Silencing Errors in Production With a Sentry Context Manager

I found a really neat usage for Python context managers in the codebase of my new job over at Custobar. We’re running sometimes large and long-running ElasticSearch indexing tasks with Celery, and exceptions inside these tasks would sometimes clog up our Sentry. Someone smarter than me wrote a context manager that would queue any exceptions and do some magic before handing them to Sentry. I liked the idea and tried writing a super simple context manager just for making Celery tasks in my own projects simpler.

SentryContextManager

I came up with the following:

# core.utils.sentry.py

from sentry_sdk import capture_exception

class SentryContextManager:
"""Context manager to capture exceptions and send them to Sentry."""

    def __enter__(self):
        pass

    def __exit__(self, exc_type, exc_value, traceback):
        if exc_type is not None:
            capture_exception(exc_value)
            print("Exception captured by Sentry: ")
            print(exc_type, exc_value, traceback)
            return True

and then:

# core.utils.__init__.py

from core.utils.sentry import SentryContextManager
send_exceptions_to_sentry = SentryContextManager()

and finally I could replace this:

# core.tasks.py
from celery import shared_task
from sentry_sdk import capture_exception

@shared_task
def my_task():
    try:
        division_by_zero = 1 / 0
    except Exception as e:
        capture_exception(e)
    print("This always prints!")

with this:

# core.tasks.py
from celery import shared_task
from core.utils import send_exceptions_to_sentry

@shared_task
def my_task():
    with send_exceptions_to_sentry:
        division_by_zero = 1 / 0
    print("This always prints!")

I like the simplicity and readability of the context manager approach a lot. This is obviously not useful everywhere but for simple cases like this it works great!