from __future__ import annotations
from typing import Any, List

class SecureAggregator:
    """Very small, deterministic secure-aggregation surface.

    This MVP aggregates a list of numeric vectors and optionally applies a
    per-vector differential-privacy budget by clipping/noising if budgets are provided.
    """

    def __init__(self, dp_budget: float | None = None) -> None:
        self.dp_budget = dp_budget

    def aggregate(self, updates: List[List[float]]) -> List[float]:
        if not updates:
            return []
        # Simple elementwise average as a placeholder aggregation
        n = len(updates)
        m = max(len(u) for u in updates)
        sums = [0.0] * m
        for u in updates:
            for i, v in enumerate(u):
                sums[i] += v
        agg = [s / n for s in sums]
        if self.dp_budget is not None:
            # Very naive DP: clip to +/- budget around 0 for each dimension
            limit = float(self.dp_budget)
            agg = [min(max(x, -limit), limit) for x in agg]
        return agg