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JSON Schema includes a few keywords for combining schemas together. Note that this doesn't necessarily mean combining schemas from multiple files or JSON trees, though these facilities help to enable that and are described in Structuring a complex schema. Combining schemas may be as simple as allowing a value to be validated against multiple criteria at the same time. These keywords correspond to
Understanding JSON SchemaJSON Schema is a powerful tool for validating the structure of JSON data. However, learning to use it by reading its specification is like learning to drive a car by looking at its blueprints. You don't need to know how an electric motor fits together if all you want to do is pick up the groceries. This book, therefore, aims to be the friendly driving instructor for JSON S
Release notes for migrating from zyp-04 and fge-00 (draft-04) to wright-01 (draft-06). Note that draft-07 core and validation are backwards-compatible with draft-06. For more information, see that draft's migration notes. Q: What are the changes between draft-04 and draft-06? Backwards-incompatible changesAdditions and backwards-compatible changesFormats: "uri" vs "uri-reference"Q: What happened t
For the Core and Validation specifications, draft-07 is a relatively minor update. In terms of validation keywords and outcomes, it is fully backwards-compatible with draft-06. Some differences exist with keywords moved over from Hyper-Schema, and with how instances and schemas are recommended to be linked together. Finally, the process of collecting annotation keyword values has been defined more
JSON Schema: A Media Type for Describing JSON Documents Abstract JSON Schema defines the media type "application/schema+json", a JSON-based format for describing the structure of JSON data. JSON Schema asserts what a JSON document must look like, ways to extract information from it, and how to interact with it. The "application/schema-instance+json" media type provides additional feature-rich inte
This example shows a possible JSON representation of a hypothetical machine’s mount points as represented in an /etc/fstab file. An entry in an fstab file can have many different forms. Here is a possible representation of a full fstab: { "/": { "storage": { "type": "disk", "device": "/dev/sda1" }, "fstype": "btrfs", "readonly": true }, "/var": { "storage": { "type": "disk", "label": "8f3ba6f4-5c7
JSON Hyper-Schema: A Vocabulary for Hypermedia Annotation of JSON draft-handrews-json-schema-hyperschema-02 Abstract JSON Schema is a JSON-based format for describing JSON data using various vocabularies. This document specifies a vocabulary for annotating JSON documents with hyperlinks. These hyperlinks include attributes describing how to manipulate and interact with remote resources through hyp
Understanding JSON Schema¶ JSON Schema is a powerful tool for validating the structure of JSON data. However, learning to use it by reading its specification is like learning to drive a car by looking at its blueprints. You don’t need to know how an electric motor fits together if all you want to do is pick up the groceries. This book, therefore, aims to be the friendly driving instructor for JSON
{ "title": "Person", "type": "object", "properties": { "firstName": { "type": "string" }, "lastName": { "type": "string" }, "age": { "description": "Age in years", "type": "integer", "minimum": 0 } }, "required": ["firstName", "lastName"] } Example schemas These sample schemas describe simple data structures which can be expressed as JSON. The “canonical url” links omit the “.json” extension, whic
Let’s pretend we’re interacting with a JSON based product catalog. This catalog has a product which has an id, a name, a price, and an optional set of tags. Example JSON data for a product API An example product in this API is: { "id": 1, "name": "A green door", "price": 12.50, "tags": ["home", "green"] } While generally straightforward, that example leaves some open questions. For example, one ma
NOTE: This page lists implementations with (or actively working towards) support for draft-06 or later. For implementations supporting only draft-04 or older, or that are no longer in development, see the Obsolete Implementations page. Implementations below are written in different languages, and support part, or all, of at least one recent version of the specification. Implementations are classif
Why JSON Schema?While JSON is probably the most popular format for exchanging data, JSON Schema is the vocabulary that enables JSON data consistency, validity, and interoperability at scale. Streamline testing and validationSimplify your validation logic to reduce your code’s complexity and save time on development. Define constraints for your data structures to catch and prevent errors, inconsist
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