#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
数据层 —— 汇总仪表盘所需的全部数据。

橘喵今日经营 + 近30天趋势来自 jm_api（jm-devops 后端统计接口，免鉴权 GET）。
天气来自 weather_api（和风天气，定位南京·江宁）。日期/时间用真实系统时间（统一按 config.TZ_NAME 时区）。
任何接口失败时相关数据以占位符 "--" 呈现，不回退 mock。

两种调用形态：
  - 本机脚本（main.py）：get_dashboard_data() —— 带文件缓存（天气/趋势/BTC），用量读本地快照；
  - 图片服务（server.py）：直接用各 `*_fetch()` 纯拉取函数 + `_usage(now, raw=<推送数据>)`，不落盘。
"""
import json
from datetime import datetime
from zoneinfo import ZoneInfo

import config
import jm_api
import weather_api
import usage_local
import btc_api

WEEK_CN = ["周一", "周二", "周三", "周四", "周五", "周六", "周日"]
TZ = ZoneInfo(config.TZ_NAME)


def now_tz():
    """当前时刻（带 config.TZ_NAME 时区）。"""
    return datetime.now(TZ)


def _local(ts):
    """epoch 秒 → 该时区的 datetime。"""
    return datetime.fromtimestamp(ts, TZ)

TREND_DAYS = 30  # 近 N 天趋势
FIVE_HOUR, SEVEN_DAY = 5 * 3600, 7 * 86400  # 两个滚动窗口长度（秒），用于算「时间已流逝%」


def _read_weather_cache():
    try:
        with open(config.WEATHER_CACHE_PATH, encoding="utf-8") as f:
            return json.load(f)  # {"ts": float, "data": {...}}
    except Exception:
        return None


def _write_weather_cache(ts, data):
    try:
        with open(config.WEATHER_CACHE_PATH, "w", encoding="utf-8") as f:
            json.dump({"ts": ts, "data": data}, f, ensure_ascii=False)
    except Exception as e:
        print(f"[警告] 天气缓存写入失败：{e}")


def _read_trend_cache():
    try:
        with open(config.TREND_CACHE_PATH, encoding="utf-8") as f:
            return json.load(f)  # {"date": "YYYY-MM-DD", "data": {...}}
    except Exception:
        return None


def _write_trend_cache(date_key, data):
    try:
        with open(config.TREND_CACHE_PATH, "w", encoding="utf-8") as f:
            json.dump({"date": date_key, "data": data}, f, ensure_ascii=False)
    except Exception as e:
        print(f"[警告] 趋势缓存写入失败：{e}")


def _trend(now):
    """近30天趋势，按日期缓存：recent-days 每天只更新一次。

    当天已有缓存（且有数据）→ 直接复用，不发请求；当天还没有 → 拉取并写缓存。
    拉取失败时沿用任意旧缓存（哪怕非当天），仍无缓存才回退空。
    API 降序 → 升序：左旧右新。
    """
    date_key = now.strftime("%Y-%m-%d")
    cached = _read_trend_cache()
    if cached and cached.get("date") == date_key and cached.get("data", {}).get("series"):
        return cached["data"]
    try:
        asc = list(reversed(jm_api.get_recent_days(TREND_DAYS)))
        trend = {
            "dates": [d["date"][5:].replace("-", "/") for d in asc],  # yyyy-MM-dd → MM/DD
            "series": [
                {"k": "单量", "style": "solid",  "data": [int(d["orderCount"]) for d in asc]},
                {"k": "流水", "style": "dashed", "data": [float(d["payAmount"]) for d in asc]},
                {"k": "毛利", "style": "dotted", "data": [float(d["grossProfit"]) for d in asc]},
            ],
        }
        _write_trend_cache(date_key, trend)
        return trend
    except Exception as e:
        print(f"[警告] 近30天趋势拉取失败：{e}")
        if cached and cached.get("data", {}).get("series"):  # 失败沿用旧缓存，避免趋势图整片 "--"
            print("[警告] 沿用上次趋势缓存")
            return cached["data"]
        return {"dates": [], "series": []}


def _weather(now):
    """和风天气（南京·江宁），带 WEATHER_TTL 文件缓存（本机脚本用）。

    缓存未过期 → 直接复用，不发请求（每分钟刷新时省掉 14/15 次天气调用）。
    过期 → 重新拉取并写缓存；全部接口失败时沿用上次缓存，仍无缓存才回退占位 "--"。
    """
    ts = now.timestamp()
    cached = _read_weather_cache()
    if cached and ts - cached.get("ts", 0) < config.WEATHER_TTL:
        return cached["data"]
    out, ok = weather_fetch()
    if ok:
        _write_weather_cache(ts, out)
        return out
    if cached:  # 全部失败：沿用上次缓存，避免天气区整片 "--"
        print("[警告] 天气全部拉取失败，沿用上次缓存")
        return cached["data"]
    return out


def weather_fetch():
    """实时拉取天气（不读不写缓存）→ （weather dict，是否至少一个接口成功）。服务端每次请求直接调用。"""
    out = {"loc": config.WEATHER_LOC_NAME, "cond": "--", "temp": "--", "range": "--", "icon": ""}
    ok = False
    try:
        w = weather_api.get_now()
        out["cond"] = w.get("text") or "--"
        out["temp"] = f"{w['temp']}°"
        out["icon"] = w.get("icon") or ""  # 和风图标代码，供 renderer 映射图标
        ok = True
    except Exception as e:
        print(f"[警告] 实时天气拉取失败：{e}")
    try:
        today = weather_api.get_today()
        out["range"] = f"{today['tempMin']}°~{today['tempMax']}°"
        ok = True
    except Exception as e:
        print(f"[警告] 今日温区拉取失败：{e}")
    return out, ok


# ---------- 格式化 ----------
def _fmt_count(n):
    return f"{int(n):,}"  # 千分位，如 1,284


def _fmt_money(yuan):
    """元金额 → 紧凑展示：≥1万显示「X.XX万」(两位小数)，否则取整元。"""
    v = float(yuan)
    return f"{v / 10000:.2f}万" if abs(v) >= 10000 else f"{v:.0f}"


def _fmt_rate(rate):
    """增长率字符串 → (方向, 文本)。null/空 → (None, '--')，方向 None 表示不画三角。
    数值统一两位小数；整数部分不足两位用前导 0 补齐(6.5→06.50)，便于环比/同比上下对齐；
    三/四位数(≥100%)原样完整输出不截断。"""
    if rate is None or rate == "":
        return (None, "--")
    v = float(rate)
    return ("down" if v < 0 else "up", f"{abs(v):05.2f}%")


def _col(k, v, wow, yoy, wide=False):
    """一列指标。wide=True 表示仅宽版（800×480）展示，400×300 小屏三列放不下、渲染时跳过。"""
    return {"k": k, "v": v, "hb": _fmt_rate(wow), "tb": _fmt_rate(yoy), "wide": wide}


def _placeholder_col(k, wide=False):
    return {"k": k, "v": "--", "hb": (None, "--"), "tb": (None, "--"), "wide": wide}


# 今日实时五列：（标签、接口字段前缀、格式化、是否仅宽版）。字段前缀 base 对应 today{Base} / {base}WowRate / {base}YoyRate，
# 见 docs/首页看板接口文档-20260911.md。团购两列为新增字段，旧后端无此键 → 占位 "--"（不报错、不影响其余列）。
REALTIME_COLS = (
    ("探店单量", "orderCount",         _fmt_count, False),
    ("探店流水", "payAmount",          _fmt_money, False),
    ("团购单量", "groupbuyOrderCount", _fmt_count, True),
    ("团购流水", "groupbuyPayAmount",  _fmt_money, True),
    ("毛利",     "grossProfit",        _fmt_money, False),   # 口径已含团购毛利（接口合计，未拆分）
)


def _col_from(rt, k, base, fmt, wide):
    cap = base[0].upper() + base[1:]
    v = rt.get(f"today{cap}")
    if v is None or v == "":
        return _placeholder_col(k, wide)
    return _col(k, fmt(v), rt.get(f"{base}WowRate"), rt.get(f"{base}YoyRate"), wide)


# ---------- 橘喵业务数据 ----------
def mao_fetch(now, with_trend=True):
    """橘喵今日经营（实时接口）；with_trend=False 时不拉近 30 天趋势（服务端与宽版都不用它，且趋势有文件缓存）。
    返回（mao dict，实时接口是否成功）。"""
    upd = now.strftime("%H:%M")
    ok = True
    # 今日经营（realtime）
    try:
        rt = jm_api.get_realtime()
        upd = (rt.get("dataTime") or "")[11:16] or upd
        cols = [_col_from(rt, k, base, fmt, wide) for k, base, fmt, wide in REALTIME_COLS]
    except Exception as e:
        print(f"[警告] 今日经营拉取失败：{e}")
        cols = [_placeholder_col(k, wide) for k, _, _, wide in REALTIME_COLS]
        ok = False
    # 近30天趋势（按日期缓存，每天只拉一次）
    trend = _trend(now) if with_trend else {"dates": [], "series": []}
    return {"upd": upd, "cols": cols, "trend": trend}, ok


def _mao(now):
    return mao_fetch(now)[0]


# ---------- 比特币 K 线 ----------
def _read_btc_cache():
    try:
        with open(config.BTC_CACHE_PATH, encoding="utf-8") as f:
            return json.load(f)  # {"ts": float, "data": {...}}
    except Exception:
        return None


def _write_btc_cache(ts, data):
    try:
        with open(config.BTC_CACHE_PATH, "w", encoding="utf-8") as f:
            json.dump({"ts": ts, "data": data}, f, ensure_ascii=False)
    except Exception as e:
        print(f"[警告] BTC 缓存写入失败：{e}")


def _btc(now):
    """比特币 K 线（宽版底部面板；周期 BTC_BAR、根数 BTC_LIMIT），带 BTC_TTL 文件缓存；
    拉取失败沿用旧缓存，仍无缓存回退空 candles。
    结构契约（renderer 依赖）：{symbol, bar, src, candles:[{t, o, h, l, c}], last, chg, chg_label}，其中 t 为轴标签文本；
    last 为最新一根（当前未收盘）的收盘价；chg 为涨跌幅（%）——时 K 取相对 24 根前（24h）收盘、不足则相对首根，
    日 K 取相对上一根收盘，chg_label 说明口径（"24h"/"1d"）；涨=绿 / 跌=红 由 renderer 按 c≥o 判定。"""
    ts = now.timestamp()
    bar = config.BTC_BAR
    cached = _read_btc_cache()
    cd = (cached or {}).get("data", {})
    # 周期或根数（BTC_BAR/BTC_LIMIT）变更即视为失效，避免改配置后 TTL 内仍显示旧范围
    if cached and ts - cached.get("ts", 0) < config.BTC_TTL and cd.get("bar") == bar and len(cd.get("candles", [])) == config.BTC_LIMIT:
        return cached["data"]
    try:
        out = btc_fetch()
        _write_btc_cache(ts, out)
        return out
    except Exception as e:
        print(f"[警告] BTC K 线拉取失败：{e}")
        if cached:
            print("[警告] 沿用上次 BTC 缓存")
            return cached["data"]
        return btc_empty()


def btc_empty():
    return {"symbol": "BTC/USDT", "bar": config.BTC_BAR, "src": "", "candles": [], "last": None, "chg": None, "chg_label": ""}


def btc_fetch():
    """实时拉取 BTC K 线并整理成渲染结构（不读不写缓存）；失败抛异常。服务端每次请求直接调用。"""
    bar = config.BTC_BAR
    src, rows = btc_api.get_candles(bar, config.BTC_LIMIT)
    fmt = "%m/%d %H:%M" if bar == "1H" else "%m/%d"
    candles = [{"t": _local(r["ts"]).strftime(fmt), "o": r["o"], "h": r["h"], "l": r["l"], "c": r["c"]} for r in rows]
    last = rows[-1]["c"]
    if bar == "1H":
        base = rows[-25]["c"] if len(rows) >= 25 else rows[0]["c"]
        chg_label = "24h" if len(rows) >= 25 else f"{len(rows) - 1}h"
    else:
        base, chg_label = rows[-2]["c"], "1d"
    return {"symbol": "BTC/USDT", "bar": bar, "src": src, "candles": candles,
            "last": last, "chg": (last - base) / base * 100 if base else 0.0, "chg_label": chg_label}


# ---------- Claude Code 用量 ----------
def _parse_reset_ts(s):
    """resets_at → epoch 秒。兼容三种：epoch 数字（Claude Code stdin 给的就是 epoch）、
    ISO 时间串（含结尾 'Z'）、空。失败返回 None。"""
    if s is None or s == "":
        return None
    s = str(s)
    if s.replace(".", "", 1).isdigit():          # 纯数字 → 当作 epoch 秒
        return float(s)
    try:
        return datetime.fromisoformat(s.replace("Z", "+00:00")).timestamp()
    except Exception:
        return None


def _window_time_pct(resets_at, window, now):
    """该滚动窗口「已流逝时间百分比」= (window − 距重置剩余) / window ×100。失败返回 None。"""
    reset = _parse_reset_ts(resets_at)
    if reset is None:
        return None
    remaining = max(0, min(window, reset - now.timestamp()))
    return int(round((window - remaining) / window * 100))


def _fmt_reset(resets_at, window):
    """重置时刻 → 文本：≤1 天的窗口只给 HH:MM，更长的窗口带 MM/DD。解析失败返回 None。"""
    ts = _parse_reset_ts(resets_at)
    if ts is None:
        return None
    dt = _local(ts)
    return dt.strftime("%H:%M") if window <= 86400 else dt.strftime("%m/%d %H:%M")


# Claude 用量窗口：（快照键，短标签，长标签，窗口长度秒，scoped）。
# 短标签 k 给 400x300 小屏（标签列只有 26px）；长标签 label 给 800x480 宽版，沿用 statusline 的写法
# （all 5h / all 7d / fable 7d，小写开头）。scoped=True 为「按模型限定」的额度（Fable 7d，来自
# /api/oauth/usage 的 limits[]，由 statusline 写入快照 seven_day_fable），小屏放不下第三行，只在宽版展示。
USAGE_WINDOWS = (
    ("five_hour", "5h", "all 5h", FIVE_HOUR, False),
    ("seven_day", "7d", "all 7d", SEVEN_DAY, False),
    ("seven_day_fable", "Fable 7d", "fable 7d", SEVEN_DAY, True),
)
# ChatGPT 用量窗口：键名沿用同一套约定（five_hour / seven_day / seven_day_codex），推送端照此结构提供原始数据即可。
GPT_WINDOWS = (
    ("five_hour", "5h", "all 5h", FIVE_HOUR, False),
    ("seven_day", "7d", "all 7d", SEVEN_DAY, False),
    ("seven_day_codex", "Codex 7d", "codex 7d", SEVEN_DAY, True),
)


def usage_from_raw(now, raw, windows, title):
    """原始快照 → 渲染结构（Claude / ChatGPT 通用）。
    raw 形如 {five_hour:{utilization, resets_at}, seven_day:{...}, <scoped 键>:{...}|null, updated_at?}；
    utilization 为已用百分比，resets_at 为 epoch 秒或 ISO；缺哪个窗口哪个显示 "--"。
    time_pct（时间已流逝%）与 pace 按传入的 now **现算**——所以推送端只需推原始快照，服务端渲染时 pace 仍随时钟准确推进。
    结构契约（renderer 依赖）：{title, warn, ok, pace_tol, updated?, bars:[{k, label, pct(0~100 或 None), time_pct?, reset?, scoped}]}；
    pct ≥ warn 时该条进度条与百分比转红（宽版另有 pct ≤ ok 绿档）；pace = pct − time_pct（>0 超前↑ / <0 节余↓，宽版按 ±pace_tol 分三色）；
    reset 为重置时刻文本；updated 为快照落盘时刻 HH:MM（活跃使用时持续刷新，空闲时停在最后一次）。"""
    raw = raw or {}
    bars = []
    for key, k, label, win, scoped in windows:
        seg = raw.get(key) or {}
        util = seg.get("utilization")
        pct = int(round(float(util))) if util is not None else None
        bar = {"k": k, "label": label, "pct": pct, "scoped": scoped}
        tp = _window_time_pct(seg.get("resets_at"), win, now)
        if pct is not None and tp is not None:
            bar["time_pct"] = tp
        rs = _fmt_reset(seg.get("resets_at"), win)
        if rs:
            bar["reset"] = rs
        bars.append(bar)
    out = {"title": title, "warn": config.USAGE_WARN, "ok": config.USAGE_OK, "pace_tol": config.PACE_TOL, "bars": bars}
    upd = _parse_reset_ts(raw.get("updated_at"))
    if upd:
        out["updated"] = _local(upd).strftime("%H:%M")
    return out


def _usage(now, raw=None):
    """Claude Code 用量（5h / 7d / Fable 7d）。raw 为 None 时读本地 statusline 快照（见 usage_local.py，**不发请求**）；
    服务端传入推送来的原始快照。utilization 来自 statusline 从 Claude Code stdin 落盘的权威实时值（Fable 行来自其转存的 API limits）。"""
    if raw is None:
        raw = {}
        try:
            raw = usage_local.get_usage()
        except Exception as e:
            print(f"[警告] Claude 用量读取失败：{e}")
    return usage_from_raw(now, raw, USAGE_WINDOWS, "Claude Usage")


def gpt_mock_raw(now):
    """ChatGPT 原始快照的 mock（尚无真实数据源时用）：刻意覆盖宽版三档配色——
    5h 88%（≥warn 红）、7d 71%（黑）、Codex 7d 22%（≤ok 绿，scoped，与左侧 fable 行对称）。"""
    t = now.timestamp()
    return {"five_hour": {"utilization": 88, "resets_at": t + 2 * 3600},
            "seven_day": {"utilization": 71, "resets_at": t + 3 * 86400},
            "seven_day_codex": {"utilization": 22, "resets_at": t + 3 * 86400}}


def _usage_gpt(now, raw=None):
    """ChatGPT 用量。raw 为推送来的原始快照（结构同 gpt_mock_raw）；为 None 时用 mock 并标 mock=True
    （renderer 在标题右侧标「示例数据」）。接入真实数据源时由推送端提供 raw，本函数无需改动。"""
    mock = raw is None
    out = usage_from_raw(now, gpt_mock_raw(now) if mock else raw, GPT_WINDOWS, "ChatGPT Usage")
    if mock:
        out["mock"] = True
    return out


def get_dashboard_data(now=None):
    """返回渲染所需的完整数据字典（本机脚本形态：带文件缓存，用量读本地快照）。"""
    now = now or now_tz()
    return {
        "date": {
            "greg": now.strftime("%Y/%m/%d"),
            "week": WEEK_CN[now.weekday()],
            "time": now.strftime("%H:%M"),
        },
        "weather": _weather(now),
        "mao": _mao(now),
        "usage": _usage(now),
        "usage_gpt": _usage_gpt(now),
        "btc": _btc(now),
    }