pydantic-to-typescript

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-typescript2

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 locally (ex: 'yarn json2ts') or if the exact path to the executable is required (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);
  }
}

Testing

# Install nvm
curl -o- https://raw.githubusercontent.com/nvm-sh/nvm/v0.39.3/install.sh | bash

# Load nvm into the current shell session
export NVM_DIR="$([ -z "${XDG_CONFIG_HOME-}" ] && printf %s "${HOME}/.nvm" || printf %s "${XDG_CONFIG_HOME}/nvm")"
[ -s "$NVM_DIR/nvm.sh" ] && \. "$NVM_DIR/nvm.sh"  # This loads nvm

# Install Node.js version 18
nvm install 18

# Use Node.js version 18
nvm use 18

# Verify Node.js installation
node -v
npm -v

# Install Python dependencies
pip install -U pip wheel pytest pytest-cov coverage
pip install -U .

# Install json-schema-to-typescript
npm install -g json-schema-to-typescript

Darius-Labs/pydantic-to-typescript2

pydantic-to-typescript

Installation

CLI

Usage

Testing