Ready for the real environment experience?
The Python 3 DateTime module supplies classes for manipulating dates and times in both simple and complex ways. While date and time arithmetic are supported, the focus of the implementation is on efficient attribute extraction for output formatting and manipulation.
This Lab is designed to introduce you to coding with date and times in Python, using the DateTime module. You will be required to complete each of the following Python coding exercises:
- Exercise 1 - DateTime: Complete the code required to work with and manipulate DateTime variables
- Exercise 2 - OldestFile: Complete the code required to query the local filesystem to discover the oldest residing file
- Exercise 3 - YoungestPresident: Complete the code required to read presidential data stored in a local text file and then sort it based on age
Note: Each exercise has a provided solution to consult with when needed.
Upon completion of this lab, you will be able to:
- Write a Python script that creates DateTime variables and manipulates date and times
- Write a Python script that queries the current state of the local filesystem
- Understand how to read in and parse DateTime information stored within a local text file
- Understand how to perform SQL inserts involving DateTime information into a locally hosted SQLite database
- 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 - DateTime
- Exercise 2 - OldestFile
- Exercise 3 - YoungestPresident
- Exercise 4 - SQLite3
June 16th, 2018 - Optimized creation of lab resources to reduce the time it takes to access the browser IDE by 60%.
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, GCP, Azure), Security, Kubernetes, and Machine Learning.
Jeremy holds professional certifications for AWS, GCP, Terraform, Kubernetes (CKA, CKAD, CKS).