Module 2 Objective Mapping

Thomas J. Kennedy

1 Module Objectives

Module 2 starts our discussion of Python… more specifically setting up a Python development environment, running some code, and exploring the Zen of Python.

 

This type of table is known as a traceability matrix. It is a topic covered quite a bit in 400-level Computer Science coursework.

You will notice quite a few mappings of Module 2 objectives (row) to Course Objectives (column). We are introducing quite a few aspects of Python (whirlwind introduction).

As we move throughout the semester… each of these topics and concepts will be incrementally covered in more detail.

# Module Objective 1 2 3 4 5 6.A 6.B 7.A 7.B 8 9 10 11 12 13 14 15
1 Checkout the course example set GitHub Repository. ✓ ✓
2 Create a project in their preferred IDE: VSCode or Vim (with appropriate plugins). ✓
3 Run a provided Python program. ✓ ✓
4 Run a set of provided tests for a Python program. ✓ ✓
5 Describe the basic structure of a Python program. ✓ ✓
6 Discuss PEP 8. ✓ ✓ ✓
7 Discuss PEP 20. ✓ ✓ ✓
8 Discuss how to approach an somewhat unfamiliar language (e.g., Python or Rust). ✓ ✓ ✓ ✓ ✓

2 Lectures & Objectives

The following table shows lectures (rows) vs Module Level Objectives (columns).

Lecture 1 2 3 4 5 6 7 8
Module 2 Objective Mapping
Why Learn Python? ✓
A First Look at PEP 20 (The Zen of Python) ✓
Structure of a Basic Python Program ✓
Structure of a Python Program with Tests ✓
Python Style & PEP 8 ✓
Procedural, Object-Oriented, and Functional ✓
Pythonic Code & “Good” Code ✓ ✓ ✓
Module 2 Summary

Note that Module Level Objectives 1 through 4 are covered in lab exercises.

3 Course Level Objectives

The course objectives are listed in section 2.4 of the syllabus and reproduced in this document for reference.

A student who successfully completes this course will be able to (in Python):

  1. Run a program consisting of a single file and containing a main function.
  2. Run a program consisting of multiple modules and containing a main function.
  3. Organize code into multiple modules.
  4. Write tests for a module.
  5. Apply the basics of test-driven development through PyTest and/or unittest.
  6. Make use of the various loops (for and while)
    1. Compare the various loops (for and while)
    2. Choose the most appropriate loop (for or while) for a given problem
  7. Make use of the conditional blocks (i.e., if, if-else, and if-else-if-else).
    1. Compare the various conditional blocks (i.e., if, if-else, and if-else-if-else)
    2. Construct the appropriate conditional block (i.e., if, if-else, and if-else-if-else) for a given problem.
  8. Test and write functions.
  9. Design ADTs in accordance with the Class Checklist.
  10. Discuss when polymorphism is appropriate.
  11. Discuss when it is appropriate to utilize dataclasses, classes, and enums.
  12. Write code that utilizes dunder functions.
  13. Refactor code to follow best practices (e.g., PEP 8 and PEP 20).
  14. Apply code linting tools (e.g., pylint and black) to write idiomatic (Pythonic) code.
  15. Discuss the various NumPy np.array mechanics (e.g., broadcasting).
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