eink-push/data.py

#!/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·秦淮）。日期/时间用真实系统时间。
任何接口失败时相关数据以占位符 "--" 呈现，不回退 mock。
"""
import json
from datetime import datetime

import config
import jm_api
import weather_api

WEEK_CN = ["周一", "周二", "周三", "周四", "周五", "周六", "周日"]

TREND_DAYS = 30  # 近 N 天趋势


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·秦淮），带 WEATHER_TTL 文件缓存。

    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 = {"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}")
    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


# ---------- 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):
    return {"k": k, "v": v, "hb": _fmt_rate(wow), "tb": _fmt_rate(yoy)}


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


# ---------- 橘喵业务数据 ----------
def _mao(now):
    upd = now.strftime("%H:%M")
    # 今日经营（realtime）
    try:
        rt = jm_api.get_realtime()
        upd = (rt.get("dataTime") or "")[11:16] or upd
        cols = [
            _col("单量", _fmt_count(rt["todayOrderCount"]), rt["orderCountWowRate"], rt["orderCountYoyRate"]),
            _col("流水", _fmt_money(rt["todayPayAmount"]), rt["payAmountWowRate"], rt["payAmountYoyRate"]),
            _col("毛利", _fmt_money(rt["todayGrossProfit"]), rt["grossProfitWowRate"], rt["grossProfitYoyRate"]),
        ]
    except Exception as e:
        print(f"[警告] 今日经营拉取失败：{e}")
        cols = [_placeholder_col(k) for k in ("单量", "流水", "毛利")]
    # 近30天趋势（按日期缓存，每天只拉一次）
    trend = _trend(now)
    return {"upd": upd, "cols": cols, "trend": trend}


def get_dashboard_data(now=None):
    """返回渲染所需的完整数据字典。"""
    now = now or datetime.now()
    return {
        "date": {
            "greg": now.strftime("%Y/%m/%d"),
            "week": WEEK_CN[now.weekday()],
            "time": now.strftime("%H:%M"),
        },
        "weather": _weather(now),
        "mao": _mao(now),
    }