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INTRODUCING LOGFIRE

From the team behind Pydantic, Logfire is a new type of observability platform
that empowers developers to understand their applications like never before.

Learn more
Learn more
> pip install logfire




RESPECTED BUILDERS OF OPEN SOURCE, FOR PYTHON & BEYOND

Pydantic is built on the pillars of open source: transparency, collaboration and
excellence. Our origins inform every product we craft. Whether it’s a community
project or enterprise solution, developer experience is our cornerstone.

Explore open source packages

from datetime import datetime
from typing import Tuple

from pydantic import BaseModel

class Delivery(BaseModel):
    timestamp: datetime
    dimensions: Tuple[int, int]

m = Delivery(timestamp='2020-01-02T03:04:05Z', dimensions=['10', '20'])
print(repr(m.timestamp))
#> datetime.datetime(2020, 1, 2, 3, 4, 5, tzinfo=TzInfo(UTC))
print(m.dimensions)
#> (10, 20)

from fastapi import HTTPException
from fastui import FastUI, AnyComponent, components as c
from fastui.components.display import DisplayMode, DisplayLookup
from fastui.events import GoToEvent, BackEvent

from my_app import router, fetch_users

@router.get("/users", response_model=FastUI, response_model_exclude_none=True)
async def users_table() -> list[AnyComponent]:
    """Show a table of users"""
    users = await fetch_users()
    return [
        c.Page(  # Page provides a basic container for components
        # Add your components here
        )
    ]


import asyncio

from arq import create_pool
from arq.connections import RedisSettings
from httpx import AsyncClient

async def main():
    redis = await create_pool(RedisSettings())
    for url in ('https://facebook.com', 'https://microsoft.com', 'https://github.com'):
        await redis.enqueue_job('download_content', url)

async def download_content(ctx, url):
    async with AsyncClient() as client:
        response = await client.get(url)
        return response.text


use speedate::{DateTime, Date, Time};

fn main() {
    let dt = DateTime::parse_str("2022-01-01T12:13:14Z").unwrap();
    assert_eq!(
        dt,
        DateTime {
            date: Date {
                year: 2022,
                month: 1,
                day: 1,
            },
            time: Time {
                hour: 12,
                minute: 13,
                second: 14,
                nanosecond: 0,
            },
        },
    );
}

use jiter::JsonValue;

fn main() {
    let json_data = r#"
        {
            \"name\": \"John Doe\",
            \"age\": 43,
            \"phones\": [
                \"+44 1234567\",
                \"+44 2345678\"
            ]
        }"#;
    let json_value = JsonValue::parse(json_data.as_bytes(), true).unwrap();
}


PYDANTIC

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PYDANTIC

The most popular data validation library for Python

view in github


FASTUI

A new way to build web application UIs

see more


ARQ

Fast job queuing and RPC in Python

see more


SPEEDATE

Date, time and duration parsing for Rust

see more


JITER

The fast, iterable JSON parser

see more


The Pydantic Library is used and trusted by some of the biggest organizations in
the world — and millions of individual developers, too.



We use Pydantic across key parts of our research and products, and it has
accelerated our work considerably.

Atty Eleti Member of Technical Staff at OpenAI

Pydantic is incredibly powerful and a must use tool for AI engineers.

Logan Kilpatrick Lead product for Google AI Studio

We use Pydantic across key parts of our research and products, and it has
accelerated our work considerably.

Atty Eleti Member of Technical Staff at OpenAI

Integrations that run on the Datadog Agent use Pydantic models that are
generated from an OpenAPI spec to validate configuration which has drastically
reduced customer confusion and support cases that we have to triage.

Ofek Lev Senior Software Engineer at Datadog

If you're not using Python yet, you should. If you're not using Pydantic yet
with Python, you should. Pydantic is the data backbone of FastAPI, but even if
you don't use FastAPI, Pydantic is extremely useful. There's always data, and
handling data with Pydantic is several times more efficient and safer than
without it and much more enjoyable.

Sebastián Ramírez creator of FastAPI
OUR MISSION


DRIVEN BY CURIOSITY, FRUSTRATION AND COFFEE




Learn more about the creators of Pydantic, our mission and open source ethos.
And see how you can get involved.

about us


OUR ARTICLES


/Release


PYDANTIC V2.10

Sydney Runkle
2024/11/13
/Observability


WHY HYPERLINT CHOSE PYDANTIC LOGFIRE AS OUR OBSERVABILITY PROVIDER

Bill Chambers
2024/10/10
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