"""Create reasoning_engine
Generated by Phi-Octopus Eden
2025-11-06 13:51:20.605830
"""

```python
from typing import List, Dict, Any


class ReasoningEngine:
    """
    A simple reasoning engine designed to solve problems with limited reasoning sophistication.
    It processes a set of rules and applies them to input data to derive conclusions.

    Args:
        rules: A list of dictionaries where each dictionary represents a rule in the format
               {"condition": condition, "action": action}.
        input_data: A dictionary representing the initial state or input data for reasoning.

    Example usage:

    rules = [
        {
            "condition": lambda x: x["temperature"] > 30 and x["humidity"] < 60,
            "action": lambda x: {**x, "status": "alert"}
        },
        {
            "condition": lambda x: x["temperature"] <= 25 or x["humidity"] >= 70,
            "action": lambda x: {**x, "status": "normal"}
        }
    ]

    input_data = {"temperature": 31, "humidity": 55}

    engine = ReasoningEngine(rules=rules, input_data=input_data)
    result = engine.reason()

    print(result)  # Output: {'temperature': 31, 'humidity': 55, 'status': 'alert'}
    """

    def __init__(self, rules: List[Dict[str, Any]], input_data: Dict[str, Any]):
        self.rules = rules
        self.input_data = input_data

    def reason(self) -> Dict[str, Any]:
        """
        Apply the reasoning process to derive a conclusion based on input data and predefined rules.

        Returns:
            A dictionary containing the updated state of the input data after applying the rules.
        """
        current_state = self.input_data.copy()
        for rule in self.rules:
            if rule["condition"](current_state):
                current_state.update(rule["action"](current_state))
        return current_state


# Example usage
if __name__ == "__main__":
    rules = [
        {
            "condition": lambda x: x["temperature"] > 30 and x["humidity"] < 60,
            "action": lambda x: {**x, "status": "alert"}
        },
        {
            "condition": lambda x: x["temperature"] <= 25 or x["humidity"] >= 70,
            "action": lambda x: {**x, "status": "normal"}
        }
    ]

    input_data = {"temperature": 31, "humidity": 55}
    engine = ReasoningEngine(rules=rules, input_data=input_data)
    result = engine.reason()
    print(result)  # Output: {'temperature': 31, 'humidity': 55, 'status': 'alert'}
```