update
This commit is contained in:
sam
parent
cf9e902480
commit
db3df13462
@ -415,13 +415,10 @@ def render_today_plan() -> None:
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LOGGER.exception("加载 agent_utils 失败", extra=LOG_EXTRA)
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st.warning("暂未写入部门/代理决策，请先运行回测或策略评估流程。")
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return
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trade_dates = [row["trade_date"] for row in date_rows]
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if not trade_dates:
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st.info("暂无决策记录，完成一次回测后即可在此查看部门意见与投票结果。")
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return
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# ADD: read default selection from URL
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q = _get_query_params()
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default_trade_date = q.get("date", [trade_dates[0]])[0]
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try:
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@ -429,7 +426,6 @@ def render_today_plan() -> None:
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except ValueError:
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default_idx = 0
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trade_date = st.selectbox("交易日", trade_dates, index=default_idx)
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with db_session(read_only=True) as conn:
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code_rows = conn.execute(
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"""
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@ -441,22 +437,9 @@ def render_today_plan() -> None:
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(trade_date,),
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).fetchall()
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symbols = [row["ts_code"] for row in code_rows]
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if not symbols:
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st.info("所选交易日暂无 agent_utils 记录。")
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return
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# ADD: 投资助理模式开关（不指定具体标的）
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assistant_mode = st.checkbox(
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"投资助理（不指定标的）",
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value=False,
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help="开启后不显示具体标的，展示基于候选投资池的组合级建议与汇总信息。",
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)
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if assistant_mode:
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ts_code = None
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batch_symbols = []
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detail_tab, assistant_tab = st.tabs(["标的详情", "投资助理模式"])
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with assistant_tab:
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st.info("已开启投资助理模式：以下内容为组合级（去标的）建议，不包含任何具体标的代码。")
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# 展示候选池聚合信息（不暴露具体代码）
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try:
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candidates = list_investment_pool(trade_date=trade_date)
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if candidates:
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@ -525,6 +508,9 @@ def render_today_plan() -> None:
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except Exception:
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LOGGER.exception("加载候选池聚合信息失败", extra=LOG_EXTRA)
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st.error("加载候选池数据时发生错误。")
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with detail_tab:
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if not symbols:
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st.info("所选交易日暂无 agent_utils 记录。")
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else:
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default_ts = q.get("code", [symbols[0]])[0]
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try:
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@ -532,10 +518,8 @@ def render_today_plan() -> None:
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except ValueError:
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default_ts_idx = 0
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ts_code = st.selectbox("标的", symbols, index=default_ts_idx)
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# ADD: batch selection for re-evaluation
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batch_symbols = st.multiselect("批量重评估（可多选）", symbols, default=[])
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# 一键重评估所有标的按钮
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if st.button("一键重评估所有标的", type="primary", width='stretch'):
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with st.spinner("正在对所有标的进行重评估，请稍候..."):
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try:
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@ -616,10 +600,7 @@ def render_today_plan() -> None:
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except Exception as exc:
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LOGGER.exception("一键重评估失败", extra=LOG_EXTRA)
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st.error(f"一键重评估执行过程中发生错误：{exc}")
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# sync URL params
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_set_query_params(date=str(trade_date), code=str(ts_code))
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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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@ -630,21 +611,17 @@ def render_today_plan() -> None:
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""",
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(trade_date, ts_code),
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).fetchall()
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if not rows:
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st.info("未查询到详细决策记录，稍后再试。")
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return
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try:
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feasible_actions = json.loads(rows[0]["feasible"] or "[]")
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except (KeyError, TypeError, json.JSONDecodeError):
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feasible_actions = []
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global_info = None
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dept_records: List[Dict[str, object]] = []
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dept_details: Dict[str, Dict[str, object]] = {}
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agent_records: List[Dict[str, object]] = []
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for item in rows:
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agent_name = item["agent"]
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action = item["action"]
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@ -715,10 +692,8 @@ def render_today_plan() -> None:
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"BUY_L": score_map.get("BUY_L", 0.0),
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}
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)
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if feasible_actions:
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st.caption(f"可行操作集合：{', '.join(feasible_actions)}")
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st.subheader("全局策略")
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if global_info:
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col1, col2, col3 = st.columns(3)
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@ -782,7 +757,6 @@ def render_today_plan() -> None:
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st.json(dept_telemetry)
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else:
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st.info("暂未写入全局策略摘要。")
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st.subheader("部门意见")
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if dept_records:
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# ADD: keyword filter for department summaries
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@ -832,7 +806,6 @@ def render_today_plan() -> None:
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st.json(telemetry)
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else:
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st.info("暂无部门记录。")
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st.subheader("代理评分")
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if agent_records:
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# ADD: sorting and CSV export for agents
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@ -857,11 +830,8 @@ def render_today_plan() -> None:
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pass
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else:
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st.info("暂无基础代理评分。")
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# 添加相关新闻展示部分
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st.divider()
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st.subheader("相关新闻")
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# 获取与当前标的相关的最新新闻
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try:
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with db_session(read_only=True) as conn:
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# 解析当前trade_date为datetime对象
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@ -959,11 +929,8 @@ def render_today_plan() -> None:
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except Exception as e:
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LOGGER.exception("获取新闻数据失败", extra=LOG_EXTRA)
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st.error(f"获取新闻数据时发生错误：{e}")
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st.divider()
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# 提示用户跳转到单独的“投资池与仓位概览”页
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st.info("投资池与仓位概览已移至单独页面。请在侧边或页面导航中选择“投资池/仓位”以查看详细信息。")
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st.divider()
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st.subheader("策略重评估")
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st.caption("对当前选中的交易日与标的，立即触发一次策略评估并回写 agent_utils。")
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@ -1081,129 +1048,6 @@ def render_today_plan() -> None:
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st.error(f"批量重评估失败：{exc}")
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def render_log_viewer() -> None:
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"""渲染日志钻取与历史对比视图页面。"""
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LOGGER.info("渲染日志视图页面", extra=LOG_EXTRA)
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st.header("日志钻取与历史对比")
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st.write("查看系统运行日志，支持时间范围筛选、关键词搜索和历史对比功能。")
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# 日志时间范围选择
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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=7))
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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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# 日志级别筛选
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log_levels = ["ALL", "DEBUG", "INFO", "WARNING", "ERROR", "CRITICAL"]
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selected_level = st.selectbox("日志级别", log_levels, index=1)
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# 关键词搜索
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search_query = st.text_input("搜索关键词")
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# 阶段筛选
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with db_session(read_only=True) as conn:
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stages = [row["stage"] for row in conn.execute("SELECT DISTINCT stage FROM run_log").fetchall()]
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stages = [s for s in stages if s] # 过滤空值
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stages.insert(0, "ALL")
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selected_stage = st.selectbox("执行阶段", stages)
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# 查询日志
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with st.spinner("加载日志数据中..."):
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try:
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with db_session(read_only=True) as conn:
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query_parts = ["SELECT ts, stage, level, msg FROM run_log WHERE 1=1"]
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params = []
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# 添加日期过滤
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start_ts = f"{start_date.isoformat()}T00:00:00Z"
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end_ts = f"{end_date.isoformat()}T23:59:59Z"
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query_parts.append("AND ts BETWEEN ? AND ?")
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params.extend([start_ts, end_ts])
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# 添加级别过滤
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if selected_level != "ALL":
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query_parts.append("AND level = ?")
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params.append(selected_level)
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# 添加关键词过滤
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if search_query:
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query_parts.append("AND msg LIKE ?")
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params.append(f"%{search_query}%")
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# 添加阶段过滤
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if selected_stage != "ALL":
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query_parts.append("AND stage = ?")
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params.append(selected_stage)
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# 添加排序
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query_parts.append("ORDER BY ts DESC")
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# 执行查询
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query = " ".join(query_parts)
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rows = conn.execute(query, params).fetchall()
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# 转换为DataFrame
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if rows:
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# 将sqlite3.Row对象转换为字典列表
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rows_dict = [{key: row[key] for key in row.keys()} for row in rows]
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log_df = pd.DataFrame(rows_dict)
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# 格式化时间戳并确保数据类型一致
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log_df["ts"] = pd.to_datetime(log_df["ts"]).dt.strftime("%Y-%m-%d %H:%M:%S")
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# 确保所有列都是字符串类型，避免PyArrow序列化错误
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for col in log_df.columns:
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log_df[col] = log_df[col].astype(str)
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else:
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log_df = pd.DataFrame(columns=["ts", "stage", "level", "msg"])
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# 显示日志表格
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st.dataframe(
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log_df,
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hide_index=True,
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width="stretch",
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column_config={
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"ts": st.column_config.TextColumn("时间"),
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"stage": st.column_config.TextColumn("执行阶段"),
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"level": st.column_config.TextColumn("日志级别"),
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"msg": st.column_config.TextColumn("日志消息", width="large")
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}
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)
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# 下载功能
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if not log_df.empty:
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csv_data = log_df.to_csv(index=False).encode('utf-8')
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st.download_button(
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label="下载日志CSV",
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data=csv_data,
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file_name=f"logs_{start_date}_{end_date}.csv",
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mime="text/csv",
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key="download_logs"
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)
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# JSON下载
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json_data = log_df.to_json(orient='records', force_ascii=False, indent=2)
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st.download_button(
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label="下载日志JSON",
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data=json_data,
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file_name=f"logs_{start_date}_{end_date}.json",
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mime="application/json",
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key="download_logs_json"
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)
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except Exception as e:
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LOGGER.exception("加载日志失败", extra=LOG_EXTRA)
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st.error(f"加载日志数据失败：{e}")
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# 历史对比功能
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st.subheader("历史对比")
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st.write("选择两个时间点的日志进行对比分析。")
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# 第一个时间点选择
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col3, col4 = st.columns(2)
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with col3:
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compare_date1 = st.date_input("对比日期1", value=date.today() - timedelta(days=1))
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with col4:
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compare_date2 = st.date_input("对比日期2", value=date.today())
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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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@ -2872,6 +2716,161 @@ def render_tests() -> None:
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st.write(response)
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def render_log_viewer() -> None:
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"""渲染日志钻取与历史对比视图页面。"""
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LOGGER.info("渲染日志视图页面", extra=LOG_EXTRA)
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st.header("日志钻取与历史对比")
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st.write("查看系统运行日志，支持时间范围筛选、关键词搜索和历史对比功能。")
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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=7))
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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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log_levels = ["ALL", "DEBUG", "INFO", "WARNING", "ERROR", "CRITICAL"]
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selected_level = st.selectbox("日志级别", log_levels, index=1)
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search_query = st.text_input("搜索关键词")
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with db_session(read_only=True) as conn:
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stages = [row["stage"] for row in conn.execute("SELECT DISTINCT stage FROM run_log").fetchall()]
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stages = [s for s in stages if s]
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stages.insert(0, "ALL")
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selected_stage = st.selectbox("执行阶段", stages)
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with st.spinner("加载日志数据中..."):
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try:
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with db_session(read_only=True) as conn:
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query_parts = ["SELECT ts, stage, level, msg FROM run_log WHERE 1=1"]
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params: list[object] = []
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start_ts = f"{start_date.isoformat()}T00:00:00Z"
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end_ts = f"{end_date.isoformat()}T23:59:59Z"
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query_parts.append("AND ts BETWEEN ? AND ?")
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params.extend([start_ts, end_ts])
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if selected_level != "ALL":
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query_parts.append("AND level = ?")
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params.append(selected_level)
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if search_query:
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query_parts.append("AND msg LIKE ?")
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params.append(f"%{search_query}%")
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if selected_stage != "ALL":
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query_parts.append("AND stage = ?")
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params.append(selected_stage)
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query_parts.append("ORDER BY ts DESC")
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query = " ".join(query_parts)
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rows = conn.execute(query, params).fetchall()
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if rows:
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rows_dict = [{key: row[key] for key in row.keys()} for row in rows]
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log_df = pd.DataFrame(rows_dict)
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log_df["ts"] = pd.to_datetime(log_df["ts"]).dt.strftime("%Y-%m-%d %H:%M:%S")
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for col in log_df.columns:
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log_df[col] = log_df[col].astype(str)
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else:
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log_df = pd.DataFrame(columns=["ts", "stage", "level", "msg"])
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st.dataframe(
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log_df,
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hide_index=True,
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width="stretch",
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column_config={
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"ts": st.column_config.TextColumn("时间"),
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"stage": st.column_config.TextColumn("执行阶段"),
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"level": st.column_config.TextColumn("日志级别"),
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"msg": st.column_config.TextColumn("日志消息", width="large"),
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},
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)
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if not log_df.empty:
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csv_data = log_df.to_csv(index=False).encode("utf-8")
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st.download_button(
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label="下载日志CSV",
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data=csv_data,
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file_name=f"logs_{start_date}_{end_date}.csv",
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mime="text/csv",
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key="download_logs",
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)
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json_data = log_df.to_json(orient="records", force_ascii=False, indent=2)
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st.download_button(
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label="下载日志JSON",
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data=json_data,
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file_name=f"logs_{start_date}_{end_date}.json",
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mime="application/json",
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key="download_logs_json",
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)
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except Exception as exc: # noqa: BLE001
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LOGGER.exception("加载日志失败", extra=LOG_EXTRA)
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st.error(f"加载日志数据失败：{exc}")
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st.subheader("历史对比")
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st.write("选择两个时间点的日志进行对比分析。")
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col3, col4 = st.columns(2)
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with col3:
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compare_date1 = st.date_input("对比日期1", value=date.today() - timedelta(days=1))
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with col4:
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compare_date2 = st.date_input("对比日期2", value=date.today())
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comparison_stage = st.selectbox("对比阶段", stages, key="compare_stage")
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st.write("选择需要比较的日志数量。")
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compare_limit = st.slider("对比日志数量", min_value=10, max_value=200, value=50, step=10)
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if st.button("生成历史对比报告"):
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with st.spinner("生成对比报告中..."):
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try:
|
||||
with db_session(read_only=True) as conn:
|
||||
def load_logs(d: date) -> pd.DataFrame:
|
||||
start_ts = f"{d.isoformat()}T00:00:00Z"
|
||||
end_ts = f"{d.isoformat()}T23:59:59Z"
|
||||
query = ["SELECT ts, level, msg FROM run_log WHERE ts BETWEEN ? AND ?"]
|
||||
params: list[object] = [start_ts, end_ts]
|
||||
if comparison_stage != "ALL":
|
||||
query.append("AND stage = ?")
|
||||
params.append(comparison_stage)
|
||||
query.append("ORDER BY ts DESC LIMIT ?")
|
||||
params.append(compare_limit)
|
||||
sql = " ".join(query)
|
||||
rows = conn.execute(sql, params).fetchall()
|
||||
if not rows:
|
||||
return pd.DataFrame(columns=["ts", "level", "msg"])
|
||||
df = pd.DataFrame([{k: row[k] for k in row.keys()} for row in rows])
|
||||
df["ts"] = pd.to_datetime(df["ts"]).dt.strftime("%Y-%m-%d %H:%M:%S")
|
||||
return df
|
||||
|
||||
df1 = load_logs(compare_date1)
|
||||
df2 = load_logs(compare_date2)
|
||||
|
||||
if df1.empty and df2.empty:
|
||||
st.info("选定日期暂无日志可对比。")
|
||||
else:
|
||||
st.write("### 对比结果")
|
||||
col_a, col_b = st.columns(2)
|
||||
with col_a:
|
||||
st.write(f"{compare_date1} 日日志")
|
||||
st.dataframe(df1, hide_index=True, width="stretch")
|
||||
with col_b:
|
||||
st.write(f"{compare_date2} 日日志")
|
||||
st.dataframe(df2, hide_index=True, width="stretch")
|
||||
|
||||
summary = {
|
||||
"日期1日志条数": int(len(df1)),
|
||||
"日期2日志条数": int(len(df2)),
|
||||
"新增日志条数": max(len(df2) - len(df1), 0),
|
||||
}
|
||||
st.write("摘要：", summary)
|
||||
except Exception as exc: # noqa: BLE001
|
||||
LOGGER.exception("历史对比生成失败", extra=LOG_EXTRA)
|
||||
st.error(f"生成历史对比失败：{exc}")
|
||||
|
||||
|
||||
def render_data_settings() -> None:
|
||||
"""渲染数据源配置界面."""
|
||||
st.subheader("Tushare 数据源")
|
||||
|
||||
Loading…
Reference in New Issue
Block a user