUIDin a deeply nested case class in aMyFamilysealed trait, it will simply say "can't find implicit for MyFamily" not "can't find implicit for UUID". When that happens, you just have to work out what is missing by trial and error. Sorry!Also, the Scala compiler has some funny [order dependency rules](https://issues.scala-lang.org/browse/SI-7755) which will sometimes make it look like you're missing an implicit for an element. The best way to avoid this is:
1. define the protocol/formatters in sibling, or otherwise independent, non-cyclic, packages. In particular, if you define your domain objects in
foo.domainand your formats infoo.formats, note that you will not be able to access the formats from thefooparent package (this catches a lot of people out). Another approach is to use separate projects for the domain and formats, which avoids the problem entirely whilst allowing you to provide zero dependency packages of your domain objects to downstream consumers (I believe this to be good practice in a microservices world, as it effectively means exporting your schema).2. define all your custom rules in an
objectthat extendsFamilyFormatsso that the implicit resolution priority rules work in your favour (see tests for an example of this style). The derivedfamilyFormatwill win over implicit formats that have been inherited from a lower implicit scope, so you will often have to explicitly bring them back into the higher scope by listing each -- see FamilyFormats for an example usingSymbolFormatand a user-defined format. i.e. provide an explicitimplicit val symbolFormat = SymbolJsonFormat, similarly forJsObjectFormat.