JSON Schema

JSON Schema allows us to validate our JSON documents (including through automated tests). We can create a json file for each domain object (ie. what we would find in each table of an SQL db), and we specify things like...

  • what properties this object has
  • what types they are
  • which ones are required
  • what restraints they have (e.g. max length, regex match etc.)

The first key-value pair of the schema should be declaring which dialect of JSON Schema that our schema uses:

  • this is called a meta schema, since it is a schema that describes another schema.
    "$schema": "https://json-schema.org/draft/2020-12/schema"

Code reuse

Like any other code, schemas are easier to maintain if they can be broken down into logical units that reference each other as necessary.

  • In order to reference a schema, we need a way to identify a schema. Schema documents are identified by non-relative URIs.

Schemas need an identifier (ie. $id) if we want to reference them from other schemas.

  • schemas without an identifier are known as anonymous schemas.


JSON Pointer:

A JSON Pointer describes a slash-separated path to traverse the keys in the objects in the document. Therefore, /properties/street_address means:

  1. find the value of the key properties
  2. within that object, find the value of the key street_address

The URI https://example.com/schemas/address#/properties/street_address identifies the highlighted subschema in the following schema.

  "$id": "https://example.com/schemas/address",
  "type": "object",
  "properties": {
      { "type": "string" }


The value of $ref is a URI-reference that is resolved against the schema’s Base URI (ie. the value of $id).



We can use this library to generate types from the json schema.


We can use ajv to take in our json schema, and generate validation functions to make sure the data coming in adheres to the schema.