Mock Schema Inferrer
Reverse-engineer a mock data schema from a sample JSON object.
POST
1 credit
/v1/mock-schema
curl -X POST "https://devtools.toolkitapi.io/v1/mock-schema" \
-H "Content-Type: application/json" \
-d '{
"sample": {
"id": 42,
"name": "Alice Johnson",
"email": "[email protected]",
"created_at": "2025-01-15T10:30:00",
"active": true,
"price": 29.99
}
}'
import httpx
resp = httpx.post(
"https://devtools.toolkitapi.io/v1/mock-schema",
json={
"sample": {
"id": 42,
"name": "Alice Johnson",
"email": "[email protected]",
"created_at": "2025-01-15T10:30:00",
"active": true,
"price": 29.99
}
},
)
print(resp.json())const resp = await fetch("https://devtools.toolkitapi.io/v1/mock-schema", {
method: "POST",
headers: {
"Content-Type": "application/json",
},
body: JSON.stringify({
"sample": {
"id": 42,
"name": "Alice Johnson",
"email": "[email protected]",
"created_at": "2025-01-15T10:30:00",
"active": true,
"price": 29.99
}
}),
});
const data = await resp.json();
console.log(data);# See curl example
Response
200 OK
{
"fields": [
{"name": "id", "type": "sequence", "options": {"start": 1}},
{"name": "name", "type": "name"},
{"name": "email", "type": "email"},
{"name": "created_at", "type": "datetime"},
{"name": "active", "type": "boolean"},
{"name": "price", "type": "price", "options": {"min": 1.0, "max": 999.99}}
],
"field_count": 6
}Try It Live
Live Demo
Response
Description
Reverse-engineer a mock data schema from a sample JSON object.
How to Use
1
1. Pass a sample JSON object (or array of objects) in the `sample` field. 2. The response contains a `fields` array ready to use with the Mock Data Generator. 3. Review and tweak the inferred types if needed, then pass to `/v1/mock-data`.
About This Tool
Mock Schema Inferrer analyzes a sample JSON object and generates a mock data field schema compatible with the Mock Data Generator. It uses key names and value patterns to intelligently guess field types — emails, dates, UUIDs, names, prices, and more.
Feed the output directly into `/v1/mock-data` to generate realistic datasets that match your data shape.
Why Use This Tool
- Quick schema bootstrap — Paste a real API response and get a mock schema instantly
- Test data generation — Generate hundreds of rows matching your existing data shape
- API prototyping — Create realistic mock endpoints from example payloads
- Database seeding — Infer schema from existing rows, then bulk-generate test data
Frequently Asked Questions
How does it infer types?
First by key name heuristics (e.g. `email` → email type, `created_at` → datetime), then by value patterns (regex matching for emails, UUIDs, dates, URLs). Key name matching takes priority.
Can I pass an array of objects?
Yes — if you pass an array, the first element is used as the sample for inference.
Start using Mock Schema Inferrer now
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