JSON to Pydantic Converter

Each JSON value is read, merged with every other sample of the same key, and then mapped to the closest Pydantic type:

A user record with a nested team, a list of invoices (one missing a note, one with a null payment date) and an awkward display-name key:

{
  "id": 1042,
  "email": "ada@example.com",
  "display-name": "Ada",
  "createdAt": "2026-11-07T09:30:00Z",
  "plan": null,
  "tags": ["beta", "founder"],
  "team": {
    "id": "7f3c9a2e-1b4d-4c8e-9f2a-6d5e4c3b2a19",
    "name": "Analytical Engines",
    "website": "https://example.com"
  },
  "invoices": [
    { "number": "INV-001", "amount": 49.5, "paid": true, "paidAt": "2026-10-01T00:00:00Z" },
    { "number": "INV-002", "amount": 49, "paid": false, "paidAt": null, "note": "Card declined" }
  ]
}

Becomes this Pydantic, generated by the same engine that runs the converter above (3 types, 16 fields):

from __future__ import annotations

from datetime import datetime
from typing import Any, Optional
from uuid import UUID

from pydantic import BaseModel, ConfigDict, Field


class Team(BaseModel):
    id: UUID
    name: str
    website: str


class Invoice(BaseModel):
    model_config = ConfigDict(populate_by_name=True)

    number: str
    amount: float
    paid: bool
    paid_at: Optional[datetime] = Field(alias="paidAt")
    note: Optional[str] = None


class Root(BaseModel):
    model_config = ConfigDict(populate_by_name=True)

    id: int
    email: str
    display_name: str = Field(alias="display-name")
    created_at: datetime = Field(alias="createdAt")
    plan: Any
    tags: list[str]
    team: Team
    invoices: list[Invoice]

• JSON to TypeScript →
• JSON to Zod →
• JSON to Go struct →
• JSON to Rust (serde) →
• JSON to JSON Schema →
• JSON to Prisma →
• JSON to GraphQL →

Or go back to the JSON to Types hub.