This repository implements a Game Server in Rust for the Microservice Dungeon Game.

This Game service does not implement a round time, instead it automatically starts the next round once every player submitted a command for themselves and their robots.

• Multiple Games can run in parallel, for faster Deep learning
• Really similar API to the original Microservice Dungeon
• Time savings due to the removal of round times.

Run docker-compose up -d in your Terminal. The Game Service will be available under 127.0.0.1:8080

This Game Server was mainly written, to empower Deep Learning for the Microservice Dungeon Project.

You can find my own Deep Learning Integration in [this Repository](https://www.archi-lab.io/compounds/dungeon_main.html](https://github.com/Amueller36/Deep-Q-Learning-Robot-Dungeon).

The Game Server provides the following API endpoints:

• POST /games: Create a new game

  • Request Body: { "max_rounds": number, "max_players": number, "map_size": number }
  • Response: { "game_id": string }

• DELETE /games/{game_id}: Delete a specific game

  • Response: { "game_id": string }

• GET /games: Get all games

  • Response: List of GameState objects

• GET /games/created: Get all created games

  • Response: List of GameState objects for games in "Created" status

• GET /games/{game_id}: Get a specific game

  • Response: GameState object

• GET /games/{game_id}/currentRound: Get the current round of a specific game

  • Response: GameState object with only the current round

• DELETE /games: Delete all games

  • Response: List of deleted game IDs

• GET /games/{game_id}/players: Get all players in a game

  • Response: { "participating_players": [string] }

• PUT /games/{game_id}: Join a game

  • Request Body: { "player_name": string }
  • Response: { "player_name": string, "game_id": string, "money": number }

• POST /games/{game_id}/gameCommands/start: Start a game

  • Response: { "game_id": string, "game_status": string }

• POST /games/{game_id}/gameCommands/end: End a game

  • Response: { "game_id": string, "game_status": string }

• GET /games/{game_id}/map: Display the map for the current round

  • Response: String representation of the map

• GET /games/{game_id}/map/rounds/{round_number}: Display the map for a specific round

  • Response: String representation of the map

• GET /games/{game_id}/map/players/{player_name}: Display the map for a specific player

  • Response: String representation of the map

• GET /games/{game_id}/map/rounds/{round_number}/players/{player_name}: Display the map for a specific round and player

  • Response: String representation of the map

• GET /games/{game_id}/currentRound/players/{player_name}/robots: Get robots for the current round

  • Response: List of Robot objects

• GET /games/{game_id}/currentRound/players/{player_name}/robots/{robot_id}: Get a specific robot for the current round

  • Response: Robot object

• GET /games/{game_id}/currentRound/players/{player_name}: Get player state for the current round

  • Response: PlayerStateDto object

• GET /games/{game_id}/currentRound/players/{player_name}/new: Get detailed player state for the current round

  • Response: PlayerStateDto object with additional information

• GET /games/{game_id}/{round_number}/players/{player_name}/new: Get detailed player state for a specific round

  • Response: PlayerStateDto object with additional information

• POST /games/{game_id}/commands: Handle a batch of commands

  • Request Body: List of Command objects
  • Response: 200 OK if successful, or appropriate error status

• POST /games/{game_id}/commands/hypothetically: Handle a batch of commands hypothetically

  • Request Body: List of Command objects
  • Response: PlayerStateDto object representing the hypothetical game state after applying the commands