181 lines
6.6 KiB
Python
181 lines
6.6 KiB
Python
#!/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),
|
||
}
|