# -*- coding: utf-8 -*-
"""园区数据模拟引擎 —— 由前端 parkData.js 移植，后端统一产生数据
   前端通过 GET /api/dashboard/snapshot 获取，或订阅 MQTT opc/dashboard/tick
"""

import random
import threading
import time

MODEL_NAMES = ["DeepSeek-V3", "通义千问", "智谱 GLM-4", "豆包", "讯飞星火"]
TOOL_NAMES = ["文档生成", "数据查询", "图像创作", "代码执行", "语音合成"]
COMPANY_NAMES = [
    "云南派音人工智能科技", "米勒克尔蓝宝石珠宝", "中泰研学合作", "云南宸中低空经济",
    "昆明智海银高文化科技", "云南廷秀文旅康养", "瀚颖AI+教育信息咨询",
    "仰光客厅", "云南上古绝学文化", "中越生物医疗", "酷享野农AI农业",
    "滇缅国际设计", "昆明舒诺生物科技", "达岸教育管理", "花仙子园艺肥料",
    "研X同行者网络", "鬼才明AI创意工作室", "朵哈·玫瑰特色产业链", "昆明云韵体育",
    "南菌优培食用菌", "五华区丽裳文化", "云南星瑞航空", "综合直播私域平台",
    "昆明屿澈电商", "蓝智科技", "云品出滇·纸享万家", "启元人工智能科技",
]


def _pick(arr):
    return arr[random.randrange(len(arr))]


def _now_time():
    return time.strftime("%H:%M:%S")


def make_series(base, growth, noise, n=30):
    out = []
    v = base
    for _ in range(n):
        v = v * (1 + growth) + (random.random() - 0.5) * noise
        out.append(round(max(1, v * 100) / 100, 2))
    return out


def gen_event():
    r = random.random
    pool = [
        {"icon": "bolt", "text": f"AI 推理任务完成 · 消耗 {round(800 + r() * 9000):,} tokens（{_pick(MODEL_NAMES)}）"},
        {"icon": "wrench", "text": f"工具「{_pick(TOOL_NAMES)}」被调用 {round(10 + r() * 90)} 次"},
        {"icon": "building", "text": f"「{_pick(COMPANY_NAMES)}」提交入驻申请 · 进入评审流程"},
        {"icon": "users", "text": f"「{_pick(COMPANY_NAMES)}」新增招聘岗位 {round(1 + r() * 5)} 个"},
        {"icon": "coin", "text": f"园区企业完成一笔 ¥{(0.5 + r() * 9):.1f}万 交易"},
        {"icon": "robot", "text": f"「{_pick(MODEL_NAMES)}」模型完成一次微调任务"},
    ]
    e = _pick(pool)
    return {"id": f"{int(time.time()*1000)}-{random.random()}", "icon": e["icon"], "text": e["text"], "time": _now_time()}


def init_feed():
    return [
        {"id": 1, "icon": "bolt", "text": "云南派音AI 完成音频向量嵌入任务 · 消耗 12,480 tokens", "time": _now_time()},
        {"id": 2, "icon": "building", "text": "「启元人工智能科技」通过评审 · 正式入驻 OPC 创业空间", "time": _now_time()},
        {"id": 3, "icon": "users", "text": "「昆明舒护安养老服务」新增招聘岗位 2 个", "time": _now_time()},
        {"id": 4, "icon": "coin", "text": "园区企业完成一笔 ¥3.6万 交易", "time": _now_time()},
    ]


def init_snapshot():
    return {
        "t": 0,
        "token": {"today": 128.64, "total": 12840, "rate": 84.6, "series": make_series(82, 0.012, 9)},
        "tools": {"today": 3568, "total": 365204, "success": 98.7},
        "projects": {"inPark": 158, "cum": 208, "todayNew": 2},
        "jobs": {"total": 2186, "todayNew": 3},
        "revenue": {"today": 38.6, "total": 20800, "growth": 8.2, "series": make_series(30, 0.006, 4)},
        "park": {"devices": 98.6, "energy": 386, "people": 127, "desk": 76, "meeting": 3, "nodes": 12},
        "feed": init_feed(),
    }


def next_snapshot(s):
    r = random.random
    t_delta = round(0.26 + r() * 0.34, 2)

    token = {
        "today": round(s["token"]["today"] + t_delta, 2),
        "total": round(s["token"]["total"] + t_delta, 2),
        "rate": round(76 + r() * 20, 1),
    }
    tool_delta = round(13 + r() * 22)
    tools = {
        "today": s["tools"]["today"] + tool_delta,
        "total": s["tools"]["total"] + tool_delta,
        "success": round(98.1 + r() * 1.2, 1),
    }
    rev_delta = round(0.6 + r() * 1.7, 1)
    revenue = {
        "today": round(s["revenue"]["today"] + rev_delta, 1),
        "total": round(s["revenue"]["total"] + rev_delta, 1),
        "growth": round(7.2 + r() * 2.2, 1),
    }
    park = {
        "devices": round(97.6 + r() * 1.6, 1),
        "energy": round(320 + r() * 130),
        "people": round(80 + r() * 95),
        "desk": round(62 + r() * 24),
        "meeting": round(2 + r() * 4),
        "nodes": 12,
    }

    projects = dict(s["projects"])
    if r() < 0.055:
        projects["todayNew"] += 1
    if r() < 0.035:
        projects["inPark"] += 1
        projects["cum"] += 1
    jobs = dict(s["jobs"])
    if r() < 0.08:
        jobs["todayNew"] += 1
    if r() < 0.05:
        jobs["total"] += 1

    t_series = list(s["token"]["series"])
    t_series[-1] = round(t_series[-1] + t_delta, 2)
    if s["t"] % 12 == 11:
        t_series = t_series[1:] + [round(72 + r() * 30, 2)]
    token["series"] = t_series

    r_series = list(s["revenue"]["series"])
    r_series[-1] = round(r_series[-1] + rev_delta, 1)
    if s["t"] % 12 == 11:
        r_series = r_series[1:] + [round(26 + r() * 9, 1)]
    revenue["series"] = r_series

    feed = [gen_event()] + s["feed"][:6] if s["t"] % 3 == 2 else s["feed"]

    return {
        "t": s["t"] + 1,
        "token": token, "tools": tools, "revenue": revenue,
        "park": park, "projects": projects, "jobs": jobs, "feed": feed,
    }


class SimEngine:
    """带锁的快照引擎：单例供 API 与 MQTT tick 共用"""

    def __init__(self):
        self._lock = threading.RLock()
        self._snap = init_snapshot()

    def snapshot(self):
        with self._lock:
            return dict(self._snap)

    def tick(self):
        with self._lock:
            self._snap = next_snapshot(self._snap)
            return dict(self._snap)


sim_engine = SimEngine()