Crossmint Challenge

candidate id - 245b9d9e-a0ae-4d24-8854-ba383f1e0ef7

Overview

• Phase 1: Build a grid using only Polyanets based on the target configuration.
• Phase 2: Construct a symmetric grid involving multiple object types using a quadrant-based approach to optimize performance.

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Code Structure

cross-mint/
├── constants.py        # Stores API endpoints, candidate ID, and object names
├── helpers.py          # Shared helper functions for fetching data and creating objects
├── shapes.py           # Astral object classes (Polyanets, Soloons, Comeths)
├── phase_1.py          # Implementation for Phase 1
├── phase_2.py          # Implementation for Phase 2
└── README.md           # Documentation

Phase 1 Intuition

Approach

1. Fetch Configuration: Retrieve the goal_shape from the API.
2. Iterate Through Grid:
   • For cells marked as POLYANET, create a Polyanet at the specified coordinates.
   • Skip cells marked as SPACE.
3. Place Polyanets: Post the Polyanet data to the API for placement.

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Phase 2 Intuition

Symmetry Insights

1. The grid can be divided into four quadrants:
   • Top-left
   • Top-right (mirrored horizontally from top-left)
   • Bottom-left (mirrored vertically from top-left)
   • Bottom-right (mirrored horizontally and vertically from top-left)
2. By processing only the top-left quadrant, the remaining quadrants can be programmatically derived.

Approach

1. Fetch Configuration: Retrieve the goal_shape from the API.
2. Extract Quadrant: Use only the top-left quadrant of the grid.
3. Place Objects in Quadrants:
   • Process the top-left quadrant and calculate mirrored placements for the other three quadrants.
   • Use the symmetry to minimize redundant API requests.
4. Post Objects to API: Place objects by sending their configurations to the API.