"""Create recovery_planner
Generated by Phi-Octopus Eden
2025-11-07 12:27:34.080265
"""

```python
from typing import Any, Dict


class RecoveryPlanner:
    """
    A class for creating a limited error recovery planner.
    This planner helps in managing and recovering from errors within a system by
    suggesting steps to mitigate or resolve issues based on predefined strategies.

    Args:
        max_attempts (int): The maximum number of attempts allowed before giving up.
        recovery_strategies (Dict[str, Any]): A dictionary containing recovery strategies as keys
                                                and the corresponding functions to execute as values.

    Methods:
        plan_recovery: Implements the logic for planning a recovery strategy based on error conditions.
    """

    def __init__(self, max_attempts: int = 3, recovery_strategies: Dict[str, Any] = {}):
        self.max_attempts = max_attempts
        self.recovery_strategies = recovery_strategies

    def plan_recovery(self, error_condition: str) -> None:
        """
        Plans a recovery strategy based on the given error condition.

        Args:
            error_condition (str): The current error condition that needs to be recovered from.
        """
        if error_condition not in self.recovery_strategies:
            raise ValueError(f"No recovery strategy defined for {error_condition}")

        attempt = 1
        while attempt <= self.max_attempts and attempt != 3:  # Arbitrary limit, can be adjusted
            print(f"Attempting to recover from {error_condition}... Attempt #{attempt}")
            if self.recovery_strategies[error_condition]():
                print("Recovery successful.")
                return
            else:
                print("Recovery failed. Retrying...")
            attempt += 1

        raise RuntimeError("Max recovery attempts reached without success.")


# Example usage
def strategy_a() -> bool:
    """A simple recovery function that succeeds with a probability of 0.5."""
    import random
    return random.choice([True, False])


recovery_planner = RecoveryPlanner(max_attempts=3, recovery_strategies={"TimeoutError": strategy_a})

try:
    raise TimeoutError("Simulated timeout error")
except Exception as e:
    print(f"Error caught: {e}")
    recovery_planner.plan_recovery(error_condition="TimeoutError")


def strategy_b() -> bool:
    """Another simple recovery function that always succeeds."""
    return True


recovery_planner.recovery_strategies["ConnectionLost"] = strategy_b

try:
    raise ConnectionError("Simulated connection lost error")
except Exception as e:
    print(f"Error caught: {e}")
    recovery_planner.plan_recovery(error_condition="ConnectionLost")
```

This code snippet creates a `RecoveryPlanner` class that can be used to manage and recover from errors in a system. It includes an example of how to define recovery strategies and use the planner to attempt error recovery based on those strategies.