Project Instructions (Module 1: Variables and Professional Python)¶

WEDNESDAY: Complete Workflow Phases 1-3¶

Follow the instructions in ⭐ Workflow: Apply Example to complete:

1. Phase 1. Start & Run - copy the project and confirm it runs
2. Phase 2. Change Authorship - update the project to your name and GitHub account
3. Phase 3. Read & Understand - review the project structure and code

FRIDAY/SUNDAY: Complete Workflow Phases 4-5¶

Again, follow the instructions above to complete:

1. Phase 4. Make a Technical Modification - make a change and verify it still runs
2. Phase 5. Apply the Skills to a New Problem

Phase 4 Suggestions¶

Make a small technical change that does not break the script. Choose any one of these (or a different modification as you like):

• Change the value of one constant to reflect something true about you (e.g., your field, your city, your years of experience)
• Add a new constant of a type not yet in the example (e.g., a dict[str, int] mapping skill names to years of experience)
• Change the formatting in get_summary() to display values differently (e.g., display the list items one per line instead of inline)
• Add a new labeled line to the summary output for one of your constants

Confirm the script still runs successfully after your change.

Phase 5 Suggestions¶

Phase 5 Suggestion 1. Same Structure, Your Domain (Directed)¶

Replace all five constants in your copy with five of your own choosing, keeping one of each type: str, int, float, bool, list[str].

Steps:

• Choose a topic or domain you know well (e.g., your profession, a sport, a hobby, a research area)
• Declare one variable of each type related to your topic
• Use ALL_CAPS_WITH_UNDERSCORES for constant names
• Add Final to each type hint
• Update get_summary() to display your variables with clear labels
• Run the script and confirm output appears in the log

Then:

• Describe the topic you chose and why
• Explain what each variable represents in that context
• Identify which type hint was most natural for your data and why

Phase 5 Suggestion 2. Add Descriptive Statistics (Original)¶

Add a get_statistics() function for a numeric list related to your topic.

Steps:

• Choose a list of at least five numeric measurements related to your domain (e.g., scores, prices, durations, distances, temperatures)
• Declare the list as a list[float] constant
• Compute: total, count, minimum, maximum, mean, and standard deviation
• Use the statistics module for mean and stdev
• Display the results using an f-string with two decimal places
• Run the script and confirm the statistics appear in the log

Then:

• Describe what the numbers represent
• Identify any values that seem unusual and explain why
• Explain what the standard deviation tells you about your data

Key Skill Focus¶

As you work, focus on:

• how to choose clear, descriptive variable names
• how type hints communicate intent without changing behavior
• how Final signals that a value should not be reassigned
• how f-strings embed variable values into readable output
• how the statistics module provides common descriptive measures

Your goal is to declare meaningful variables and display them clearly.

Professional Communication¶

Make sure the title and narrative reflect your work. Verify key files:

• README.md
• docs/ (source and hosted on GitHub Pages)
• src/ (your renamed script)

Ensure your project clearly demonstrates:

• correct variable declarations with type hints
• a working get_summary() function with your variables
• successful script execution with output in the log