181 lines
7.5 KiB
Python
181 lines
7.5 KiB
Python
"""日志钻取视图。"""
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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 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 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(
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"开始日期",
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value=date.today() - timedelta(days=7),
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key="log_view_start_date",
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)
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with col2:
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end_date = st.date_input(
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"结束日期",
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value=date.today(),
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key="log_view_end_date",
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)
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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(
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"对比日期1",
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value=date.today() - timedelta(days=1),
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key="log_view_compare_date1",
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)
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with col4:
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compare_date2 = st.date_input(
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"对比日期2",
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value=date.today(),
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key="log_view_compare_date2",
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)
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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:
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with db_session(read_only=True) as conn:
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def load_logs(d: date) -> pd.DataFrame:
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start_ts = f"{d.isoformat()}T00:00:00Z"
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end_ts = f"{d.isoformat()}T23:59:59Z"
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query = ["SELECT ts, level, msg FROM run_log WHERE ts BETWEEN ? AND ?"]
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params: list[object] = [start_ts, end_ts]
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if comparison_stage != "ALL":
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query.append("AND stage = ?")
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params.append(comparison_stage)
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query.append("ORDER BY ts DESC LIMIT ?")
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params.append(compare_limit)
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sql = " ".join(query)
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rows = conn.execute(sql, params).fetchall()
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if not rows:
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return pd.DataFrame(columns=["ts", "level", "msg"])
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df = pd.DataFrame([{k: row[k] for k in row.keys()} for row in rows])
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df["ts"] = pd.to_datetime(df["ts"]).dt.strftime("%Y-%m-%d %H:%M:%S")
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return df
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df1 = load_logs(compare_date1)
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df2 = load_logs(compare_date2)
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if df1.empty and df2.empty:
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st.info("选定日期暂无日志可对比。")
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else:
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st.write("### 对比结果")
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col_a, col_b = st.columns(2)
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with col_a:
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st.write(f"{compare_date1} 日日志")
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st.dataframe(df1, hide_index=True, width="stretch")
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with col_b:
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st.write(f"{compare_date2} 日日志")
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st.dataframe(df2, hide_index=True, width="stretch")
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summary = {
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"日期1日志条数": int(len(df1)),
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"日期2日志条数": int(len(df2)),
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"新增日志条数": max(len(df2) - len(df1), 0),
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}
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st.write("摘要：", summary)
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except Exception as exc: # noqa: BLE001
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LOGGER.exception("历史对比生成失败", extra=LOG_EXTRA)
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st.error(f"生成历史对比失败：{exc}")
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