Python

Add observability to your Python applications with OpenTelemetry.

Overview

Python applications can be instrumented with OpenTelemetry to capture traces, logs, and metrics. The Python SDK supports both automatic and manual instrumentation, giving you flexibility in how you add observability to your application.

Use Cases

Monitor Django, Flask, and FastAPI web applications
Trace database queries with SQLAlchemy, psycopg2, and other database libraries
Track async operations with asyncio instrumentation
Capture HTTP client requests with requests and urllib3

Install

Install the OpenTelemetry Python SDK with auto-instrumentation:

pip install opentelemetry-distro opentelemetry-exporter-otlp
opentelemetry-bootstrap -a install

The opentelemetry-bootstrap command detects your installed libraries and installs the appropriate instrumentation packages.

Configure

1. Set the service name

export OTEL_SERVICE_NAME="my-python-service"

2. Configure the OTLP endpoint

export OTEL_EXPORTER_OTLP_ENDPOINT="https://ingress.us-east-2.rocketgraph.app"
export OTEL_EXPORTER_OTLP_HEADERS="Authorization=Bearer YOUR_ROCKETLOGS_API_TOKEN"

Replace YOUR_ROCKETLOGS_API_TOKEN with your API token from Settings.

3. Run your application with auto-instrumentation

opentelemetry-instrument python your_app.py

Or for a web framework like Flask:

opentelemetry-instrument flask run

Framework Examples

Django

opentelemetry-instrument python manage.py runserver

FastAPI with uvicorn

opentelemetry-instrument uvicorn main:app --host 0.0.0.0 --port 8000

Celery workers

opentelemetry-instrument celery -A tasks worker --loglevel=info

Supported libraries

The following libraries are automatically instrumented:

Django, Flask, FastAPI, Starlette
SQLAlchemy, psycopg2, mysql-connector, pymongo
requests, urllib3, aiohttp, httpx
redis, celery, asyncio
And many more via OpenTelemetry Registry