How to Return Exact Error Codes in Python with Try and Except

Learn how to effectively capture and handle error codes in Python using the try and except structure, ensuring better error management and notifications in your scripts.
---

Visit these links for original content and any more details, such as alternate solutions, latest updates/developments on topic, comments, revision history etc. For example, the original title of the Question was: Return Error code when using try and except? (without raise)

If anything seems off to you, please feel free to write me at vlogize [AT] gmail [DOT] com.
---
Handling Errors in Python Without Raising Exceptions

When writing Python scripts, especially those running in environments like Docker containers, you may encounter unexpected crashes due to various reasons, such as unavailability of data while fetching it from APIs like Yahoo Finance (yfinance). These crashes can disrupt the flow of your application, and it becomes essential to handle errors gracefully. A common requirement in such scenarios is to send notifications, such as emails, with exact error codes that caused the script to fail. This guide will guide you on how to achieve this effectively using the try and except blocks in Python.

Understanding the Problem

You are running scripts that pull data from yfinance and sometimes those scripts crash. You want to implement an error-handling mechanism that captures the specific error codes when a script fails and send them via email for debugging. Simply printing out a generic error message isn't sufficient; you need to capture the exact error that caused the problem.

The Traditional Approach

A typical try-except block in Python looks like this:

[[See Video to Reveal this Text or Code Snippet]]

In this code, if an error occurs, you catch it with an except block. However, this only captures the fact that an error occurred; it does not provide any details about the nature of the error. To enhance this, we can use a more descriptive approach.

Capture Specific Error Codes

Instead of using a generic exception handling block, you can modify the except clause to capture and print the exact error message. Here’s how you can do it:

Step-by-Step Solution

Modify the Except Clause: Use the except Exception as e: syntax to capture the error details.

Print the Error or Use Variable: You can print the error or store it in a variable to send via email.

Send Email Notification: Use the stored error information to send an email alert.

Here's the modified version of your code:

[[See Video to Reveal this Text or Code Snippet]]

Key Points to Note

Use of Exception as e: This syntax allows you to capture the specific error object, providing more context about the issue at hand.

Sending the Exact Error: You can send the exact error message that the program encountered, making your debugging process much more efficient.

Improving User Awareness: By sending detailed error notifications, you can better address issues as they arise, leading to more robust applications.

Conclusion

Effectively handling errors in Python can significantly improve your script's reliability, especially in unpredictable environments like data collection scripts. By capturing and using exact error codes instead of generic messages, you enable better error management and faster issue resolution. Consider adopting this structured error handling method in your Python scripts, and you'll find that debugging and maintenance become much smoother.

Implement these changes in your code, and see how much easier it becomes to manage errors in your applications!