update
This commit is contained in:
sam
parent
a492d6a9f7
commit
8a4ca05155
@ -2470,6 +2470,130 @@ def render_llm_settings() -> None:
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st.caption("部门配置存储为独立 LLM 参数，执行时会自动套用对应 Provider 的连接信息。")
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def render_market_visualization() -> None:
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"""Render a standalone market data visualization dashboard."""
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st.header("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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LOGGER.debug("选择股票：%s", ts_code, extra=LOG_EXTRA)
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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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LOGGER.debug("输入股票：%s", ts_code, extra=LOG_EXTRA)
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col_start, col_end = st.columns(2)
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default_start = date.today() - timedelta(days=180)
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start_date = col_start.date_input("开始日期", value=default_start, key="viz_start")
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end_date = col_end.date_input("结束日期", value=date.today(), key="viz_end")
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LOGGER.debug("行情可视化日期范围：%s-%s", start_date, end_date, extra=LOG_EXTRA)
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if start_date > end_date:
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LOGGER.warning("无效日期范围：%s>%s", start_date, end_date, extra=LOG_EXTRA)
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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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LOGGER.exception("加载行情数据失败", extra=LOG_EXTRA)
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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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LOGGER.warning("指定区间无行情数据：%s %s-%s", ts_code, start_date, end_date, extra=LOG_EXTRA)
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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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sampled = price_df.resample("3D").last().dropna() if price_df.shape[0] > 180 else price_df
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volume_sampled = volume_df.resample("3D").mean().dropna() if volume_df.shape[0] > 180 else 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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numeric_columns = ["开盘价", "最高价", "最低价", "收盘价", "成交量(手)", "成交额(千元)"]
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for col in numeric_columns:
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if col in df_reset.columns:
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df_reset[col] = pd.to_numeric(df_reset[col], errors="coerce")
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df_reset["交易日"] = pd.to_datetime(df_reset["交易日"])
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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, width="stretch")
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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, width="stretch")
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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, width="stretch")
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df_reset["月份"] = df_reset["交易日"].dt.to_period("M").astype(str)
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df_reset["收盘价"] = pd.to_numeric(df_reset["收盘价"], errors="coerce")
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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, width="stretch")
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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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LOGGER.info("行情可视化完成，展示行数=%s", len(df_reset), extra=LOG_EXTRA)
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def render_tests() -> None:
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LOGGER.info("渲染自检页面", extra=LOG_EXTRA)
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st.header("自检测试")
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@ -2627,138 +2751,6 @@ def render_tests() -> None:
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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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LOGGER.debug("选择股票：%s", ts_code, extra=LOG_EXTRA)
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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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LOGGER.debug("输入股票：%s", ts_code, extra=LOG_EXTRA)
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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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LOGGER.debug("行情可视化日期范围：%s-%s", start_date, end_date, extra=LOG_EXTRA)
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if start_date > end_date:
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LOGGER.warning("无效日期范围：%s>%s", start_date, end_date, extra=LOG_EXTRA)
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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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LOGGER.exception("加载行情数据失败", extra=LOG_EXTRA)
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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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LOGGER.warning("指定区间无行情数据：%s %s-%s", ts_code, start_date, end_date, extra=LOG_EXTRA)
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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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# 确保所有列的数据类型正确，避免PyArrow序列化错误
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numeric_columns = ["开盘价", "最高价", "最低价", "收盘价", "成交量(手)", "成交额(千元)"]
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for col in numeric_columns:
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if col in df_reset.columns:
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df_reset[col] = pd.to_numeric(df_reset[col], errors='coerce')
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# 确保日期列是datetime类型
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df_reset["交易日"] = pd.to_datetime(df_reset["交易日"])
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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, width='stretch')
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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, width='stretch')
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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, width='stretch')
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df_reset["月份"] = df_reset["交易日"].dt.to_period("M").astype(str)
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# 确保收盘价列是数值类型
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df_reset["收盘价"] = pd.to_numeric(df_reset["收盘价"], errors='coerce')
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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, width='stretch')
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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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LOGGER.info("行情可视化完成，展示行数=%s", len(df_reset), extra=LOG_EXTRA)
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st.divider()
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st.subheader("LLM 接口测试")
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st.json(llm_config_snapshot())
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@ -2889,10 +2881,10 @@ def main() -> None:
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st.error(f"❌ 自动数据更新失败：{exc}")
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render_global_dashboard()
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tabs = st.tabs(["今日计划", "回测与复盘", "日志钻取", "数据与设置", "自检测试"])
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tabs = st.tabs(["今日计划", "回测与复盘", "行情可视化", "日志钻取", "数据与设置", "自检测试"])
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LOGGER.debug(
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"Tabs 初始化完成：%s",
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["今日计划", "回测与复盘", "日志钻取", "数据与设置", "自检测试"],
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["今日计划", "回测与复盘", "行情可视化", "日志钻取", "数据与设置", "自检测试"],
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extra=LOG_EXTRA,
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)
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with tabs[0]:
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@ -2900,8 +2892,10 @@ def main() -> None:
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with tabs[1]:
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render_backtest_review()
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with tabs[2]:
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render_log_viewer()
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render_market_visualization()
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with tabs[3]:
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render_log_viewer()
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with tabs[4]:
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st.header("系统设置")
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settings_tabs = st.tabs(["配置概览", "LLM 设置", "投资组合", "数据源"])
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@ -2917,7 +2911,7 @@ def main() -> None:
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with settings_tabs[3]:
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render_data_settings()
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with tabs[4]:
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with tabs[5]:
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render_tests()
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