Lesson 10 — Best Practices

Validation and JSON Schema Basics

As JSON documents become more complex, JSON Schema provides a way to formally describe and validate their expected shape, catching structural mistakes before they cause problems downstream.

Why Validate JSON?

Just because a document is syntactically valid JSON doesn't mean it has the fields and types your application expects. Validation checks the actual structure and content — required fields, correct types, allowed value ranges — against a defined schema.

A Simple JSON Schema

JSON Schema is itself written in JSON, describing the expected shape of another JSON document.

JSON Schema — Describing a product 
{
  "type": "object",
  "properties": {
    "name": { "type": "string" },
    "price": { "type": "number", "minimum": 0 },
    "inStock": { "type": "boolean" }
  },
  "required": ["name", "price"]
}

Common Mistakes

  • Assuming syntactically valid JSON is automatically the correct shape your application expects — parsing success and structural correctness are two different concerns.
  • Not marking essential fields as required in a schema, allowing incomplete data through unnoticed.
  • Skipping validation entirely for data coming from external or third-party APIs, which can change unexpectedly.
  • Writing overly rigid schemas that reject valid but slightly different data structures, such as additional optional fields.

Professional Tip

Validate JSON at the boundary of your system — right where external data enters, like an API response or a file upload — rather than scattering ad-hoc checks throughout your codebase. This keeps validation logic centralised and consistent.

Your Turn

Write a JSON Schema describing a valid 'user' object requiring a string username and a numeric age with a minimum of 0, then list two example JSON objects — one that would pass and one that would fail.

Mini Quiz

What is the main purpose of JSON Schema?