Implementing Logging in FastAPI Endpoints

Logging is an essential tool for debugging, monitoring, and troubleshooting FastAPI applications. By effectively logging information about requests, responses, errors, and other relevant events, you can gain valuable insights into your application’s behavior and identify potential issues. This guide will demonstrate how to implement logging within FastAPI endpoints.

Basic Logging

Import the Logging Module:

Python

import logging

Create a Logger:

Python

logger = logging.getLogger(name)

Log Messages:

Python

@app.get(“/”)
def read_root():
logger.info(“Received a GET request to /”)
return {“Hello”: “World”}

Logging Request and Response Information

To log details about incoming requests and outgoing responses, use the request and response objects provided by FastAPI:

Python

@app.get("/items/{item_id}")
def read_item(item_id: int, request: Request, response: Response):
    logger.info(f"Received GET request for item {item_id}")
    # ...
    logger.info(f"Sending response: {response.json()}")

Logging Exceptions

Log exceptions using try...except blocks:

Python

@app.get("/items/{item_id}")
def read_item(item_id: int):
    try:
        # ...
    except Exception as e:
        logger.error(f"Error reading item {item_id}: {e}")
        raise

Additional Terms:

  • Logging Level: Adjust the logging level based on your application’s needs (DEBUG, INFO, WARNING, ERROR, CRITICAL).
  • Logging Format: Customize the format to include timestamps, thread IDs, and other relevant information.
  • Logging Handlers: Use different handlers (file, email, database) for different logging scenarios.
  • Structured Logging: Consider using structured logging formats (e.g., JSON) for easier parsing and analysis.
  • Logging Libraries: Explore third-party libraries like uvicorn.logging for additional features.
Python Logging: Filters and Custom Filters
Adding File Handlers for Log Storage

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