Feat/python rooms supabase

[swayam0]

Objective
This PR expands the Python curriculum to cover fundamental topics more deeply and transitions the room system to a dedicated persistence layer using Supabase. This move optimizes performance by reducing the client-side bundle size and allows for dynamic content updates without redeployments.

🛠️ Key Changes

1. Python Room Expansion
   Extended Curriculum: Increased the room count from 12 to 16 rooms (4 rooms for each core topic: Variables, Data Types, Control Flow, and Functions).
   New Content:
   Variables: Added Update and Increment (focus on variable reassignment).
   Data Types: Added Introduction to Lists (focus on indexing and basic list operations).
   Control Flow: Added The While Loop (focus on indefinite iteration).
   Functions: Added Default Parameters (focus on flexible function signatures).
   Constraint Compliance: All new rooms strictly follow the

RoomBlueprint
type and utilize bannedConcepts to maintain a beginner-friendly focus.
2. Supabase Persistence Layer
Dynamic Fetching: Updated @/src/lib/supabase/python-rooms.ts to fetch room data from the python_rooms table at runtime.
Bundle Optimization: Refactored the fetching logic to use dynamic imports for the hardcoded fallback blueprints. This ensures that the large blueprint array is only loaded if the Supabase connection fails, significantly reducing the initial payload.
Data Synchronization:
Updated

supabase/seed_python_rooms.sql
with the complete 16-room dataset.
Added helper scripts in scripts/ to streamline future seeding operations.
🧪 Verification Results
Visual Audit: Verified the rendering of new rooms via local development (Screenshots attached in the workspace walkthrough).
Fallback Integrity: Confirmed that the system gracefully falls back to local blueprints if the database is unreachable.
Performance: Verified that

room-blueprints.ts
is no longer part of the critical path in the main client bundle.

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