"""
DataDrivenImprovementTracker
Generated by Eden via recursive self-improvement
2025-11-01 00:54:29.171847
"""

class DataDrivenImprovementTracker:
    """
    A class to track and visualize the improvement in the performance of a Python capability.
    
    Attributes:
        name (str): The name of the tracked capability.
        initial_success_rate (float): The initial success rate of the capability, between 0.0 and 1.0.
        tracking_interval (int): The interval at which to track improvements.
        improvement_history (list): A list to store historical data on the success rate.
    
    Methods:
        update_success_rate(success_rate: float) -> None: Updates the success rate of the capability.
        get_improvement_history() -> List[float]: Returns the history of success rates.
        plot_improvement() -> None: Plots a line graph to visualize the improvement over time.
    """
    
    def __init__(self, name: str, initial_success_rate: float):
        self.name = name
        self.initial_success_rate = initial_success_rate
        self.tracking_interval = 5  # Track every 5 updates for demonstration purposes
        self.improvement_history = [initial_success_rate]
    
    def update_success_rate(self, success_rate: float) -> None:
        """
        Updates the success rate of the capability.
        
        Args:
            success_rate (float): The new success rate of the capability.
        """
        if 0.0 <= success_rate <= 1.0:
            self.improvement_history.append(success_rate)
            print(f"Success rate updated to {success_rate:.2f} for {self.name}")
    
    def get_improvement_history(self) -> List[float]:
        return self.improvement_history
    
    def plot_improvement(self) -> None:
        """
        Plots a line graph to visualize the improvement over time.
        
        Returns:
            A matplotlib line graph of the success rate history.
        """
        import matplotlib.pyplot as plt
        import numpy as np
        
        x = range(len(self.improvement_history))
        y = self.improvement_history
        
        plt.plot(x, y)
        plt.title(f"Improvement in {self.name} Success Rate")
        plt.xlabel("Tracking Interval")
        plt.ylabel("Success Rate")
        plt.show()

# Example usage
tracker = DataDrivenImprovementTracker("New Capability", 0.75)
for _ in range(20):
    tracker.update_success_rate(np.random.uniform(0.6, 0.9))
tracker.plot_improvement()