Handling and Logging Errors in Python

Errors are a common part of any programming language, and Python is no exception. Knowing how to handle and log errors is crucial for building robust and maintainable software. In this post, we’ll dive deep into how to raise errors in Python and discuss how to use logging to keep track of those errors.

Raising Errors in Python

In Python, errors are communicated through a mechanism called exceptions. An exception is a signal that an error condition has occurred. Python has numerous built-in exceptions, like ValueError, TypeError, KeyError, and many more.

To manually trigger an exception, you use the raise keyword:

def square_root(x):
if x < 0:
raise ValueError("Cannot compute the square root of a negative number.")
return math.sqrt(x)

Here, we raise a ValueError if the function is asked to compute the square root of a negative number.

Catching Errors

Other functions or parts of your program can “catch” these exceptions and respond to them using a try…except block:

result = square_root(-4)
except ValueError as e:
print(f"An error occurred: {e}")

This way, your program doesn’t crash when an exception is raised; instead, it gracefully handles the error and can continue executing.

The Power of Logging

While raising and catching exceptions is vital for handling errors, it’s equally essential to keep a record of what went wrong. This is where logging comes in. Logging allows developers to capture information about a program’s execution, making it easier to diagnose and debug issues.

Python provides a built-in module called logging that makes logging straightforward. Here’s a basic setup:

import logging

# Configure logging
logger = logging.getLogger(__name__)

With this setup, you can now log messages at various severity levels: DEBUG, INFO, WARNING, ERROR, and CRITICAL.

Combining Exceptions and Logging

When raising exceptions, it’s a good idea to log information about the error:

def square_root(x):
if x < 0:
logger.error("Attempted to compute the square root of a negative number.")
raise ValueError("Cannot compute the square root of a negative number.")
return math.sqrt(x)

Now, when this function encounters an error, it not only raises an exception but also logs an error message. This dual approach provides multiple benefits:

  1. User Feedback: The exception provides immediate feedback to users or other parts of your software that something went wrong.
  2. Developer Insight: The log captures the error, making it easier for developers to diagnose and fix issues, especially when they manifest in production environments.


Error handling and logging are essential components of robust software development. By raising appropriate exceptions and logging valuable information, developers can ensure that their software is both user-friendly and maintainable. If you haven’t already, start incorporating these techniques into your code to create more resilient and traceable applications.

Author: robot learner
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