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Convert pydantic models to typescript interfaces

Project description

pydantic-to-typescript

PyPI version

A simple CLI tool for converting pydantic models into typescript interfaces. Useful for any scenario in which python and javascript applications are interacting, since it allows you to have a single source of truth for type definitions.

This tool requires that you have the lovely json2ts CLI utility installed. Instructions can be found here: https://www.npmjs.com/package/json-schema-to-typescript

Installation

$ pip install pydantic-to-typescript

CLI

Prop Description
‑‑module name or filepath of the python module you would like to convert. All the pydantic models within it will be converted to typescript interfaces. Discoverable submodules will also be checked.
‑‑output name of the file the typescript definitions should be written to. Ex: './frontend/apiTypes.ts'
‑‑exclude name of a pydantic model which should be omitted from the resulting typescript definitions. This option can be defined multiple times, ex: --exclude Foo --exclude Bar to exclude both the Foo and Bar models from the output.
‑‑json2ts‑cmd optional, the command used to invoke json2ts. The default is 'json2ts'. Specify this if you have it installed in a strange location and need to provide the exact path (ex: /myproject/node_modules/bin/json2ts)

Usage

Define your pydantic models (ex: /backend/api.py):

from fastapi import FastAPI
from pydantic import BaseModel
from typing import List, Optional

api = FastAPI()

class LoginCredentials(BaseModel):
    username: str
    password: str

class Profile(BaseModel):
    username: str
    age: Optional[int]
    hobbies: List[str]

class LoginResponseData(BaseModel):
    token: str
    profile: Profile

@api.post('/login/', response_model=LoginResponseData)
def login(body: LoginCredentials):
    profile = Profile(**body.dict(), age=72, hobbies=['cats'])
    return LoginResponseData(token='very-secure', profile=profile)

Execute the command for converting these models into typescript definitions, via:

$ pydantic2ts --module backend.api --output ./frontend/apiTypes.ts

or:

$ pydantic2ts --module ./backend/api.py --output ./frontend/apiTypes.ts

or:

from pydantic2ts import generate_typescript_defs

generate_typescript_defs("backend.api", "./frontend/apiTypes.ts")

The models are now defined in typescript...

/* tslint:disable */
/**
/* This file was automatically generated from pydantic models by running pydantic2ts.
/* Do not modify it by hand - just update the pydantic models and then re-run the script
*/

export interface LoginCredentials {
  username: string;
  password: string;
}
export interface LoginResponseData {
  token: string;
  profile: Profile;
}
export interface Profile {
  username: string;
  age?: number;
  hobbies: string[];
}

...and can be used in your typescript code with complete confidence.

import { LoginCredentials, LoginResponseData } from './apiTypes.ts';

async function login(
  credentials: LoginCredentials,
  resolve: (data: LoginResponseData) => void,
  reject: (error: string) => void,
) {
  try {
    const response: Response = await fetch('/login/', {
      method: 'POST',
      headers: {'Content-Type': 'application/json'},
      body: JSON.stringify(credentials),
    });
    const data: LoginResponseData = await response.json();
    resolve(data);
  } catch (error) {
    reject(error.message);
  }
}

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