Instrument a Python application with the Pyroscope SDK for continuous profiling

Steps

1. Install the Pyroscope Python SDK: pip install pyroscope-io
2. Initialize the profiler at application startup by calling pyroscope.configure() with server_address pointing to your Pyroscope or Grafana Pyroscope endpoint, application_name, and auth_token=YOUR_TOKEN if using Grafana Cloud
3. Add tags to the profiler configuration using the tags dict for static labels (environment, version) and use pyroscope.tag_wrapper() as a context manager to attach dynamic labels (like endpoint or job type) around specific code blocks
4. For background tasks and async applications call pyroscope.configure() once and rely on the SDK's thread-based sampling; for multi-process applications initialize the profiler in each worker process after fork
5. Deploy the application and navigate to the Pyroscope or Grafana Explore Profiles UI; select the application name and profile type (cpu, memory allocations) and inspect the flamegraph
6. Compare profiles across time windows or between app versions using the diff flamegraph view to identify regressions