Python
Set Up Profiling
With profiling, Sentry allows you to collect and analyze performance profiles from real user devices in production to give you a complete picture of how your application performs in a variety of environments.
Enable Performance Monitoring
Profiling depends on Sentry’s performance monitoring product being enabled beforehand. To enable performance monitoring in the SDK:
sentry_sdk.init(
dsn="https://examplePublicKey@o0.ingest.sentry.io/0",
traces_sample_rate=1.0,
)Check out the performance setup documentation for more detailed information on how to configure sampling. Setting the sample rate to 1.0 means all transactions will be captured.
Enable Profiling
Python profiling is available starting in SDK version 1.18.0.
import sentry_sdk
def profiles_sampler(sampling_context):
# ...
# return a number between 0 and 1 or a boolean
sentry_sdk.init(
dsn="https://examplePublicKey@o0.ingest.sentry.io/0",
traces_sample_rate=1.0,
# To set a uniform sample rate
# Set profiles_sample_rate to 1.0 to profile 100%
# of sampled transactions.
# We recommend adjusting this value in production,
profiles_sample_rate=1.0,
# Alternatively, to control sampling dynamically
profiles_sampler=profiles_sampler
)The profiles_sample_rate setting is relative to the traces_sample_rate setting.
Upgrading from older SDK versions
The feature was experimental prior to version 1.17.0. To update to the latest SDK, remove profiles_sample_rate from _experiments and set it in the top-level options.
sentry_sdk.init(
dsn="https://examplePublicKey@o0.ingest.sentry.io/0",
traces_sample_rate=1.0,
_experiments={
"profiles_sample_rate": 1.0, # for versions before 1.17.0
},
)Our documentation is open source and available on GitHub. Your contributions are welcome, whether fixing a typo (drat!) to suggesting an update ("yeah, this would be better").
- Package:
- pypi:sentry-sdk
- Version:
- 1.31.0
- Repository:
- https://github.com/getsentry/sentry-python