Converter — Convert JSON, YAML, XML, and JSON Schema Instantly

What this tool does

This converter bridges modern and legacy data formats so teams can move faster between APIs, DevOps configs, and partner integrations. Convert JSON ↔ YAML for Kubernetes and CI pipelines, JSON ↔ XML for B2B and enterprise systems, and generate JSON Schema from sample JSON—or produce example JSON from a schema for testing. All processing happens locally in your browser for speed and privacy.

How it works (high level)

• JSON ↔ YAML: Uses a YAML engine that preserves types and structures where possible, normalizing indentation and quoting.
• JSON ↔ XML: Converts objects and arrays to elements; attributes are preserved where present; output is indented for readability.
• JSON → JSON Schema: Infers types, required fields, and constraints from a representative sample JSON.
• JSON Schema → Example JSON: Expands a schema into a valid sample document; toggle Include optional fields to control output size.

Step-by-step

1. Select a mode (e.g., JSON → YAML).
2. Paste your data or drop a file. Use Beautify to normalize indentation.
3. Click Convert to generate output. Errors show line and column to fix quickly.
4. Use Tree view to explore nested structures visually.
5. Copy or download your result and continue your workflow.

Examples by mode

JSON → YAML

{
  "name": "Alice",
  "roles": ["dev","ops"],
  "active": true
}

name: Alice
roles:
  - dev
  - ops
active: true

JSON → XML

{
  "order": { "id": 1001, "total": 29.5 }
}

<root xmlns="https://www.json-util.com/ns">
  <order>
    <id>1001</id>
    <total>29.5</total>
  </order>
</root>

JSON → JSON Schema

{
  "name": "Alice",
  "age": 30,
  "tags": ["pro", "beta"]
}

{
  "$schema": "https://json-schema.org/draft/2020-12/schema",
  "type": "object",
  "properties": {
    "name": { "type": "string" },
    "age":  { "type": "number" },
    "tags": { "type": "array", "items": { "type": "string" } }
  },
  "required": ["name","age"]
}

Best practices & edge cases

• YAML indentation: Use spaces, not tabs. Quoting scalars (like on, off, yes, no) avoids implicit type coercion.
• XML structure: Ensure proper nesting and close all tags. Attributes vs. elements may vary when converting complex JSON—review the output schema before production use.
• Collections: Arrays in JSON become repeated elements in XML; verify downstream systems accept that shape.
• Schema inference limits: JSON → Schema is best-effort; provide representative samples and refine constraints manually as needed.
• Large files: Browsers handle typical configs fine. For huge payloads, convert sections or use a local CLI to avoid memory limits.

JSON Schema quick primer

JSON Schema defines structure, types, and rules for JSON documents. It’s ideal for validating API payloads and generating test data. This converter infers a draft-2020-12 schema from your sample or materializes a realistic example from a provided schema, helping teams bootstrap tests quickly.

Privacy & performance

All conversions are client-side. Nothing is uploaded or stored, which suits enterprise environments with strict data policies. Local processing also keeps the experience fast and responsive.