#!/usr/bin/env python3
"""
TI沉淀/新进拆分 - 线索明细补全
需求：基于 xiaoxi_xhs_lead_detail.csv 进线月 3-5 月，join bi_vala_app_account 补全字段
输出：ti_pool_split_20260608.csv
"""

import csv
import psycopg2
from datetime import datetime, date
from collections import defaultdict

# ── 1. 读取线索明细 ──────────────────────────────────────────
leads = []
with open('/root/.openclaw/workspace/tmp/xiaoxi_xhs_lead_detail.csv', 'r', encoding='utf-8') as f:
    reader = csv.DictReader(f)
    for row in reader:
        intake_month = row.get('进线月', '').strip()
        if intake_month in ('2026-03', '2026-04', '2026-05'):
            leads.append(row)

print(f"进线月 3-5 月共 {len(leads)} 条线索")

# ── 2. 收集所有用户ID ────────────────────────────────────────
user_ids = set()
for row in leads:
    uid = row.get('用户ID', '').strip()
    if uid and uid.isdigit():
        user_ids.add(int(uid))

print(f"去重用户ID: {len(user_ids)} 个")

# ── 3. 查询 bi_vala_app_account ──────────────────────────────
conn = psycopg2.connect(
    host='bj-postgres-16pob4sg.sql.tencentcdb.com',
    port=28591,
    user='ai_member',
    password='LdfjdjL83h3h3^$&**YGG*',
    dbname='vala_bi'
)
cur = conn.cursor()

# 批量查询
account_map = {}  # id -> {created_at, key_from}
batch_size = 500
uid_list = list(user_ids)
for i in range(0, len(uid_list), batch_size):
    batch = uid_list[i:i+batch_size]
    placeholders = ','.join(['%s'] * len(batch))
    cur.execute(f"""
        SELECT id, created_at, key_from
        FROM bi_vala_app_account
        WHERE id IN ({placeholders})
    """, batch)
    for row in cur.fetchall():
        account_map[row[0]] = {
            'created_at': row[1],
            'key_from': row[2] or ''
        }

print(f"bi_vala_app_account 匹配到 {len(account_map)} 个用户")

# ── 4. 计算 prior_lead_same_phone ────────────────────────────
# 读取全部线索（含2月/6月），按手机号找最早进线月
all_leads = []
with open('/root/.openclaw/workspace/tmp/xiaoxi_xhs_lead_detail.csv', 'r', encoding='utf-8') as f:
    reader = csv.DictReader(f)
    for row in reader:
        all_leads.append(row)

phone_earliest_month = {}
for row in all_leads:
    phone = row.get('手机号', '').strip()
    intake_month = row.get('进线月', '').strip()
    if phone and intake_month:
        if phone not in phone_earliest_month or intake_month < phone_earliest_month[phone]:
            phone_earliest_month[phone] = intake_month

print(f"去重手机号: {len(phone_earliest_month)} 个")

# ── 5. 组装输出 ──────────────────────────────────────────────
output_rows = []
for row in leads:
    uid_str = row.get('用户ID', '').strip()
    uid = int(uid_str) if uid_str.isdigit() else None
    phone = row.get('手机号', '').strip()
    intake_month = row.get('进线月', '').strip()
    intake_date_str = row.get('进线日期', '').strip()

    acct = account_map.get(uid, {})
    create_time = acct.get('created_at')
    key_from = acct.get('key_from', '')

    # register_before_intake: 注册是否早于进线月第一天
    register_before_intake = ''
    days_register_to_intake = ''
    if create_time and intake_month:
        try:
            intake_first_day = datetime.strptime(intake_month + '-01', '%Y-%m-%d').date()
            create_date = create_time.date() if hasattr(create_time, 'date') else datetime.strptime(str(create_time)[:10], '%Y-%m-%d').date()
            register_before_intake = '是' if create_date < intake_first_day else '否'
            # days from registration to intake date
            if intake_date_str:
                intake_date = datetime.strptime(intake_date_str, '%Y-%m-%d').date()
                days_register_to_intake = (intake_date - create_date).days
        except:
            pass

    # prior_lead_same_phone: 进线月前是否另有同手机留资
    prior_lead_same_phone = ''
    if phone and intake_month and phone in phone_earliest_month:
        earliest = phone_earliest_month[phone]
        prior_lead_same_phone = '是' if earliest < intake_month else '否'

    out = dict(row)
    out['create_time'] = str(create_time)[:19] if create_time else ''
    out['key_from'] = key_from
    out['register_before_intake'] = register_before_intake
    out['days_register_to_intake'] = days_register_to_intake
    out['prior_lead_same_phone'] = prior_lead_same_phone
    output_rows.append(out)

# ── 6. 写 CSV ────────────────────────────────────────────────
fieldnames = list(leads[0].keys()) + ['create_time', 'key_from', 'register_before_intake', 'days_register_to_intake', 'prior_lead_same_phone']

with open('/root/.openclaw/workspace/output/ti_pool_split_20260608.csv', 'w', encoding='utf-8-sig', newline='') as f:
    writer = csv.DictWriter(f, fieldnames=fieldnames)
    writer.writeheader()
    writer.writerows(output_rows)

print(f"\n输出: output/ti_pool_split_20260608.csv, {len(output_rows)} 行")

# ── 7. 统计摘要 ──────────────────────────────────────────────
reg_before = sum(1 for r in output_rows if r['register_before_intake'] == '是')
reg_after = sum(1 for r in output_rows if r['register_before_intake'] == '否')
reg_unknown = sum(1 for r in output_rows if r['register_before_intake'] == '')
prior_yes = sum(1 for r in output_rows if r['prior_lead_same_phone'] == '是')
prior_no = sum(1 for r in output_rows if r['prior_lead_same_phone'] == '否')
prior_unknown = sum(1 for r in output_rows if r['prior_lead_same_phone'] == '')

print(f"\n── 统计摘要 ──")
print(f"注册早于进线月: 是={reg_before}, 否={reg_after}, 未知={reg_unknown}")
print(f"同手机号早前进线: 是={prior_yes}, 否={prior_no}, 未知={prior_unknown}")

cur.close()
conn.close()