DEV Community

Crypto.Andy (DEV)
Crypto.Andy (DEV)

Posted on

Best Practices for Handling Errors in Python

Error handling is key to writing robust and maintainable Python code. Here's a quick guide to making your error management smarter and more effective.

☝️ Catch Specific Exceptions. Always catch specific exceptions rather than using a general except block. This helps you identify the root cause of the issue more easily and prevents masking other potential errors.
☝️ Raise Exceptions for Invalid Conditions. If certain conditions aren’t met, raise an exception deliberately. This is a great way to enforce constraints and ensure the program behaves as expected. For example, raise an exception if a function receives invalid input.
☝️ Log Errors Instead of Printing. Instead of relying on print statements, use Python's logging module to record errors. Logging gives you more control over how and where you store error messages (console, files, external systems), and it’s easier to manage different levels of severity (e.g., INFO, ERROR, CRITICAL).
☝️ Provide Clear and Informative Error Messages. When an error occurs, provide detailed and helpful messages. Avoid vague statements like "Something went wrong." Include context such as the function name, the input values, and any other relevant details to make debugging easier.

What are your go-to error-handling practices in Python? Let me know in the comments!

Image description

Image of Datadog

The Future of AI, LLMs, and Observability on Google Cloud

Datadog sat down with Google’s Director of AI to discuss the current and future states of AI, ML, and LLMs on Google Cloud. Discover 7 key insights for technical leaders, covering everything from upskilling teams to observability best practices

Learn More

Top comments (0)

Postmark Image

Speedy emails, satisfied customers

Are delayed transactional emails costing you user satisfaction? Postmark delivers your emails almost instantly, keeping your customers happy and connected.

Sign up