445 lines
16 KiB
Python
445 lines
16 KiB
Python
# -*- coding: utf-8 -*-
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"""
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助教月度业绩汇总任务
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功能说明：
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以"助教+月份"为粒度，汇总月度业绩及档位计算
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数据来源：
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- dws_assistant_daily_detail: 日度明细（聚合）
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- dim_assistant: 助教维度（入职日期、等级）
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- cfg_performance_tier: 绩效档位配置
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目标表：
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billiards_dws.dws_assistant_monthly_summary
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更新策略：
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- 更新频率：每日更新当月数据
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- 幂等方式：delete-before-insert（按月份）
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业务规则：
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- 新入职判断：入职日期在月1日0点之后则为新入职
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- 有效业绩：total_hours - trashed_hours
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- 档位匹配：根据有效业绩小时数匹配cfg_performance_tier
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- 排名计算：按有效业绩小时数降序，考虑并列（如2个第一则都是1，下一个是3）
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作者：ETL团队
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创建日期：2026-02-01
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"""
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from __future__ import annotations
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from datetime import date, datetime, timedelta
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from decimal import Decimal
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from typing import Any, Dict, List, Optional, Set, Tuple
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from .base_dws_task import BaseDwsTask, TaskContext
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class AssistantMonthlyTask(BaseDwsTask):
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"""
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助教月度业绩汇总任务
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汇总每个助教每月的：
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- 工作天数、服务次数、时长
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- 有效业绩（扣除废除记录后）
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- 档位匹配
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- 月度排名（用于Top3奖金）
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"""
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def get_task_code(self) -> str:
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return "DWS_ASSISTANT_MONTHLY"
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def get_target_table(self) -> str:
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return "dws_assistant_monthly_summary"
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def get_primary_keys(self) -> List[str]:
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return ["site_id", "assistant_id", "stat_month"]
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# ==========================================================================
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# ETL主流程
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# ==========================================================================
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def extract(self, context: TaskContext) -> Dict[str, Any]:
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"""
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提取数据：从日度明细表聚合
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"""
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# 确定月份范围
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start_date = context.window_start.date() if hasattr(context.window_start, 'date') else context.window_start
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end_date = context.window_end.date() if hasattr(context.window_end, 'date') else context.window_end
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site_id = context.store_id
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# 获取涉及的月份列表
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months = self._get_months_in_range(start_date, end_date)
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self.logger.info(
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"%s: 提取数据，月份范围 %s",
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self.get_task_code(), [str(m) for m in months]
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)
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# 1. 获取日度明细聚合数据
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daily_aggregates = self._extract_daily_aggregates(site_id, months)
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# 2. 获取助教基本信息
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assistant_info = self._extract_assistant_info(site_id)
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# 3. 加载配置缓存
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self.load_config_cache()
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return {
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'daily_aggregates': daily_aggregates,
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'assistant_info': assistant_info,
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'months': months,
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'site_id': site_id
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}
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def transform(self, extracted: Dict[str, Any], context: TaskContext) -> List[Dict[str, Any]]:
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"""
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转换数据：计算月度汇总、档位匹配、排名
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"""
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daily_aggregates = extracted['daily_aggregates']
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assistant_info = extracted['assistant_info']
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months = extracted['months']
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site_id = extracted['site_id']
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self.logger.info(
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"%s: 转换数据，%d 个月份，%d 条聚合记录",
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self.get_task_code(), len(months), len(daily_aggregates)
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)
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# 按月份处理
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all_results = []
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for month in months:
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month_results = self._process_month(
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daily_aggregates,
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assistant_info,
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month,
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site_id
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)
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all_results.extend(month_results)
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return all_results
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def load(self, transformed: List[Dict[str, Any]], context: TaskContext) -> Dict:
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"""
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加载数据：写入DWS表
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"""
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if not transformed:
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self.logger.info("%s: 无数据需要写入", self.get_task_code())
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return {"counts": {"fetched": 0, "inserted": 0, "updated": 0, "skipped": 0, "errors": 0}}
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# 删除已存在的数据（按月份）
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deleted = self._delete_by_months(context, transformed)
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# 批量插入
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inserted = self.bulk_insert(transformed)
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self.logger.info(
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"%s: 加载完成，删除 %d 行，插入 %d 行",
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self.get_task_code(), deleted, inserted
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)
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return {
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"counts": {
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"fetched": len(transformed),
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"inserted": inserted,
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"updated": 0,
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"skipped": 0,
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"errors": 0
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},
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"extra": {"deleted": deleted}
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}
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# ==========================================================================
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# 数据提取方法
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# ==========================================================================
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def _get_months_in_range(self, start_date: date, end_date: date) -> List[date]:
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"""
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获取日期范围内的所有月份（月第一天）
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"""
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months = []
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current = start_date.replace(day=1)
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end_month = end_date.replace(day=1)
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while current <= end_month:
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months.append(current)
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# 下个月
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if current.month == 12:
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current = current.replace(year=current.year + 1, month=1)
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else:
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current = current.replace(month=current.month + 1)
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return months
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def _extract_daily_aggregates(
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self,
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site_id: int,
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months: List[date]
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) -> List[Dict[str, Any]]:
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"""
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从日度明细表提取并按月聚合
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"""
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if not months:
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return []
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# 构建月份条件
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month_conditions = []
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for month in months:
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next_month = (month.replace(day=28) + timedelta(days=4)).replace(day=1)
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month_conditions.append(f"(stat_date >= '{month}' AND stat_date < '{next_month}')")
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month_where = " OR ".join(month_conditions)
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sql = f"""
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SELECT
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assistant_id,
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assistant_nickname,
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assistant_level_code,
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assistant_level_name,
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DATE_TRUNC('month', stat_date)::DATE AS stat_month,
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COUNT(DISTINCT stat_date) AS work_days,
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SUM(total_service_count) AS total_service_count,
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SUM(base_service_count) AS base_service_count,
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SUM(bonus_service_count) AS bonus_service_count,
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SUM(total_hours) AS total_hours,
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SUM(base_hours) AS base_hours,
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SUM(bonus_hours) AS bonus_hours,
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SUM(total_ledger_amount) AS total_ledger_amount,
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SUM(base_ledger_amount) AS base_ledger_amount,
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SUM(bonus_ledger_amount) AS bonus_ledger_amount,
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SUM(unique_customers) AS total_unique_customers,
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SUM(unique_tables) AS total_unique_tables,
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SUM(trashed_seconds) AS trashed_seconds,
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SUM(trashed_count) AS trashed_count
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FROM billiards_dws.dws_assistant_daily_detail
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WHERE site_id = %s AND ({month_where})
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GROUP BY assistant_id, assistant_nickname, assistant_level_code, assistant_level_name,
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DATE_TRUNC('month', stat_date)
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"""
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rows = self.db.query(sql, (site_id,))
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return [dict(row) for row in rows] if rows else []
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def _extract_assistant_info(self, site_id: int) -> Dict[int, Dict[str, Any]]:
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"""
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提取助教基本信息
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"""
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sql = """
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SELECT
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site_assistant_id AS assistant_id,
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nickname,
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assistant_level,
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entry_date AS hire_date
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FROM billiards_dwd.dim_assistant
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WHERE site_id = %s
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AND valid_to IS NULL -- 当前有效记录
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"""
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rows = self.db.query(sql, (site_id,))
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result = {}
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for row in (rows or []):
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row_dict = dict(row)
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result[row_dict['assistant_id']] = row_dict
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return result
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# ==========================================================================
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# 数据转换方法
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# ==========================================================================
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def _process_month(
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self,
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daily_aggregates: List[Dict[str, Any]],
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assistant_info: Dict[int, Dict[str, Any]],
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month: date,
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site_id: int
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) -> List[Dict[str, Any]]:
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"""
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处理单个月份的数据
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"""
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# 筛选该月份的数据
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month_data = [
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agg for agg in daily_aggregates
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if agg.get('stat_month') == month
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]
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if not month_data:
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return []
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# 构建月度汇总记录
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month_records = []
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for agg in month_data:
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assistant_id = agg.get('assistant_id')
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asst_info = assistant_info.get(assistant_id, {})
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# 计算有效业绩
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total_hours = self.safe_decimal(agg.get('total_hours', 0))
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trashed_hours = self.seconds_to_hours(self.safe_int(agg.get('trashed_seconds', 0)))
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effective_hours = total_hours - trashed_hours
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# 判断是否新入职
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hire_date = asst_info.get('hire_date')
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is_new_hire = False
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if hire_date:
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if isinstance(hire_date, datetime):
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hire_date = hire_date.date()
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is_new_hire = self.is_new_hire_in_month(hire_date, month)
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# 匹配档位
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tier_hours = effective_hours
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max_tier_level = None
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if is_new_hire:
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tier_hours = self._calc_new_hire_tier_hours(effective_hours, self.safe_int(agg.get('work_days', 0)))
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if hire_date and hire_date.day > 25:
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max_tier_level = 3
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tier = self.get_performance_tier(
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tier_hours,
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is_new_hire,
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effective_date=month,
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max_tier_level=max_tier_level
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)
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# 获取月末的等级信息（用于记录）
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month_end = self._get_month_end(month)
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level_info = self.get_assistant_level_asof(assistant_id, month_end)
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record = {
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'site_id': site_id,
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'tenant_id': self.config.get("app.tenant_id", site_id),
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'assistant_id': assistant_id,
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'assistant_nickname': agg.get('assistant_nickname'),
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'stat_month': month,
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'assistant_level_code': level_info.get('level_code') if level_info else agg.get('assistant_level_code'),
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'assistant_level_name': level_info.get('level_name') if level_info else agg.get('assistant_level_name'),
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'hire_date': hire_date,
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'is_new_hire': is_new_hire,
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'work_days': self.safe_int(agg.get('work_days', 0)),
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'total_service_count': self.safe_int(agg.get('total_service_count', 0)),
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'base_service_count': self.safe_int(agg.get('base_service_count', 0)),
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'bonus_service_count': self.safe_int(agg.get('bonus_service_count', 0)),
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'total_hours': total_hours,
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'base_hours': self.safe_decimal(agg.get('base_hours', 0)),
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'bonus_hours': self.safe_decimal(agg.get('bonus_hours', 0)),
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'effective_hours': effective_hours,
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'trashed_hours': trashed_hours,
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'total_ledger_amount': self.safe_decimal(agg.get('total_ledger_amount', 0)),
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'base_ledger_amount': self.safe_decimal(agg.get('base_ledger_amount', 0)),
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'bonus_ledger_amount': self.safe_decimal(agg.get('bonus_ledger_amount', 0)),
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'unique_customers': self.safe_int(agg.get('total_unique_customers', 0)),
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'unique_tables': self.safe_int(agg.get('total_unique_tables', 0)),
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'avg_service_seconds': self._calc_avg_service_seconds(agg),
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'tier_id': tier.get('tier_id') if tier else None,
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'tier_code': tier.get('tier_code') if tier else None,
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'tier_name': tier.get('tier_name') if tier else None,
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'rank_by_hours': None, # 后面计算
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'rank_with_ties': None, # 后面计算
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}
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month_records.append(record)
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# 计算排名
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self._calculate_ranks(month_records)
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return month_records
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def _get_month_end(self, month: date) -> date:
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"""
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获取月末日期
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"""
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if month.month == 12:
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next_month = month.replace(year=month.year + 1, month=1, day=1)
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else:
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next_month = month.replace(month=month.month + 1, day=1)
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return next_month - timedelta(days=1)
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def _calc_avg_service_seconds(self, agg: Dict[str, Any]) -> Decimal:
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"""
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计算平均单次服务时长
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"""
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total_count = self.safe_int(agg.get('total_service_count', 0))
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if total_count == 0:
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return Decimal('0')
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total_hours = self.safe_decimal(agg.get('total_hours', 0))
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total_seconds = total_hours * Decimal('3600')
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return total_seconds / Decimal(str(total_count))
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def _calc_new_hire_tier_hours(self, effective_hours: Decimal, work_days: int) -> Decimal:
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"""
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新入职定档：日均 * 30（仅用于定档，不影响奖金与排名）
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"""
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if work_days <= 0:
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return Decimal('0')
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return (effective_hours / Decimal(str(work_days))) * Decimal('30')
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def _calculate_ranks(self, records: List[Dict[str, Any]]) -> None:
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"""
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计算排名（考虑并列）
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Top3排名口径：按有效业绩总小时数排名，
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如遇并列则都算，比如2个第一，则记为2个第一，一个第三
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"""
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if not records:
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return
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# 按有效业绩降序排序
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sorted_records = sorted(
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records,
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key=lambda x: x.get('effective_hours', Decimal('0')),
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reverse=True
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)
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# 计算考虑并列的排名
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values = [
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(r.get('assistant_id'), r.get('effective_hours', Decimal('0')))
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for r in sorted_records
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]
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ranked = self.calculate_rank_with_ties(values)
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# 创建排名映射
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rank_map = {
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assistant_id: (rank, dense_rank)
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for assistant_id, rank, dense_rank in ranked
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}
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# 更新记录
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for record in records:
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assistant_id = record.get('assistant_id')
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if assistant_id in rank_map:
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rank, _ = rank_map[assistant_id]
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record['rank_by_hours'] = rank
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record['rank_with_ties'] = rank # 使用考虑并列的排名
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def _delete_by_months(
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self,
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context: TaskContext,
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records: List[Dict[str, Any]]
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) -> int:
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"""
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按月份删除已存在的数据
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"""
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# 获取涉及的月份
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months = set(r.get('stat_month') for r in records if r.get('stat_month'))
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if not months:
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return 0
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target_table = self.get_target_table()
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full_table = f"{self.DWS_SCHEMA}.{target_table}"
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total_deleted = 0
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with self.db.conn.cursor() as cur:
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for month in months:
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sql = f"""
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DELETE FROM {full_table}
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WHERE site_id = %s AND stat_month = %s
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"""
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cur.execute(sql, (context.store_id, month))
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total_deleted += cur.rowcount
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return total_deleted
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# 便于外部导入
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__all__ = ['AssistantMonthlyTask']
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