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A JSON Patch document is structured as a JSON array of objects where each object contains one of the six JSON Patch operations: add, remove, replace, move, copy, and test. This structure was influenced by the specification of XML patch.
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.
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.
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.
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 ...
Every JSON value is itself a value in jq, which accordingly has the types shown in the table below. [13] The gojq and jaq implementations distinguish between integers and non-integer numbers. The gojq implementation supports unbounded-precision integer arithmetic , as did the original implementation of jq in Haskell.
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.