Python programming practice

Status: Outline with beginner lessons available in the foundations track.

Prerequisites

• Computing and Python foundations
• Variables, conditions, loops, functions, and basic debugging

Learning objectives

• break a problem into inputs, transformations, and outputs;
• choose readable data structures and functions;
• test normal, edge, and invalid inputs; and
• explain time, space, and maintainability trade-offs.

Ordered subtopics

1. Decomposing problems and writing pseudocode
2. Functions and reusable modules
3. Text and file processing
4. APIs, JSON, and network requests
5. Classes and object-oriented design
6. Searching and sorting
7. Stacks, queues, trees, and graphs
8. Recursion and algorithmic thinking
9. Complexity and performance
10. Testing, code review, and project structure

Planned projects: quiz game, maze solver, API dashboard, and shortest-path visualizer.

Best practices

• Prefer small functions with one clear responsibility.
• Validate input at the boundary of a program.
• Keep network calls, file access, and core logic separable.
• Use tests and examples before optimizing performance.
• Never execute untrusted code or paste secrets into a debugging request.

References

• Python tutorial
• The Python standard library

Problem-solving pattern

For every project, write these four parts before coding:

1. Input: What information does the program receive?
2. Process: What steps transform the input?
3. Output: What should the user see?
4. Examples: Which normal and unusual cases should work?