auv/backend/auvops.sh

#!/usr/bin/env bash
# auvops.sh - AUV 容器内运维工具（在容器内直接执行，非宿主机 docker exec）
#
# 拷贝进容器 /app（backend 根）后运行。后续新增运维能力都收敛到这个文件：
# 加一个 cmd_xxx 函数 + 在 main 的 case 里注册一行即可。
#
# 用法（容器内）:
#   ./auvops.sh cache-clear            # 清空全部缓存（当日数据全新）
#   ./auvops.sh cache-clear-graph      # 只清空热点穿透(theme_graph)缓存
#   ./auvops.sh clean-expired          # 只清理已过期的缓存
#   ./auvops.sh cache-count            # 查看缓存条数
#   ./auvops.sh recollect [DATE]       # 删除并重采指定交易日（默认当天）
#   ./auvops.sh sh                     # 进入交互式 shell
#   ./auvops.sh help                   # 查看帮助
#
# 依赖: 容器内 python 可用（能 import services.*），工作目录自动切到脚本所在目录。
#
# 示例:
#   ./auvops.sh cache-clear
#   ./auvops.sh recollect 2026-08-10
#   ./auvops.sh cache-count

set -euo pipefail

# 容器内 backend 根：脚本所在目录（/app）
ROOT="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
cd "${ROOT}"

# 容器内用 python；本机验证时可 PY=./venv/bin/python ./auvops.sh ...
PY="${PY:-python}"
"${PY}" -c "import services" >/dev/null 2>&1 || {
  echo "❌ 无法在 ${ROOT} 下 import services（确认已在容器内 /app 且 python 可用）" >&2
  exit 1
}

# 在容器内跑 python 代码。日期等参数通过环境变量传，避免拼接进代码字符串。
# 用法: py_env "KEY1=val1" "KEY2=val2" <<'EOF'
#   <python 代码>
# EOF
py_env() {
  local env_args=()
  while [[ "$#" -gt 0 ]]; do
    env_args+=("${1%%=*}=${1#*=}"); shift
  done
  env "${env_args[@]}" "${PY}" -
}

# ---- 子命令实现 ----

# 清空全部缓存（当日数据全新）
cmd_cache_clear() {
  echo "① 清空全部缓存"
  "${PY}" - <<'EOF'
from services.cache import clear_all
clear_all()
print("  cache 表已清空")
EOF
  echo "✅ 缓存已清空"
}

# 仅清空热点穿透(theme_graph)缓存：改写 top/排序后旧图数据过期，删掉让下次请求重建
cmd_cache_clear_graph() {
  echo "① 清空热点穿透(theme_graph)缓存"
  "${PY}" - <<'EOF'
from database import get_connection
conn = get_connection()
try:
    cur = conn.execute("DELETE FROM cache WHERE key LIKE 'theme_graph:%'")
    conn.commit()
    print(f"  已删除 {cur.rowcount} 条 theme_graph 缓存")
finally:
    conn.close()
EOF
  echo "✅ 热点穿透缓存已清空"
}

# 只清理已过期缓存
cmd_clean_expired() {
  echo "① 清理过期缓存"
  "${PY}" - <<'EOF'
from services.cache import clean_expired
clean_expired()
print("  过期缓存已清理")
EOF
  echo "✅ 完成"
}

# 查看缓存条数
cmd_cache_count() {
  "${PY}" - <<'EOF'
from database import get_connection
conn = get_connection()
try:
    n = conn.execute("SELECT COUNT(*) FROM cache").fetchone()[0]
    print(f"缓存条数: {n}")
finally:
    conn.close()
EOF
}

# 删除指定交易日旧数据，并用新选股逻辑重新采集入库
cmd_recollect() {
  local date="${1:-$(date +%F)}"
  if ! [[ "${date}" =~ ^[0-9]{4}-[0-9]{2}-[0-9]{2}$ ]]; then
    echo "❌ 日期格式错误：${date}（应为 YYYY-MM-DD）" >&2
    exit 1
  fi

  echo "================================================"
  echo "🚀 容器: ${HOSTNAME:-unknown}  交易日: ${date}"
  echo "================================================"

  echo "① 删除 ${date} 旧数据"
  py_env "TARGET_DATE=${date}" <<'EOF'
import os
from database import get_connection
date = os.environ["TARGET_DATE"]
conn = get_connection()
try:
    for tbl in ("daily_core_stocks", "daily_core_stock_themes", "daily_top_themes"):
        cur = conn.execute("DELETE FROM " + tbl + " WHERE trade_date = ?", (date,))
        print(f"  {tbl}: 删除 {cur.rowcount} 行")
    conn.commit()
finally:
    conn.close()
EOF

  echo "② 用新选股逻辑重采 ${date}"
  py_env "TARGET_DATE=${date}" <<'EOF'
import asyncio
import os
from services.daily_collector import collect_daily
result = asyncio.run(collect_daily(os.environ["TARGET_DATE"]))
print("  结果:", result)
EOF
  echo "✅ 完成"
}

# 进入交互式 shell
cmd_sh() {
  "${PY}" || true
}

# 帮助
usage() {
  awk 'NR >= 2 && /^#/ { sub(/^# ?/, ""); print; next } NR >= 2 && !/^#/ { exit }' "${BASH_SOURCE[0]}"
}

# ---- 入口 ----
main() {
  if [[ "$#" -eq 0 ]]; then
    usage
    exit 1
  fi
  local cmd="$1"; shift
  case "${cmd}" in
    cache-clear|cc)    cmd_cache_clear "$@" ;;
    cache-clear-graph) cmd_cache_clear_graph "$@" ;;
    clean-expired)     cmd_clean_expired "$@" ;;
    cache-count)       cmd_cache_count "$@" ;;
    recollect)         cmd_recollect "$@" ;;
    sh|shell|python)   cmd_sh "$@" ;;
    help|-h|--help)    usage ;;
    *)                 echo "❌ 未知命令: ${cmd}（./auvops.sh help 查看用法）" >&2; exit 1 ;;
  esac
}

main "$@"