Summary
I interviewed for a Level I Python Full Stack Developer role at Aspire Systems, facing questions on Python core concepts, JWT, logging, and a practical coding challenge to implement a logging decorator.
Full Experience
I recently had my technical interview for the Level I Python Full Stack Developer position at Aspire Systems. The interview began with a standard self-introduction, where I spoke about my background and experience.
Following this, we dived deep into several technical topics. The Python Concepts section covered decorators, generators, built-in decorators, and the distinctions between @staticmethod and @classmethod. Next, we discussed JWT and security, specifically what JWT is, how it functions, the difference between encoding and encryption, and the algorithms used for JWT signing/verification. We also covered logging and error handling, where I was asked about implementing logging with Python's logging package and handling exceptions in production.
Finally, I was given a coding challenge to design a sophisticated Python decorator for comprehensive function call logging, capturing timestamps, function details, execution duration, and return values or exceptions, with an emphasis on production-quality code. The interviewer emphasized writing clean, production-quality code and being ready to explain my approach.
Interview Questions (10)
Explain what decorators are in Python, their purpose, and how they are used.
Explain generators in Python and how they differ from normal functions, including use cases.
Describe some built-in decorators available in Python and their functionalities.
Explain the difference between @staticmethod and @classmethod in Python, along with examples of their appropriate use.
Explain what JWT (JSON Web Token) is, its structure, and the overall process of how it works for authentication/authorization.
Clarify the distinction between encoding and encryption, providing examples of when each is used.
Identify the common algorithm types used for signing and verifying JSON Web Tokens (JWTs).
How do you implement logging using Python's built-in logging package? Describe basic setup and common practices.
Describe strategies and best practices for handling exceptions and logging them effectively in production-level Python code.
Design a sophisticated Python decorator that implements a comprehensive logging mechanism for function calls.
Your decorator should capture and log the following details for each function invocation:
- Timestamp of function execution
- Function name and arguments passed
- Execution duration
- Return value or any exceptions raised
The decorator should be flexible enough to work with functions of varying signatures and handle potential errors gracefully without disrupting the original function's behavior.
Focus on writing clean, production-quality code and be ready to explain your approach, especially around decorators and logging mechanisms.