in

How you can Troubleshoot Python Scripts with the Logging Module | by Aashish Nair | Aug, 2023


Print statements can solely take you to this point…

Picture by Tima Miroshnichenko: https://www.pexels.com/photo/a-person-writing-on-a-notebook-5336909/

Desk of Contents

Introduction
The Logging Module
The Levels of Logging
Configuring Levels
Configuring Levels for Debugging
Creating Log Files
Formatting Log Messages
Key Takeaways

Introduction

Think about the next state of affairs: You’ve written a chunk of code that both returns an error or yields an sudden worth.

x1 = function1(x)
x2 = function2(x1)
x3 = function3(x2)

To seek out the inaccurate line of code, you write a print assertion…

x1 = function1(x)
print(x)
x2 = function2(x1)
x3 = function3(x2)

Then add one other print assertion…

x1 = function1(x)
print(x)
x2 = function2(x1)
print(x)
x3 = function3(x2)

Then observe it up with one other print assertion.

x1 = function1(x)
print(x)
x2 = function2(x1)
print(x)
x3 = function3(x2)
print(x)

When you’ve recognized and glued the problem, these print statements are ineffective. So, you delete or remark out every of them one after the other:

x1 = function1(x)
#print(x)
x2 = function2(x1)
#print(x)
x3 = function3(x2)
#print(x)

In case your troubleshooting expertise resembles the state of affairs above, you’re already aware of the frustration of utilizing print statements to take care of inaccurate strains of code.

Luckily, there’s a software in Python that provides a way more efficient technique for debugging code: the logging module.

Right here, we delve into the essential functionalities of the logging module and discover the options that make it such a strong troubleshooting software.

The Logging Module

The logging module is designed for programmers trying to monitor sure occasions of their applications successfully.

Monte Carlo Strategies. An Introduction to Reinforcement… | by Steve Roberts | Aug, 2023

Efficient coding with dates and occasions in Python | by Alicia Horsch | Aug, 2023