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JSONiq [11] is a query and transformation language for JSON. XPath 3.1 [12] is an expression language that allows the processing of values conforming to the XDM [13] data model. The version 3.1 of XPath supports JSON as well as XML. jq is like sed for JSON data – it can be used to slice and filter and map and transform structured data.
removes a value from an object or array. Replace replaces a value. Logically identical to using remove and then add. Copy copies a value from one path to another by adding the value at a specified location to another location. Move moves a value from one place to another by removing from one location and adding to another. Test
When deserializing, Gson navigates the type tree of the object being deserialized, which means that it ignores extra fields present in the JSON input. The user can: write a custom serializer and/or deserializer so that they can control the whole process, and even deserialize instances of classes for which the source code is inaccessible.
In computing, Jackson is a high-performance JSON processor for Java. Its developers extol the combination of fast, correct, lightweight, and ergonomic attributes of the library. Its developers extol the combination of fast, correct, lightweight, and ergonomic attributes of the library.
The sample JSONiq code below computes the area code and the number of all people older than 20 from a collection of JSON person objects (see the JSON article for an example object). for $ p in collection ( "persons" ) where $ p.age gt 20 let $ home := $ p.phoneNumber [][ $ $. type eq "home" ] . number group by $ area := substring-before ...
While JSON provides a syntactic framework for data interchange, unambiguous data interchange also requires agreement between producer and consumer on the semantics of specific use of the JSON syntax. [25] One example of where such an agreement is necessary is the serialization of data types that are not part of the JSON standard, for example ...
In object-oriented programming, behavior is sometimes shared between classes which are not related to each other. For example, many unrelated classes may have methods to serialize objects to JSON. Historically, there have been several approaches to solve this without duplicating the code in every class needing the behavior.
JSON-LD is designed around the concept of a "context" to provide additional mappings from JSON to an RDF model. The context links object properties in a JSON document to concepts in an ontology. In order to map the JSON-LD syntax to RDF, JSON-LD allows values to be coerced to a specified type or to be tagged with a language.