"""Create reasoning_engine
Generated by Phi-Octopus Eden
2025-11-07 02:33:17.272065
"""

```python
from typing import Dict, List

class ReasoningEngine:
    """
    A basic reasoning engine that addresses limited reasoning sophistication.
    
    This class provides a simple mechanism to evaluate logical conditions based on input data,
    thus allowing for basic decision making and rule-based problem solving.
    """

    def __init__(self):
        self.rules = []

    def add_rule(self, condition: str, action: str) -> None:
        """
        Add a new rule to the reasoning engine.

        Args:
            condition (str): The logical condition that needs to be met.
            action (str): The action or decision to make if the condition is true.
        
        Example usage:
            >>> engine = ReasoningEngine()
            >>> engine.add_rule("temperature > 30", "turn_on_air_conditioner")
            >>> engine.add_rule("humidity < 40", "activate_humidifier")
        """
        self.rules.append({"condition": condition, "action": action})

    def evaluate(self, data: Dict[str, any]) -> List[str]:
        """
        Evaluate all rules against the provided data.

        Args:
            data (Dict[str, any]): A dictionary containing variable values to test conditions.

        Returns:
            List[str]: A list of actions that should be executed based on the evaluated rules.
        
        Example usage:
            >>> engine.evaluate({"temperature": 32, "humidity": 50})
            ['turn_on_air_conditioner']
        """
        actions_to_execute = []
        for rule in self.rules:
            if eval(rule["condition"], {}, data):
                actions_to_execute.append(rule["action"])
        return actions_to_execute

# Example usage
if __name__ == "__main__":
    engine = ReasoningEngine()
    engine.add_rule("temperature > 30", "turn_on_air_conditioner")
    engine.add_rule("humidity < 40", "activate_humidifier")
    
    data = {"temperature": 25, "humidity": 39}
    actions = engine.evaluate(data)
    print(actions)  # Should output: ['activate_humidifier']

    data = {"temperature": 31, "humidity": 40}
    actions = engine.evaluate(data)
    print(actions)  # Should output: ['turn_on_air_conditioner']
```