"""Create recovery_planner
Generated by Phi-Octopus Eden
2025-11-08 13:03:04.630831
"""

```python
from typing import List, Dict

class RecoveryPlanner:
    """A class for creating a limited error recovery planner.

    Attributes:
        max_attempts (int): The maximum number of attempts to recover.
        failure_rates (Dict[str, float]): A dictionary containing the failure rates for different tasks.

    Methods:
        plan_recovery: Plans and executes a recovery strategy based on the task's failure rate.
    """

    def __init__(self, max_attempts: int = 3):
        self.max_attempts = max_attempts
        self.failure_rates = {}

    def add_task_failure_rate(self, task_name: str, failure_rate: float) -> None:
        """Add or update a task's failure rate.

        Args:
            task_name (str): The name of the task.
            failure_rate (float): The probability of the task failing.
        """
        self.failure_rates[task_name] = failure_rate

    def plan_recovery(self, task_name: str) -> bool:
        """Plan and attempt recovery for a specific task.

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

        Returns:
            bool: True if successful in recovery, False otherwise.
        """
        for attempt in range(self.max_attempts):
            # Simulate task execution
            success = self._execute_task(task_name)
            if success:
                return True

            # Check if it's the last attempt and fail if so
            if attempt == self.max_attempts - 1:
                print(f"Failed to recover from {task_name} after {self.max_attempts} attempts.")
                return False
            else:
                print(f"{task_name} failed. Attempting recovery...")

    def _execute_task(self, task_name: str) -> bool:
        """Simulate the execution of a task.

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

        Returns:
            bool: True if the task was successful, False otherwise.
        """
        failure_rate = self.failure_rates.get(task_name)
        if failure_rate is None:
            raise ValueError(f"Failure rate for {task_name} not set.")
        
        # Simulate a random success or failure based on the failure rate
        import random
        return random.random() > failure_rate


# Example usage
if __name__ == "__main__":
    planner = RecoveryPlanner()
    planner.add_task_failure_rate("DataLoad", 0.1)
    planner.add_task_failure_rate("NetworkConnect", 0.05)
    
    print("Recovering from DataLoad task...")
    success_data_load = planner.plan_recovery("DataLoad")
    print(f"DataLoad recovery successful: {success_data_load}")
    
    print("\nRecovering from NetworkConnect task...")
    success_network_connect = planner.plan_recovery("NetworkConnect")
    print(f"NetworkConnect recovery successful: {success_network_connect}")

```

This Python code defines a class `RecoveryPlanner` with methods to add failure rates for tasks, plan recoveries, and simulate the execution of those tasks. The example usage demonstrates how you can use this class to manage limited error recovery scenarios.