"""Create recovery_planner
Generated by Phi-Octopus Eden
2025-11-06 03:35:09.960187
"""

```python
from typing import List, Dict


class RecoveryPlanner:
    """
    A class for creating a limited error recovery planner that attempts to recover from errors in a process.
    
    Attributes:
        max_retries (int): The maximum number of retries allowed before giving up on recovery.
        failure_tolerance (float): The tolerance level for failures. Lower values mean higher sensitivity to errors.
        retry_interval (int): The time interval between retries in seconds.

    Methods:
        plan_recovery: Plans a recovery process given a list of tasks and their error probabilities.
        execute_plan: Executes the planned recovery process, handling errors as they occur.
    """
    
    def __init__(self, max_retries: int = 3, failure_tolerance: float = 0.1, retry_interval: int = 5):
        self.max_retries = max_retries
        self.failure_tolerance = failure_tolerance
        self.retry_interval = retry_interval

    def plan_recovery(self, tasks: List[Dict[str, float]]) -> Dict[str, int]:
        """
        Plans a recovery process for given tasks with their error probabilities.

        Args:
            tasks (List[Dict[str, float]]): A list of dictionaries representing the tasks.
                                             Each dictionary should have 'task_name' and 'error_probability'.

        Returns:
            Dict[str, int]: A dictionary mapping each task name to the number of retries it will undergo.
        """
        recovery_plan = {task['task_name']: 0 for task in tasks}
        return recovery_plan

    def execute_plan(self, plan: Dict[str, int]) -> None:
        """
        Executes the planned recovery process and handles errors.

        Args:
            plan (Dict[str, int]): A dictionary mapping each task name to its current number of retries.
        """
        for _ in range(self.max_retries):
            for task_name, retries in plan.items():
                error_probability = self._get_error_probability(task_name)
                if error_probability > self.failure_tolerance and retries < self.max_retries:
                    print(f"Task '{task_name}' failed with {error_probability*100:.2f}% probability. Retrying...")
                    plan[task_name] += 1
                else:
                    print(f"Task '{task_name}' completed successfully or within retry limits.")
            import time
            time.sleep(self.retry_interval)
        if any(plan.values()):
            print("Failed to recover all tasks after maximum retries.")

    def _get_error_probability(self, task_name: str) -> float:
        """
        Mock method to simulate retrieval of error probability for a given task.

        Args:
            task_name (str): The name of the task.

        Returns:
            float: A simulated error probability.
        """
        # Simulated data
        return 0.15 if task_name == 'DatabaseSync' else 0.08


# Example usage
if __name__ == "__main__":
    recovery_planner = RecoveryPlanner(max_retries=3, failure_tolerance=0.2)
    tasks = [
        {'task_name': 'DataBackup', 'error_probability': 0.1},
        {'task_name': 'DatabaseSync', 'error_probability': 0.25}
    ]
    plan = recovery_planner.plan_recovery(tasks)
    print("Recovery Plan:", plan)
    recovery_planner.execute_plan(plan)
```