JSON to Pydantic Model Generator

Ek JSON sample se Pydantic v2 model classes instantly apne browser mein generate karein. Aapka JSON aapke device par rehta hai.

Aapka JSON poori tarah aapke browser mein parse aur Pydantic models mein convert hota hai, isliye woh aapke device par rehta hai aur kuch bhi server par upload nahi hota.

Go, Rust ya TypeScript types chahiye? JSON to Code try karein.

JSON to Pydantic ke baare mein

Yeh json to pydantic generator ek sample JSON object ya array ko seconds mein ready-to-use Pydantic v2 model classes mein badal deta hai. Ek real API response paste karein aur yeh har field ka type infer karta hai, str, int, float aur bool, nullable fields ko Optional mark karta hai, arrays ko list[...] types mein unify karta hai, aur har nested object ko apne khud ke BaseModel mein promote karta hai jise naam se reference kiya jaata hai. Jo keys valid Python identifiers nahi hain unhe Field(alias=...) ke zariye rakha jaata hai taaki model abhi bhi aapke original payload ko parse kare. Yeh un Python aur FastAPI developers ke liye banaya gaya hai jo typed client wire karte waqt pydantic models ko hand-write karne ki jagah json se generate karna pasand karte hain. Sab kuch locally aapke browser mein chalta hai, isliye aap jo JSON paste karte hain woh aapke device par process hota hai aur kuch bhi server par upload nahi hota.

Features

JSON to Pydantic kaise use karein

  1. Apna JSON object ya array input box mein paste karein.
  2. Root model name ko apne schema se match karne ke liye set karein, ya use Model rehne dein.
  3. Output panel mein generate hui Pydantic classes review karein.
  4. Result copy karein ya use .py file ke roop mein download karein.

Example

Input

{ "id": 1, "name": "Ada", "address": { "city": "London" } }

Output

from pydantic import BaseModel


class Address(BaseModel):
    city: str


class Model(BaseModel):
    id: int
    name: str
    address: Address

Ek nested object apna khud ka BaseModel ban jaata hai, root class sabse last mein.

Common errors aur troubleshooting

Aksar pooche jaane wale sawaal

Kya yeh Pydantic v2 models generate karta hai?
Haan. Output Pydantic v2 syntax ko target karta hai: har model ek class hai jo BaseModel ko subclass karti hai, annotated fields ke saath aur Field(alias=...) wahan jahan koi JSON key valid Python identifier nahi hai.
Nested objects kaise handle hote hain?
Har nested object apna khud ka BaseModel class ban jaata hai, jiska naam owning key se PascalCase mein banta hai, aur parent use type se reference karta hai. Classes dependency order mein emit hoti hain, root model sabse last mein.
Yeh JSON types ko Python types mein kaise map karta hai?
Strings str ban jaati hain, whole numbers int, decimals float, booleans bool, null Optional banata hai, arrays ek unified element type ke saath list[...] ban jaate hain, aur objects nested BaseModels ban jaate hain.
Jo keys valid Python names nahi hain unke saath kya hota hai?
first-name ya 2fa jaisi key, ya class jaisa reserved word, ek safe snake_case attribute ke under expose hoti hai aur original key Field(alias="...") ke saath preserve hoti hai taaki model abhi bhi aapke payload ko parse kare.
Arrays aur empty arrays kaise convert hote hain?
Arrays apne elements ke unified type ka istemaal karke list[...] ban jaate hain, jisme objects ke arrays ke liye ek nested BaseModel bhi shaamil hai. Ek empty array ke paas infer karne ke liye koi element type nahi hota, isliye woh list[Any] ban jaata hai.
Pydantic models generate karte waqt mera JSON kahin bheja jaata hai kya?
Nahi. JSON to Pydantic conversion poori tarah aapke browser mein chalti hai, isliye aap jo data paste karte hain woh locally process hota hai aur kabhi aapke device se bahar nahi jaata.

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