163 lines
6.8 KiB
Python
163 lines
6.8 KiB
Python
"""投资池与仓位概览页面。"""
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from __future__ import annotations
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import pandas as pd
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import plotly.express as px
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import streamlit as st
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from app.utils.db import db_session
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from app.utils.portfolio import (
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get_latest_snapshot,
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list_investment_pool,
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list_positions,
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list_recent_trades,
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)
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from app.ui.shared import LOGGER, LOG_EXTRA, get_latest_trade_date
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def render_pool_overview() -> None:
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"""单独的投资池与仓位概览页面（从今日计划中提取）。"""
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LOGGER.info("渲染投资池与仓位概览页面", extra=LOG_EXTRA)
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st.header("投资池与仓位概览")
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snapshot = get_latest_snapshot()
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if snapshot:
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col_a, col_b, col_c = st.columns(3)
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if snapshot.total_value is not None:
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col_a.metric("组合净值", f"{snapshot.total_value:,.2f}")
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if snapshot.cash is not None:
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col_b.metric("现金余额", f"{snapshot.cash:,.2f}")
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if snapshot.invested_value is not None:
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col_c.metric("持仓市值", f"{snapshot.invested_value:,.2f}")
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detail_cols = st.columns(4)
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if snapshot.unrealized_pnl is not None:
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detail_cols[0].metric("浮盈", f"{snapshot.unrealized_pnl:,.2f}")
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if snapshot.realized_pnl is not None:
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detail_cols[1].metric("已实现盈亏", f"{snapshot.realized_pnl:,.2f}")
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if snapshot.net_flow is not None:
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detail_cols[2].metric("净流入", f"{snapshot.net_flow:,.2f}")
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if snapshot.exposure is not None:
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detail_cols[3].metric("风险敞口", f"{snapshot.exposure:.2%}")
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if snapshot.notes:
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st.caption(f"备注：{snapshot.notes}")
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else:
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st.info("暂无组合快照，请在执行回测或实盘同步后写入 portfolio_snapshots。")
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try:
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latest_date = get_latest_trade_date()
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candidates = list_investment_pool(trade_date=latest_date)
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except Exception: # noqa: BLE001
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LOGGER.exception("加载候选池失败", extra=LOG_EXTRA)
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candidates = []
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if candidates:
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candidate_df = pd.DataFrame(
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[
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{
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"交易日": item.trade_date,
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"代码": item.ts_code,
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"评分": item.score,
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"状态": item.status,
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"标签": "、".join(item.tags) if item.tags else "-",
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"理由": item.rationale or "",
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}
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for item in candidates
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]
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)
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st.write("候选投资池：")
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st.dataframe(candidate_df, width='stretch', hide_index=True)
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else:
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st.caption("候选投资池暂无数据。")
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positions = list_positions(active_only=False)
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if positions:
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position_df = pd.DataFrame(
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[
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{
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"ID": pos.id,
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"代码": pos.ts_code,
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"开仓日": pos.opened_date,
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"平仓日": pos.closed_date or "-",
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"状态": pos.status,
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"数量": pos.quantity,
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"成本": pos.cost_price,
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"现价": pos.market_price,
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"市值": pos.market_value,
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"浮盈": pos.unrealized_pnl,
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"已实现": pos.realized_pnl,
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"目标权重": pos.target_weight,
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}
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for pos in positions
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]
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)
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st.write("组合持仓：")
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st.dataframe(position_df, width='stretch', hide_index=True)
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else:
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st.caption("组合持仓暂无记录。")
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trades = list_recent_trades(limit=20)
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if trades:
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trades_df = pd.DataFrame(trades)
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st.write("近期成交：")
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st.dataframe(trades_df, width='stretch', hide_index=True)
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else:
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st.caption("近期成交暂无记录。")
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st.caption("数据来源：agent_utils、investment_pool、portfolio_positions、portfolio_trades、portfolio_snapshots。")
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if st.button("执行对比", type="secondary"):
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with st.spinner("执行日志对比分析中..."):
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try:
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with db_session(read_only=True) as conn:
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query_date1 = f"{compare_date1.isoformat()}T00:00:00Z" # type: ignore[name-defined]
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query_date2 = f"{compare_date1.isoformat()}T23:59:59Z" # type: ignore[name-defined]
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logs1 = conn.execute(
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"SELECT level, COUNT(*) as count FROM run_log WHERE ts BETWEEN ? AND ? GROUP BY level",
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(query_date1, query_date2),
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).fetchall()
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query_date3 = f"{compare_date2.isoformat()}T00:00:00Z" # type: ignore[name-defined]
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query_date4 = f"{compare_date2.isoformat()}T23:59:59Z" # type: ignore[name-defined]
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logs2 = conn.execute(
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"SELECT level, COUNT(*) as count FROM run_log WHERE ts BETWEEN ? AND ? GROUP BY level",
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(query_date3, query_date4),
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).fetchall()
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df1 = pd.DataFrame(logs1, columns=["level", "count"])
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df1["date"] = compare_date1.strftime("%Y-%m-%d") # type: ignore[name-defined]
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df2 = pd.DataFrame(logs2, columns=["level", "count"])
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df2["date"] = compare_date2.strftime("%Y-%m-%d") # type: ignore[name-defined]
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for df in (df1, df2):
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for col in df.columns:
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if col != "level":
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df[col] = df[col].astype(object)
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compare_df = pd.concat([df1, df2])
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fig = px.bar(
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compare_df,
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x="level",
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y="count",
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color="date",
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barmode="group",
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title=f"日志级别分布对比 ({compare_date1} vs {compare_date2})", # type: ignore[name-defined]
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)
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st.plotly_chart(fig, width='stretch')
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st.write("日志统计对比：")
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date1_str = compare_date1.strftime("%Y%m%d") # type: ignore[name-defined]
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date2_str = compare_date2.strftime("%Y%m%d") # type: ignore[name-defined]
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merged_df = df1.merge(
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df2,
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on="level",
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suffixes=(f"_{date1_str}", f"_{date2_str}"),
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how="outer",
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).fillna(0)
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st.dataframe(merged_df, hide_index=True, width="stretch")
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except Exception as exc: # noqa: BLE001
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LOGGER.exception("日志对比失败", extra=LOG_EXTRA)
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st.error(f"日志对比分析失败：{exc}")
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return
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