You want to pass that Python coding interview.
Have you been rejected for a job because your code wasn’t production quality? It runs without errors but you were told that it is not ready for production. You are now confused, and wondering, what does production-level code even mean? It sure feels like a waste of your time and energy.
You already know the language features (how to use
You have studied or refreshed the concepts of data structures and algorithms.
You have used some Python back-end frameworks.
What are you missing?
Is it the lack of tests, readability or error handling?
It's more than just code.
It is not about knowing certain programming language features, tips or neat tricks. Given the constrain of time, an interviewer is unlikely to expect you to write perfect code in one try. The expectation is that you show some key concepts very well and have the skills to implement them. If you do it with confidence and on time, the person will be satisfied.
One may think that to write production quality programs requires a lot of time and years of real-world experience. While this might be true, you can greatly shorten the learning process with deliberately focused practice.
The most effective way to think about software quality is logically and without assumptions about the execution environment. It’s impossible to predict all the failure modes of an application. Yet, the number of error handling strategies is small.
For the sake of brevity, most textbooks will explain concepts while leaving the exception handling as ‘an exercise to the reader’. But what if you had an interactive workbook that specifically teaches you this skill?
You don't have to take long lectures with a lot of details and little time to practice. Neither have to waste your time searching for answers, and filtering the low quality content that is in many online communities.
You do not want to deal with unfriendly moderators that flag your questions as duplicated. And avoid anyone downvoting your comments.
I'm making a workbook to help you get the job you want. If you like learning by doing, this is for you.
With this workbook you will:
- Learn the 5 error handling strategies.
- Understand which one is appropriate for the main function or a library function.
- How to implement the code, with production-level examples, like Big Tech companies expect.
- Get rapid feedback after each step with automated tests.
- Find pythonic, idiomatically clear, code with tests for you to study and imitate.
If you complete the workbook, you will understand how resilient code should be written. You will have the mindset to devise methods to handle most errors in production.
Not only you will become a better programmer but also be more prepared to pass that technical interview.
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