Argus Python SDK - Instrumentation for AI-native observability
Project description
argus-python
Argus Python SDK — instrumentation for AI-native observability, monitoring, and security.
Installation
pip install argus-ai-sdk
With framework extras:
pip install argus-ai-sdk[fastapi]
pip install argus-ai-sdk[flask]
Quick Start
Initialize the SDK
import argus
argus.init(
server_url="https://argus.example.com",
api_key="your-api-key",
service_name="my-service",
)
Framework Middleware
FastAPI:
from fastapi import FastAPI
from argus.middleware.fastapi import ArgusMiddleware
app = FastAPI()
app.add_middleware(ArgusMiddleware)
Flask:
from flask import Flask
from argus.middleware.flask import ArgusFlask
app = Flask(__name__)
ArgusFlask(app)
Trace Functions
from argus.decorators import trace
@trace("fetch_user")
async def fetch_user(user_id: str):
# Automatically creates a span with timing and error capture
...
Capture Exceptions
try:
risky_operation()
except Exception:
argus.capture_exception()
Breadcrumbs
argus.add_breadcrumb(
category="http",
message="GET /api/users",
data={"status_code": 200}
)
Custom Events
argus.event("payment_processed", {"amount": 99.99, "currency": "USD"})
Features
- Distributed Tracing — W3C Traceparent propagation across services
- Framework Middleware — FastAPI and Flask integrations
- Function Tracing —
@tracedecorator for sync and async functions - Exception Capture — Automatic stack traces with breadcrumb context
- Breadcrumbs — Trail of events leading up to errors
- Custom Events — Send arbitrary telemetry data
- HTTP Instrumentation — Auto-instrument outgoing httpx requests
- Serverless Support — Auto-detects AWS Lambda, Vercel, GCP Functions, and more
- Non-blocking — Events are batched and flushed asynchronously
License
MIT — see LICENSE for details.
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