The Error Handling Workbook

Write code that survives production.

Interviewers reject code that runs but isn’t production quality. What separates working code from production code?

You know the language features. You’ve studied data structures and algorithms. You’ve built projects with back-end frameworks. What are you missing?

Knowing the language isn’t enough.

AI tools generate code fast. Hiring managers have shifted from algorithm tests to real-world engineering challenges. They want code reviews, deployment readiness, and clear reasoning about failure. Most candidates skip error handling. This workbook won’t.

Each exercise targets one strategy. You practice until it sticks.

You can’t predict every failure mode. But error handling strategies are few — this workbook distills them into five.

A workbook, not a lecture.

Most textbooks explain error handling in theory and leave practice as ‘an exercise to the reader.’ This workbook teaches the skill directly, with exercises you complete and tests that give you immediate feedback.

The workbook uses Python, but the strategies apply to any language.

Coming Soon

Here’s what you’ll get:

• Learn 5 error handling strategies.
• Know which strategy fits a main function versus a library function.
• Build production code — retry a failed API call, validate user input, propagate errors across layers.
• Run automated tests after each step.
• Study clean, idiomatic code you can imitate.

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