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Pydantic Logfire — Uncomplicated Observability

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From the team behind Pydantic, Logfire is an observability platform built on the same belief as our open source library — that the most powerful tools can be easy to use.

What sets Logfire apart:

See the documentation for more information.

Feel free to report issues and ask any questions about Logfire in this repository!

This repo contains the Python SDK for logfire and documentation; the server application for recording and displaying data is closed source.

Using Logfire

This is a very brief overview of how to use Logfire, the documentation has much more detail.

Install

pip install logfire

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Authenticate

logfire auth

(learn more)

Manual tracing

Here's a simple manual tracing (aka logging) example:

import logfire from datetime import date

logfire.configure() logfire.info('Hello, {name}!', name='world')

with logfire.span('Asking the user their {question}', question='age'): user_input = input('How old are you [YYYY-mm-dd]? ') dob = date.fromisoformat(user_input) logfire.debug('{dob=} {age=!r}', dob=dob, age=date.today() - dob)

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Integration

Or you can also avoid manual instrumentation and instead integrate with lots of popular packages, here's an example of integrating with FastAPI:

import logfire from pydantic import BaseModel from fastapi import FastAPI

app = FastAPI()

logfire.configure() logfire.instrument_fastapi(app)

next, instrument your database connector, http library etc. and add the logging handler

class User(BaseModel): name: str country_code: str

@app.post('/') async def add_user(user: User): # we would store the user here return {'message': f'{user.name} added'}

(learn more)

Logfire gives you a view into how your code is running like this:

Logfire screenshot

Contributing

We'd love anyone interested to contribute to the Logfire SDK and documentation, see the contributing guide.

Reporting a Security Vulnerability

See our security policy.

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