Mastering Python Logging and Loguru: Complete Guide

Install Python 3.12 on your computer from Python.org, configure the path and environment variables, and verify the setup using the command line and pip.

Create and manage a Python virtual environment (venv), activate and deactivate it, install packages with pip, and verify installations by inspecting site-packages and the scripts.

Explore defining and using Python functions with examples like simple hello, default parameters, two-argument functions, looping over names, dict display, and squaring numbers, preparing you for packages, imports, and classes.

Explore modules and packages in Python through practical import examples, including whole module imports, specific attribute imports, aliases, custom modules, built-in modules, and import error handling.

Explore Python classes by building an animal with name and sound and a make_sound method, then use a bird subclass and classmethod staticmethod for rectangle area.

Set up basic logging in Python with the built-in logging module, format messages with a timestamp and level, and log info, debug, warning, error (division by zero example), and critical.

Master Python logging by defining levels—debug, info, warning, error, and critical—and using stream and file handlers, including rotating files by size or time to console and files.

Learn to format Python logs for readability using the logging format and formatters, with placeholders like asc time, level name, and message, plus basic config and dynamic formatting.

Use filters and custom handlers to tailor Python logging. Create a custom filter for messages containing 'special' and a custom handler that prints to the console.

Structure a Python project with packages and subpackages, configure a basic logger across modules, and observe debug, info, and warning messages in the console.

Learn how Python's logging module provides thread-safe logging for multi-threaded apps, with each thread using its own logger and context to emit start and finish messages.

Learn how to log exceptions in Python using the logging module, capture the exception type, message, and stack traces, and customize exception logs with a custom exception handler.

Master easy loguru setup: install with pip, import the pre-configured logger, and log messages and exceptions with rotating, colorized levels like debug, info, warning, error, and critical.

Learn to configure Loguru with configurable log levels, formatting, and filters, and to customize log processing using a record-based sync function, while exploring rotation, compression, and async logging.

Learn how loguru automatically logs exceptions with full stack traces to simplify debugging. Use the catch decorator, customize exception logging, and filter traces to diagnose issues without crashing the app.

Mastering Python Loguru: serialization and file management teaches structured logging with Json data, custom serialization, and log file management through rotation, retention, and compression.

Compare loguru and Python's logging across levels, file logging, and custom formatting, including asynchronous usage with loguru, exception handling, and practical examples.

Design a configuration class that reads settings from a YAML file, exposes get_config, and demonstrates accessing person details, address, and hobbies to support logging and loguru configuration.

Create a logging class from scratch using a configuration-driven format and level. Route logs to a console via a stream handler and switch between debug and info via app config.

Create a full loguru logger class from scratch, configure console and file handlers with YAML config, enable rotation and levels, and bind the logger by name for context.

Explore how to implement loguru logging in fastapi web applications, using middleware to log incoming requests, processing times, and HTTP errors with uvicorn and swagger docs.

Master API logging with requests by building a script that fetches data from a local API, logs info and errors with Loguru, and processes data with a simulated delay.

Integrate logging with monitoring tools using prometheus_client to expose metrics, track requests, and set up alerts for an application's visibility and performance.

Review the course objectives and recap how to set up Python logging, log levels, and basic formatting, YAML configurations, Luguru, fast API, and Prometheus integration.