zod

Wed, 21 May 2025 15:29:33 +0800

colinhacks/zod

Zod

✨ https://zod.dev ✨
TypeScript-first schema validation with static type inference

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Read the docs →

What is Zod?

Zod is a TypeScript-first validation library. Define a schema and parse some data with it. You’ll get back a strongly typed, validated result.

import { z } from "zod/v4";

const User = z.object({
  name: z.string(),
});

// some untrusted data...
const input = { /* stuff */ };

// the parsed result is validated and type safe!
const data = User.parse(input);

// so you can use it with confidence :)
console.log(data.name);

Features

Zero external dependencies
Works in Node.js and all modern browsers
Tiny: 2kb core bundle (gzipped)
Immutable API: methods return a new instance
Concise interface
Works with TypeScript and plain JS
Built-in JSON Schema conversion
Extensive ecosystem

Installation

`1`	`npm install zod`

Basic usage

Before you can do anything else, you need to define a schema. For the purposes of this guide, we’ll use a simple object schema.

import { z } from "zod/v4"; 

const Player = z.object({ 
  username: z.string(),
  xp: z.number()
});

Parsing data

Given any Zod schema, use .parse to validate an input. If it’s valid, Zod returns a strongly-typed deep clone of the input.

1
2

Player.parse({ username: "billie", xp: 100 }); 
// => returns { username: "billie", xp: 100 }

Note — If your schema uses certain asynchronous APIs like async refinements or transforms, you’ll need to use the .parseAsync() method instead.

const schema = z.string().refine(async (val) => val.length <= 8);

await schema.parseAsync("hello");
// => "hello"

Handling errors

When validation fails, the .parse() method will throw a ZodError instance with granular information about the validation issues.

try {
  Player.parse({ username: 42, xp: "100" });
} catch(err){
  if(error instanceof z.ZodError){
    err.issues; 
    /* [
      {
        expected: 'string',
        code: 'invalid_type',
        path: [ 'username' ],
        message: 'Invalid input: expected string'
      },
      {
        expected: 'number',
        code: 'invalid_type',
        path: [ 'xp' ],
        message: 'Invalid input: expected number'
      }
    ] */
  }
}

To avoid a try/catch block, you can use the .safeParse() method to get back a plain result object containing either the successfully parsed data or a ZodError. The result type is a discriminated union, so you can handle both cases conveniently.

const result = Player.parse({ username: 42, xp: "100" });
if (!result.success) {
  result.error;   // ZodError instance
} else {
  result.data;    // { username: string; xp: number }
}

Note — If your schema uses certain asynchronous APIs like async refinements or transforms, you’ll need to use the .safeParseAsync() method instead.

const schema = z.string().refine(async (val) => val.length <= 8);

await schema.safeParseAsync("hello");
// => { success: true; data: "hello" }

Inferring types

Zod infers a static type from your schema definitions. You can extract this type with the z.infer<> utility and use it however you like.

const Player = z.object({ 
  username: z.string(),
  xp: z.number()
});

// extract the inferred type
type Player = z.infer<typeof Player>;

// use it in your code
const player: Player = { username: "billie", xp: 100 };

In some cases, the input & output types of a schema can diverge. For instance, the .transform() API can convert the input from one type to another. In these cases, you can extract the input and output types independently:

const mySchema = z.string().transform((val) => val.length);

type MySchemaIn = z.input<typeof mySchema>;
// => string

type MySchemaOut = z.output<typeof mySchema>; // equivalent to z.infer<typeof mySchema>
// number

pydantic

Sun, 04 May 2025 15:27:18 +0800

pydantic/pydantic

Pydantic

Data validation using Python type hints.

Fast and extensible, Pydantic plays nicely with your linters/IDE/brain. Define how data should be in pure, canonical Python 3.9+; validate it with Pydantic.

Pydantic Logfire :fire:

We’ve recently launched Pydantic Logfire to help you monitor your applications. Learn more

Pydantic V1.10 vs. V2

Pydantic V2 is a ground-up rewrite that offers many new features, performance improvements, and some breaking changes compared to Pydantic V1.

If you’re using Pydantic V1 you may want to look at the pydantic V1.10 Documentation or, 1.10.X-fixes git branch. Pydantic V2 also ships with the latest version of Pydantic V1 built in so that you can incrementally upgrade your code base and projects: from pydantic import v1 as pydantic_v1.

Help

See documentation for more details.

Installation

Install using pip install -U pydantic or conda install pydantic -c conda-forge. For more installation options to make Pydantic even faster, see the Install section in the documentation.

A Simple Example

from datetime import datetime
from typing import Optional
from pydantic import BaseModel

class User(BaseModel):
    id: int
    name: str = 'John Doe'
    signup_ts: Optional[datetime] = None
    friends: list[int] = []

external_data = {'id': '123', 'signup_ts': '2017-06-01 12:22', 'friends': [1, '2', b'3']}
user = User(**external_data)
print(user)
#> User id=123 name='John Doe' signup_ts=datetime.datetime(2017, 6, 1, 12, 22) friends=[1, 2, 3]
print(user.id)
#> 123

Contributing

For guidance on setting up a development environment and how to make a contribution to Pydantic, see Contributing to Pydantic.

Reporting a Security Vulnerability

See our security policy.

Data Validation on Producthunt daily

zod

colinhacks/zod

Zod

Featured sponsor: Jazz

Read the docs →

What is Zod?

Features

Installation

Basic usage

Parsing data

Handling errors

Inferring types

pydantic

pydantic/pydantic

Pydantic

Pydantic Logfire :fire:

Pydantic V1.10 vs. V2

Help

Installation

A Simple Example

Contributing

Reporting a Security Vulnerability