| title | Set Up Tracing |
|---|---|
| sidebar_title | Tracing |
| description | With Tracing, Sentry tracks your software performance, measuring metrics like throughput and latency, and displays the impact of errors across multiple systems. |
| sidebar_order | 6 |
| sidebar_section | features |
Install Sentry's agent skills to teach your AI coding assistant how to set up tracing in your Python application.
npx @sentry/dotagents add getsentry/sentry-for-ai --name sentry-python-sdknpx skills add getsentry/sentry-for-ai --skill sentry-python-sdkSee the full list of available skills and installation docs for more details.
- You have the Python SDK installed (version 0.11.2 or higher)
To enable tracing in your application, adjust the traces_sample_rate based on the number of trace samples you want to send to Sentry by adding the highlighted code snippet below. (Setting a value of 1.0 will send 100% of your traces.)
import sentry_sdk
sentry_sdk.init(
dsn="___PUBLIC_DSN___",
# Add data like request headers and IP for users, if applicable;
# see https://docs.sentry.io/platforms/python/data-management/data-collected/ for more info
send_default_pii=True,
# Set traces_sample_rate to 1.0 to capture 100%
# of transactions for tracing.
+ traces_sample_rate=1.0,
)If you’re adopting Tracing in a high-throughput environment, we recommend testing prior to deployment to ensure that your service’s performance characteristics maintain expectations.
Learn more about tracing options, how to use the traces_sampler function, or how to sample transactions.