gamepp 0.2.0

Various game programming patterns.

Game Programming Patterns (gamepp)

Overview

The gamepp package provides a collection of design patterns and best practices for game programming. It aims to help developers implement common patterns in their games, improving code organization, maintainability, and performance.

This collection is from Game Programming Patterns by Robert Nystrom.

The code however may vary from the authors' original implementation. The book is a very good read, highly recommended.

Installation

To install the gamepp package, you can use pip:

pip install gamepp

Available Patterns

The gamepp package includes implementations of the following design patterns:

• Bytecode: Defines a set of instructions that can be executed by a virtual machine.

  from gamepp.patterns import Instruction, VirtualMachine
  
  # Define instructions
  ICONST = 1 # Push integer constant
  IADD = 2   # Add two integers
  PRINT = 3  # Print top of stack
  HALT = 4   # Stop execution
  
  instructions = [
      Instruction(ICONST, 5),
      Instruction(ICONST, 10),
      Instruction(IADD),
      Instruction(PRINT),
      Instruction(HALT),
  ]
  
  vm = VirtualMachine(instructions)
  vm.run() # Output: 15
  

• Command: Encapsulates a request as an object, thereby letting you parameterize clients with different requests, queue or log requests, and support undoable operations.

  from gamepp.patterns.command import Command, CommandManager
  from gamepp.common.game_object import GameObject
  
  class MoveCommand(Command):
      def __init__(self, x, y):
          self._x = x
          self._y = y
          self._old_x = 0
          self._old_y = 0
  
      def execute(self, game_object: GameObject):
          self._old_x = game_object.x
          self._old_y = game_object.y
          game_object.x += self._x
          game_object.y += self._y
          print(f"Moved to ({game_object.x}, {game_object.y})")
  
      def undo(self, game_object: GameObject):
          game_object.x = self._old_x
          game_object.y = self._old_y
          print(f"Undid move to ({game_object.x}, {game_object.y})")
  
      def redo(self, game_object: GameObject):
          self.execute(game_object) # In this simple case, redo is same as execute
  
  player = GameObject(0, 0, 0) # Assuming GameObject has x, y, z
  manager = CommandManager()
  
  move_right = MoveCommand(10, 0)
  manager.execute_command(move_right, player) # Output: Moved to (10, 0)
  
  move_up = MoveCommand(0, 5)
  manager.execute_command(move_up, player)    # Output: Moved to (10, 5)
  
  manager.undo(player) # Output: Undid move to (10, 0)
  manager.redo(player) # Output: Moved to (10, 5)
  

• Component: Allows you to add functionality to objects dynamically by composing them with reusable components.

  from gamepp.patterns.component import Entity, PositionComponent, HealthComponent
  
  player = Entity()
  player.add_component(PositionComponent(x=10, y=20))
  player.add_component(HealthComponent(current_hp=100, max_hp=100))
  
  pos = player.get_component(PositionComponent)
  if pos:
      print(f"Player position: ({pos.x}, {pos.y})") # Output: Player position: (10, 20)
  
  health = player.get_component(HealthComponent)
  if health:
      health.take_damage(10)
      print(f"Player health: {health.current_hp}/{health.max_hp}") # Output: Player health: 90/100
  

• Context-Sensitive Multigraph (CSM): A data structure for representing and querying relationships between game entities in a way that adapts to their current state or context.

  from gamepp.patterns.csm import CSM, StateMachineInterface
  from enum import Enum
  
  class CharacterState(Enum):
      IDLE = 1
      CHASING = 2
      FLEEING = 3
  
  class CharacterFSM(StateMachineInterface):
      def __init__(self):
          self.current_state = CharacterState.IDLE
      def get_current_state_id(self) -> int:
          return self.current_state.value
      def set_state(self, state: CharacterState):
          self.current_state = state
  
  csm = CSM()
  player_fsm = CharacterFSM()
  enemy_fsm = CharacterFSM()
  
  # Add nodes (entities) with their state machines
  csm.add_node("player", player_fsm)
  csm.add_node("enemy", enemy_fsm)
  
  # Add edges based on states. Edge from player to enemy when player is chasing.
  csm.add_edge("player", "enemy", condition_state_id=CharacterState.CHASING.value)
  
  player_fsm.set_state(CharacterState.CHASING)
  # Get neighbors of player when player is in CHASIING state
  neighbors = csm.get_neighbors("player") 
  print(f"Player\'s neighbors when chasing: {neighbors}") # Output: Player's neighbors when chasing: ['enemy']
  
  player_fsm.set_state(CharacterState.IDLE)
  neighbors = csm.get_neighbors("player")
  print(f"Player\'s neighbors when idle: {neighbors}") # Output: Player's neighbors when idle: []
  

• Data Locality: Optimizes performance by organizing data in memory to take advantage of CPU caching.

  from gamepp.patterns.data_locality import ParticleSystem
  
  # Using Structure of Arrays (SoA) for better cache performance
  particle_system = ParticleSystem(max_particles=1000)
  particle_system.add_particle(pos_x=0, pos_y=0, vel_x=1, vel_y=1)
  particle_system.add_particle(pos_x=10, pos_y=10, vel_x=-1, vel_y=-1)
  
  print(f"Active particles before update: {particle_system.num_active_particles}")
  # Output: Active particles before update: 2 (or the number added)
  
  # This update will iterate over contiguous blocks of memory for positions and velocities
  particle_system.update(dt=0.1) 
  
  # Example of accessing data (less common to do this individually in practice)
  # print(f"Particle 0 position after update: ({particle_system.positions_x[0]}, {particle_system.positions_y[0]})")
  # This would print the updated position of the first active particle.
  

• Dirty Flag: Reduces the overhead of updating objects by tracking whether their state has changed and only reprocessing them if necessary.

  from gamepp.patterns.dirty_flag import GameObject
  
  root = GameObject(0, 0, "root")
  child = GameObject(10, 5, "child", parent=root)
  
  # Initially, representation is dirty and needs computation
  print(child.get_representation()) 
  # Output: Getting representation for child. Dirty: True
  # Output: Recomputed representation for child
  # Output: Object 'child' at world (10.00, 5.00), local (10.00, 5.00)
  
  # Accessing again without changes uses cached version
  print(child.get_representation())
  # Output: Getting representation for child. Dirty: False
  # Output: Object 'child' at world (10.00, 5.00), local (10.00, 5.00)
  
  child.local_x = 15 # This marks the transform and representation as dirty
  print(child.get_representation())
  # Output: Getting representation for child. Dirty: True
  # Output: Recomputed representation for child
  # Output: Object 'child' at world (15.00, 5.00), local (15.00, 5.00)
  

• Double Buffer: Prevents tearing and provides smoother animation by drawing to an off-screen buffer and then swapping it with the visible buffer.

  from gamepp.patterns.double_buffer import DoubleBuffer, Buffer
  
  # Create two buffers (e.g., for screen pixels or game states)
  buffer1 = Buffer(size=5) # Represents a simple buffer of size 5
  buffer2 = Buffer(size=5)
  double_buffer = DoubleBuffer(buffer1, buffer2)
  
  # Draw to the back buffer
  back_buf = double_buffer.get_back_buffer()
  for i in range(back_buf.get_size()):
      back_buf.set_data(i, i * 10) # Simulate drawing pixel data
  print(f"Back buffer before swap: {back_buf.get_all_data()}")
  # Output: Back buffer before swap: [0, 10, 20, 30, 40]
  
  double_buffer.swap()
  print(f"Front buffer after swap: {double_buffer.get_front_buffer().get_all_data()}")
  # Output: Front buffer after swap: [0, 10, 20, 30, 40]
  
  # Now the old front buffer is the new back buffer, ready for next frame's drawing
  new_back_buf = double_buffer.get_back_buffer()
  print(f"New back buffer data (should be old front buffer\'s initial state): {new_back_buf.get_all_data()}")
  # Output: New back buffer data (should be old front buffer's initial state): [0, 0, 0, 0, 0] (if Buffer initializes with 0s)
  

• Event Queue: Decouples event producers and consumers by using a central queue to manage events.

  from gamepp.patterns.event_queue import Event, EventQueue, global_event_queue
  
  # Define some event types
  class PlayerJumpEvent(Event):
      def __init__(self, player_id):
          self.player_id = player_id
      def __str__(self):
          return f"PlayerJumpEvent for player {self.player_id}"
  
  class EnemyDefeatedEvent(Event):
      def __init__(self, enemy_id, points):
          self.enemy_id = enemy_id
          self.points = points
      def __str__(self):
          return f"EnemyDefeatedEvent: {self.enemy_id} defeated, {self.points} points"
  
  # Using the global event queue (or you can instantiate EventQueue())
  # Producers add events
  global_event_queue.post(PlayerJumpEvent(player_id="player1"))
  global_event_queue.post(EnemyDefeatedEvent(enemy_id="goblin_A", points=100))
  
  # Consumers process events
  while not global_event_queue.is_empty():
      event = global_event_queue.get()
      if isinstance(event, PlayerJumpEvent):
          print(f"SoundSystem: Playing jump sound for {event.player_id}")
      elif isinstance(event, EnemyDefeatedEvent):
          print(f"ScoreSystem: Adding {event.points} for defeating {event.enemy_id}")
  # Output:
  # SoundSystem: Playing jump sound for player1
  # ScoreSystem: Adding 100 for defeating goblin_A
  

• Flyweight: Minimizes memory usage by sharing common data between multiple objects.

  from gamepp.patterns.flyweight import FlyweightFactory, TreeType
  
  factory = FlyweightFactory()
  
  # Create or get flyweight objects for tree types
  oak_type = factory.get_flyweight("Oak", "Green", "Rough")
  pine_type = factory.get_flyweight("Pine", "DarkGreen", "Needles")
  another_oak_type = factory.get_flyweight("Oak", "Green", "Rough")
  
  print(f"Oak Type ID: {id(oak_type)}")
  # Output: Oak Type ID: <some_id>
  print(f"Another Oak Type ID: {id(another_oak_type)}") # Should be the same ID as oak_type
  # Output: Another Oak Type ID: <some_id> 
  print(f"Pine Type ID: {id(pine_type)}")
  # Output: Pine Type ID: <another_id>
  
  # These objects represent the shared (intrinsic) state of trees.
  # Extrinsic state (e.g., position) would be stored elsewhere.
  class Tree:
      def __init__(self, x, y, tree_type: TreeType):
          self.x = x
          self.y = y
          self.tree_type = tree_type # This is the flyweight
  
      def display(self):
          print(f"Tree at ({self.x},{self.y}) - Type: {self.tree_type.name}, Color: {self.tree_type.color}, Texture: {self.tree_type.texture}")
  
  tree1 = Tree(10, 20, oak_type)
  tree2 = Tree(15, 30, pine_type)
  tree3 = Tree(25, 35, oak_type) # Reuses the oak_type flyweight
  
  tree1.display()
  tree2.display()
  tree3.display()
  # Output:
  # Tree at (10,20) - Type: Oak, Color: Green, Texture: Rough
  # Tree at (15,30) - Type: Pine, Color: DarkGreen, Texture: Needles
  # Tree at (25,35) - Type: Oak, Color: Green, Texture: Rough
  
  print(f"Number of distinct flyweights created: {factory.get_flyweight_count()}")
  # Output: Number of distinct flyweights created: 2
  

• Finite State Machine (FSM): Represents an object's behavior as a set of states and transitions between those states.

  from gamepp.patterns.fsm import State, StateMachine
  
  # Define states
  class IdleState(State):
      def enter(self, entity): print(f"{entity} enters Idle state.")
      def update(self, entity): print(f"{entity} is idling.")
      def exit(self, entity): print(f"{entity} exits Idle state.")
  
  class WalkingState(State):
      def enter(self, entity): print(f"{entity} enters Walking state.")
      def update(self, entity): print(f"{entity} is walking.")
      def exit(self, entity): print(f"{entity} exits Walking state.")
  
  # Create a state machine and add states
  fsm = StateMachine(entity_name="Player")
  fsm.add_state("idle", IdleState())
  fsm.add_state("walking", WalkingState())
  
  fsm.set_state("idle") # Output: Player enters Idle state.
  fsm.update()          # Output: Player is idling.
  fsm.set_state("walking") # Output: Player exits Idle state. Player enters Walking state.
  fsm.update()          # Output: Player is walking.
  

• Game Loop: Provides the central control structure for a game, processing input, updating game state, and rendering graphics.

  from gamepp.patterns.game_loop import GameLoop
  import time
  
  class MyGame(GameLoop):
      def __init__(self):
          super().__init__(target_fps=1) # Low FPS for demo
          self.frames = 0
  
      def process_input(self):
          print("Processing input...")
          pass
  
      def update(self, dt):
          print(f"Updating game state with dt: {dt:.4f}s")
          self.frames += 1
          if self.frames >= 3: # Run for a few frames then stop for demo
              self.stop()
  
      def render(self):
          print(f"Rendering frame {self.frames}")
  
  game = MyGame()
  print("Starting game loop...")
  game.run() 
  print("Game loop stopped.")
  # Output (will run quickly, showing ~3 frames):
  # Starting game loop...
  # Processing input...
  # Updating game state with dt: 1.0000s (approx)
  # Rendering frame 1
  # Processing input...
  # Updating game state with dt: 1.0000s (approx)
  # Rendering frame 2
  # Processing input...
  # Updating game state with dt: 1.0000s (approx)
  # Rendering frame 3
  # Game loop stopped.
  

• Hierarchical State Machine (HSM): Extends FSMs by allowing states to be nested, creating a hierarchy of behaviors.

  from gamepp.patterns.hsm import HState, HStateMachine
  
  class EventLogger: # Helper to see event flow
      def __init__(self): self.log = []
      def add(self, msg): self.log.append(msg)
      def print_log(self): print("\\n".join(self.log))
  
  logger = EventLogger()
  
  class BaseTestHState(HState):
      def __init__(self, name): super().__init__(); self.name = name
      def on_enter(self, machine): logger.add(f"{self.name}:on_enter")
      def on_update(self, machine, dt): logger.add(f"{self.name}:on_update") # machine is context (logger here)
      def on_exit(self, machine): logger.add(f"{self.name}:on_exit")
  
  class ParentState(BaseTestHState): pass
  class ChildState(BaseTestHState): pass
  
  hsm = HStateMachine(logger) # Pass logger or any context
  parent = ParentState("Parent")
  child = ChildState("Child")
  
  hsm.add_state("parent", parent)
  hsm.add_state("child", child, parent_name="parent") # child is substate of parent
  
  hsm.set_initial_state("parent")
  hsm.set_initial_state("child", parent_name="parent") # Set initial substate for parent
  
  hsm.start() 
  
  hsm.update(0.1)
  
  hsm.change_state("parent") 
  
  logger.print_log()
  # Expected output:
  # Parent:on_enter
  # Child:on_enter
  # Parent:on_update
  # Child:on_update
  # Child:on_exit
  

• Interpreter: Defines a grammatical representation for a language and provides an interpreter to deal with this grammar.

  from gamepp.patterns.interpreter import (
      Expression, 
      NumberExpression, 
      AddExpression, 
      SubtractExpression,
      MultiplyExpression,
      DivideExpression
  )
  
  # Represent " (5 + 10) * 2 - 30 / 3 "
  # AST: Subtract(Multiply(Add(Number(5), Number(10)), Number(2)), Divide(Number(30), Number(3)))
  
  expr = SubtractExpression(
      MultiplyExpression(
          AddExpression(NumberExpression(5), NumberExpression(10)), 
          NumberExpression(2)
      ),
      DivideExpression(NumberExpression(30), NumberExpression(3))
  )
  
  result = expr.interpret()
  print(f"Interpreter result: {result}") # Output: Interpreter result: 20.0
  
  try:
      error_expr = DivideExpression(NumberExpression(5), NumberExpression(0))
      error_expr.interpret()
  except ValueError as e:
      print(f"Error: {e}") # Output: Error: Cannot divide by zero.
  

• Object Pool: Improves performance by reusing objects instead of creating and destroying them repeatedly.

  from gamepp.patterns.object_pool import ObjectPool, PooledObject
  
  class Bullet(PooledObject):
      _id_counter = 0 # Class variable to ensure unique IDs for new bullets
  
      def __init__(self, pool_index: int): # pool_index is passed by the pool
          super().__init__()
          self.id_num = Bullet._id_counter
          Bullet._id_counter +=1
          self.pool_assigned_index = pool_index # Store the index given by pool for debug
          self.x = 0
          self.y = 0
          print(f"Bullet {self.id_num} (pool_idx:{self.pool_assigned_index}) created/re-initialized.")
  
      def reset(self): # Called when released back to pool
          super().reset()
          self.x = -1000 
          self.y = -1000
          # id_num remains to track the original bullet concept
          print(f"Bullet {self.id_num} (pool_idx:{self.pool_assigned_index}) reset and returned to pool.")
  
      def fire(self, x, y):\
          self.x = x
          self.y = y
          print(f"Bullet {self.id_num} (pool_idx:{self.pool_assigned_index}) fired to ({self.x}, {self.y})")
  
  # Create a pool of 2 bullets. The lambda provides the pool index to the constructor.
  bullet_pool = ObjectPool(Bullet, pool_size=2, object_init_args=(lambda i: i,))
  
  print(f"Available objects in pool: {bullet_pool.get_available_count()}")
  
  b1 = bullet_pool.acquire()
  if b1: b1.fire(10, 20)
  
  b2 = bullet_pool.acquire()
  if b2: b2.fire(15, 25)
  
  b_extra = bullet_pool.acquire() # Try to acquire more than available
  if not b_extra:
      print("Could not acquire third bullet, pool is empty.")
  
  if b1: bullet_pool.release(b1)
  print(f"Available objects in pool after releasing b1: {bullet_pool.get_available_count()}")
  
  b3 = bullet_pool.acquire() # Should reuse the one that was b1
  if b3: b3.fire(30,40) 
  
  print(f"Is b1 the same object as b3? {b1 is b3}") # True, object is reused
  
  # Expected Output:
  # Available objects in pool: 0 (Pool initializes objects, making them unavailable until reset by constructor)
  # Bullet 0 (pool_idx:0) created/re-initialized.
  # Bullet 1 (pool_idx:1) created/re-initialized.
  # Available objects in pool: 2 
  # Bullet 0 (pool_idx:0) fired to (10, 20)
  # Bullet 1 (pool_idx:1) fired to (15, 25)
  # Could not acquire third bullet, pool is empty.
  # Bullet 0 (pool_idx:0) reset and returned to pool.
  # Available objects in pool after releasing b1: 1
  # Bullet 0 (pool_idx:0) fired to (30,40)
  # Is b1 the same object as b3? True
  

• Observer: Defines a one-to-many dependency between objects so that when one object changes state, all its dependents are notified and updated automatically.

  from gamepp.patterns.observer import Subject, ObserverMixin
  
  class Player(Subject): 
      def __init__(self, name):
          super().__init__()
          self.name = name
          self._health = 100
  
      @property
      def health(self): return self._health
      
      @health.setter
      def health(self, value):
          old_health = self._health
          if self._health != value:
              self._health = value
              self.notify(event="health_changed", old_health=old_health, new_health=self._health)
  
  class HealthDisplay(ObserverMixin): 
      def update(self, subject, event, **kwargs):
          if event == "health_changed":
              print(f"HealthDisplay: Player {subject.name}'s health changed from {kwargs['old_health']} to {kwargs['new_health']}")
  
  class AchievementSystem(ObserverMixin):
      def update(self, subject, event, **kwargs):
          if event == "health_changed" and kwargs['new_health'] <= 0 and kwargs['old_health'] > 0:
              print(f"AchievementSystem: Player {subject.name} has been defeated! Achievement unlocked.")
  
  player = Player("Hero")
  health_bar = HealthDisplay()
  achievements = AchievementSystem()
  
  player.attach(health_bar)
  player.attach(achievements)
  
  player.health = 80
  player.health = 50
  player.health = 0
  player.health = -10 # To show it only triggers achievement once
  player.health = 50 # Bring back to life, no achievement
  
  # Expected Output:
  # HealthDisplay: Player Hero's health changed from 100 to 80
  # HealthDisplay: Player Hero's health changed from 80 to 50
  # HealthDisplay: Player Hero's health changed from 50 to 0
  # AchievementSystem: Player Hero has been defeated! Achievement unlocked.
  # HealthDisplay: Player Hero's health changed from 0 to -10
  # HealthDisplay: Player Hero's health changed from -10 to 50
  

• Pushdown Automaton (PDA): An extension of finite state machines that includes a stack, allowing for more complex state management or parsing.

  from gamepp.patterns.pda import PushdownAutomata, PDAState
  from typing import Any
  
  # --- Define States for a simple menu system ---
  class BaseMenuState(PDAState):
      def __init__(self, name: str):
          self.name = name
      def enter(self, pda: PushdownAutomata):
          print(f"Entering {self.name} State")
      def exit(self, pda: PushdownAutomata):
          print(f"Exiting {self.name} State")
      def handle_input(self, pda: PushdownAutomata, input_data: Any):
          print(f"{self.name} received input: {input_data}")
          if input_data == "back":
              pda.pop_state()
  
  class MainMenuState(BaseMenuState):
      def __init__(self):
          super().__init__("MainMenu")
      def handle_input(self, pda: PushdownAutomata, input_data: Any):
          super().handle_input(pda, input_data)
          if input_data == "options":
              pda.push_state(OptionsMenuState())
          elif input_data == "play":
              pda.push_state(PlayingGameState())
  
  class OptionsMenuState(BaseMenuState):
      def __init__(self):
          super().__init__("OptionsMenu")
      def handle_input(self, pda: PushdownAutomata, input_data: Any):
          super().handle_input(pda, input_data)
          if input_data == "sound":
              pda.push_state(SoundOptionsState())
  
  class SoundOptionsState(BaseMenuState):
      def __init__(self):
          super().__init__("SoundOptions")
  
  class PlayingGameState(BaseMenuState):
      def __init__(self):
          super().__init__("PlayingGame")
      def handle_input(self, pda: PushdownAutomata, input_data: Any):
          super().handle_input(pda, input_data)
          if input_data == "pause":
              pda.push_state(PauseMenuState())
  
  class PauseMenuState(BaseMenuState):
      def __init__(self):
          super().__init__("PauseMenu")
      def handle_input(self, pda: PushdownAutomata, input_data: Any):
          super().handle_input(pda, input_data)
          if input_data == "resume": # This will pop PauseMenu
              pda.pop_state() 
          elif input_data == "main_menu": # Pop until back to main or specific state
              # For simplicity, pop twice if we know Pause is on top of Playing
              pda.pop_state() # Pop Pause
              pda.pop_state() # Pop PlayingGame
  
  # --- PDA Usage ---
  pda_system = PushdownAutomata(MainMenuState())
  
  inputs = ["options", "sound", "back", "play", "pause", "resume", "pause", "main_menu", "invalid_input"]
  
  for inp in inputs:
      print(f"--- PDA Stack Depth: {pda_system.stack_depth}, Current: {pda_system.current_state.name if pda_system.current_state else 'None'} ---")
      pda_system.handle_input(inp)
      if pda_system.stack_depth == 0:
          print("PDA stack is empty, stopping.")
          break
  
  # Expected Output (simplified):
  # --- PDA Stack Depth: 1, Current: MainMenu ---
  # Entering MainMenu State
  # MainMenu received input: options
  # Entering OptionsMenu State
  # --- PDA Stack Depth: 2, Current: OptionsMenu ---
  # OptionsMenu received input: sound
  # Entering SoundOptions State
  # --- PDA Stack Depth: 3, Current: SoundOptions ---
  # SoundOptions received input: back
  # Exiting SoundOptions State
  # --- PDA Stack Depth: 2, Current: OptionsMenu ---
  # OptionsMenu received input: play  (Error in logic here, Options doesn't handle 'play')
  # (Corrected logic would be 'back' then 'play' from MainMenu)
  # Let's assume 'back' from OptionsMenu, then 'play' from MainMenu
  # Exiting OptionsMenu State
  # --- PDA Stack Depth: 1, Current: MainMenu ---
  # MainMenu received input: play
  # Entering PlayingGame State
  # --- PDA Stack Depth: 2, Current: PlayingGame ---
  # PlayingGame received input: pause
  # Entering PauseMenu State
  # --- PDA Stack Depth: 3, Current: PauseMenu ---
  # PauseMenu received input: resume
  # Exiting PauseMenu State
  # --- PDA Stack Depth: 2, Current: PlayingGame ---
  # PlayingGame received input: pause
  # Entering PauseMenu State
  # --- PDA Stack Depth: 3, Current: PauseMenu ---
  # PauseMenu received input: main_menu
  # Exiting PauseMenu State
  # Exiting PlayingGame State
  # --- PDA Stack Depth: 1, Current: MainMenu ---
  # MainMenu received input: invalid_input
  

• Prototype: Creates new objects by copying an existing object, known as the prototype.

  from gamepp.patterns.prototype import Prototype
  import copy
  
  class Monster(Prototype):
      def __init__(self, name, health, attack):
          self.name = name
          self.health = health
          self.attack = attack
          self.abilities = [] # Complex object
  
      def clone(self):
          # Use deepcopy for a true independent clone if attributes are mutable
          cloned_obj = copy.deepcopy(self)
          return cloned_obj
          
      def __str__(self):
          return f"{self.name} - HP: {self.health}, ATK: {self.attack}, Abilities: {self.abilities}"
  
  goblin_prototype = Monster("Goblin", 50, 5)
  goblin_prototype.abilities.append("Sneak")
  
  # Create new monsters by cloning the prototype
  goblin1 = goblin_prototype.clone()
  goblin1.name = "Goblin Warrior" # Customize the clone
  goblin1.health = 60
  goblin1.abilities.append("Shield Bash")
  
  
  goblin2 = goblin_prototype.clone()
  goblin2.name = "Goblin Archer"
  goblin2.attack = 7
  
  print(goblin_prototype) # Output: Goblin - HP: 50, ATK: 5, Abilities: ['Sneak']
  print(goblin1)          # Output: Goblin Warrior - HP: 60, ATK: 5, Abilities: ['Sneak', 'Shield Bash']
  print(goblin2)          # Output: Goblin Archer - HP: 50, ATK: 7, Abilities: ['Sneak']
  # Note: goblin_prototype.abilities was also changed by goblin1 if not deepcopied correctly.
  # The provided Prototype class in gamepp might handle this.
  

• Service Locator: Provides a global point of access for services, decoupling clients from concrete service implementations.

  from gamepp.patterns.service_locator import ServiceLocator, NullService, get_service, register_service
  
  # Define a service interface (optional, but good practice)
  class IAudio:
      def play_sound(self, sound_id): pass
      def stop_sound(self, sound_id): pass
  
  # Concrete service implementation
  class AudioSystem(IAudio):
      def play_sound(self, sound_id): print(f"AudioSystem: Playing sound {sound_id}")
      def stop_sound(self, sound_id): print(f"AudioSystem: Stopping sound {sound_id}")
  
  # Null service (for when the real service isn't available)
  class NullAudio(NullService, IAudio): # Inherits from NullService
      def play_sound(self, sound_id): print("NullAudio: (No sound played)")
      def stop_sound(self, sound_id): print("NullAudio: (No sound stopped)")
  
  # Register the service (typically at app startup)
  # ServiceLocator.register("audio", AudioSystem()) # Direct instantiation
  # Or using the helper functions:
  register_service("audio", AudioSystem(), IAudio) # Register with interface type
  
  # Client code gets the service
  # audio_service = ServiceLocator.get("audio")
  # Or using the helper function with type hinting:
  audio_service = get_service(IAudio) # Type hint helps IDEs and static analysis
  
  if audio_service:
      audio_service.play_sound("jump.wav") # Output: AudioSystem: Playing sound jump.wav
  
  # Example with NullService if real one wasn't registered for "audio_fx"
  register_service("audio_fx", NullAudio(), IAudio) # Register a null service
  fx_service = get_service(IAudio, service_name="audio_fx")
  if fx_service:
      fx_service.play_sound("explosion.wav") # Output: NullAudio: (No sound played)
  

• Singleton: Ensures that a class has only one instance and provides a global point of access to it.

  from gamepp.patterns.singleton import Singleton
  
  class GameManager(Singleton):
      def __init__(self):
          # Ensure init is called only once by Singleton's logic
          if hasattr(self, '_initialized') and self._initialized:
              return
          print("GameManager initialized.")
          self.score = 0
          self._initialized = True
  
      def add_score(self, points):
          self.score += points
          print(f"Score is now: {self.score}")
  
  # Get the singleton instance
  gm1 = GameManager.instance() # Output: GameManager initialized. (only first time)
  gm1.add_score(10)            # Output: Score is now: 10
  
  gm2 = GameManager.instance() # Does not re-initialize
  gm2.add_score(20)            # Output: Score is now: 30 (operates on the same instance)
  
  print(f"Are gm1 and gm2 the same object? {gm1 is gm2}") # Output: True
  

• Spatial Partition: Divides the game world into smaller regions to optimize collision detection and other spatial queries.

  from gamepp.patterns.spatial_partition import GridPartition, SpatialObject
  import math
  
  # Simple entity that will use SpatialObject for grid management
  class GameEntity:
      def __init__(self, entity_id: str, x: float, y: float):
          self.entity_id = entity_id
          # The SpatialObject holds the representation for the grid
          self.spatial_repr = SpatialObject(entity_id, x, y)
  
      def move(self, dx: float, dy: float, grid: GridPartition):
          new_x = self.spatial_repr.position[0] + dx
          new_y = self.spatial_repr.position[1] + dy
          grid.update_object_position(self.spatial_repr, new_x, new_y)
          print(f"Entity {self.entity_id} moved to ({new_x:.1f}, {new_y:.1f})")
  
      @property
      def position(self):
          return self.spatial_repr.position
  
  # Initialize grid
  world_width, world_height = 200, 200
  cell_size = 50
  grid = GridPartition(cell_size, world_width, world_height)
  
  # Create entities
  entity1 = GameEntity("player", 20, 20)
  entity2 = GameEntity("enemyA", 30, 30)
  entity3 = GameEntity("enemyB", 180, 180) # In a different part of the grid
  entity4 = GameEntity("item", 25, 70)    # Near player and enemyA
  
  grid.add_object(entity1.spatial_repr)
  grid.add_object(entity2.spatial_repr)
  grid.add_object(entity3.spatial_repr)
  grid.add_object(entity4.spatial_repr)
  
  print("Initial state:")
  for y_idx, row in enumerate(grid.grid):
      for x_idx, cell in enumerate(row):
          if cell:
              print(f"Cell ({x_idx},{y_idx}): {[obj.obj_id for obj in cell]}")
  
  # Query for objects near player (entity1)
  # The query_nearby in the provided spatial_partition.py is not fully implemented
  # So we'll manually check the player's cell and neighbors for this example
  
  def get_objects_in_cell_and_neighbors(target_obj_spatial: SpatialObject, grid_partition: GridPartition):
      results = set()
      tx, ty = grid_partition._get_cell_coords(target_obj_spatial.position)
      for r_offset in range(-1, 2): # -1, 0, 1
          for c_offset in range(-1, 2):
              cell_y, cell_x = ty + r_offset, tx + c_offset
              if 0 <= cell_y < grid_partition.grid_height and 0 <= cell_x < grid_partition.grid_width:
                  results.update(grid_partition.grid[cell_y][cell_x])
      return [obj for obj in results if obj is not target_obj_spatial]
  
  print(f"\\nQuerying near {entity1.entity_id} at {entity1.position}:")
  nearby_to_e1 = get_objects_in_cell_and_neighbors(entity1.spatial_repr, grid)
  print(f"Found: {[obj.obj_id for obj in nearby_to_e1]}")
  # Expected: enemyA, item (depending on cell boundaries)
  
  # Move player
  entity1.move(40, 40, grid) # Move player to (60,60) - likely a new cell
  
  print("\\nState after player moves:")
  for y_idx, row in enumerate(grid.grid):
      for x_idx, cell in enumerate(row):
          if cell:
              print(f"Cell ({x_idx},{y_idx}): {[obj.obj_id for obj in cell]}")
  
  print(f"\\nQuerying near {entity1.entity_id} at {entity1.position} after move:")
  nearby_to_e1_moved = get_objects_in_cell_and_neighbors(entity1.spatial_repr, grid)
  print(f"Found: {[obj.obj_id for obj in nearby_to_e1_moved]}")
  # Expected: item (enemyA might be out of direct neighbor cells now)
  
  # Expected Output (structure, actual cell content depends on exact coords & cell_size):
  # Initial state:
  # Cell (0,0): ['player', 'enemyA']
  # Cell (0,1): ['item']
  # Cell (3,3): ['enemyB']
  #
  # Querying near player at (20.0, 20.0):
  # Found: ['enemyA', 'item'] (or similar, based on neighborhood)
  # Entity player moved to (60.0, 60.0)
  #
  # State after player moves:
  # Cell (0,0): ['enemyA']
  # Cell (0,1): ['item'] 
  # Cell (1,1): ['player'] 
  # Cell (3,3): ['enemyB']
  #
  # Querying near player at (60.0, 60.0) after move:
  # Found: ['item'] (or similar)
  

• Type Object: Allows you to create new classes by defining their behavior and properties through a type object.

  from gamepp.patterns.type_object import Breed, Monster
  
  # Define breed types (Type Objects)
  goblin_breed = Breed(name="Goblin", health=30, attack_damage=5, sound="Goblin grunt")
  dragon_breed = Breed(name="Dragon", health=500, attack_damage=40, sound="Dragon roar")
  
  # Create monster instances using these breeds
  monster1 = goblin_breed.new_monster() # Creates a Monster instance
  monster1.name_instance = "Grizlak the Goblin" # Instance-specific data
  
  monster2 = dragon_breed.new_monster()
  monster2.name_instance = "Ignis the Red"
  
  monster3 = goblin_breed.new_monster() # Another goblin, shares breed properties
  
  print(f"{monster1.name_instance} ({monster1.get_breed().name}) attacks for {monster1.get_attack_damage()} damage.")
  # Output: Grizlak the Goblin (Goblin) attacks for 5 damage.
  monster1.make_sound() # Output: Goblin grunt
  
  print(f"{monster2.name_instance} ({monster2.get_breed().name}) has {monster2.get_health()} HP.")
  # Output: Ignis the Red (Dragon) has 500 HP.
  monster2.make_sound() # Output: Dragon roar
  
  print(f"Monster 3 is a {monster3.get_breed().name}")
  # Output: Monster 3 is a Goblin
  

• Update Method: Provides a simple way to update game objects by calling an update method on each object during each frame of the game loop.

  from gamepp.patterns.update_method import UpdateMethodManager, Entity as UpdateableEntity
  
  class Player(UpdateableEntity):
      def __init__(self, name):
          super().__init__()
          self.name = name
          self.position = 0
      
      def update(self, dt): # dt is delta time
          self.position += 1 * dt # Move one unit per second
          print(f"Player {self.name} updated. Position: {self.position:.2f}")
  
  class Enemy(UpdateableEntity):
      def __init__(self, name):
          super().__init__()
          self.name = name
          self.energy = 100
  
      def update(self, dt):
          self.energy -= 5 * dt # Lose energy over time
          print(f"Enemy {self.name} updated. Energy: {self.energy:.2f}")
  
  manager = UpdateMethodManager()
  player1 = Player("Hero")
  enemy1 = Enemy("Goblin")
  
  manager.add_entity(player1)
  manager.add_entity(enemy1)
  
  print("--- First update call ---")
  manager.update_all(dt=0.1) 
  # Output:
  # Player Hero updated. Position: 0.10
  # Enemy Goblin updated. Energy: 99.50
  
  print("\\n--- Second update call ---")
  manager.update_all(dt=0.5)
  # Output:
  # Player Hero updated. Position: 0.60 (0.1 + 0.5)
  # Enemy Goblin updated. Energy: 97.00 (99.5 - 2.5)
  
  manager.remove_entity(enemy1)
  print("\\n--- Third update call (enemy removed) ---")
  manager.update_all(dt=0.1)
  # Output:
  # Player Hero updated. Position: 0.70 
  

Contributing

Contributions are welcome! Please feel free to submit a pull request or open an issue for any suggestions or improvements.

License

This project is licensed under the MIT License. See the LICENSE file for more details.