116 lines
3.6 KiB
Python
116 lines
3.6 KiB
Python
"""行情可视化页面。"""
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from __future__ import annotations
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from datetime import date, timedelta
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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.utils.db import db_session
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from app.ui.shared import LOGGER, LOG_EXTRA
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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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"""
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SELECT DISTINCT ts_code
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FROM daily
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ORDER BY trade_date DESC
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LIMIT ?
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""",
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(limit,),
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).fetchall()
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except Exception: # noqa: BLE001
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LOGGER.exception("加载股票列表失败", extra=LOG_EXTRA)
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return []
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return [row["ts_code"] for row in rows]
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def _parse_ts_code(selection: str) -> str:
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return selection.split(" ", 1)[0]
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def _load_daily_frame(ts_code: str, start: date, end: date) -> pd.DataFrame:
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with db_session(read_only=True) as conn:
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df = pd.read_sql_query(
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"""
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SELECT trade_date, open, high, low, close, vol, amount
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FROM daily
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WHERE ts_code = ? AND trade_date BETWEEN ? AND ?
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ORDER BY trade_date
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""",
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conn,
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params=(ts_code, start.strftime("%Y%m%d"), end.strftime("%Y%m%d")),
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)
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if df.empty:
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return df
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df["trade_date"] = pd.to_datetime(df["trade_date"], format="%Y%m%d")
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return df
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def render_market_visualization() -> None:
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st.header("行情可视化")
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st.caption("按标的查看 K 线、成交量以及常用指标。")
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options = _load_stock_options()
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if not options:
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st.warning("暂未加载到可用的行情标的，请先执行数据同步。")
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return
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selection = st.selectbox("选择标的", options, index=0)
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ts_code = _parse_ts_code(selection)
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col1, col2 = st.columns(2)
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with col1:
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start_date = st.date_input("开始日期", value=date.today() - timedelta(days=120))
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with col2:
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end_date = st.date_input("结束日期", value=date.today())
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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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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"加载行情数据失败：{exc}")
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return
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if df.empty:
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st.info("所选区间内无行情数据。")
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return
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st.metric("最新收盘价", f"{df['close'].iloc[-1]:.2f}")
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fig = go.Figure(
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data=[
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go.Candlestick(
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x=df["trade_date"],
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open=df["open"],
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high=df["high"],
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low=df["low"],
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close=df["close"],
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name="K线",
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)
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]
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)
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fig.update_layout(title=f"{ts_code} K线图", xaxis_title="日期", yaxis_title="价格")
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st.plotly_chart(fig, use_container_width=True)
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fig_vol = px.bar(df, x="trade_date", y="vol", title="成交量")
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st.plotly_chart(fig_vol, use_container_width=True)
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df_ma = df.copy()
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df_ma["MA5"] = df_ma["close"].rolling(window=5).mean()
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df_ma["MA20"] = df_ma["close"].rolling(window=20).mean()
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df_ma["MA60"] = df_ma["close"].rolling(window=60).mean()
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fig_ma = px.line(df_ma, x="trade_date", y=["close", "MA5", "MA20", "MA60"], title="均线对比")
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st.plotly_chart(fig_ma, use_container_width=True)
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st.dataframe(df, hide_index=True, width='stretch')
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