"""Create error_monitor
Generated by Phi-Octopus Eden
2025-11-06 20:34:57.159418
"""

```python
from typing import Any, Dict


class ErrorMonitor:
    """
    A class for monitoring and handling errors in a limited capacity.

    Attributes:
        max_retries (int): The maximum number of times to retry an operation.
        error_log (Dict[str, int]): A log to track the occurrence of each error.

    Methods:
        __init__: Initialize the ErrorMonitor with a specific number of retries.
        record_error: Log that an error has occurred and increase its count.
        handle_exception: Attempt to recover from exceptions up to max_retries.
    """

    def __init__(self, max_retries: int = 3):
        self.max_retries = max_retries
        self.error_log: Dict[str, int] = {}

    def record_error(self, error_message: str) -> None:
        """
        Record an error occurrence in the log.

        Args:
            error_message (str): A description of the error.
        """
        if error_message not in self.error_log:
            self.error_log[error_message] = 0
        self.error_log[error_message] += 1

    def handle_exception(self, func: Any) -> Any:
        """
        Decorator to wrap a function and attempt recovery from exceptions.

        Args:
            func (Any): The function to be wrapped for error handling.

        Returns:
            Any: The result of the function or None if max retries are exceeded.
        """

        def wrapper(*args, **kwargs):
            retry_count = 0
            while retry_count < self.max_retries:
                try:
                    return func(*args, **kwargs)
                except Exception as e:
                    self.record_error(str(e))
                    retry_count += 1
                    print(f"Error occurred: {e}, Attempt {retry_count} of {self.max_retries}")
            return None

        return wrapper


# Example Usage:

@ErrorMonitor().handle_exception
def risky_function(x: int, y: int) -> int:
    """
    A function that simulates potential errors during execution.

    Args:
        x (int): First integer.
        y (int): Second integer.

    Returns:
        int: The result of the operation or None if an error is not recoverable within max retries.
    """
    import random

    if random.random() < 0.5:
        raise ValueError("Operation failed due to a simulated issue")
    return x + y


if __name__ == "__main__":
    result = risky_function(10, 20)
    print(f"Result: {result}")
```

Note that in this example, the `risky_function` has a 50% chance of raising an exception. The `ErrorMonitor` class logs error occurrences and attempts to recover from exceptions up to a maximum number of retries specified during initialization.