#!/usr/bin/env python3
"""mofin_query.py — MoFin 数据库通用查询工具

用法:
    python3 mofin_query.py "半导体最近5次采集的涨跌幅"
    python3 mofin_query.py "今天资金净流入最多的5个板块"
    python3 mofin_query.py "最近3天连续净流入的板块"
    python3 mofin_query.py "市场情绪趋势(最近10次)"
"""

import sqlite3
import sys
from pathlib import Path

DB_PATH = Path(__file__).parent / "data" / "mofin.db"


def get_conn():
    conn = sqlite3.connect(str(DB_PATH))
    conn.row_factory = sqlite3.Row
    return conn


# ── 预定义查询 ──────────────────────────────────────

def query_sector_trend(name: str, limit: int = 5):
    """查询某板块最近N次采集的涨跌幅趋势"""
    conn = get_conn()
    rows = conn.execute("""
        SELECT s.timestamp, ss.change_pct, ss.net_inflow,
               ss.up_count, ss.down_count, ss.lead_stock, ss.lead_stock_change
        FROM sector_snapshots ss
        JOIN market_snapshots s ON ss.snapshot_id = s.id
        WHERE ss.name = ?
        ORDER BY s.timestamp DESC
        LIMIT ?
    """, (name, limit)).fetchall()
    conn.close()

    if not rows:
        print(f"未找到板块「{name}」的数据")
        return

    print(f"\n{'='*60}")
    print(f"  {name} 板块 — 最近 {len(rows)} 次采集")
    print(f"{'='*60}")
    print(f"{'时间':<20} {'涨跌幅%':>8} {'净流入(亿)':>10} {'上涨':>6} {'下跌':>6} {'领涨股':>10}")
    print(f"{'-'*20} {'-'*8} {'-'*10} {'-'*6} {'-'*6} {'-'*10}")
    for r in reversed(rows):
        print(f"{r['timestamp']:<20} {r['change_pct']:>8.2f} {r['net_inflow']:>10.2f} "
              f"{r['up_count'] or '-':>6} {r['down_count'] or '-':>6} {r['lead_stock'] or '-':>10}")


def query_top_inflow(limit: int = 5):
    """最新一次采集中资金净流入最多的板块"""
    conn = get_conn()
    rows = conn.execute("""
        SELECT ss.name, ss.change_pct, ss.net_inflow, ss.lead_stock, s.timestamp
        FROM sector_snapshots ss
        JOIN market_snapshots s ON ss.snapshot_id = s.id
        WHERE s.id = (SELECT MAX(id) FROM market_snapshots)
          AND ss.net_inflow IS NOT NULL
        ORDER BY ss.net_inflow DESC
        LIMIT ?
    """, (limit,)).fetchall()
    conn.close()

    if not rows:
        print("暂无数据")
        return

    print(f"\n{'='*60}")
    print(f"  资金净流入 Top {len(rows)}（{rows[0]['timestamp']}）")
    print(f"{'='*60}")
    print(f"{'板块':<12} {'涨跌幅%':>8} {'净流入(亿)':>10} {'领涨股':>10}")
    print(f"{'-'*12} {'-'*8} {'-'*10} {'-'*10}")
    for r in rows:
        print(f"{r['name']:<12} {r['change_pct']:>8.2f} {r['net_inflow']:>10.2f} {r['lead_stock'] or '-':>10}")


def query_consecutive_inflow(days: int = 3):
    """最近N次采集中连续净流入的板块"""
    conn = get_conn()
    rows = conn.execute("""
        SELECT name, COUNT(*) as times, ROUND(AVG(net_inflow), 2) as avg_inflow,
               ROUND(AVG(change_pct), 2) as avg_change
        FROM sector_snapshots ss
        JOIN market_snapshots s ON ss.snapshot_id = s.id
        WHERE s.id > (SELECT MAX(id) - ? FROM market_snapshots)
          AND net_inflow > 0
        GROUP BY name
        HAVING COUNT(*) >= ?
        ORDER BY avg_inflow DESC
    """, (days, days)).fetchall()
    conn.close()

    if not rows:
        print(f"没有板块连续 {days} 次净流入")
        return

    print(f"\n{'='*60}")
    print(f"  连续 {days} 次净流入的板块")
    print(f"{'='*60}")
    print(f"{'板块':<12} {'次数':>4} {'均净流入(亿)':>12} {'均涨跌幅%':>10}")
    print(f"{'-'*12} {'-'*4} {'-'*12} {'-'*10}")
    for r in rows:
        print(f"{r['name']:<12} {r['times']:>4} {r['avg_inflow']:>12.2f} {r['avg_change']:>10.2f}")


def query_market_mood(limit: int = 10):
    """市场情绪趋势"""
    conn = get_conn()
    rows = conn.execute("""
        SELECT timestamp, source, up_ratio, mood
        FROM market_snapshots
        ORDER BY timestamp DESC
        LIMIT ?
    """, (limit,)).fetchall()
    conn.close()

    if not rows:
        print("暂无数据")
        return

    print(f"\n{'='*60}")
    print(f"  市场情绪趋势 — 最近 {len(rows)} 次")
    print(f"{'='*60}")
    print(f"{'时间':<20} {'来源':>10} {'上涨占比%':>10} {'情绪':>10}")
    print(f"{'-'*20} {'-'*10} {'-'*10} {'-'*10}")
    for r in reversed(rows):
        mood_emoji = {"bullish": "🟢", "neutral": "🟡", "bearish": "🔴"}.get(r['mood'], "⚪")
        print(f"{r['timestamp']:<20} {r['source']:>10} {r['up_ratio']:>10.1f} {mood_emoji} {r['mood']:>8}")


def query_stats():
    """数据库概览统计"""
    conn = get_conn()
    snap_count = conn.execute("SELECT COUNT(*) FROM market_snapshots").fetchone()[0]
    sector_count = conn.execute("SELECT COUNT(*) FROM sector_snapshots").fetchone()[0]
    latest = conn.execute(
        "SELECT timestamp, source FROM market_snapshots ORDER BY id DESC LIMIT 1"
    ).fetchone()
    conn.close()

    print(f"\n{'='*40}")
    print(f"  MoFin 数据库概览")
    print(f"{'='*40}")
    print(f"  采集次数: {snap_count}")
    print(f"  板块快照: {sector_count}")
    if latest:
        print(f"  最新采集: {latest['timestamp']} ({latest['source']})")
    else:
        print(f"  最新采集: 暂无")


# ── 智能路由 ──────────────────────────────────────

def route(query: str):
    q = query.strip()

    # 板块趋势
    if "最近" in q and "次" in q and ("涨跌" in q or "趋势" in q or "采集" in q):
        # 提取板块名
        import re
        names = re.findall(r'["「]([^"」]+)["」]', q)
        if not names:
            # 尝试无引号匹配
            for word in ["半导体", "银行", "医药", "新能源", "白酒", "军工", "芯片", "房地产", "汽车"]:
                if word in q:
                    names = [word]
                    break
        if names:
            limit = 5
            m = re.search(r'(\d+)\s*次', q)
            if m:
                limit = int(m.group(1))
            query_sector_trend(names[0], limit)
            return

    # 资金净流入排行
    if "净流入" in q and ("最多" in q or "排行" in q or "top" in q.lower()):
        limit = 5
        import re
        m = re.search(r'(\d+)', q)
        if m:
            limit = int(m.group(1))
        query_top_inflow(limit)
        return

    # 连续净流入
    if "连续" in q and "净流入" in q:
        days = 3
        import re
        m = re.search(r'(\d+)\s*天', q)
        if m:
            days = int(m.group(1))
        query_consecutive_inflow(days)
        return

    # 市场情绪
    if "情绪" in q or "mood" in q.lower():
        limit = 10
        import re
        m = re.search(r'(\d+)\s*次', q)
        if m:
            limit = int(m.group(1))
        query_market_mood(limit)
        return

    # 统计概览
    if "概览" in q or "统计" in q or "stats" in q.lower():
        query_stats()
        return

    # 直接 SQL（以 SELECT 开头）
    if q.upper().strip().startswith("SELECT"):
        conn = get_conn()
        try:
            rows = conn.execute(q).fetchall()
            if rows:
                cols = rows[0].keys()
                print("\t".join(cols))
                for r in rows:
                    print("\t".join(str(r[c]) for c in cols))
            else:
                print("(empty)")
        except Exception as e:
            print(f"SQL 错误: {e}")
        finally:
            conn.close()
        return

    # 未匹配
    print(f"未识别的查询: {q}")
    print()
    print("支持的查询模式:")
    print("  「半导体」最近5次采集的涨跌幅")
    print("  今天资金净流入最多的5个板块")
    print("  最近3天连续净流入的板块")
    print("  市场情绪趋势(最近10次)")
    print("  数据库概览")
    print("  SELECT * FROM market_snapshots ORDER BY id DESC LIMIT 5")


if __name__ == "__main__":
    if len(sys.argv) < 2:
        print("用法: python3 mofin_query.py \"查询语句\"")
        print("示例: python3 mofin_query.py \"半导体最近5次采集的涨跌幅\"")
        sys.exit(1)

    route(sys.argv[1])