Introduction

CUE is a concise and powerful language for describing and constraining data, but not all systems speak CUE. Some systems can only produce schemas formatted in JSON Schema. This isn’t a problem for the cue command because it speaks JSON Schema - letting you use JSON Schema alongside schemas written in CUE.

In this tutorial you’ll use cue to convert a JSON Schema to CUE, and then use the result to validate some data.

Prerequisites

  • The cue binary – follow the installation instructions if you don’t already use cue
  • A tool to edit text files – any text editor you have will be fine, such as VSCode, Notepad, or Vim
  • A command terminalcue works on all platforms, so you can use any Linux or macOS terminal, or a Windows terminal such as PowerShell, cmd, or WSL to run commands.
  • Some awareness of CUE schemata – the language tour’s pages on Constraints and Definitions are a good refresher

This tutorial is written using the following version of cue:

TERMINAL
$ cue version
cue version v0.11.1
...

Steps

This tutorial takes you through converting some JSON Schema to a CUE definition using the cue import command, and then using the result to validate some YAML.

1

Create a JSON schema file:

schema.json
{
    "$schema": "https://json-schema.org/draft/2020-12/schema",
    "type": "object",
    "additionalProperties": false,
    "required": [
        "name",
        "cuisine",
        "tables"
    ],
    "properties": {
        "name": {
            "type": "string"
        },
        "cuisine": {
            "type": "string"
        },
        "tables": {
            "type": "array",
            "items": {
                "$ref": "#/$defs/table"
            }
        }
    },
    "$defs": {
        "table": {
            "type": "object",
            "additionalProperties": false,
            "required": [
                "seats"
            ],
            "properties": {
                "seats": {
                    "type": "number",
                    "minimum": 2,
                    "maximum": 10
                },
                "view": {
                    "type": "boolean"
                }
            }
        }
    }
}

This schema validates data that defines a restaurant.

2

Convert the JSON Schema to a CUE definition called #restaurant:

TERMINAL
$ cue import -l '#restaurant:' -p cuisine schema.json

It’s good practise to tell cue to place imported CUE inside a package. Here, we choose the cuisine package.

cue import creates the file schema.cue containing this CUE:

schema.cue
package cuisine

#restaurant: {
	@jsonschema(schema="https://json-schema.org/draft/2020-12/schema")
	close({
		name!:    string
		cuisine!: string
		tables!: [...#table]
	})

	#table: close({
		seats!: >=2 & <=10
		view?:  bool
	})
}

CUE natively understands JSON Schema, and is able to convert all of the JSON Schema constraints into CUE constraints. Notice the CUE schema is also considerably more concise and readable.

3

Create some data files that contain restaurant details:

split_pea.yml
name: The Split Pea
cuisine: Contemporary
tables:
  - seats: 4
    view: true
  - seats: 6
pomodoro.yml
name: Il Pomodoro Marcio
cuisine: Italian
tables:
  - seats: 100
  - seats: 8
    view: true

One of these files contains a deliberate problem that cue will catch for us, shortly. If you spotted the problem while entering the data, make sure you didn’t correct it!

4

Validate the data using the schema and constraints:

TERMINAL
$ cue vet -d '#restaurant' schema.cue *.yml
tables.0.seats: invalid value 100 (out of bound <=10):
    ./schema.cue:12:17
    ./pomodoro.yml:4:12

cue vet outputs nothing when validation succeeds. But as you can see, there are some validation errors.

5

Fix the data validation error by updating your pomodoro.yml file:

pomodoro.yml
name: Il Pomodoro Marcio
cuisine: Italian
tables:
  - seats: 10
  - seats: 8
    view: true
6

Re-validate the data using the schema and constraints:

TERMINAL
$ cue vet -d '#restaurant' schema.cue *.yml

The “silent” lack of output from cue vet confirms that the fixed data validates successfully.

Conclusion

You’ve completed this tutorial - well done!

In this tutorial you converted JSON Schema to CUE using cue import, and then used the resulting CUE to catch and fix an error in some data.