329 lines
12 KiB
Python
329 lines
12 KiB
Python
"""Streamlit UI scaffold for the investment assistant."""
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from __future__ import annotations
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import sys
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from datetime import date, timedelta
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from pathlib import Path
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ROOT = Path(__file__).resolve().parents[2]
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if str(ROOT) not in sys.path:
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sys.path.insert(0, str(ROOT))
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import pandas as pd
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import plotly.express as px
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import plotly.graph_objects as go
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import streamlit as st
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from app.backtest.engine import BtConfig, run_backtest
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from app.data.schema import initialize_database
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from app.ingest.checker import run_boot_check
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from app.ingest.tushare import FetchJob, run_ingestion
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from app.llm.explain import make_human_card
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from app.utils.config import get_config
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from app.utils.db import db_session
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def _load_stock_options(limit: int = 500) -> list[str]:
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try:
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with db_session(read_only=True) as conn:
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rows = conn.execute(
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"SELECT ts_code, name FROM stock_basic WHERE list_status = 'L' ORDER BY ts_code"
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).fetchall()
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except Exception:
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return []
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options: list[str] = []
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for row in rows[:limit]:
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code = row["ts_code"]
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name = row["name"] or ""
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label = f"{code} | {name}" if name else code
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options.append(label)
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return options
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def _parse_ts_code(selection: str) -> str:
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return selection.split(' | ')[0].strip().upper()
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def _load_daily_frame(ts_code: str, start: date, end: date) -> pd.DataFrame:
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start_str = start.strftime('%Y%m%d')
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end_str = end.strftime('%Y%m%d')
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range_query = (
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"SELECT trade_date, open, high, low, close, vol, amount "
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"FROM daily WHERE ts_code = ? AND trade_date BETWEEN ? AND ? ORDER BY trade_date"
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)
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fallback_query = (
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"SELECT trade_date, open, high, low, close, vol, amount "
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"FROM daily WHERE ts_code = ? ORDER BY trade_date DESC LIMIT 200"
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)
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with db_session(read_only=True) as conn:
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df = pd.read_sql_query(range_query, conn, params=(ts_code, start_str, end_str))
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if df.empty:
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df = pd.read_sql_query(fallback_query, conn, params=(ts_code,))
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if df.empty:
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return df
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df = df.sort_values('trade_date')
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df['trade_date'] = pd.to_datetime(df['trade_date'])
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df.set_index('trade_date', inplace=True)
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return df
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def render_today_plan() -> None:
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st.header("今日计划")
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st.write("待接入候选池筛选与多智能体决策结果。")
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sample = make_human_card("000001.SZ", "2025-01-01", {"decisions": []})
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st.json(sample)
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def render_backtest() -> None:
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st.header("回测与复盘")
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st.write("在此运行回测、展示净值曲线与代理贡献。")
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default_start = date(2020, 1, 1)
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default_end = date(2020, 3, 31)
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col1, col2 = st.columns(2)
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start_date = col1.date_input("开始日期", value=default_start)
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end_date = col2.date_input("结束日期", value=default_end)
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universe_text = st.text_input("股票列表（逗号分隔）", value="000001.SZ")
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target = st.number_input("目标收益（例：0.035 表示 3.5%）", value=0.035, step=0.005, format="%.3f")
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stop = st.number_input("止损收益（例：-0.015 表示 -1.5%）", value=-0.015, step=0.005, format="%.3f")
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hold_days = st.number_input("持有期（交易日）", value=10, step=1)
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if st.button("运行回测"):
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with st.spinner("正在执行回测..."):
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try:
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universe = [code.strip() for code in universe_text.split(',') if code.strip()]
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cfg = BtConfig(
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id="streamlit_demo",
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name="Streamlit Demo Strategy",
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start_date=start_date,
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end_date=end_date,
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universe=universe,
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params={
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"target": target,
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"stop": stop,
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"hold_days": int(hold_days),
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},
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)
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result = run_backtest(cfg)
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st.success("回测执行完成，详见回测结果摘要。")
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st.json({"nav_records": result.nav_series, "trades": result.trades})
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except Exception as exc: # noqa: BLE001
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st.error(f"回测执行失败：{exc}")
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def render_settings() -> None:
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st.header("数据与设置")
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cfg = get_config()
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token = st.text_input("TuShare Token", value=cfg.tushare_token or "", type="password")
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if st.button("保存设置"):
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cfg.tushare_token = token.strip() or None
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st.success("设置已保存，仅在当前会话生效。")
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st.write("新闻源开关与数据库备份将在此配置。")
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def render_tests() -> None:
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st.header("自检测试")
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st.write("用于快速检查数据库与数据拉取是否正常工作。")
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if st.button("测试数据库初始化"):
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with st.spinner("正在检查数据库..."):
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result = initialize_database()
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if result.skipped:
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st.success("数据库已存在，检查通过。")
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else:
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st.success(f"数据库初始化完成，共执行 {result.executed} 条语句。")
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st.divider()
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if st.button("测试 TuShare 拉取（示例 2024-01-01 至 2024-01-03）"):
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with st.spinner("正在调用 TuShare 接口..."):
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try:
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run_ingestion(
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FetchJob(
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name="streamlit_self_test",
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start=date(2024, 1, 1),
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end=date(2024, 1, 3),
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ts_codes=("000001.SZ",),
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),
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include_limits=False,
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)
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st.success("TuShare 示例拉取完成，数据已写入数据库。")
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except Exception as exc: # noqa: BLE001
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st.error(f"拉取失败：{exc}")
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st.info("注意：TuShare 拉取依赖网络与 Token，若环境未配置将出现错误提示。")
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st.divider()
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days = int(st.number_input("检查窗口（天数）", min_value=30, max_value=1095, value=365, step=30))
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cfg = get_config()
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force_refresh = st.checkbox(
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"强制刷新数据（关闭增量跳过）",
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value=cfg.force_refresh,
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help="勾选后将重新拉取所选区间全部数据",
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)
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if force_refresh != cfg.force_refresh:
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cfg.force_refresh = force_refresh
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if st.button("执行开机检查"):
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progress_bar = st.progress(0.0)
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status_placeholder = st.empty()
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log_placeholder = st.empty()
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messages: list[str] = []
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def hook(message: str, value: float) -> None:
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progress_bar.progress(min(max(value, 0.0), 1.0))
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status_placeholder.write(message)
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messages.append(message)
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with st.spinner("正在执行开机检查..."):
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try:
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report = run_boot_check(
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days=days,
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progress_hook=hook,
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force_refresh=force_refresh,
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)
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st.success("开机检查完成，以下为数据覆盖摘要。")
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st.json(report.to_dict())
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if messages:
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log_placeholder.markdown("\n".join(f"- {msg}" for msg in messages))
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except Exception as exc: # noqa: BLE001
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st.error(f"开机检查失败：{exc}")
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if messages:
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log_placeholder.markdown("\n".join(f"- {msg}" for msg in messages))
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finally:
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progress_bar.progress(1.0)
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st.divider()
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st.subheader("股票行情可视化")
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options = _load_stock_options()
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default_code = options[0] if options else "000001.SZ"
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if options:
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selection = st.selectbox("选择股票", options, index=0)
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ts_code = _parse_ts_code(selection)
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else:
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ts_code = st.text_input("输入股票代码（如 000001.SZ）", value=default_code).strip().upper()
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viz_col1, viz_col2 = st.columns(2)
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default_start = date.today() - timedelta(days=180)
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start_date = viz_col1.date_input("开始日期", value=default_start, key="viz_start")
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end_date = viz_col2.date_input("结束日期", value=date.today(), key="viz_end")
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if start_date > end_date:
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st.error("开始日期不能晚于结束日期")
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return
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with st.spinner("正在加载行情数据..."):
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try:
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df = _load_daily_frame(ts_code, start_date, end_date)
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except Exception as exc: # noqa: BLE001
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st.error(f"读取数据失败：{exc}")
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return
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if df.empty:
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st.warning("未查询到该区间的交易数据，请确认数据库已拉取对应日线。")
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return
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price_df = df[["close"]].rename(columns={"close": "收盘价"})
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volume_df = df[["vol"]].rename(columns={"vol": "成交量(手)"})
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if price_df.shape[0] > 180:
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sampled = price_df.resample('3D').last().dropna()
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else:
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sampled = price_df
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if volume_df.shape[0] > 180:
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volume_sampled = volume_df.resample('3D').mean().dropna()
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else:
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volume_sampled = volume_df
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first_close = sampled.iloc[0, 0]
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last_close = sampled.iloc[-1, 0]
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delta_abs = last_close - first_close
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delta_pct = (delta_abs / first_close * 100) if first_close else 0.0
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metric_col1, metric_col2, metric_col3 = st.columns(3)
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metric_col1.metric("最新收盘价", f"{last_close:.2f}", delta=f"{delta_abs:+.2f}")
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metric_col2.metric("区间涨跌幅", f"{delta_pct:+.2f}%")
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metric_col3.metric("平均成交量", f"{volume_sampled['成交量(手)'].mean():.0f}")
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df_reset = df.reset_index().rename(columns={
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"trade_date": "交易日",
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"open": "开盘价",
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"high": "最高价",
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"low": "最低价",
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"close": "收盘价",
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"vol": "成交量(手)",
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"amount": "成交额(千元)",
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})
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df_reset["成交额(千元)"] = df_reset["成交额(千元)"] / 1000
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candle_fig = go.Figure(
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data=[
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go.Candlestick(
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x=df_reset["交易日"],
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open=df_reset["开盘价"],
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high=df_reset["最高价"],
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low=df_reset["最低价"],
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close=df_reset["收盘价"],
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name="K线",
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)
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]
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)
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candle_fig.update_layout(height=420, margin=dict(l=10, r=10, t=40, b=10))
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st.plotly_chart(candle_fig, use_container_width=True)
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vol_fig = px.bar(
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df_reset,
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x="交易日",
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y="成交量(手)",
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labels={"成交量(手)": "成交量(手)"},
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title="成交量",
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)
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vol_fig.update_layout(height=280, margin=dict(l=10, r=10, t=40, b=10))
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st.plotly_chart(vol_fig, use_container_width=True)
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amt_fig = px.bar(
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df_reset,
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x="交易日",
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y="成交额(千元)",
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labels={"成交额(千元)": "成交额(千元)"},
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title="成交额",
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)
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amt_fig.update_layout(height=280, margin=dict(l=10, r=10, t=40, b=10))
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st.plotly_chart(amt_fig, use_container_width=True)
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df_reset["月份"] = df_reset["交易日"].dt.to_period("M").astype(str)
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box_fig = px.box(
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df_reset,
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x="月份",
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y="收盘价",
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points="outliers",
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title="月度收盘价分布",
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)
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box_fig.update_layout(height=320, margin=dict(l=10, r=10, t=40, b=10))
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st.plotly_chart(box_fig, use_container_width=True)
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st.caption("提示：成交量单位为手，成交额以千元显示。箱线图按月展示收盘价分布。")
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st.dataframe(df_reset.tail(20), width='stretch')
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def main() -> None:
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st.set_page_config(page_title="多智能体投资助理", layout="wide")
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tabs = st.tabs(["今日计划", "回测与复盘", "数据与设置", "自检测试"])
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with tabs[0]:
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render_today_plan()
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with tabs[1]:
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render_backtest()
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with tabs[2]:
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render_settings()
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with tabs[3]:
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render_tests()
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if __name__ == "__main__":
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main()
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