"""Create reasoning_engine
Generated by Phi-Octopus Eden
2025-11-06 05:16:22.322344
"""

```python
from typing import List, Dict


class ReasoningEngine:
    """
    A basic reasoning engine that processes a set of rules and applies them to given data.
    
    This is intended to demonstrate addressing limited reasoning sophistication by providing clear,
    rule-based logic processing.
    """

    def __init__(self, rules: List[Dict[str, any]]):
        """
        Initialize the ReasoningEngine with predefined rules.

        :param rules: A list of dictionaries where each dictionary represents a rule
                      {'condition': (lambda function), 'action': (lambda function)}
        """
        self.rules = rules

    def apply_rules(self, data: Dict[str, any]) -> List[Dict[str, any]]:
        """
        Apply all applicable rules to the given data and return the updated data with actions applied.

        :param data: A dictionary representing the input data where keys are attributes and values are their states.
        :return: The same data dictionary but with actions from applicable rules applied.
        """
        results = [data]  # Start with original data
        for rule in self.rules:
            new_data = data.copy()
            condition, action = rule['condition'], rule['action']
            if condition(new_data):
                action(new_data)
            results.append(new_data)

        return results


# Example usage

def is_above_threshold(data: Dict[str, int]) -> bool:
    """
    Condition for checking if a value in 'quantity' attribute exceeds 10.
    
    :param data: Input data dictionary
    :return: Boolean indicating whether the condition is met.
    """
    return data.get('quantity', 0) > 10


def apply_discount(data: Dict[str, any]) -> None:
    """
    Action to apply a 20% discount if 'quantity' exceeds 10.

    :param data: Input data dictionary
    :return: None (applies changes in-place)
    """
    quantity = data.get('quantity', 0)
    if quantity > 10:
        price = data.setdefault('price', 1.0) * 0.8
        data['discounted_price'] = price


# Define some rules and apply them to the engine

rules = [
    {
        'condition': is_above_threshold,
        'action': apply_discount
    }
]

reasoning_engine = ReasoningEngine(rules)
input_data = {'quantity': 15, 'price': 2.5}
output = reasoning_engine.apply_rules(input_data)

for result in output:
    print(result)
```

This code snippet defines a basic `ReasoningEngine` class that applies predefined rules to input data. The example usage demonstrates how the engine can be used to apply simple logic like checking for a condition and performing an action based on it, such as applying a discount if a certain threshold is met.