📋 Data Generator API
Generate realistic mock data programmatically via REST API
Endpoint
POSThttps://pk-toolbox.vercel.app/api/data-generateRequest Schema
Required Fields
{
"id": number, // Unique identifier
"name": string, // Field name in output
"type": "string" | "number" | "boolean"
}Optional String Properties
{
"stringType"?: "text" | "sentence" | "firstName" | "email" | ...,
"minWords"?: number,
"maxWords"?: number,
"startsWith"?: string,
"endsWith"?: string,
"emailDomain"?: string,
"passwordAlphabets"?: number,
"passwordNumbers"?: number,
"passwordSymbols"?: number
}Optional Number Properties
{
"min"?: number,
"max"?: number,
"decimals"?: number
}Example Request

{
"fields": [
{
"id": 1,
"name": "name",
"type": "string",
"stringType": "fullName"
},
{
"id": 2,
"name": "email",
"type": "string",
"stringType": "email",
"emailDomain": "@example.com"
},
{
"id": 3,
"name": "age",
"type": "number",
"min": 18,
"max": 65,
"decimals": 0
}
],
"count": 100,
"format": "json"
}Example Response

[
{
"name": "John Smith",
"email": "john.smith@example.com",
"age": 45
},
{
"name": "Mary Johnson",
"email": "mary.johnson@example.com",
"age": 32
}
]Code Examples
cURL
curl -X POST https://pk-toolbox.vercel.app/api/data-generate \
-H "Content-Type: application/json" \
-d '{
"fields": [
{"id": 1, "name": "name", "type": "string", "stringType": "fullName"}
],
"count": 10,
"format": "json"
}'JavaScript
const response = await fetch('https://pk-toolbox.vercel.app/api/data-generate', {
method: 'POST',
headers: { 'Content-Type': 'application/json' },
body: JSON.stringify({
fields: [
{ id: 1, name: 'name', type: 'string', stringType: 'fullName' }
],
count: 10,
format: 'json'
})
});
const data = await response.json();
console.log(data);Python
import requests
response = requests.post(
'https://pk-toolbox.vercel.app/api/data-generate',
json={
'fields': [
{'id': 1, 'name': 'name', 'type': 'string', 'stringType': 'fullName'}
],
'count': 10,
'format': 'json'
}
)
data = response.json()
print(data)