from typing import Dict, Any, List from collections import defaultdict import json # For optional persistence class AdaptiveLearningEnvironment: """Creates environments for real-time learning and adaptation""" def __init__(self): # Use defaultdict for simpler logic self.environment_state = defaultdict(list) def update_environment(self, user_id: int, interaction: Dict[str, Any]) -> None: """ Update the environment based on user interactions. Args: user_id (int): The ID of the user. interaction (Dict[str, Any]): Details of the user interaction. """ if not isinstance(interaction, dict): raise ValueError("Interaction must be a dictionary.") # Append interaction to the user's state self.environment_state[user_id].append(interaction) def adapt_to_user(self, user_id: int) -> List[Dict[str, Any]]: """ Adapt the environment to the user's preferences and interactions. Args: user_id (int): The ID of the user. Returns: List[Dict[str, Any]]: The user's interaction history. """ return self.environment_state.get(user_id, []) def save_state(self, file_path: str) -> None: """ Save the environment state to a file (optional persistence). Args: file_path (str): The file path to save the state. """ with open(file_path, 'w') as file: json.dump(self.environment_state, file) def load_state(self, file_path: str) -> None: """ Load the environment state from a file. Args: file_path (str): The file path to load the state from. """ try: with open(file_path, 'r') as file: data = json.load(file) self.environment_state = defaultdict(list, data) except FileNotFoundError: print(f"File '{file_path}' not found. Starting with an empty state.") # Example usage if __name__ == "__main__": ale = AdaptiveLearningEnvironment() # Update environment with user interactions ale.update_environment(1, {"action": "click", "page": "homepage"})