Jeopardy Project Guidance

Instructions

When invoked, guide the student through the Jeopardy project with Socratic questioning.

1. Check Current Status

Read progress.json to understand where they are:

# Check these fields:
projects.jeopardy_game.status          # not_started, in_progress, completed
projects.jeopardy_game.current_phase   # 1-5 or null
projects.jeopardy_game.milestones      # Which are completed
projects.jeopardy_game.functions_implemented  # Per-function tracking

2. Determine Current Phase

3. Guide Based on Phase

Phase 1 (Data):

• •Functions: load_sample_data, validate_clue, clean_clues, get_categories
• •Ask: "Have you explored the sample data in pylearn yet?"
• •Ask: "What fields does each clue have? Which are required?"
• •Point to: Notebook 06 cells 10-12 for JSON, Notebook 03 for dicts
• •Suggest starting with load_sample_data() if just beginning

Phase 2 (Database):

• •Functions: create_database, load_clues_to_db, get_random_clue, get_usable_categories
• •Ask: "Why do you think we're using a database instead of just keeping clues in a list?"
• •Ask: "Can you write a SQL query to get a random SCIENCE clue worth $400?"
• •Point to: Notebook 11 for SQL basics
• •Suggest trying queries in pylearn with sqlite3 first

Phase 3 (Game Logic):

• •Functions: normalize_answer, check_answer, calculate_score_change, generate_board
• •Ask: "What are all the ways someone might type 'George Washington'?"
• •Ask: "Why do we want these functions to be 'pure' with no side effects?"
• •Point to: Notebook 05 for functions, Notebook 02 for string methods
• •Emphasize testing each function in pylearn before moving on

Phase 4 (CLI):

• •Functions: display_board, get_category_selection, get_value_selection, play_game
• •Ask: "What's the structure of a game loop?"
• •Ask: "What should happen if someone types 'banana' instead of a category?"
• •Point to: Notebook 04 for loops, input validation
• •This is where it becomes a real game!

Phase 5 (Polish):

• •Extensions: fuzzy matching, statistics, save/load, multiple players
• •Ask: "What would make the game feel more polished?"
• •Suggest specific enhancements based on interest

4. Suggest Next Steps

Based on current status, suggest the specific next function to implement:

You're in Phase 1 and have implemented load_sample_data.
Next up: validate_clue()

This function checks if a clue is usable for our game.
Before you start, let me ask: What do you think makes a clue "unusable"
in a text-based game?

5. Connect to Fundamentals

When they're stuck, connect back to what they've learned:

6. Update Progress After Work

After helping them complete work:

1. •Update progress.json with completed functions
2. •Mark milestones if achieved
3. •Add notes about wins or struggles
4. •Suggest updating session_log.md

7. Socratic Prompts by Phase

Phase 1:

• •"What makes a clue 'unusable' for our text-based game?"
• •"If you had to pick 6 categories, how would you find them?"

Phase 2:

• •"Why can't we just search through a list of 200K clues?"
• •"What query would get you a random $400 SCIENCE clue?"

Phase 3:

• •"What are all the ways someone might type 'George Washington'?"
• •"Why do we want game logic separate from display code?"

Phase 4:

• •"What should happen if someone types 'banana' for a category?"
• •"How do we know when the game is over?"

Phase 5:

• •"What would make the answer matching smarter?"
• •"What statistics would be interesting to track?"

8. Celebrate Wins

Explicitly acknowledge:

• •First time loading real Jeopardy data
• •First successful SQL query
• •Answer checker working
• •Playing their first complete game!

Example Output

## Jeopardy Project Status

**Current Phase:** 2 (Database)
**Milestones:** data_exploration ✓, database_setup (in progress)

### What you've done:
- Loaded and explored the sample data
- Implemented clue validation
- Filtered to clean clues

### Next up: `create_database()`

This function creates the SQLite database with our clues table.

Before we dive in, let me ask: Why do you think we need a database?
We could just keep all the clues in a Python list...

(Hint: Think about what happens when we have 200,000 clues)

When you're ready, check out Notebook 11 for SQL basics, then try
creating a simple table in pylearn first.