Python Log Monitoring with LogMonitor
>_ why python apps need log monitoring
Python powers everything from web APIs to data pipelines, and debugging across these systems requires centralized logging. Standard logging to files or stdout gets lost in production, especially when running multiple workers or containers. LogMonitor gives you a single real-time dashboard for all your Python logs.
>_ how logmonitor works with python
Use the LogMonitor HTTP API to send logs from any Python application. Make an HTTP POST request to https://api.logmonitor.io/v1/logs with your API key, log level, message, and optional metadata. The API returns 202 Accepted on success. You can wrap this in a helper function or integrate it into Python's built-in logging framework.
>_ quick start
import requestsimport timeLOGMONITOR_URL = "https://api.logmonitor.io/v1/logs"API_KEY = "YOUR_API_KEY"def send_log(level, message, meta=None): requests.post( LOGMONITOR_URL, headers={ "X-Logmonitor-Api-Key": API_KEY, "Content-Type": "application/json", }, json=[{"level": level, "message": message, "clientTimestamp": int(time.time())}], ) # Returns 202 Accepted on success# Usagesend_log("info", "User signed up")send_log("error", "Payment failed")>_ what you can monitor
- $Web request errors in Django, Flask, or FastAPI
- $Background task and Celery worker failures
- $Database query errors and ORM exceptions
- $External API call timeouts
- $Data pipeline processing logs
- $Authentication and permission errors
>_ frequently asked questions
LogMonitor currently provides native SDKs for JavaScript and Flutter. For Python, you use the HTTP API which is just as simple: a single HTTP POST sends your log to the Live Console in real time.
Yes. You can create a custom logging handler that sends logs to the LogMonitor HTTP API. This way all your existing logging.info() and logging.error() calls are automatically forwarded.
The HTTP call is fast, but for zero overhead you can send logs asynchronously using a background thread, asyncio, or a task queue like Celery.
Any Python framework. The HTTP API is framework-agnostic, so it works with Django, Flask, FastAPI, Tornado, aiohttp, Sanic, and standalone scripts.
Yes. You can include additional fields in the log objects sent to the HTTP API. You can include user IDs, request IDs, error details, or any other context you need for debugging.