"""
SelfEvaluationFramework
Generated by Eden via recursive self-improvement
2025-11-01 19:37:14.328857
"""

class SelfEvaluationFramework:
    def __init__(self):
        self.metrics = {
            'productivity': [],
            'revenue': [],
            'market_research_efficiency': [],
            'customer_satisfaction': []
        }

    def add_metric(self, metric_name: str, value: float, timestamp: str) -> None:
        if metric_name in self.metrics:
            self.metrics[metric_name].append((value, timestamp))
        else:
            raise ValueError(f"Metric {metric_name} not recognized.")

    def calculate_average(self, metric_name: str) -> float:
        values = [val for val, _ in self.metrics[metric_name]]
        if len(values) == 0:
            return 0.0
        return sum(values) / len(values)

    def generate_report(self) -> dict:
        report = {
            'productivity': f"Average productivity: {self.calculate_average('productivity')}",
            'revenue': f"Total revenue over time: {sum(val for val, _ in self.metrics['revenue'])}",
            'market_research_efficiency': f"Average market research efficiency: {self.calculate_average('market_research_efficiency')}",
            'customer_satisfaction': f"Average customer satisfaction: {self.calculate_average('customer_satisfaction')}"
        }
        return report

# Example Usage
if __name__ == "__main__":
    self_eval = SelfEvaluationFramework()
    
    # Adding example metrics
    self_eval.add_metric('productivity', 90.0, "2023-10-01")
    self_eval.add_metric('revenue', 10000.0, "2023-10-01")
    self_eval.add_metric('market_research_efficiency', 85.0, "2023-10-01")
    self_eval.add_metric('customer_satisfaction', 4.5, "2023-10-01")

    report = self_eval.generate_report()
    
    for metric, value in report.items():
        print(f"{metric}: {value}")