"""检查 ODS/DWD 数据为什么只到 2/14，以及 SPI canonical_member_id 映射"""
import os
from pathlib import Path
from dotenv import load_dotenv

load_dotenv(Path(__file__).resolve().parents[2] / ".env")

PG_DSN = os.environ.get("PG_DSN")
if not PG_DSN:
    raise RuntimeError("PG_DSN 未设置")

import psycopg2
import psycopg2.extras

conn = psycopg2.connect(PG_DSN)
conn.autocommit = True

def q(sql, params=None):
    with conn.cursor(cursor_factory=psycopg2.extras.RealDictCursor) as cur:
        cur.execute(sql, params or ())
        return cur.fetchall()

# 1. 查 ODS 结算表的实际表名
print("ODS 结算相关表:")
rows = q("""
    SELECT table_name FROM information_schema.tables
    WHERE table_schema = 'ods' AND table_name LIKE '%settle%'
    ORDER BY table_name
""")
for r in rows:
    print(f"  {r['table_name']}")

rows2 = q("""
    SELECT table_name FROM information_schema.tables
    WHERE table_schema = 'ods' AND table_name LIKE '%payment%'
    ORDER BY table_name
""")
for r in rows2:
    print(f"  {r['table_name']}")

# 2. 查 ODS payment 表的最新数据
rows3 = q("""
    SELECT table_name FROM information_schema.tables
    WHERE table_schema = 'ods'
    ORDER BY table_name
""")
print(f"\nODS 全部表 ({len(rows3)} 张):")
for r in rows3:
    print(f"  {r['table_name']}")

# 3. 检查 SPI 的 canonical_member_id 映射
print("\n" + "=" * 60)
print("SPI canonical_member_id 映射分析")
rows4 = q("""
    WITH consume_source AS (
        SELECT
            s.member_id AS raw_member_id,
            COALESCE(NULLIF(s.member_id, 0), mca.tenant_member_id) AS canonical_member_id,
            s.pay_time,
            COALESCE(s.pay_amount, 0) AS pay_amount
        FROM dwd.dwd_settlement_head s
        LEFT JOIN dwd.dim_member_card_account mca
            ON s.member_card_account_id = mca.member_card_id
           AND mca.scd2_is_current = 1
           AND mca.register_site_id = s.site_id
           AND COALESCE(mca.is_delete, 0) = 0
        WHERE s.site_id = (SELECT DISTINCT site_id FROM dwd.dwd_settlement_head LIMIT 1)
          AND s.settle_type IN (1, 3)
          AND s.pay_time >= NOW() - INTERVAL '90 days'
    )
    SELECT
        COUNT(*) AS total_records,
        COUNT(DISTINCT raw_member_id) AS raw_members,
        COUNT(DISTINCT canonical_member_id) AS canonical_members,
        COUNT(*) FILTER (WHERE canonical_member_id IS NULL OR canonical_member_id = 0) AS null_canonical,
        COUNT(*) FILTER (WHERE raw_member_id != canonical_member_id) AS remapped
    FROM consume_source
""")
r = rows4[0]
print(f"  总记录: {r['total_records']}")
print(f"  原始 member_id 去重: {r['raw_members']}")
print(f"  canonical_member_id 去重: {r['canonical_members']}")
print(f"  canonical 为 NULL/0: {r['null_canonical']}")
print(f"  被重映射的记录: {r['remapped']}")

# 4. 30 天窗口内 canonical_member_id 有消费的会员数
rows5 = q("""
    WITH consume_source AS (
        SELECT
            COALESCE(NULLIF(s.member_id, 0), mca.tenant_member_id) AS canonical_member_id,
            s.pay_time,
            COALESCE(s.pay_amount, 0) AS pay_amount
        FROM dwd.dwd_settlement_head s
        LEFT JOIN dwd.dim_member_card_account mca
            ON s.member_card_account_id = mca.member_card_id
           AND mca.scd2_is_current = 1
           AND mca.register_site_id = s.site_id
           AND COALESCE(mca.is_delete, 0) = 0
        WHERE s.site_id = (SELECT DISTINCT site_id FROM dwd.dwd_settlement_head LIMIT 1)
          AND s.settle_type IN (1, 3)
          AND s.pay_time >= NOW() - INTERVAL '90 days'
    )
    SELECT
        canonical_member_id,
        SUM(pay_amount) AS spend_90,
        SUM(CASE WHEN pay_time >= NOW() - INTERVAL '30 days' THEN pay_amount ELSE 0 END) AS spend_30
    FROM consume_source
    WHERE canonical_member_id > 0
    GROUP BY canonical_member_id
""")
total = len(rows5)
has_30 = sum(1 for r in rows5 if float(r['spend_30']) > 0)
has_90 = sum(1 for r in rows5 if float(r['spend_90']) > 0)
print(f"\nSPI 视角（canonical_member_id）:")
print(f"  90天有消费会员: {total}")
print(f"  30天有消费会员: {has_30} ({has_30/total*100:.1f}%)")
print(f"  30天无消费会员: {total - has_30} ({(total-has_30)/total*100:.1f}%)")

# 5. 中位数计算
spend_30_vals = sorted([float(r['spend_30']) for r in rows5])
spend_90_vals = sorted([float(r['spend_90']) for r in rows5])
n = len(spend_30_vals)
median_30 = spend_30_vals[n // 2] if n else 0
median_90 = spend_90_vals[n // 2] if n else 0
print(f"\n  spend_30 中位数: {median_30:.2f}")
print(f"  spend_90 中位数: {median_90:.2f}")

# 6. 检查 API 拉取的最新数据时间（从 ODS 表看）
print("\n" + "=" * 60)
print("ODS 各表最新数据时间:")
for r in rows3[:5]:
    tname = r['table_name']
    try:
        cols = q(f"""
            SELECT column_name FROM information_schema.columns
            WHERE table_schema = 'ods' AND table_name = '{tname}'
            AND column_name IN ('pay_time', 'create_time', 'updated_at', 'etl_loaded_at')
            ORDER BY column_name
        """)
        if cols:
            col = cols[0]['column_name']
            maxr = q(f"SELECT MAX({col}) AS max_time FROM ods.{tname}")
            if maxr and maxr[0]['max_time']:
                print(f"  {tname}.{col}: {maxr[0]['max_time']}")
    except Exception as e:
        print(f"  {tname}: 查询失败 ({e})")

conn.close()
print("\n诊断完成。")