Advanced Guide

JSON Schema Validation: Complete Developer Guide

Learn how to use JSON Schema for data validation. Includes practical examples, best practices, and implementation tips for building robust APIs and applications.

Validate JSON Format JSON

What is JSON Schema?

JSON Schema is a vocabulary that allows you to annotate and validate JSON documents. It provides a contract for your JSON data, ensuring it meets specific requirements.

Key Benefits:

✅ Validates data structure and types
✅ Documents your data format
✅ Generates documentation automatically
✅ Enables code generation
✅ Improves API reliability

Basic Schema Example

JSON Data:

{
  "name": "John Doe",
  "age": 30,
  "email": "john@example.com"
}

JSON Schema:

{
  "$schema": "http://json-schema.org/draft-07/schema#",
  "type": "object",
  "required": ["name", "age", "email"],
  "properties": {
    "name": {
      "type": "string",
      "minLength": 1
    },
    "age": {
      "type": "integer",
      "minimum": 0,
      "maximum": 150
    },
    "email": {
      "type": "string",
      "format": "email"
    }
  }
}

Common Schema Keywords

Type Keywords

type - Data type
enum - Allowed values
const - Constant value

String Keywords

minLength - Min length
maxLength - Max length
pattern - Regex pattern
format - Format (email, uri)

Number Keywords

minimum - Min value
maximum - Max value
multipleOf - Multiple of

Array Keywords

items - Item schema
minItems - Min items
maxItems - Max items
uniqueItems - Unique items

Advanced Schema Example

{
  "$schema": "http://json-schema.org/draft-07/schema#",
  "title": "User",
  "description": "A user in the system",
  "type": "object",
  "required": ["id", "username", "email"],
  "properties": {
    "id": {
      "type": "integer",
      "description": "Unique user identifier"
    },
    "username": {
      "type": "string",
      "minLength": 3,
      "maxLength": 20,
      "pattern": "^[a-zA-Z0-9_]+$"
    },
    "email": {
      "type": "string",
      "format": "email"
    },
    "roles": {
      "type": "array",
      "items": {
        "type": "string",
        "enum": ["admin", "user", "moderator"]
      },
      "minItems": 1,
      "uniqueItems": true
    },
    "profile": {
      "type": "object",
      "properties": {
        "firstName": { "type": "string" },
        "lastName": { "type": "string" },
        "age": {
          "type": "integer",
          "minimum": 13,
          "maximum": 120
        }
      }
    }
  }
}

Implementation Examples

JavaScript (Ajv)

const Ajv = require('ajv');
const ajv = new Ajv();

const schema = {
  type: 'object',
  required: ['name', 'email'],
  properties: {
    name: { type: 'string' },
    email: { type: 'string', format: 'email' }
  }
};

const validate = ajv.compile(schema);
const valid = validate(data);

if (!valid) {
  console.log(validate.errors);
}

Python (jsonschema)

from jsonschema import validate, ValidationError

schema = {
    "type": "object",
    "required": ["name", "email"],
    "properties": {
        "name": {"type": "string"},
        "email": {"type": "string", "format": "email"}
    }
}

try:
    validate(instance=data, schema=schema)
    print("Valid!")
except ValidationError as e:
    print(f"Invalid: {e.message}")

Best Practices

Use Descriptive Titles and Descriptions

Help developers understand your schema with clear documentation

Define Required Fields

Always specify which fields are required vs optional

Use Appropriate Constraints

Add min/max, patterns, and formats to validate data properly

Version Your Schemas

Track schema changes and maintain backward compatibility

Validate Your JSON Data

Use our free JSON validator to test your data against schemas and ensure data integrity.

Validate JSON Format JSON

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