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Web 界面:浏览器打开即可输入指令,报告在页面展示。
定时任务自动推送日报/周报到钉钉群。
"""
import logging
import os
import sys
from datetime import date, datetime, timedelta
from pathlib import Path
_root = Path(__file__).resolve().parent.parent
if str(_root) not in sys.path:
sys.path.insert(0, str(_root))
from flask import Flask, request, jsonify, render_template
from src.analyzer import run_analysis, run_monthly_analysis, run_daily_analysis, run_range_analysis, build_trend_table
from src.dingtalk import send_markdown
from src.formatter import (
format_report, format_title,
format_monthly_report, format_monthly_title,
format_daily_report, format_daily_title,
format_range_report, format_range_title,
)
from src.loader import load_config, load_weekly_data, get_available_weeks
from src.ai_analyzer import ai_parse_query, chat_with_chence, build_business_context
from src.memory import save_analysis, build_memory_context
from src.monitor import run_daily_monitor, format_monitor_dingtalk, compute_trend_data, compute_dashboard_data, get_filter_options
from src.budget import compute_budget_tracking
log = logging.getLogger("ad-agent")
app = Flask(__name__, template_folder=str(_root / "templates"))
CONFIG_PATH = _root / "config.yaml"
import math
import numpy as np
_API_TOKEN = os.environ.get("API_TOKEN", "").strip()
@app.before_request
def _check_auth():
"""When API_TOKEN is set, protect /api/* endpoints with Bearer token auth."""
if not _API_TOKEN:
return
if not request.path.startswith("/api/"):
return
auth = request.headers.get("Authorization", "")
if auth == f"Bearer {_API_TOKEN}":
return
return jsonify(ok=False, error="Unauthorized"), 401
_monitor_cache = {"data": None, "ts": None}
_last_quick_sync: datetime | None = None
def _clean_nan(obj):
"""递归清理:NaN/Inf→None,numpy 类型→Python 原生类型,确保 JSON 可序列化。"""
if isinstance(obj, (np.integer,)):
return int(obj)
if isinstance(obj, (np.floating,)):
v = float(obj)
return None if (math.isnan(v) or math.isinf(v)) else v
if isinstance(obj, np.ndarray):
return _clean_nan(obj.tolist())
if isinstance(obj, float) and (math.isnan(obj) or math.isinf(obj)):
return None
if isinstance(obj, dict):
return {k: _clean_nan(v) for k, v in obj.items()}
if isinstance(obj, (list, tuple)):
return [_clean_nan(v) for v in obj]
return obj
@app.route("/")
def index():
return render_template("index.html", api_token=_API_TOKEN)
@app.route("/api/datasource")
def datasource():
config = load_config(CONFIG_PATH)
gs = config.get("google_sheets", {})
url = gs.get("spreadsheet_url", "") if gs.get("enabled") else ""
try:
from src.loader import load_daily_data
df = load_daily_data(CONFIG_PATH)
latest = df["date"].max()
latest_str = latest.strftime("%Y-%m-%d") if latest is not None and str(latest) != "NaT" else None
except Exception:
latest_str = None
return jsonify(ok=True, sheets_url=url, latest_date=latest_str)
@app.route("/api/memory")
def memory():
from src.memory import load_recent
records = load_recent(10)
return jsonify(ok=True, records=records)
def _sync_platform(platform: str, fetch_fn, config_key: str):
"""通用同步逻辑:拉取 API 数据 → 写回 Google Sheets → 保存本地 CSV。"""
from src.loader import write_api_data_to_sheets
config = load_config(CONFIG_PATH)
p_cfg = config.get(config_key, {})
if not p_cfg.get("enabled"):
return jsonify(ok=False, error=f"{platform} API 未启用(config.yaml → {config_key}.enabled)")
days_back = p_cfg.get("days_back", 90)
df = fetch_fn(days_back=days_back)
if df.empty:
return jsonify(ok=False, error="未拉取到数据")
# 保存本地 CSV 备份
save_path = _root / "data" / f"{config_key}_data.csv"
save_path.parent.mkdir(parents=True, exist_ok=True)
df.to_csv(save_path, index=False)
# 写回 Google Sheets
sheets_result = {"added": 0}
sheets_error = None
try:
sheets_result = write_api_data_to_sheets(df, config_path=CONFIG_PATH)
except Exception as e:
sheets_error = str(e)
log.warning(f"{platform} 数据写回 Sheets 失败(数据已存本地): {e}")
date_min = df["date"].min().strftime("%Y-%m-%d")
date_max = df["date"].max().strftime("%Y-%m-%d")
log.info(f"{platform} 数据已同步: {len(df)} 条, {date_min}~{date_max}, 写入 Sheets {sheets_result['added']} 行")
_monitor_cache["data"] = None
_monitor_cache["ts"] = None
resp = dict(
ok=True, rows=len(df),
date_range=f"{date_min} ~ {date_max}",
sheets_added=sheets_result["added"],
)
if sheets_error:
resp["sheets_warning"] = sheets_error
return jsonify(resp)
@app.route("/api/rebuild_sheets", methods=["POST"])
def rebuild_sheets():
"""一次性操作:清空分平台表旧数据 → 全量重新同步(纯数字格式)。"""
import importlib
from src.loader import load_config, _get_spreadsheet, write_api_data_to_sheets
try:
config = load_config(CONFIG_PATH)
sh = _get_spreadsheet(config)
gs_cfg = config.get("google_sheets", {})
platform_sheets = gs_cfg.get("platform_sheets", ["Meta", "Google", "Criteo", "Bing"])
cleared = []
for name in platform_sheets:
try:
ws = sh.worksheet(name)
rows = ws.row_count
if rows > 1:
ws.delete_rows(2, rows)
cleared.append(name)
log.info(f"[rebuild] 已清空 Sheet [{name}] ({rows - 1} 行)")
except Exception as e:
log.warning(f"[rebuild] 清空 {name} 失败: {e}")
platform_defs = [
("Meta", "meta_api", "src.meta_api", "fetch_meta_data"),
("Google", "google_ads_api", "src.google_api", "fetch_google_data"),
("Criteo", "criteo_api", "src.criteo_api", "fetch_criteo_data"),
("Bing", "bing_api", "src.bing_api", "fetch_bing_data"),
]
synced = {}
for name, cfg_key, mod_path, fn_name in platform_defs:
p_cfg = config.get(cfg_key, {})
if not p_cfg.get("enabled"):
continue
try:
mod = importlib.import_module(mod_path)
fetch_fn = getattr(mod, fn_name)
days = p_cfg.get("days_back", 90)
df = fetch_fn(days_back=days)
if df.empty:
synced[name] = {"rows": 0, "status": "no_data"}
continue
res = write_api_data_to_sheets(df, config_path=CONFIG_PATH)
synced[name] = {"rows": len(df), "sheets_added": res.get("added", 0), "status": "ok"}
log.info(f"[rebuild] {name}: {len(df)} 条, Sheets +{res.get('added', 0)}")
except Exception as e:
synced[name] = {"status": "error", "error": str(e)}
log.warning(f"[rebuild] {name} 同步失败: {e}")
_monitor_cache["data"] = None
_monitor_cache["ts"] = None
return jsonify(ok=True, cleared=cleared, synced=synced)
except Exception as e:
log.exception(f"rebuild_sheets 出错: {e}")
return jsonify(ok=False, error=str(e))
@app.route("/api/sync_meta", methods=["POST"])
def sync_meta():
"""从 Meta API 拉取数据 → 写回 Google Sheets → 保存本地 CSV。"""
try:
from src.meta_api import fetch_meta_data
return _sync_platform("Meta", fetch_meta_data, "meta_api")
except Exception as e:
log.exception(f"Meta 同步出错: {e}")
return jsonify(ok=False, error=str(e))
@app.route("/api/sync_google", methods=["POST"])
def sync_google():
"""从 Google Ads API 拉取数据 → 写回 Google Sheets → 保存本地 CSV。"""
try:
from src.google_api import fetch_google_data
return _sync_platform("Google", fetch_google_data, "google_ads_api")
except Exception as e:
log.exception(f"Google Ads 同步出错: {e}")
return jsonify(ok=False, error=str(e))
@app.route("/api/sync_criteo", methods=["POST"])
def sync_criteo():
"""从 Criteo API 拉取数据 → 写回 Google Sheets → 保存本地 CSV。"""
try:
from src.criteo_api import fetch_criteo_data
return _sync_platform("Criteo", fetch_criteo_data, "criteo_api")
except Exception as e:
log.exception(f"Criteo 同步出错: {e}")
return jsonify(ok=False, error=str(e))
@app.route("/api/sync_bing", methods=["POST"])
def sync_bing():
"""从 Bing Ads API 拉取数据 → 写回 Google Sheets → 保存本地 CSV。"""
try:
from src.bing_api import fetch_bing_data
return _sync_platform("Bing", fetch_bing_data, "bing_api")
except Exception as e:
log.exception(f"Bing Ads 同步出错: {e}")
return jsonify(ok=False, error=str(e))
def _quick_sync_stale_platforms():
"""每天至多执行一次:拉取最近 7 天数据并写回 Sheets。"""
global _last_quick_sync
import importlib
from src.loader import write_api_data_to_sheets
now = datetime.now()
if _last_quick_sync and _last_quick_sync.date() == now.date():
return []
config = load_config(CONFIG_PATH)
platform_defs = [
("Meta", "meta_api", "src.meta_api", "fetch_meta_data"),
("Google", "google_ads_api", "src.google_api", "fetch_google_data"),
("Criteo", "criteo_api", "src.criteo_api", "fetch_criteo_data"),
("Bing", "bing_api", "src.bing_api", "fetch_bing_data"),
]
synced = []
for name, cfg_key, mod_path, fn_name in platform_defs:
p_cfg = config.get(cfg_key, {})
if not p_cfg.get("enabled"):
continue
try:
mod = importlib.import_module(mod_path)
fetch_fn = getattr(mod, fn_name)
df_new = fetch_fn(days_back=7)
if df_new.empty:
log.info(f"[快速同步] {name}: 无新数据")
continue
try:
res = write_api_data_to_sheets(df_new, config_path=CONFIG_PATH)
log.info(f"[快速同步] {name}: {len(df_new)} 条, Sheets +{res.get('added', 0)} 行")
except Exception as e:
log.warning(f"[快速同步] {name}: 写 Sheets 失败: {e}")
synced.append(name)
except Exception as e:
log.warning(f"[快速同步] {name}: 同步失败 - {e}")
_last_quick_sync = now
if synced:
_monitor_cache["data"] = None
_monitor_cache["ts"] = None
return synced
@app.route("/api/monitor")
def monitor():
try:
date_str = request.args.get("date")
target_date = date.fromisoformat(date_str) if date_str else None
country_param = request.args.get("country")
has_filter = bool(date_str or (country_param and country_param.lower() != "all"))
if not has_filter:
now = datetime.now()
cached = _monitor_cache["data"]
cached_ts = _monitor_cache["ts"]
if cached and cached_ts and cached_ts.date() == now.date():
age_min = int((now - cached_ts).total_seconds() // 60)
return jsonify(ok=True, cached=True, cache_age_min=age_min, **cached)
result = run_daily_monitor(CONFIG_PATH, target_date=target_date, country=country_param)
result = _clean_nan(result)
if not has_filter:
_monitor_cache["data"] = result
_monitor_cache["ts"] = datetime.now()
return jsonify(ok=True, cached=False, **result)
except Exception as e:
log.exception(f"监控出错: {e}")
return jsonify(ok=False, error=str(e))
@app.route("/api/monitor/trend")
def monitor_trend():
try:
start_str = request.args.get("start")
end_str = request.args.get("end")
if start_str:
start = date.fromisoformat(start_str)
else:
start = date.today() - timedelta(days=14)
if end_str:
end = date.fromisoformat(end_str)
else:
end = date.today() - timedelta(days=1)
country = request.args.get("country")
result = compute_trend_data(CONFIG_PATH, start, end, country=country)
result = _clean_nan(result)
return jsonify(ok=True, **result)
except Exception as e:
log.exception(f"趋势数据出错: {e}")
return jsonify(ok=False, error=str(e))
@app.route("/api/dashboard")
def api_dashboard():
"""数据看板:区间 + 多维筛选。"""
try:
start_str = request.args.get("start")
end_str = request.args.get("end")
if start_str:
start = date.fromisoformat(start_str)
else:
start = date.today() - timedelta(days=14)
if end_str:
end = date.fromisoformat(end_str)
else:
end = date.today() - timedelta(days=1)
filters = {}
for dim in ("country", "platform", "ad_objective", "product_line", "product_model", "project_type"):
val = request.args.get(dim)
if val:
filters[dim] = val
result = compute_dashboard_data(CONFIG_PATH, start, end, filters=filters or None)
result = _clean_nan(result)
return jsonify(ok=True, **result)
except Exception as e:
log.exception(f"Dashboard 出错: {e}")
return jsonify(ok=False, error=str(e))
@app.route("/api/dashboard/filters")
def api_dashboard_filters():
"""返回各筛选维度的可选值。"""
try:
options = get_filter_options(CONFIG_PATH)
return jsonify(ok=True, **options)
except Exception as e:
log.exception(f"Dashboard filters 出错: {e}")
return jsonify(ok=False, error=str(e))
@app.route("/api/budget")
def api_budget():
try:
month = request.args.get("month")
result = compute_budget_tracking(CONFIG_PATH, target_month=month)
result = _clean_nan(result)
if "error" in result:
config = load_config(CONFIG_PATH)
gs = config.get("google_sheets", {})
if gs.get("enabled") and gs.get("spreadsheet_url"):
result["sheets_url"] = gs["spreadsheet_url"]
return jsonify(ok=False, **result)
return jsonify(ok=True, **result)
except Exception as e:
log.exception(f"预算追踪出错: {e}")
return jsonify(ok=False, error=str(e))
@app.route("/api/analyze", methods=["POST"])
def analyze():
data = request.get_json(force=True)
query = (data.get("query") or "").strip()
if not query:
return jsonify(ok=False, error="请输入指令")
biz_note = (data.get("biz_note") or "").strip()
platform_filter = (data.get("platform") or "").strip() or None
params, parse_err = ai_parse_query(query)
if params is None:
return jsonify(ok=False, error=parse_err or "无法理解你的查询")
try:
mode = params["mode"]
mem_ctx = build_memory_context(n=5)
config = load_config(CONFIG_PATH)
if mode == "range":
s = datetime.strptime(params["start"], "%Y-%m-%d").date()
e = datetime.strptime(params["end"], "%Y-%m-%d").date()
trend = build_trend_table(config_path=CONFIG_PATH, mode="day", current_date=e, n=8)
biz_ctx = build_business_context(config, f"{s} ~ {e}", biz_note)
result = run_range_analysis(config_path=CONFIG_PATH, start_date=s, end_date=e,
trend_table=trend, memory_context=mem_ctx,
business_context=biz_ctx, platform=platform_filter)
if result.get("error"):
return jsonify(ok=False, error=result["error"])
title = format_range_title(result)
period_label = result.get("period_label", title)
cp = result.get("prev_label", "")
yp = result.get("yoy_label", "")
days = result.get("days_count", "")
cmp_parts = []
if days:
cmp_parts.append(f"共 {days} 天")
if cp:
cmp_parts.append(f"环比 vs {cp}")
if yp:
cmp_parts.append(f"同比 vs {yp}")
compare_label = " | ".join(cmp_parts)
elif mode == "day":
target_date = datetime.strptime(params["date"], "%Y-%m-%d").date()
trend = build_trend_table(config_path=CONFIG_PATH, mode="day", current_date=target_date, n=8)
biz_ctx = build_business_context(config, params["date"], biz_note)
result = run_daily_analysis(config_path=CONFIG_PATH, target_date=target_date,
trend_table=trend, memory_context=mem_ctx,
business_context=biz_ctx, platform=platform_filter)
if result.get("error"):
return jsonify(ok=False, error=result["error"])
title = format_daily_title(result)
period_label = result.get("period_label", title)
cp = result.get("prev_label", "")
yp = result.get("yoy_label", "")
compare_label = " | ".join(filter(None, [f"环比 vs {cp}" if cp else "", f"同比 vs {yp}" if yp else ""]))
elif mode == "month":
trend = build_trend_table(config_path=CONFIG_PATH, mode="month",
current_year=params["year"], current_period=params["month"], n=6)
biz_ctx = build_business_context(config, f"{params['year']}年{params['month']}月", biz_note)
result = run_monthly_analysis(
config_path=CONFIG_PATH,
target_year=params["year"],
target_month=params["month"],
trend_table=trend, memory_context=mem_ctx,
business_context=biz_ctx,
platform=platform_filter,
)
if result.get("error"):
return jsonify(ok=False, error=result["error"])
title = format_monthly_title(result)
period_label = result.get("period_label", title)
cp = result.get("prev_label", "")
yp = result.get("yoy_label", "")
compare_label = " | ".join(filter(None, [f"环比 vs {cp}" if cp else "", f"同比 vs {yp}" if yp else ""]))
else:
year, week = None, None
if mode == "week":
year, week = params["year"], params["week"]
elif mode == "prev":
df = load_weekly_data(CONFIG_PATH)
weeks = get_available_weeks(df)
if len(weeks) >= 2:
year, week = weeks[-2]
trend = build_trend_table(config_path=CONFIG_PATH, mode="week",
current_year=year, current_period=week, n=8)
wk_label = f"{year} W{week}" if year and week else ""
biz_ctx = build_business_context(config, wk_label, biz_note)
result = run_analysis(config_path=CONFIG_PATH, target_year=year, target_week=week,
trend_table=trend, memory_context=mem_ctx,
business_context=biz_ctx, platform=platform_filter)
title = format_title(result)
cp_ = result.get("current_period", {})
period_label = f"{cp_.get('year', '')} W{cp_.get('week', '')}"
pp = result.get("previous_period")
yp = result.get("yoy_period")
parts = []
if pp:
parts.append(f"环比 vs {pp['year']} W{pp['week']}")
if yp:
parts.append(f"同比 vs {yp['year']} W{yp['week']}")
compare_label = " | ".join(parts)
expert = result.get("expert")
metrics_snap = (result.get("current") or {}).get("total")
save_analysis(period_label, expert, metrics_snap)
report_context = _build_chat_context(title, result, expert)
report_data = _clean_nan({
"title": title,
"compare_label": compare_label,
"current": result.get("current"),
"wow_total": result.get("wow_total"),
"yoy_total": result.get("yoy_total"),
"wow_by_platform": result.get("wow_by_platform"),
"yoy_by_platform": result.get("yoy_by_platform"),
"wow_by_campaign": result.get("wow_by_campaign"),
"yoy_by_campaign": result.get("yoy_by_campaign"),
"wow_by_country": result.get("wow_by_country"),
"yoy_by_country": result.get("yoy_by_country"),
"expert": expert,
})
return jsonify(ok=True, title=title, report=report_data, report_context=report_context)
except Exception as e:
log.exception(f"分析出错: {e}")
return jsonify(ok=False, error=str(e))
def _build_chat_context(title: str, result: dict, expert: dict | None) -> str:
"""构建报告摘要字符串,供多轮对话时作为上下文。"""
parts = [f"报告: {title}"]
total = (result.get("current") or {}).get("total", {})
if total:
nums = []
for k in ["Cost", "Ads.Sales", "ROAS", "CPC", "CTR", "CVR", "GA4.Sessions"]:
v = total.get(k)
if v is not None and v == v:
if k in ("CTR", "CVR"):
nums.append(f"{k}: {v*100:.2f}%")
elif abs(v) >= 1000:
nums.append(f"{k}: {v:,.0f}")
else:
nums.append(f"{k}: {v:.2f}")
parts.append("整体: " + ", ".join(nums))
wow = result.get("wow_total") or {}
if wow:
chgs = [f"{k}: {v:+.1f}%" for k, v in wow.items() if v is not None and v == v][:6]
if chgs:
parts.append("环比: " + ", ".join(chgs))
for dim_key, dim_label in [("by_platform", "平台"), ("by_campaign_type", "漏斗"), ("by_country", "市场")]:
dim = (result.get("current") or {}).get(dim_key, {})
for name, metrics in dim.items():
roas = metrics.get("ROAS")
cost = metrics.get("Cost")
if roas is not None:
parts.append(f"{dim_label}-{name}: ROAS {roas:.2f}, Cost ${cost:,.0f}" if cost else f"{dim_label}-{name}: ROAS {roas:.2f}")
if expert:
if expert.get("verdict"):
parts.append(f"判定: {expert['verdict']}")
for f in (expert.get("key_findings") or []):
parts.append(f"发现: {f}")
return "\n".join(parts)
# ─────────────────────────────────────────────
# P3 投放分析 API
# ─────────────────────────────────────────────
@app.route("/api/p3/analysis")
def p3_analysis():
"""P3 四层投放分析。"""
try:
from src.p3_analyzer import run_p3_analysis
from src.p3_benchmark import load_benchmarks, load_platform_benchmarks, apply_benchmarks, run_diagnostics
from src.p3_report import format_p3_report
period_type = request.args.get("period_type", "week")
year = request.args.get("year", type=int)
period = request.args.get("period", type=int)
start_str = request.args.get("start")
end_str = request.args.get("end")
market_filter = request.args.get("market")
start_date = date.fromisoformat(start_str) if start_str else None
end_date = date.fromisoformat(end_str) if end_str else None
result = run_p3_analysis(
config_path=CONFIG_PATH,
period_type=period_type,
target_year=year,
target_period=period,
start_date=start_date,
end_date=end_date,
market=market_filter,
)
if result.get("error"):
return jsonify(ok=False, error=result["error"])
p3_cfg = result.pop("p3_config", {})
benchmarks = load_benchmarks(p3_cfg)
plat_benchmarks = load_platform_benchmarks(p3_cfg)
result["L1"] = apply_benchmarks(result["L1"], benchmarks, "L1")
result["L2"] = apply_benchmarks(result["L2"], benchmarks, "L2")
result["L3"] = apply_benchmarks(result["L3"], benchmarks, "L3", platform_benchmarks=plat_benchmarks)
result["L4"] = apply_benchmarks(result["L4"], benchmarks, "L4")
diagnostics = run_diagnostics(result, p3_cfg)
result["diagnostics"] = diagnostics
report_md = format_p3_report(result, diagnostics)
result["report_markdown"] = report_md
return jsonify(ok=True, **_clean_nan(result))
except Exception as e:
log.exception(f"P3 分析出错: {e}")
return jsonify(ok=False, error=str(e))
@app.route("/api/p3/config")
def p3_config():
"""当前 P3 配置数据(从 Google Sheets 动态读取)。"""
try:
from src.p3_config import load_all_p3_config
cfg = load_all_p3_config(CONFIG_PATH)
return jsonify(ok=True, **_clean_nan(cfg))
except Exception as e:
log.exception(f"P3 配置读取出错: {e}")
return jsonify(ok=False, error=str(e))
@app.route("/api/p3/push", methods=["POST"])
def p3_push():
"""手动推送 P3 周报到钉钉。"""
try:
from src.p3_analyzer import run_p3_analysis
from src.p3_benchmark import load_benchmarks, load_platform_benchmarks, apply_benchmarks, run_diagnostics
from src.p3_report import format_p3_report, format_p3_title
result = run_p3_analysis(config_path=CONFIG_PATH, period_type="week")
if result.get("error"):
return jsonify(ok=False, error=result["error"])
p3_cfg = result.pop("p3_config", {})
benchmarks = load_benchmarks(p3_cfg)
plat_benchmarks = load_platform_benchmarks(p3_cfg)
result["L1"] = apply_benchmarks(result["L1"], benchmarks, "L1")
result["L2"] = apply_benchmarks(result["L2"], benchmarks, "L2")
result["L3"] = apply_benchmarks(result["L3"], benchmarks, "L3", platform_benchmarks=plat_benchmarks)
result["L4"] = apply_benchmarks(result["L4"], benchmarks, "L4")
diagnostics = run_diagnostics(result, p3_cfg)
title = format_p3_title(result)
body = format_p3_report(result, diagnostics)
ok_push, err_push = send_markdown(title=title, text=body)
if ok_push:
return jsonify(ok=True, message=f"P3 周报已推送: {title}")
return jsonify(ok=False, error=f"推送失败: {err_push}")
except Exception as e:
log.exception(f"P3 推送出错: {e}")
return jsonify(ok=False, error=str(e))
@app.route("/api/chat", methods=["POST"])
def chat():
data = request.get_json(force=True)
messages = data.get("messages", [])
report_context = data.get("report_context", "")
biz_note = (data.get("biz_note") or "").strip()
if not messages:
return jsonify(ok=False, error="无对话内容")
try:
biz_ctx = None
if biz_note:
biz_ctx = f"【用户补充的业务备注】\n{biz_note}"
reply = chat_with_chence(messages, report_context, business_context=biz_ctx)
return jsonify(ok=True, reply=reply)
except Exception as e:
log.exception(f"对话出错: {e}")
return jsonify(ok=False, error=str(e))
# ─────────────────────────────────────────────
# 定时推送:自动同步 + 日报 + 周报 → 钉钉
# ─────────────────────────────────────────────
def _auto_sync():
"""定时自动同步所有 API 数据源。"""
from src.loader import write_api_data_to_sheets
config = load_config(CONFIG_PATH)
platforms = [
("Meta", "meta_api", "src.meta_api", "fetch_meta_data"),
("Google", "google_ads_api", "src.google_api", "fetch_google_data"),
("Criteo", "criteo_api", "src.criteo_api", "fetch_criteo_data"),
("Bing", "bing_api", "src.bing_api", "fetch_bing_data"),
]
for name, cfg_key, mod_path, fn_name in platforms:
p_cfg = config.get(cfg_key, {})
if not p_cfg.get("enabled"):
continue
try:
import importlib
mod = importlib.import_module(mod_path)
fetch_fn = getattr(mod, fn_name)
df = fetch_fn(days_back=p_cfg.get("days_back", 90))
if df.empty:
log.info(f"[自动同步] {name}: 无数据")
continue
save_path = _root / "data" / f"{cfg_key}_data.csv"
save_path.parent.mkdir(parents=True, exist_ok=True)
df.to_csv(save_path, index=False)
try:
res = write_api_data_to_sheets(df, config_path=CONFIG_PATH)
log.info(f"[自动同步] {name}: {len(df)} 条, Sheets +{res.get('added', 0)} 行")
except Exception as e:
log.warning(f"[自动同步] {name}: 写 Sheets 失败: {e}")
except Exception as e:
log.warning(f"[自动同步] {name}: 同步失败: {e}")
_monitor_cache["data"] = None
_monitor_cache["ts"] = None
log.info("[自动同步] 完成")
def _push_daily_report():
"""每天 9:30 执行:推送监控告警 + 昨日日报到钉钉。"""
try:
import pytz
yesterday = (datetime.now(pytz.timezone("Asia/Shanghai")) - timedelta(days=1)).date()
log.info(f"[定时] 生成日报: {yesterday}")
# 1) 推送监控告警
try:
monitor_result = run_daily_monitor(CONFIG_PATH, target_date=yesterday)
mon_title, mon_body = format_monitor_dingtalk(monitor_result)
ok_m, err_m = send_markdown(title=mon_title, text=mon_body)
if ok_m:
log.info(f"[定时] 监控已推送: {mon_title}")
else:
log.warning(f"[定时] 监控推送失败: {err_m}")
except Exception as e:
log.warning(f"[定时] 监控推送异常: {e}")
# 2) 推送日报
result = run_daily_analysis(config_path=CONFIG_PATH, target_date=yesterday)
if result.get("error"):
log.warning(f"[定时] 日报跳过: {result['error']}")
return
title = format_daily_title(result)
body = format_daily_report(result)
ok, err = send_markdown(title=title, text=body)
if ok:
log.info(f"[定时] 日报已推送: {title}")
else:
log.warning(f"[定时] 日报推送失败: {err}")
except Exception as e:
log.exception(f"[定时] 日报异常: {e}")
def _push_weekly_report():
"""每周一 9:30 执行:推送上周周报到钉钉。"""
try:
log.info("[定时] 生成周报")
df = load_weekly_data(CONFIG_PATH)
weeks = get_available_weeks(df)
if len(weeks) < 2:
log.warning("[定时] 周报跳过: 数据不足两周")
return
year, week = weeks[-2]
result = run_analysis(config_path=CONFIG_PATH, target_year=year, target_week=week)
title = format_title(result)
body = format_report(result)
ok, err = send_markdown(title=title, text=body)
if ok:
log.info(f"[定时] 周报已推送: {title}")
else:
log.warning(f"[定时] 周报推送失败: {err}")
except Exception as e:
log.exception(f"[定时] 周报异常: {e}")
def _init_scheduler():
"""启动后台定时任务。"""
try:
from apscheduler.schedulers.background import BackgroundScheduler
from apscheduler.triggers.cron import CronTrigger
import pytz
except ImportError:
log.warning("apscheduler 或 pytz 未安装,定时任务未启动")
return
tz = pytz.timezone("Asia/Shanghai")
config = load_config(CONFIG_PATH)
schedule_cfg = config.get("schedule", {})
if schedule_cfg.get("disabled"):
log.info("[定时] 定时任务已禁用 (schedule.disabled: true)")
return
sync_cron = schedule_cfg.get("sync_cron", "0 9 * * *").strip().split()
daily_cron = schedule_cfg.get("daily_cron", "30 9 * * *").strip().split()
weekly_cron = schedule_cfg.get("weekly_cron", "30 9 * * 1").strip().split()
scheduler = BackgroundScheduler()
if len(sync_cron) == 5:
mi, hr, d, mo, dow = sync_cron
scheduler.add_job(
_auto_sync,
CronTrigger(minute=mi, hour=hr, day=d, month=mo, day_of_week=dow, timezone=tz),
id="auto_sync",
)
log.info(f"[定时] 自动同步已注册: {' '.join(sync_cron)} (Asia/Shanghai)")
if len(daily_cron) == 5:
mi, hr, d, mo, dow = daily_cron
scheduler.add_job(
_push_daily_report,
CronTrigger(minute=mi, hour=hr, day=d, month=mo, day_of_week=dow, timezone=tz),
id="daily_report",
)
log.info(f"[定时] 日报任务已注册: {' '.join(daily_cron)} (Asia/Shanghai)")
if len(weekly_cron) == 5:
mi, hr, d, mo, dow = weekly_cron
scheduler.add_job(
_push_weekly_report,
CronTrigger(minute=mi, hour=hr, day=d, month=mo, day_of_week=dow, timezone=tz),
id="weekly_report",
)
log.info(f"[定时] 周报任务已注册: {' '.join(weekly_cron)} (Asia/Shanghai)")
scheduler.start()
def start_web(host: str = "0.0.0.0", port: int = None):
port = port or int(os.environ.get("PORT", 5000))
_init_scheduler()
if os.environ.get("CLOUD") != "1":
import webbrowser
webbrowser.open(f"http://127.0.0.1:{port}")
app.run(host=host, port=port, debug=False)
if __name__ == "__main__":
start_web()
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