Ready for the real environment experience?
This is a long-running lab that you can pause for up to 1 hour
up to 1h
Knowing how to write code in a Pythonic style is an important skill that should be mastered!
This lab is designed to show you how to exploit various Python language features to produce code that is considered to be Pythonic - being clear, concise, readable and maintainable.
- Exercise 1 - List, Set, and Dictionary Comprehensions: Complete the code required to dynamically generate Lists, Sets, and Dictionaries using comprehensions
- Exercise 2 - Generators: Complete the code required to create a Generator Function that yields numbers from the Fibonacci sequence. Also learn to use the builtin functions sum(), min(), max() using Generator Expressions
- Exercise 3 - Lambdas: Complete the code required to use Lambdas to Map and Filter on lists of numbers
Note: Each exercise has a provided solution to consult with when needed.
Upon completion of this lab, you will be able to:
- Write Pythonic code to generate Lists, Sets, and Dictionaries
- Write Pythonic code that leverages Generator Functions and Generator Expressions
- Write Pythonic code that leverages Lambdas to map and filter lists
- Use the terminal to launch and debug Python scripts
- Be comfortable with using a browser-based IDE
This lab will start with the following AWS resources provisioned automatically for you:
- A single EC2 instance, named ide.python.platform.instance, which will have a public IP address attached. This instance will host a web-based Python IDE (based on the Visual Code editor).
To achieve the lab end state, you will be walked through the process of:
- Using your local browser, access the web-based Python IDE served from the ide.python.platform.instance
- Completing the following lab exercises:
- Exercise 1 - List, Set, and Dictionary Comprehensions
- Exercise 2 - Generators
- Exercise 3 - Lambdas
Jeremy is a Content Lead Architect and DevOps SME here at Cloud Academy where he specializes in developing DevOps technical training documentation.
He has a strong background in software engineering, and has been coding with various languages, frameworks, and systems for the past 25+ years. In recent times, Jeremy has been focused on DevOps, Cloud (AWS, Azure, GCP), Security, Kubernetes, and Machine Learning.
Jeremy holds professional certifications for AWS, Azure, GCP, Terraform, Kubernetes (CKA, CKAD, CKS).