Compare commits
| Author | SHA1 | Date | |
|---|---|---|---|
 hz4th_coder
|
4da5e091a5 | ||
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hz4th_coder
|
adc54d509f |
@@ -24,7 +24,7 @@
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| 📑 AI 分析详情 | `/analysis/<id>` | 研报正文 + **大模型参考的数据源**（RAG新闻/概况/指标/评级/持仓/提示词） |
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| 🧭 持仓跟踪报告 | `/tracking` | 产业链深度跟踪报告总览（⏰ 自动化页入口进入） |
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| 🔧 系统设置 | `/settings` | 邮件 SMTP + 大模型接口配置 |
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| ⚙️ 数据管理 | `/admin` | 数据统计、向量库状态、一键重灌、重建回测、依赖体检 |
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| ⚙️ 数据管理 | `/admin` | 数据统计、向量库状态、一键重灌、重建回测、**定时报告手动触发与日志** |
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---
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@@ -132,6 +132,8 @@ cd works/stock-advisor
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| `notification_log` | 舆情通知日志 | news_id/importance/status |
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| `watch_targets` | 跟踪目标（概念/主题/股票） | type/name/keywords/enabled |
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| `tracking_reports` | 跟踪报告（含类型/数据源/影响度 JSON） | target_type/code/report/meta |
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| `report_log` | 定时报告发送日志 | kind/subject/status |
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| `global_markets` | 全球主要指数（模拟） | date/data(JSON) |
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---
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@@ -219,14 +221,31 @@ cd works/stock-advisor
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- **重大变化通知**：impact_score ≥ 阈值（默认 65）自动邮件（股票/概念通用）
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- **页面 `/tracking`**：股票+概念报告总览；**⏰ 自动化**页可管理持仓与目标、查看最近报告
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### 5. 系统设置（/settings）
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### 6. 系统设置（/settings）
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- **📧 邮件**：SMTP 服务器/端口/加密模式（plain/starttls/ssl）/账号/密码/收件人 + 测试邮件
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- **🤖 大模型**：base_url / api_key / model（**运行时生效**）+ 测试连接
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- **📰 监控**：开关/间隔/分类/阈值/关键词 + 立即扫描 + 通知日志
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> 设置存入 `settings` 表，优先于 `config.py` 默认值，无需改代码。
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### 7. 每日定时报告（engine/report.py + reports.py + cron）
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工作日自动发送两封行情报告到邮箱：
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| 时段 | cron | 内容 |
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|---|---|---|
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| 🌅 盘前分析 | `0 9 * * 1-5` | 昨日市场回顾 / 昨日至今要闻 / 全球市场 / 持仓与关注目标 / 盘前研判 |
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| 🌇 盘后总结 | `30 15 * * 1-5` | 今日市场总结 / 今日要闻 / 全球市场 / 持仓表现 / 盘后研判 |
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每期输出**两份报告**：
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- **简单版**：邮件正文（指数/涨跌结构/要闻/持仓/目标 + AI 研判速览）
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- **详细版**：HTML 附件（数据总览表格 + 全球市场 + 持仓明细 + AI 深度分析全文）
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- **全球市场数据** `global_markets` 表（模拟）：道琼斯/纳斯达克/标普/恒生/日经/KOSPI/德法英等 9 大指数
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- 报告由 DeepSeek 基于当日数据生成研判（简版+详版两次调用），失败自动降级为数据速览
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- **手动触发**：数据管理页「定时报告」卡片（🌅/🌇 按钮）+ 发送日志 `report_log` 表
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- CLI：`python3 reports.py premarket|postmarket`
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---
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## 🔌 API 文档
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@@ -364,6 +383,7 @@ IS_MOCK = False
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| v1.4.0 | 持仓跟踪智能体：产业链上下游深度分析（上游供给/成本、下游需求/景气、同业），影响度判定+重大变化通知 |
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| v1.5.0 | 舆情监控与持仓跟踪合并为「⏰ 自动化」导航入口（双选项卡）；修复布尔设置存储兼容 |
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| v1.6.0 | 目标跟踪：概念/主题/股票（watch_targets），概念智能体分析+受益个股，持仓管理与目标管理，报告支持双类型 |
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| v1.7.0 | 每日定时报告：工作日 9:00 盘前 / 15:30 盘后，简版正文+详细版附件，全球市场数据，cron 定时+手动触发 |
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---
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@@ -741,6 +741,32 @@ def api_targets_delete(tid):
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return jsonify(delete_target(tid))
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# ------------------------------------------------------------------ 定时报告
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@app.route("/api/report/send", methods=["POST"])
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def api_report_send():
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"""手动触发定时报告（后台生成 + 邮件）"""
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from engine.report import send_daily_report
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import threading
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body = request.get_json(silent=True) or {}
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kind = body.get("kind", "premarket")
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def run():
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try:
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r = send_daily_report(kind)
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log.info("report send: %s", r)
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except Exception as e:
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log.error("report send fail: %s", e)
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threading.Thread(target=run, daemon=True).start()
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return jsonify({"ok": True, "msg": f"{'盘前分析' if kind == 'premarket' else '盘后总结'}生成已启动，约需 1-2 分钟"})
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@app.route("/api/report/log")
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def api_report_log():
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from engine.report import report_log
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return jsonify({"items": report_log()})
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# ------------------------------------------------------------------ 数据管理
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@app.route("/api/admin/stats")
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def api_admin_stats():
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+17
-1
@@ -164,12 +164,28 @@ CREATE TABLE IF NOT EXISTS watch_targets (
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created_at TEXT DEFAULT (datetime('now','localtime'))
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);
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CREATE TABLE IF NOT EXISTS report_log (
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id INTEGER PRIMARY KEY AUTOINCREMENT,
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kind TEXT DEFAULT '', -- premarket / postmarket
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subject TEXT DEFAULT '',
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brief_len INTEGER DEFAULT 0,
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detail_len INTEGER DEFAULT 0,
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status TEXT DEFAULT 'sent',
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message TEXT DEFAULT '',
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sent_at TEXT DEFAULT (datetime('now','localtime'))
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);
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CREATE TABLE IF NOT EXISTS market_index (
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date TEXT PRIMARY KEY,
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sh REAL DEFAULT 0, -- 上证指数（点）
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sz REAL DEFAULT 0, -- 深证成指（点）
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cy REAL DEFAULT 0 -- 创业板指（点）
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);
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CREATE TABLE IF NOT EXISTS global_markets (
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date TEXT PRIMARY KEY,
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data TEXT DEFAULT '{}' -- JSON：全球主要指数 {key: {value, chg}}
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);
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"""
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@@ -235,7 +251,7 @@ def wipe_all():
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for t in ("stock_daily", "inst_ratings", "fund_holdings", "news",
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"institutions", "stocks", "watchlist", "analysis_cache", "analysis_history",
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"market_index", "strategy_backtests", "notification_log", "tracking_reports",
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"watch_targets"):
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"watch_targets", "global_markets", "report_log"):
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with db() as conn:
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conn.execute(f'DELETE FROM "{t}"')
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with db() as conn:
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+17
-3
@@ -30,11 +30,25 @@ STRONG_WORDS = ["回购", "中标", "减持", "问询", "停牌", "重组", "预
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# ===================================================================== 邮件
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def send_email(subject, html_body, to=None, cfg=None, sender_name=None):
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"""发送 HTML 邮件。cfg 来自设置；失败抛异常（调用方捕获）"""
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def send_email(subject, html_body, to=None, cfg=None, sender_name=None, attachments=None):
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"""发送 HTML 邮件。cfg 来自设置；attachments: [{filename, content(bytes)}]；失败抛异常"""
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from email.mime.multipart import MIMEMultipart
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from email.mime.base import MIMEBase
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from email import encoders
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cfg = cfg or mail_config()
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to = to or cfg["email_to"]
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msg = MIMEText(html_body, "html", "utf-8")
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if attachments:
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msg = MIMEMultipart()
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msg.attach(MIMEText(html_body, "html", "utf-8"))
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for att in attachments:
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part = MIMEBase("application", "octet-stream")
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part.set_payload(att.get("content") or b"")
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encoders.encode_base64(part)
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part.add_header("Content-Disposition", "attachment",
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filename=("utf-8", "", att.get("filename", "report.html")))
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msg.attach(part)
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else:
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msg = MIMEText(html_body, "html", "utf-8")
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msg["From"] = formataddr((sender_name or cfg["sender_name"], cfg["smtp_user"]))
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msg["To"] = to
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msg["Subject"] = subject
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@@ -0,0 +1,463 @@
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# -*- coding: utf-8 -*-
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"""
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每日行情报告引擎（盘前 / 盘后）
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- premarket : 工作日 9:00 —— 昨日市场回顾 / 昨日至今要闻 / 全球市场 / 持仓与关注目标 / 盘前研判
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- postmarket : 交易日 15:30 —— 今日市场总结 / 今日要闻 / 全球市场 / 持仓表现 / 盘后研判
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每期输出两份报告：
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简单版 —— 邮件正文（HTML，快速浏览）
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详细版 —— HTML 附件（完整结构化 + AI 深度解读）
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"""
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import datetime as dt
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import html as html_mod
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import json
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import logging
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import time
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from database import query, query_one, execute
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from settings import mail_config
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from engine.analyst import llm_chat
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log = logging.getLogger("report")
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GLOBAL_ORDER = ["dji", "nasdaq", "sp500", "hsi", "nikkei", "kospi", "dax", "cac", "ftse"]
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KIND_META = {
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"premarket": {"name": "盘前分析", "scope": "昨日与今日", "title": "盘前 · 昨日市场回顾与今日展望"},
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"postmarket": {"name": "盘后总结", "scope": "今日", "title": "盘后 · 今日市场总结"},
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}
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# ===================================================================== 数据采集
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def latest_trading_day():
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r = query_one("SELECT MAX(date) d FROM stock_daily")
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return r["d"] if r else dt.date.today().isoformat()
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def collect_market(day):
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"""指数 / 涨跌 / 量能 / 行业 / 个股"""
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idx = query("SELECT * FROM market_index WHERE date<=? ORDER BY date DESC LIMIT 2", (day,))
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latest = idx[0] if idx else {}
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prev = idx[1] if len(idx) > 1 else latest
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inds = []
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for k, label in (("sh", "上证指数"), ("sz", "深证成指"), ("cy", "创业板指")):
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cur, old = latest.get(k, 0), prev.get(k, 0) or 1
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inds.append({"key": k, "label": label, "value": cur,
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"chg": round((cur - old) / old * 100, 2)})
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stat = query_one(
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"SELECT COUNT(*) total, SUM(CASE WHEN change_pct>0 THEN 1 ELSE 0 END) up,"
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"SUM(CASE WHEN change_pct<0 THEN 1 ELSE 0 END) down,"
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"SUM(CASE WHEN change_pct>=9.8 THEN 1 ELSE 0 END) limit_up,"
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"SUM(CASE WHEN change_pct<=-9.8 THEN 1 ELSE 0 END) limit_down,"
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"ROUND(SUM(amount)/10000,2) amount_yi "
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"FROM stock_daily WHERE date=?", (day,))
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heat = query(
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"SELECT s.industry, ROUND(AVG(d.change_pct),2) chg, COUNT(*) cnt "
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"FROM stock_daily d JOIN stocks s ON s.code=d.code WHERE d.date=? "
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"GROUP BY s.industry ORDER BY chg DESC", (day,))
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gainers = query(
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"SELECT s.name, s.code, s.industry, d.change_pct FROM stock_daily d "
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"JOIN stocks s ON s.code=d.code WHERE d.date=? ORDER BY d.change_pct DESC LIMIT 8", (day,))
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losers = query(
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"SELECT s.name, s.code, s.industry, d.change_pct FROM stock_daily d "
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"JOIN stocks s ON s.code=d.code WHERE d.date=? ORDER BY d.change_pct ASC LIMIT 8", (day,))
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return {"date": day, "indexes": inds, "stat": stat, "heat": heat,
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"gainers": gainers, "losers": losers}
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def collect_news(since_date, limit=20):
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rows = query(
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"SELECT id,title,content,source,category,publish_date,sentiment,related_stocks FROM news "
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"WHERE publish_date>=? ORDER BY publish_date DESC, id DESC LIMIT ?", (since_date, limit))
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# 按重要度排序（类别权重 + 情感强度）
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w = {"公司": 3, "业绩": 3, "机构观点": 2, "行业": 2, "市场": 1}
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for n in rows:
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n["_score"] = w.get(n["category"], 1) * 10 + abs(n["sentiment"]) * 5
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rows.sort(key=lambda x: x["_score"], reverse=True)
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return rows
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def collect_positions():
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rows = query(
|
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"SELECT w.code, s.name, s.industry, s.market_cap, d.close, d.change_pct "
|
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"FROM watchlist w JOIN stocks s ON s.code=w.code "
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"LEFT JOIN stock_daily d ON d.code=s.code AND d.date=(SELECT MAX(date) FROM stock_daily) "
|
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"ORDER BY w.added_at")
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out = []
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for r in rows:
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sc = query_one(
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"SELECT AVG(sentiment) s FROM news WHERE (related_stocks=? OR related_stocks LIKE ? OR related_stocks LIKE ?) "
|
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"AND publish_date>=date('now','-7 day')", (r["code"], f"%,{r['code']}", f"{r['code']},%"))
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out.append({**r, "news_score": round(sc["s"], 2) if sc and sc["s"] is not None else 0})
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return out
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|
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|
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def collect_targets():
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tgts = query("SELECT id, type, code, name, keywords FROM watch_targets WHERE enabled=1")
|
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out = []
|
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for t in tgts:
|
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if t["type"] == "stock" and t["code"]:
|
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latest = query_one(
|
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"SELECT meta, created_at FROM tracking_reports WHERE code=? ORDER BY id DESC LIMIT 1", (t["code"],))
|
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else:
|
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latest = query_one(
|
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"SELECT meta, created_at FROM tracking_reports WHERE code=? ORDER BY id DESC LIMIT 1",
|
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(f"CONCEPT:{t['name']}",))
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m = json.loads(latest["meta"]) if latest else {}
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out.append({"type": t["type"], "name": t["name"],
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"impact": m.get("impact_score"), "change_kind": m.get("change_kind"),
|
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"summary": m.get("summary", ""), "tracked_at": latest["created_at"] if latest else None})
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return out
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|
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|
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def collect_global():
|
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r = query_one("SELECT date, data FROM global_markets ORDER BY date DESC LIMIT 1")
|
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if not r:
|
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return []
|
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try:
|
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data = json.loads(r["data"])
|
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except Exception:
|
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return []
|
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items = []
|
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for k in GLOBAL_ORDER:
|
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if k in data:
|
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items.append(data[k])
|
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return items
|
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|
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|
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# ===================================================================== 文本渲染
|
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def fmt_market(mkt):
|
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s = mkt["stat"] or {}
|
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idx_txt = " ".join(f"{i['label']} {i['value']:.2f} ({i['chg']:+.2f}%)" for i in mkt["indexes"])
|
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heat_txt = "、".join(f"{h['industry']}({h['chg']:+.2f}%)" for h in mkt["heat"][:6]) or "无"
|
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g_txt = "、".join(f"{g['name']}({g['change_pct']:+.2f}%)" for g in mkt["gainers"][:5])
|
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l_txt = "、".join(f"{g['name']}({g['change_pct']:+.2f}%)" for g in mkt["losers"][:5])
|
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return {
|
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"idx": idx_txt,
|
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"breadth": (f"上涨 {s.get('up',0)} / 下跌 {s.get('down',0)} 家，"
|
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f"涨停 {s.get('limit_up',0)} / 跌停 {s.get('limit_down',0)}，"
|
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f"两市成交 {s.get('amount_yi',0)} 亿"),
|
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"heat": heat_txt,
|
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"gainers": g_txt or "无",
|
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"losers": l_txt or "无",
|
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}
|
||||
|
||||
|
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def fmt_news(news, top=8):
|
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lines = []
|
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for n in news[:top]:
|
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tone = "利好" if n["sentiment"] > 0 else ("利空" if n["sentiment"] < 0 else "中性")
|
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lines.append(f"- [{n['publish_date']}] {n['title']}（{n['category']}·{tone}{n['sentiment']:+.2f}）{n['content'][:60]}")
|
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return "\n".join(lines) or "（暂无）"
|
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|
||||
|
||||
def fmt_positions(pos):
|
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if not pos:
|
||||
return "（当前无持仓/自选股）"
|
||||
return "\n".join(
|
||||
f"- {p['name']}({p['code']}) {p['industry']} 收盘{p['close']} ({p['change_pct']:+.2f}%) 市值{p['market_cap']:.0f}亿 近7日消息面{p['news_score']:+.2f}"
|
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for p in pos)
|
||||
|
||||
|
||||
def fmt_targets(tgts):
|
||||
if not tgts:
|
||||
return "（当前无跟踪目标）"
|
||||
return "\n".join(
|
||||
f"- [{t['type']}] {t['name']} 影响度{t['impact'] or '--'}/100 {t['change_kind'] or ''} {t['summary'][:50]}"
|
||||
for t in tgts)
|
||||
|
||||
|
||||
def fmt_global(items):
|
||||
return " ".join(f"{g.get('label','')} {g.get('value',0):.2f} ({g.get('chg',0):+.2f}%)" for g in items) or "（暂无）"
|
||||
|
||||
|
||||
# ===================================================================== 生成报告
|
||||
def _build_context(kind):
|
||||
day = latest_trading_day()
|
||||
mkt = collect_market(day)
|
||||
fm = fmt_market(mkt)
|
||||
if kind == "premarket":
|
||||
news = collect_news(day, limit=24)
|
||||
scope_txt = "昨日/最近交易日"
|
||||
else:
|
||||
news = collect_news(day, limit=24)
|
||||
scope_txt = "今日"
|
||||
pos = collect_positions()
|
||||
tgts = collect_targets()
|
||||
glob = collect_global()
|
||||
ctx = {
|
||||
"kind_name": KIND_META[kind]["name"],
|
||||
"date": day,
|
||||
"scope": scope_txt,
|
||||
"mkt": mkt, "fm": fm,
|
||||
"news": news, "news_txt": fmt_news(news, 10),
|
||||
"pos": pos, "pos_txt": fmt_positions(pos),
|
||||
"tgts": tgts, "tgts_txt": fmt_targets(tgts),
|
||||
"global_txt": fmt_global(glob),
|
||||
"global": glob,
|
||||
}
|
||||
return ctx
|
||||
|
||||
|
||||
def _base_prompt(ctx, detailed):
|
||||
d = ctx["date"]
|
||||
title = KIND_META[ctx["kind_name"] if ctx["kind_name"] in KIND_META else "premarket"]["title"] if False else ""
|
||||
kind = "盘前分析" if "盘前" in ctx["kind_name"] else "盘后总结"
|
||||
return f"""你是资深A股市场分析师，请基于下方【数据】生成一份{kind}报告。
|
||||
|
||||
【报告日期】{d}
|
||||
【指数】{ctx['fm']['idx']}
|
||||
【涨跌结构】{ctx['fm']['breadth']}
|
||||
【领涨行业】{ctx['fm']['heat']}
|
||||
【领涨个股】{ctx['fm']['gainers']}
|
||||
【领跌个股】{ctx['fm']['losers']}
|
||||
【重点要闻】
|
||||
{ctx['news_txt']}
|
||||
【全球市场】
|
||||
{ctx['global_txt']}
|
||||
【持仓/自选股】
|
||||
{ctx['pos_txt']}
|
||||
【关注目标/主题】
|
||||
{ctx['tgts_txt']}
|
||||
"""
|
||||
|
||||
|
||||
def _brief_prompt(ctx):
|
||||
return _base_prompt(ctx, False) + """
|
||||
【输出要求】输出一份精炼的盘前/盘后速览（约 200-300 字），Markdown 格式，包含：
|
||||
1. 一句话大盘研判
|
||||
2. 3-5 条关键要点（行情/消息/持仓/主题）
|
||||
3. 今日关注提示
|
||||
要求信息密集、数据准确，不要编造数据。"""
|
||||
|
||||
|
||||
def _detail_prompt(ctx):
|
||||
return _base_prompt(ctx, True) + """
|
||||
【输出要求】输出一份完整的盘前/盘后分析报告（Markdown），结构如下：
|
||||
## 一、市场概览（指数表现/涨跌结构/量能/领涨领跌板块个股解读）
|
||||
## 二、消息面解析（分类解读重点要闻及影响：政策/行业/公司/机构观点）
|
||||
## 三、全球市场联动（外围市场表现及对A股的传导）
|
||||
## 四、持仓表现（逐只点评：涨跌、评分依据、近期消息面）
|
||||
## 五、关注目标/主题（各主题/个股的最新动态与影响度解读）
|
||||
## 六、操作策略与风险提示
|
||||
数据须严格来自上文【数据】，可补充合理分析逻辑，不得编造数字。"""
|
||||
|
||||
|
||||
def generate_reports(kind):
|
||||
"""生成 (brief_html, detail_html)"""
|
||||
ctx = _build_context(kind)
|
||||
brief_md = ""
|
||||
detail_md = ""
|
||||
try:
|
||||
brief_md = llm_chat([
|
||||
{"role": "system", "content": "你是一名严谨专业的A股市场分析师。"},
|
||||
{"role": "user", "content": _brief_prompt(ctx)},
|
||||
]).strip()
|
||||
except Exception as e:
|
||||
log.warning("brief llm fail: %s", e)
|
||||
try:
|
||||
detail_md = llm_chat([
|
||||
{"role": "system", "content": "你是一名严谨专业的A股市场分析师。"},
|
||||
{"role": "user", "content": _detail_prompt(ctx)},
|
||||
]).strip()
|
||||
except Exception as e:
|
||||
log.warning("detail llm fail: %s", e)
|
||||
|
||||
brief_html = _render_brief(ctx, brief_md)
|
||||
detail_html = _render_detail(ctx, detail_md)
|
||||
return brief_html, detail_html
|
||||
|
||||
|
||||
# ===================================================================== 渲染
|
||||
def _render_brief(ctx, brief_md):
|
||||
kind = KIND_META[ctx["kind_name"] if ctx["kind_name"] in KIND_META else "premarket"]
|
||||
rows = []
|
||||
for i in ctx["mkt"]["indexes"]:
|
||||
rows.append(f"<b style='color:{'#e03e3e' if i['chg']>=0 else '#17a34a'}'>{i['label']} {i['value']:.2f} ({i['chg']:+.2f}%)</b>")
|
||||
news_li = "".join(f"<li>[{n['publish_date']}] {html_mod.escape(n['title'])} <span style='color:#888'>({n['category']})</span></li>"
|
||||
for n in ctx["news"][:6]) or "<li>暂无</li>"
|
||||
pos_li = "".join(f"<li><b>{p['name']}</b>({p['code']}) 收{p['close']} "
|
||||
f"<b style='color:{'#e03e3e' if p['change_pct']>=0 else '#17a34a'}'>{p['change_pct']:+.2f}%</b> · {p['industry']}</li>"
|
||||
for p in ctx["pos"]) or "<li>暂无持仓</li>"
|
||||
tgt_li = "".join(f"<li>{html_mod.escape(t['name'])}（影响度{t['impact'] or '--'}，{t['change_kind'] or '—'}）</li>"
|
||||
for t in ctx["tgts"][:5]) or "<li>暂无目标</li>"
|
||||
gb = " ｜ ".join(f"{g.get('label','')} {g.get('value',0):.2f} "
|
||||
f"<b style='color:{'#e03e3e' if g.get('chg',0)>=0 else '#17a34a'}'>({g.get('chg',0):+.2f}%)</b>" for g in ctx["global"][:6])
|
||||
ai = html_mod.escape(brief_md) if brief_md else "（AI 简评生成失败，请查看附件详细版）"
|
||||
return f"""<html><body style="font-family:Microsoft YaHei,Arial;background:#f5f6f8;padding:20px;">
|
||||
<div style="max-width:680px;margin:auto;background:#fff;border-radius:8px;border:1px solid #e5e7eb;overflow:hidden;">
|
||||
<div style="background:#1e293b;color:#fff;padding:16px 22px;">
|
||||
<div style="font-size:20px;font-weight:bold;">📊 智能荐股 · {kind['name']}</div>
|
||||
<div style="font-size:12px;opacity:.8;margin-top:4px;">{ctx['date']} · 简版速览 · 详细版见附件</div>
|
||||
</div>
|
||||
<div style="padding:18px 22px;">
|
||||
<div style="font-size:15px;color:#333;margin-bottom:6px;">🔎 大盘：</div>
|
||||
<div style="font-size:15px;">{' '.join(rows)}</div>
|
||||
<div style="color:#666;font-size:13px;margin-top:4px;">{ctx['fm']['breadth']}</div>
|
||||
<div style="color:#666;font-size:13px;margin-top:4px;"><b>领涨行业：</b>{ctx['fm']['heat']}</div>
|
||||
<div style="margin:14px 0;border-top:1px solid #eee;"></div>
|
||||
<div style="font-size:14px;color:#333;margin-bottom:6px;">📰 重点要闻：</div>
|
||||
<ul style="color:#444;font-size:13px;padding-left:20px;line-height:1.8;">{news_li}</ul>
|
||||
<div style="margin:14px 0;border-top:1px solid #eee;"></div>
|
||||
<div style="font-size:14px;color:#333;margin-bottom:6px;">🌏 全球市场：</div>
|
||||
<div style="color:#444;font-size:13px;">{gb}</div>
|
||||
<div style="margin:14px 0;border-top:1px solid #eee;"></div>
|
||||
<div style="font-size:14px;color:#333;margin-bottom:6px;">💼 持仓：</div>
|
||||
<ul style="color:#444;font-size:13px;padding-left:20px;line-height:1.8;">{pos_li}</ul>
|
||||
<div style="margin:14px 0;border-top:1px solid #eee;"></div>
|
||||
<div style="font-size:14px;color:#333;margin-bottom:6px;">🎯 关注目标/主题：</div>
|
||||
<ul style="color:#444;font-size:13px;padding-left:20px;line-height:1.8;">{tgt_li}</ul>
|
||||
<div style="margin:14px 0;border-top:1px solid #eee;"></div>
|
||||
<div style="font-size:14px;color:#333;margin-bottom:6px;">🤖 AI 研判：</div>
|
||||
<div style="color:#333;font-size:13px;line-height:1.8;white-space:pre-wrap;">{ai}</div>
|
||||
</div>
|
||||
<div style="background:#f8fafc;padding:10px 22px;color:#94a3b8;font-size:11px;text-align:center;">
|
||||
智能荐股系统自动生成 · 内容基于模拟数据，仅供演示，不构成投资建议
|
||||
</div></div></body></html>"""
|
||||
|
||||
|
||||
def _md_to_html(md):
|
||||
"""极简 Markdown → HTML（用于附件详细版）"""
|
||||
md = html_mod.escape(md or "")
|
||||
out, in_list = [], False
|
||||
for line in md.splitlines():
|
||||
line = line.rstrip()
|
||||
if not line:
|
||||
if in_list:
|
||||
out.append("</ul>"); in_list = False
|
||||
continue
|
||||
if line.startswith("## "):
|
||||
if in_list:
|
||||
out.append("</ul>"); in_list = False
|
||||
out.append(f"<h2>{line[3:]}</h2>")
|
||||
elif line.startswith("### "):
|
||||
if in_list:
|
||||
out.append("</ul>"); in_list = False
|
||||
out.append(f"<h3>{line[4:]}</h3>")
|
||||
elif line.startswith("##"):
|
||||
if in_list:
|
||||
out.append("</ul>"); in_list = False
|
||||
out.append(f"<h2>{line[2:].strip()}</h2>")
|
||||
elif line.startswith("- "):
|
||||
if not in_list:
|
||||
out.append("<ul>"); in_list = True
|
||||
out.append(f"<li>{line[2:]}</li>")
|
||||
elif line.startswith("# "):
|
||||
if in_list:
|
||||
out.append("</ul>"); in_list = False
|
||||
out.append(f"<h1>{line[2:]}</h1>")
|
||||
else:
|
||||
if in_list:
|
||||
out.append("</ul>"); in_list = False
|
||||
out.append(f"<p>{line}</p>")
|
||||
if in_list:
|
||||
out.append("</ul>")
|
||||
return "".join(out)
|
||||
|
||||
|
||||
def _render_detail(ctx, detail_md):
|
||||
kind = KIND_META[ctx["kind_name"] if ctx["kind_name"] in KIND_META else "premarket"]
|
||||
idx_rows = "".join(
|
||||
f"<tr><td>{i['label']}</td><td>{i['value']:.2f}</td>"
|
||||
f"<td style='color:{'#e03e3e' if i['chg']>=0 else '#17a34a'}'>{i['chg']:+.2f}%</td></tr>"
|
||||
for i in ctx["mkt"]["indexes"])
|
||||
stat = ctx["mkt"]["stat"] or {}
|
||||
heat_rows = "".join(f"<tr><td>{h['industry']}</td><td>{h['cnt']}</td>"
|
||||
f"<td style='color:{'#e03e3e' if h['chg']>=0 else '#17a34a'}'>{h['chg']:+.2f}%</td></tr>"
|
||||
for h in ctx["mkt"]["heat"])
|
||||
g_rows = "".join(f"<tr><td>{g['name']}</td><td>{g['code']}</td>"
|
||||
f"<td style='color:{'#e03e3e' if g['change_pct']>=0 else '#17a34a'}'>{g['change_pct']:+.2f}%</td></tr>"
|
||||
for g in ctx["mkt"]["gainers"])
|
||||
l_rows = "".join(f"<tr><td>{g['name']}</td><td>{g['code']}</td>"
|
||||
f"<td style='color:{'#e03e3e' if g['change_pct']>=0 else '#17a34a'}'>{g['change_pct']:+.2f}%</td></tr>"
|
||||
for g in ctx["mkt"]["losers"])
|
||||
news_rows = "".join(
|
||||
f"<tr><td>{n['publish_date']}</td><td>{n['category']}</td><td>{html_mod.escape(n['title'])}</td>"
|
||||
f"<td style='color:{'#e03e3e' if n['sentiment']>=0 else '#17a34a'}'>{n['sentiment']:+.2f}</td></tr>"
|
||||
for n in ctx["news"][:15])
|
||||
pos_rows = "".join(
|
||||
f"<tr><td><b>{p['name']}</b>{p['code']}</td><td>{p['industry']}</td><td>{p['close']}</td>"
|
||||
f"<td style='color:{'#e03e3e' if p['change_pct']>=0 else '#17a34a'}'>{p['change_pct']:+.2f}%</td>"
|
||||
f"<td>{p['market_cap']:.0f}亿</td><td>{p['news_score']:+.2f}</td></tr>"
|
||||
for p in ctx["pos"]) or "<tr><td colspan='6'>暂无持仓</td></tr>"
|
||||
gb_rows = "".join(f"<tr><td>{g.get('label','')}</td><td>{g.get('value',0):.2f}</td>"
|
||||
f"<td style='color:{'#e03e3e' if g.get('chg',0)>=0 else '#17a34a'}'>{g.get('chg',0):+.2f}%</td></tr>"
|
||||
for g in ctx["global"])
|
||||
body = _md_to_html(detail_md) if detail_md else "<p>（AI 分析生成失败）</p>"
|
||||
return f"""<!DOCTYPE html><html lang="zh-CN"><head><meta charset="UTF-8">
|
||||
<title>智能荐股 · {kind['name']} {ctx['date']}</title>
|
||||
<style>
|
||||
body{{font-family:Microsoft YaHei,Arial,sans-serif;background:#f5f6f8;padding:24px;color:#333;line-height:1.8;}}
|
||||
.wrap{{max-width:820px;margin:auto;background:#fff;border:1px solid #e5e7eb;border-radius:10px;overflow:hidden;}}
|
||||
.head{{background:#1e293b;color:#fff;padding:20px 28px;}}
|
||||
.head h1{{margin:0;font-size:22px;}}
|
||||
.head .sub{{font-size:12px;opacity:.8;margin-top:4px;}}
|
||||
.body{{padding:20px 28px;}}
|
||||
h2{{border-bottom:2px solid #eef2f7;padding-bottom:8px;margin-top:28px;color:#1e293b;font-size:18px;}}
|
||||
h3{{color:#334155;margin-top:18px;}}
|
||||
table{{width:100%;border-collapse:collapse;margin:10px 0;font-size:13px;}}
|
||||
th,td{{border:1px solid #e5e7eb;padding:7px 10px;text-align:left;}}
|
||||
th{{background:#f8fafc;color:#475569;}}
|
||||
.up{{color:#e03e3e;}}.down{{color:#17a34a;}}
|
||||
.card{{background:#f8fafc;border:1px solid #e5e7eb;border-radius:8px;padding:14px 16px;margin:12px 0;font-size:13px;}}
|
||||
.foot{{background:#f8fafc;padding:12px 28px;color:#94a3b8;font-size:11px;text-align:center;}}
|
||||
</style></head><body><div class="wrap">
|
||||
<div class="head">
|
||||
<h1>📊 智能荐股 · {kind['name']}（{ctx['date']}）</h1>
|
||||
<div class="sub">市场/要闻/全球/持仓/主题 全景分析 · 详细版报告 · 自动生成</div>
|
||||
</div>
|
||||
<div class="body">
|
||||
<h2>〇、数据总览</h2>
|
||||
<div class="card"><b>指数</b><table><tr><th>指数</th><th>收盘</th><th>涨跌</th></tr>{idx_rows}</table>
|
||||
<b>涨跌结构</b>：{ctx['fm']['breadth']}</div>
|
||||
<div class="card"><b>行业热度</b><table><tr><th>行业</th><th>家数</th><th>平均涨跌</th></tr>{heat_rows}</table></div>
|
||||
<div class="card"><b>领涨个股</b><table><tr><th>名称</th><th>代码</th><th>涨跌</th></tr>{g_rows}</table>
|
||||
<b>领跌个股</b><table><tr><th>名称</th><th>代码</th><th>涨跌</th></tr>{l_rows}</table></div>
|
||||
<h2>重点要闻</h2>
|
||||
<table><tr><th>日期</th><th>分类</th><th>标题</th><th>情感</th></tr>{news_rows}</table>
|
||||
<h2>全球市场</h2>
|
||||
<table><tr><th>指数</th><th>点位</th><th>涨跌</th></tr>{gb_rows}</table>
|
||||
<h2>持仓 / 自选股</h2>
|
||||
<table><tr><th>股票</th><th>行业</th><th>收盘</th><th>涨跌</th><th>市值</th><th>消息面</th></tr>{pos_rows}</table>
|
||||
<h2>关注目标 / 主题</h2>
|
||||
{html_mod.escape(ctx['tgts_txt']).replace(chr(10), '<br>')}
|
||||
<h2>AI 深度分析</h2>
|
||||
{body}
|
||||
</div>
|
||||
<div class="foot">智能荐股系统自动生成 · 内容基于模拟数据，仅供演示，不构成投资建议</div>
|
||||
</div></body></html>"""
|
||||
|
||||
|
||||
# ===================================================================== 发送
|
||||
def send_daily_report(kind="premarket"):
|
||||
"""生成并发送报告：正文=简版，附件=详细版 HTML。返回 dict 状态"""
|
||||
from engine.notifier import send_email
|
||||
mc = mail_config()
|
||||
brief_html, detail_html = generate_reports(kind)
|
||||
meta = KIND_META.get(kind, KIND_META["premarket"])
|
||||
subject = f"[智能荐股] {meta['name']} {time.strftime('%Y-%m-%d')}"
|
||||
detail_file = f"智能荐股_{meta['name']}_{time.strftime('%Y%m%d')}.html"
|
||||
try:
|
||||
send_email(subject, brief_html, cfg=mc,
|
||||
attachments=[{"filename": detail_file, "content": detail_html.encode("utf-8")}])
|
||||
execute("INSERT INTO report_log(kind, subject, brief_len, detail_len, status, message) "
|
||||
"VALUES(?,?,?,?,'sent','附件: '||?)",
|
||||
(kind, subject, len(brief_html), len(detail_html), detail_file))
|
||||
return {"ok": True, "subject": subject, "detail_file": detail_file}
|
||||
except Exception as e:
|
||||
execute("INSERT INTO report_log(kind, subject, brief_len, detail_len, status, message) "
|
||||
"VALUES(?,?,?,?,'failed',?)",
|
||||
(kind, subject, len(brief_html), len(detail_html), str(e)))
|
||||
return {"ok": False, "error": str(e)}
|
||||
|
||||
|
||||
def report_log(limit=20):
|
||||
return query("SELECT * FROM report_log ORDER BY id DESC LIMIT ?", (limit,))
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
import sys
|
||||
kind = sys.argv[1] if len(sys.argv) > 1 else "premarket"
|
||||
if kind not in ("premarket", "postmarket"):
|
||||
kind = "premarket"
|
||||
logging.basicConfig(level=logging.INFO)
|
||||
r = send_daily_report(kind)
|
||||
print(r)
|
||||
+28
@@ -0,0 +1,28 @@
|
||||
# -*- coding: utf-8 -*-
|
||||
"""
|
||||
定时报告 CLI 入口（配合 crontab 使用）
|
||||
用法：
|
||||
python3 reports.py premarket # 盘前分析（工作日 9:00）
|
||||
python3 reports.py postmarket # 盘后总结（交易日 15:30）
|
||||
"""
|
||||
import logging
|
||||
import os
|
||||
import sys
|
||||
|
||||
BASE_DIR = os.path.dirname(os.path.abspath(__file__))
|
||||
sys.path.insert(0, BASE_DIR)
|
||||
os.chdir(BASE_DIR)
|
||||
|
||||
from database import init_db
|
||||
|
||||
if __name__ == "__main__":
|
||||
logging.basicConfig(level=logging.INFO,
|
||||
format="%(asctime)s %(levelname)s %(name)s %(message)s")
|
||||
kind = sys.argv[1] if len(sys.argv) > 1 else "premarket"
|
||||
if kind not in ("premarket", "postmarket"):
|
||||
kind = "premarket"
|
||||
init_db()
|
||||
from engine.report import send_daily_report
|
||||
r = send_daily_report(kind)
|
||||
print(f"[{kind}] {r}")
|
||||
sys.exit(0 if r.get("ok") else 1)
|
||||
+32
-2
@@ -15,6 +15,7 @@
|
||||
"""
|
||||
import argparse
|
||||
import datetime as dt
|
||||
import json
|
||||
import math
|
||||
import random
|
||||
import sys
|
||||
@@ -238,7 +239,8 @@ def gen_daily(dates):
|
||||
drift = {0: 0.0011, 1: 0.00025, 2: -0.00085}[trend]
|
||||
# 最近30天加速（制造趋势分化，让荐股有区分度）
|
||||
recent_drift = {0: 0.0045, 1: 0.0001, 2: -0.0045}[trend]
|
||||
base_vol = float_shares * 10000 * random.uniform(0.8, 2.2) # 基准成交量（万股）
|
||||
# 基准成交量（万股）= 流通盘 × 0.4%~1.5% 日换手（贴近真实市场）
|
||||
base_vol = float_shares * 10000 * random.uniform(0.004, 0.015)
|
||||
for i, d in enumerate(dates):
|
||||
phase = max(0, i - (len(dates) - 30))
|
||||
dr = drift + (recent_drift if phase > 0 else 0)
|
||||
@@ -250,7 +252,7 @@ def gen_daily(dates):
|
||||
open_p = prev * (1 + random.gauss(0, vol * 0.5))
|
||||
high = max(open_p, p) * (1 + abs(random.gauss(0, vol * 0.35)))
|
||||
low = min(open_p, p) * (1 - abs(random.gauss(0, vol * 0.35)))
|
||||
volume = base_vol * (1 + 3 * abs(r) / vol) * random.uniform(0.6, 1.4)
|
||||
volume = base_vol * (1 + 1.5 * abs(r) / vol) * random.uniform(0.6, 1.4)
|
||||
amount = volume * (open_p + p) / 2 # 万元
|
||||
chg = (p - prev) / prev * 100
|
||||
daily.append((code, d, round(open_p, 2), round(high, 2), round(low, 2),
|
||||
@@ -339,6 +341,30 @@ def _recent_days(n):
|
||||
return dates
|
||||
|
||||
|
||||
GLOBAL_INDICES = [
|
||||
("dji", "道琼斯", 34000), ("nasdaq", "纳斯达克", 12800), ("sp500", "标普500", 4400),
|
||||
("hsi", "恒生指数", 17500), ("nikkei", "日经225", 33000), ("kospi", "韩国KOSPI", 2500),
|
||||
("dax", "德国DAX", 16000), ("cac", "法国CAC40", 7000), ("ftse", "英国FTSE100", 7500),
|
||||
]
|
||||
|
||||
|
||||
def _gen_global(dates):
|
||||
"""生成全球主要指数模拟序列（随机游走，chg 基于前一交易日）"""
|
||||
vals = {k: v for k, _, v in GLOBAL_INDICES}
|
||||
prev = dict(vals)
|
||||
out = {}
|
||||
for d in dates:
|
||||
row = {}
|
||||
for k, label, _v in GLOBAL_INDICES:
|
||||
vals[k] *= (1 + random.gauss(0.0002, 0.009))
|
||||
row[k] = {"label": label, "value": round(vals[k], 2),
|
||||
"chg": round((vals[k] - prev[k]) / prev[k] * 100, 2)}
|
||||
for k in prev:
|
||||
prev[k] = vals[k]
|
||||
out[d] = row
|
||||
return out
|
||||
|
||||
|
||||
def gen_holdings(price, dates):
|
||||
"""基金季度持仓：2025Q4 / 2026Q1 / 2026Q2"""
|
||||
rows = []
|
||||
@@ -424,6 +450,10 @@ def main():
|
||||
"VALUES(?,?,?,?,?,?,?,?,?)", daily)
|
||||
executemany("INSERT OR REPLACE INTO market_index(date,sh,sz,cy) VALUES(?,?,?,?)",
|
||||
[(d, v["sh"], v["sz"], v["cy"]) for d, v in index.items()])
|
||||
# 全球市场指数（模拟）
|
||||
gm = _gen_global(dates)
|
||||
executemany("INSERT OR REPLACE INTO global_markets(date,data) VALUES(?,?)",
|
||||
[(d, json.dumps(v, ensure_ascii=False)) for d, v in gm.items()])
|
||||
# 回填市值
|
||||
for code, name, industry, board, base, fs, trend, vol, biz in STOCKS:
|
||||
from database import execute as ex
|
||||
|
||||
@@ -40,6 +40,34 @@ async function rebuildBt() {
|
||||
} catch (e) { toast('启动失败'); }
|
||||
}
|
||||
|
||||
/* 定时报告 */
|
||||
async function sendReport(kind) {
|
||||
const btn = event.target; btn.disabled = true;
|
||||
try {
|
||||
const r = await api('/api/report/send', { method: 'POST', headers: { 'Content-Type': 'application/json' }, body: JSON.stringify({ kind }) });
|
||||
toast(r.msg || '已启动');
|
||||
setTimeout(loadReportLog, 60000);
|
||||
setTimeout(loadReportLog, 150000);
|
||||
} catch (e) { toast('启动失败：' + e.message); }
|
||||
btn.disabled = false;
|
||||
}
|
||||
|
||||
async function loadReportLog() {
|
||||
try {
|
||||
const d = await api('/api/report/log');
|
||||
const items = d.items || [];
|
||||
if (!items.length) return;
|
||||
$('#reportLogTb').innerHTML = items.map(r => `
|
||||
<tr>
|
||||
<td style="color:var(--muted)">${r.sent_at}</td>
|
||||
<td>${r.kind === 'premarket' ? '🌅 盘前' : '🌇 盘后'}</td>
|
||||
<td>${escapeHtml(r.subject)}</td>
|
||||
<td><span class="tag ${r.status === 'sent' ? 'tag-推荐' : 'tag-负'}">${r.status}</span></td>
|
||||
<td style="color:var(--text2);font-size:12px">${escapeHtml(r.message || '')}</td>
|
||||
</tr>`).join('');
|
||||
} catch (e) {}
|
||||
}
|
||||
|
||||
async function reseed() {
|
||||
if (!confirm('将清空全部业务数据并重新生成（含向量索引重建，需 1-3 分钟），确定继续？')) return;
|
||||
try {
|
||||
@@ -67,3 +95,4 @@ async function health() {
|
||||
}
|
||||
|
||||
refreshStats();
|
||||
loadReportLog();
|
||||
@@ -13,6 +13,25 @@
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<div class="card mt16">
|
||||
<div class="card-title"><span class="bar" style="background:#8b5cf6"></span>📧 定时报告（工作日 9:00 盘前 / 交易日 15:30 盘后）</div>
|
||||
<div class="flex wrap">
|
||||
<button class="btn btn-primary" onclick="sendReport('premarket')">🌅 手动发送盘前分析</button>
|
||||
<button class="btn btn-primary" onclick="sendReport('postmarket')">🌇 手动发送盘后总结</button>
|
||||
</div>
|
||||
<div class="mt16" style="color:var(--muted);font-size:12px;line-height:1.8">
|
||||
自动触发已配置系统 cron：<code>0 9 * * 1-5</code> 盘前 · <code>30 15 * * 1-5</code> 盘后。<br>
|
||||
每期发送两封形态：<b>简单版</b>（邮件正文速览）+ <b>详细版</b>（HTML 附件）。发送记录见下方表格。
|
||||
</div>
|
||||
<div class="card-title mt16" style="font-size:14px"><span class="bar" style="background:#8b5cf6"></span>发送记录</div>
|
||||
<div style="overflow:auto;max-height:300px">
|
||||
<table>
|
||||
<thead><tr><th>时间</th><th>类型</th><th>主题</th><th>状态</th><th>说明</th></tr></thead>
|
||||
<tbody id="reportLogTb"><tr><td colspan="5" class="empty">暂无记录</td></tr></tbody>
|
||||
</table>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<div class="card mt16">
|
||||
<div class="card-title"><span class="bar" style="background:var(--gold)"></span>系统维护</div>
|
||||
<div class="flex wrap">
|
||||
|
||||
Reference in New Issue
Block a user