Mastering Python Logging And Loguru: Complete Guide

Unleash the Power of Efficient Logging: Boost Your Python Development Skills with Best Practices and Loguru

What you’ll learn
Understand the fundamentals of logging in Python and why it’s crucial for software development.
The significance of logging in software development
Configuring Python’s built-in logging module for various use cases
Advanced logging techniques, including custom handlers and filters
Introduction and setup of Loguru for simplified logging
Comparing Python’s logging module with Loguru for different scenarios
Best practices for log message formatting and file management
Real-world logging strategies for application monitoring and debugging
Implementing logging in multi-threaded environments
Integrating logging with application performance and error monitoring tools
Structuring loggers in large projects for clarity and maintainability

Requirements
Basic Knowledge of Python: Familiarity with Python syntax and fundamental programming concepts such as variables, loops, and functions.
Access to a Computer: A computer that can run Python and text editing software, for practicing course exercises and projects.

Description
“Mastering Logging in Python with Built-in Modules and Loguru” is a specialized course designed for developers aiming to enhance their Python applications through effective logging strategies. By delving into both Python’s built-in logging module and the Loguru library, students will learn how to implement sophisticated logging mechanisms that can significantly improve application debugging, monitoring, and maintenance. What Students Will Learn:The fundamentals of logging in Python and its importance in software development.How to configure and utilize Python’s logging module across different scenarios and applications.Comparing Python’s logging module with Loguru for different scenariosTechniques for formatting log messages to ensure they are informative and actionable.Best practices for log message formatting and file managementStrategies for log file management, including rotation and retention policies.Best practices for integrating logging into Python applications, ensuring they are robust and easier to maintain.Why You Need This Course:Logging is an essential aspect of software development, offering insights into the behavior of applications and aiding in the quick identification of errors and performance bottlenecks. Through this course, you’ll:Gain a deep understanding of how to leverage logging to debug and monitor Python applications effectively.Learn to configure logging for various complexity levels, from basic scripts to large-scale applications.Enhance your ability to maintain and improve the quality of software, making your applications more reliable and user-friendly.Become proficient in using logging as a proactive tool for performance optimization and error prevention.Who Is This Course For:Intermediate Python developers looking to deepen their debugging and application monitoring skills.Software engineers and web developers seeking to implement advanced logging strategies in their projects.Data scientists and analysts requiring logging to better manage and understand their data processing workflows.DevOps professionals interested in leveraging logs for improved application deployment and management.Technical team leads and managers aiming to standardize logging practices within their teams.This course is tailor-made for anyone passionate about software development and committed to learning the intricacies of Python logging. Whether you’re looking to solve complex debugging challenges or simply improve the quality and reliability of your applications, “Mastering Python Logging and Loguru: Complete Guide” provides the knowledge and hands-on experience you need to succeed.Idan Chen

Overview
Section 1: Introduction to Logging in Python

Lecture 1 Importance of Logging

Lecture 2 Overview of Python Logging & Introduction to Loguru

Lecture 3 Understanding Log Levels

Section 2: Getting Started with Python

Lecture 4 Installing Python 3 on your computer

Lecture 5 Creating virtual environment (VENV)

Lecture 6 How to Install Python 3 and Use Virtual Environments (venv) on Windows- Article

Lecture 7 How to Install Python 3 and Use Virtual Environments (venv) on linux- Article

Lecture 8 How to Install Python 3 and Use Virtual Environments (venv) on Mac- Article

Lecture 9 Installing Pycharm – Article

Section 3: Python Programming Foundations

Lecture 10 Functions in Python: Definition and Usage

Lecture 11 Modules and Packages: Organizing Code

Lecture 12 Understanding Python Classes and Objects

Section 4: Python’s Built-in Logging Module – Detailed

Lecture 13 Setting Up Basic Logging

Lecture 14 Deep Dive: Log Levels and Handlers

Lecture 15 Formatting Logs for Better Readability

Lecture 16 Using Filters and Custom Handlers

Lecture 17 Structuring Loggers in a Project

Lecture 18 Logging in Multithreaded Applications

Lecture 19 Handling Exceptions and Stack Trace

Section 5: Advanced Logging with Loguru

Lecture 20 Easy Logging Setup with Loguru

Lecture 21 Configurations and Customization

Lecture 22 Exception Handling and Stack Traces with Loguru

Lecture 23 Serialization and File Management

Lecture 24 Comparing Loguru and Python’s Logging (including Asynchronous with loguru)

Section 6: Real-world Applications and Best Practices

Lecture 25 working with yaml files as configuration – Article

Lecture 26 Building Configuration Class for easy logging and loguru configuration

Lecture 27 Creating logging class from scratch

Lecture 28 Creating loguru class from scratch

Lecture 29 Introduction to FastAPI with Python – Article

Lecture 30 loguru in Web Applications

Lecture 31 Logging in Scripting and Automation using requests

Lecture 32 Prometheus Introduction – Article

Lecture 33 Integrating Logging with Monitoring Tools using prometheus_client

Section 7: Course Conclusion

Lecture 34 Course Recap and Next Steps

Intermediate Python Developers: Those who have a grasp of Python basics and wish to deepen their understanding of application diagnostics, debugging, and monitoring.,Software Engineers: Professionals looking to improve their ability to troubleshoot, monitor, and maintain Python applications effectively.,Data Scientists and Analysts: Individuals in data-centric roles seeking to implement logging for better data processing and analysis workflow management.,DevOps Engineers: Those who are involved in the deployment and management of Python applications and want to enhance application observability and operational intelligence.,Web Developers: Python web developers looking to integrate robust logging mechanisms into their web applications for enhanced error tracking and performance monitoring.,Students and Lifelong Learners: Anyone interested in software development practices, keen on learning a critical aspect of software maintenance and quality assurance.,Technical Team Leads and Managers: Leaders who want to understand the intricacies of logging to oversee and improve the development and maintenance processes within their teams.