pydantic/logfire

Celery needs to be instrumented on client side for distributed tracing

Open

#972 aperta il 31 mar 2025

Vedi su GitHub
 (3 commenti) (0 reazioni) (0 assegnatari)Python (244 fork)github user discovery
documentationgood first issue

Metriche repository

Star
 (4282 star)
Metriche merge PR
 (Merge medio 7g 8h) (35 PR mergiate in 30 g)

Descrizione

Demo:

import logfire
from celery import Celery
from celery.signals import worker_init
from fastapi import FastAPI

@worker_init.connect()
def init_worker(*args, **kwargs):
    logfire.configure(service_name="worker")
    logfire.instrument_celery()

app = Celery("tasks", broker="redis://localhost:6379/0")

@app.task
def add(x: int, y: int):
    return x + y

fapp = FastAPI()

logfire.configure()
logfire.instrument_fastapi(fapp)
########### Important:
logfire.instrument_celery()


@fapp.get("/hello")
async def hello(name: str):
    add.delay(42, 50)
    return {"message": f"hello {name}"}


if __name__ == "__main__":
    import uvicorn

    uvicorn.run(fapp)

The top-level logfire.instrument_celery() is required for the context propagation, based on https://github.com/open-telemetry/opentelemetry-python-contrib/issues/1002#issuecomment-1275273134

This should be documented at least, maybe fixed in some other way, e.g. in OTel.

Guida contributor