import math
import statistics


class SecureAggregator:
    @staticmethod
    def aggregate(local_results: list) -> dict:
        # local_results: list of dicts with numeric values
        if not local_results:
            return {}
        # collect all metric keys
        keys = set()
        for d in local_results:
            keys.update(d.keys())

        aggregated = {}
        for k in keys:
            values = [d[k] for d in local_results if k in d and isinstance(d[k], (int, float))]
            if not values:
                continue
            n = len(values)
            mean = sum(values) / n
            if n < 2:
                ci_lower = ci_upper = mean
            else:
                std = statistics.pstdev(values)
                se = std / math.sqrt(n)
                margin = 1.96 * se
                ci_lower = mean - margin
                ci_upper = mean + margin
            aggregated[k] = {"mean": mean, "ci_lower": ci_lower, "ci_upper": ci_upper}
        return aggregated