init: init proj

data.py

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+#!/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),
+    }