"""v2 统计聚合器（V2Stats）—— token 计量与账单（纯标准库）。

T9：每请求 API token 记账；聚合快路径命中率、回合数分布、熔断次数、累计 token/成本。
配合 /metrics 对外透出（论文 E1 token 经济学数据来源之一）。
"""
from __future__ import annotations

import threading
from typing import Any, Dict, List, Optional


class V2Stats:
    """线程安全的 v2 运行统计。"""

    def __init__(self):
        self._lock = threading.Lock()
        self._total = 0
        self._fast_path = 0
        self._breach = 0
        self._by_status: Dict[str, int] = {}
        self._rounds: List[int] = []
        self._api_input_tokens = 0
        self._api_output_tokens = 0
        self._api_cost_usd = 0.0
        self._by_model: Dict[str, Dict[str, Any]] = {}
        self._recent: List[Dict[str, Any]] = []

    def record(self, result) -> None:
        """记录一次 PipelineResult。"""
        with self._lock:
            self._total += 1
            if getattr(result, "fast_path", False):
                self._fast_path += 1
            status = getattr(result, "status", "?")
            self._by_status[status] = self._by_status.get(status, 0) + 1
            self._rounds.append(getattr(result, "rounds_used", 0))
            if "breach" in " ".join(getattr(result, "route", [])):
                self._breach += 1
            self._api_input_tokens += getattr(result, "api_input_tokens", 0)
            self._api_output_tokens += getattr(result, "api_output_tokens", 0)
            self._api_cost_usd += getattr(result, "cost_est", 0.0)
            # 按模型分账（token / 成本 / 次数）
            model = getattr(result, "model_used", None) or "unknown"
            in_tok = getattr(result, "api_input_tokens", 0)
            out_tok = getattr(result, "api_output_tokens", 0)
            bucket = self._by_model.setdefault(model, {
                "requests": 0, "input_tokens": 0, "output_tokens": 0, "cost_est_usd": 0.0,
            })
            bucket["requests"] += 1
            bucket["input_tokens"] += in_tok
            bucket["output_tokens"] += out_tok
            bucket["cost_est_usd"] = round(bucket["cost_est_usd"] + getattr(result, "cost_est", 0.0), 6)
            self._recent.append({
                "request_id": getattr(result, "request_id", ""),
                "status": status,
                "fast_path": getattr(result, "fast_path", False),
                "api_input_tokens": getattr(result, "api_input_tokens", 0),
                "api_output_tokens": getattr(result, "api_output_tokens", 0),
                "rounds_used": getattr(result, "rounds_used", 0),
            })
            if len(self._recent) > 200:
                self._recent = self._recent[-200:]

    def summary(self) -> Dict[str, Any]:
        with self._lock:
            total = self._total
            rounds = self._rounds
            return {
                "total_requests": total,
                "fast_path_rate": round(self._fast_path / total, 4) if total else 0.0,
                "status_distribution": dict(self._by_status),
                "breach_count": self._breach,
                "rounds_used": {
                    "avg": round(sum(rounds) / len(rounds), 2) if rounds else 0.0,
                    "max": max(rounds) if rounds else 0,
                    "distribution": _histogram(rounds),
                },
                "api_tokens": {
                    "input": self._api_input_tokens,
                    "output": self._api_output_tokens,
                    "total": self._api_input_tokens + self._api_output_tokens,
                    "cost_est_usd": round(self._api_cost_usd, 6),
                },
                "by_model": {
                    m: {**b, "cost_est_usd": round(b["cost_est_usd"], 6)}
                    for m, b in self._by_model.items()
                },
            }


def _histogram(values: List[int], max_bucket: int = 10) -> Dict[str, int]:
    out: Dict[str, int] = {}
    for v in values:
        key = str(v) if v <= max_bucket else f">{max_bucket}"
        out[key] = out.get(key, 0) + 1
    return out