586 lines
23 KiB
Python
586 lines
23 KiB
Python
# -*- coding: utf-8 -*-
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"""生成 2025年10-12月 助教排行榜 + 助教详情表（CSV + MD）。
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输出目录：etl_billiards/docs/table_2025-12-19
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注意：客户流水/充值归因涉及“多助教/多订单命中”时按全额复制计入，会导致助教汇总>门店汇总，表格说明会写明。
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"""
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from __future__ import annotations
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import csv
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import re
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from dataclasses import dataclass
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from decimal import Decimal
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from pathlib import Path
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from statistics import median
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from typing import Any
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import psycopg2
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import psycopg2.extras
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SITE_ID = 2790685415443269
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TZ = "Asia/Shanghai"
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WIN_OCT = ("2025-10-01 00:00:00+08", "2025-11-01 00:00:00+08")
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WIN_NOV = ("2025-11-01 00:00:00+08", "2025-12-01 00:00:00+08")
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WIN_DEC = ("2025-12-01 00:00:00+08", "2026-01-01 00:00:00+08")
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WIN_ALL = (WIN_OCT[0], WIN_DEC[1])
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MONTHS = [
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("2025-10", "10月", WIN_OCT),
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("2025-11", "11月", WIN_NOV),
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("2025-12", "12月", WIN_DEC),
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]
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REPO_ROOT = Path(__file__).resolve().parents[3]
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ENV_PATH = REPO_ROOT / "etl_billiards" / ".env"
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OUT_DIR = Path(__file__).resolve().parent
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@dataclass(frozen=True)
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class SqlBlock:
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title: str
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sql: str
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def read_pg_dsn() -> str:
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text = ENV_PATH.read_text(encoding="utf-8")
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m = re.search(r"^PG_DSN=(.+)$", text, re.M)
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if not m:
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raise RuntimeError(f"未在 {ENV_PATH} 中找到 PG_DSN")
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return m.group(1).strip()
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def conn():
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return psycopg2.connect(read_pg_dsn(), connect_timeout=10)
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def sanitize_filename(name: str) -> str:
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name = name.strip()
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name = re.sub(r"[<>:\"/\\|?*]+", "_", name)
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name = re.sub(r"\s+", " ", name)
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return name
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def d(v: Any) -> Decimal:
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if v is None:
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return Decimal("0")
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if isinstance(v, Decimal):
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return v
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return Decimal(str(v))
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def fmt_money(v: Any) -> str:
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return f"{d(v):.2f}"
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def fmt_hours(v: Any, digits: int = 2) -> str:
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q = Decimal("1").scaleb(-digits)
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return f"{d(v).quantize(q):f}h"
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def write_csv(path: Path, title: str, description: str, header_rows: list[list[str]], rows: list[list[Any]]) -> None:
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path.parent.mkdir(parents=True, exist_ok=True)
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with path.open("w", newline="", encoding="utf-8") as f:
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w = csv.writer(f)
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w.writerow([title])
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w.writerow([description])
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w.writerow([])
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for hr in header_rows:
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w.writerow(hr)
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for r in rows:
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w.writerow(["" if v is None else v for v in r])
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def write_csv_sections(path: Path, title: str, description: str, section_rows: list[list[Any]]) -> None:
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path.parent.mkdir(parents=True, exist_ok=True)
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with path.open("w", newline="", encoding="utf-8") as f:
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w = csv.writer(f)
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w.writerow([title])
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w.writerow([description])
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w.writerow([])
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for r in section_rows:
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w.writerow(["" if v is None else v for v in r])
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def write_md(path: Path, title: str, thinking: str, description: str, sql_blocks: list[SqlBlock]) -> None:
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parts: list[str] = []
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parts.append(f"# {title}\n")
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parts.append("## 思考过程\n")
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parts.append(thinking.strip() + "\n")
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parts.append("\n## 查询说明\n")
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parts.append(description.strip() + "\n")
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parts.append("\n## SQL\n")
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for b in sql_blocks:
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parts.append(f"\n### {b.title}\n")
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parts.append("```sql\n")
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parts.append(b.sql.strip() + "\n")
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parts.append("```\n")
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path.parent.mkdir(parents=True, exist_ok=True)
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path.write_text("".join(parts), encoding="utf-8")
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def fetch_all(cur, sql: str, params: dict[str, Any]) -> list[dict[str, Any]]:
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cur.execute(sql, params)
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return list(cur.fetchall())
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def month_case(ts_expr: str) -> str:
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parts = []
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for month_key, _, (ws, we) in MONTHS:
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parts.append(
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f"when {ts_expr} >= '{ws}'::timestamptz and {ts_expr} < '{we}'::timestamptz then '{month_key}'"
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)
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return "case " + " ".join(parts) + " else null end"
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def sql_order_base(window_start: str, window_end: str) -> str:
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return f"""
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with base_orders as (
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select
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tfl.order_settle_id,
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max(tfl.member_id) as member_id,
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min(tfl.start_use_time) as order_start_time,
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max(tfl.ledger_end_time) as order_end_time,
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sum(tfl.ledger_amount) as table_amount
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from billiards_dwd.dwd_table_fee_log tfl
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where tfl.site_id = %(site_id)s
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and coalesce(tfl.is_delete,0) = 0
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and tfl.start_use_time >= '{window_start}'::timestamptz
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and tfl.start_use_time < '{window_end}'::timestamptz
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group by tfl.order_settle_id
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),
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assistant_amount as (
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select
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asl.order_settle_id,
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sum(asl.ledger_amount) as assistant_amount
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from billiards_dwd.dwd_assistant_service_log asl
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join base_orders bo on bo.order_settle_id = asl.order_settle_id
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where asl.site_id = %(site_id)s
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and coalesce(asl.is_delete,0) = 0
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group by asl.order_settle_id
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),
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goods_amount as (
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select
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g.order_settle_id,
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sum(g.ledger_amount) as goods_amount
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from billiards_dwd.dwd_store_goods_sale g
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join base_orders bo on bo.order_settle_id = g.order_settle_id
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where g.site_id = %(site_id)s
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and coalesce(g.is_delete,0) = 0
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group by g.order_settle_id
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),
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orders as (
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select
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bo.order_settle_id,
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bo.member_id,
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bo.order_start_time,
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bo.order_end_time,
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coalesce(bo.table_amount,0) + coalesce(a.assistant_amount,0) + coalesce(g.goods_amount,0) as order_amount
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from base_orders bo
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left join assistant_amount a on a.order_settle_id = bo.order_settle_id
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left join goods_amount g on g.order_settle_id = bo.order_settle_id
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)
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"""
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def dense_rank_desc(values: dict[str, Decimal]) -> dict[str, int]:
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uniq = sorted({v for v in values.values() if v > 0}, reverse=True)
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rank_map = {v: i + 1 for i, v in enumerate(uniq)}
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return {k: rank_map.get(v, 0) for k, v in values.items()}
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def calc_diff(all_values: dict[str, Decimal], current: Decimal) -> tuple[Decimal, Decimal]:
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xs = [v for v in all_values.values() if v > 0]
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if not xs or current <= 0:
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return Decimal("0"), Decimal("0")
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avg = sum(xs) / Decimal(len(xs))
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med = Decimal(str(median([float(v) for v in xs])))
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return current - avg, current - med
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def main() -> None:
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OUT_DIR.mkdir(parents=True, exist_ok=True)
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with conn() as c, c.cursor(cursor_factory=psycopg2.extras.RealDictCursor) as cur:
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assistants_rows = fetch_all(
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cur,
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"""
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select distinct nickname as assistant
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from billiards_dwd.dwd_assistant_service_log
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where site_id=%(site_id)s and coalesce(is_delete,0)=0
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and start_use_time >= %(window_start)s::timestamptz
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and start_use_time < %(window_end)s::timestamptz
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order by assistant;
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""",
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{"site_id": SITE_ID, "window_start": WIN_ALL[0], "window_end": WIN_ALL[1]},
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)
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assistants = [r["assistant"] for r in assistants_rows if r.get("assistant")]
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# 助教-客户-月份：服务时长
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sql_svc = f"""
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with raw as (
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select
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asl.nickname as assistant,
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asl.tenant_member_id as member_id,
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{month_case('asl.start_use_time')} as month_key,
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asl.order_assistant_type,
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asl.income_seconds
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from billiards_dwd.dwd_assistant_service_log asl
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where asl.site_id=%(site_id)s and coalesce(asl.is_delete,0)=0
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and asl.start_use_time >= %(window_start)s::timestamptz
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and asl.start_use_time < %(window_end)s::timestamptz
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and asl.tenant_member_id is not null and asl.tenant_member_id<>0
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)
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select
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assistant,
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member_id,
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month_key,
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sum(case when order_assistant_type=1 then income_seconds else 0 end)/3600.0 as base_hours,
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sum(case when order_assistant_type=2 then income_seconds else 0 end)/3600.0 as extra_hours
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from raw
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where month_key is not null
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group by assistant, member_id, month_key;
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"""
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svc_rows = fetch_all(cur, sql_svc, {"site_id": SITE_ID, "window_start": WIN_ALL[0], "window_end": WIN_ALL[1]})
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# 助教-客户-月份：客户流水
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sql_rev = sql_order_base(WIN_ALL[0], WIN_ALL[1]) + f"""
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, assistant_orders as (
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select distinct order_settle_id, nickname as assistant
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from billiards_dwd.dwd_assistant_service_log
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where site_id=%(site_id)s and coalesce(is_delete,0)=0
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and start_use_time >= %(window_start)s::timestamptz
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and start_use_time < %(window_end)s::timestamptz
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),
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raw as (
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select
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ao.assistant,
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o.member_id,
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{month_case('o.order_start_time')} as month_key,
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o.order_amount
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from orders o
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join assistant_orders ao on ao.order_settle_id=o.order_settle_id
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where o.member_id is not null and o.member_id<>0
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)
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select
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assistant,
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member_id,
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month_key,
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sum(order_amount) as revenue_amount
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from raw
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where month_key is not null
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group by assistant, member_id, month_key;
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"""
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rev_rows = fetch_all(cur, sql_rev, {"site_id": SITE_ID, "window_start": WIN_ALL[0], "window_end": WIN_ALL[1]})
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# 助教-客户-月份：充值归因
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sql_rech = f"""
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with base_orders as (
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select
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tfl.order_settle_id,
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max(tfl.member_id) as member_id,
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min(tfl.start_use_time) as table_start_time,
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max(tfl.ledger_end_time) as table_end_time
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from billiards_dwd.dwd_table_fee_log tfl
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where tfl.site_id=%(site_id)s and coalesce(tfl.is_delete,0)=0
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and tfl.start_use_time >= %(window_start)s::timestamptz
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and tfl.start_use_time < %(window_end)s::timestamptz
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group by tfl.order_settle_id
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),
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assistant_time as (
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select
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asl.order_settle_id,
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min(asl.start_use_time) as assistant_start_time,
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max(asl.last_use_time) as assistant_end_time
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from billiards_dwd.dwd_assistant_service_log asl
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join base_orders bo on bo.order_settle_id=asl.order_settle_id
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where asl.site_id=%(site_id)s and coalesce(asl.is_delete,0)=0
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group by asl.order_settle_id
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),
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order_windows as (
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select
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bo.order_settle_id,
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bo.member_id,
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least(bo.table_start_time, coalesce(at.assistant_start_time, bo.table_start_time)) as win_start,
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greatest(bo.table_end_time, coalesce(at.assistant_end_time, bo.table_end_time)) as win_end
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from base_orders bo
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left join assistant_time at on at.order_settle_id=bo.order_settle_id
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where bo.member_id is not null and bo.member_id<>0
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),
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assistant_orders as (
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select distinct order_settle_id, nickname as assistant
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from billiards_dwd.dwd_assistant_service_log
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where site_id=%(site_id)s and coalesce(is_delete,0)=0
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and start_use_time >= %(window_start)s::timestamptz
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and start_use_time < %(window_end)s::timestamptz
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),
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recharge_pay as (
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select
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p.pay_time,
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r.member_id,
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p.pay_amount
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from billiards_dwd.dwd_payment p
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join billiards_dwd.dwd_recharge_order r on r.recharge_order_id=p.relate_id
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where p.site_id=%(site_id)s
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and p.relate_type=5
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and p.pay_status=2
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and p.pay_amount>0
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and p.pay_time >= %(window_start)s::timestamptz
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and p.pay_time < %(window_end)s::timestamptz
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),
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matched as (
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select
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rp.pay_time,
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ow.order_settle_id,
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ow.member_id,
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rp.pay_amount
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from recharge_pay rp
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join order_windows ow
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on ow.member_id=rp.member_id
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and rp.pay_time >= ow.win_start - interval '30 minutes'
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and rp.pay_time <= ow.win_end + interval '30 minutes'
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),
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raw as (
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select
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ao.assistant,
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m.member_id,
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{month_case('m.pay_time')} as month_key,
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m.pay_amount
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from matched m
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join assistant_orders ao on ao.order_settle_id=m.order_settle_id
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)
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select
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assistant,
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member_id,
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month_key,
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sum(pay_amount) as recharge_amount
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from raw
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where month_key is not null
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group by assistant, member_id, month_key;
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"""
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rech_rows = fetch_all(cur, sql_rech, {"site_id": SITE_ID, "window_start": WIN_ALL[0], "window_end": WIN_ALL[1]})
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# 汇总：月度助教指标
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svc_map = {mk: {a: {"base": Decimal('0'), "extra": Decimal('0')} for a in assistants} for mk,_,_ in MONTHS}
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for r in svc_rows:
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mk = r["month_key"]; a = r["assistant"]
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if mk in svc_map and a in svc_map[mk]:
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svc_map[mk][a]["base"] += d(r["base_hours"])
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svc_map[mk][a]["extra"] += d(r["extra_hours"])
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revenue_map = {mk: {a: Decimal('0') for a in assistants} for mk,_,_ in MONTHS}
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for r in rev_rows:
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mk = r["month_key"]; a = r["assistant"]
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if mk in revenue_map and a in revenue_map[mk]:
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revenue_map[mk][a] += d(r["revenue_amount"])
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recharge_map = {mk: {a: Decimal('0') for a in assistants} for mk,_,_ in MONTHS}
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for r in rech_rows:
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mk = r["month_key"]; a = r["assistant"]
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if mk in recharge_map and a in recharge_map[mk]:
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recharge_map[mk][a] += d(r["recharge_amount"])
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# ====== 输出4张排行榜 ======
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def write_rank(file_stem: str, title: str, desc: str, rows: list[list[Any]]):
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write_csv(OUT_DIR / f"{file_stem}.csv", title, desc, [["月份", "排名", "助教昵称", "指标"]], rows)
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write_md(OUT_DIR / f"{file_stem}.md", title, "按月聚合并做dense_rank排名。", desc, [])
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rows = []
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for mk,_,_ in MONTHS:
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values = {a: svc_map[mk][a]["base"] for a in assistants}
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ranks = dense_rank_desc(values)
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for a in sorted(assistants, key=lambda x: (ranks[x] if ranks[x] else 999999, x)):
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v = values[a]
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if v > 0:
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rows.append([mk, ranks[a], a, fmt_hours(v, 2)])
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write_rank(
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"助教_基础课时长排行_2025年10-12月",
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"2025年10-12月 助教基础课时长排行榜",
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"口径：order_assistant_type=1，时长=income_seconds/3600（小时），按月排名。",
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rows,
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)
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rows = []
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for mk,_,_ in MONTHS:
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values = {a: svc_map[mk][a]["extra"] for a in assistants}
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ranks = dense_rank_desc(values)
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for a in sorted(assistants, key=lambda x: (ranks[x] if ranks[x] else 999999, x)):
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v = values[a]
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if v > 0:
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rows.append([mk, ranks[a], a, fmt_hours(v, 2)])
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write_rank(
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"助教_附加课时长排行_2025年10-12月",
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"2025年10-12月 助教附加课(超休)时长排行榜",
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"口径：order_assistant_type=2，超休时长=income_seconds/3600（小时），按月排名。",
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rows,
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)
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rows = []
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for mk,_,_ in MONTHS:
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values = revenue_map[mk]
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ranks = dense_rank_desc(values)
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for a in sorted(assistants, key=lambda x: (ranks[x] if ranks[x] else 999999, x)):
|
||
v = values[a]
|
||
if v > 0:
|
||
rows.append([mk, ranks[a], a, fmt_money(v)])
|
||
write_rank(
|
||
"助教_客户流水排行_2025年10-12月",
|
||
"2025年10-12月 助教客户流水排行榜（全额复制口径）",
|
||
"口径：客户流水=台费+助教+商品应付金额按订单归集后，全额计入订单内每位助教；多助教会导致汇总>门店总额。",
|
||
rows,
|
||
)
|
||
|
||
rows = []
|
||
for mk,_,_ in MONTHS:
|
||
values = recharge_map[mk]
|
||
ranks = dense_rank_desc(values)
|
||
for a in sorted(assistants, key=lambda x: (ranks[x] if ranks[x] else 999999, x)):
|
||
v = values[a]
|
||
if v > 0:
|
||
rows.append([mk, ranks[a], a, fmt_money(v)])
|
||
write_rank(
|
||
"助教_客户充值归因排行_2025年10-12月",
|
||
"2025年10-12月 助教客户充值归因排行榜（全额复制口径）",
|
||
"口径：充值支付(dwd_payment.relate_type=5)在消费窗口±30分钟内命中且订单有助教，则全额计入助教；多助教/多订单命中会重复计入。",
|
||
rows,
|
||
)
|
||
|
||
# ====== 输出助教详情（每人一份） ======
|
||
# 会员昵称
|
||
cur.execute("select member_id, nickname from billiards_dwd.dim_member where scd2_is_current=1")
|
||
member_name = {r["member_id"]: (r.get("nickname") or "") for r in cur.fetchall()}
|
||
|
||
# 索引：assistant->member->month
|
||
svc_idx = {a: {} for a in assistants}
|
||
for r in svc_rows:
|
||
a = r["assistant"]; mid = int(r["member_id"]); mk = r["month_key"]
|
||
svc_idx.setdefault(a, {}).setdefault(mid, {})[mk] = {"base": d(r["base_hours"]), "extra": d(r["extra_hours"])}
|
||
|
||
rev_idx = {a: {} for a in assistants}
|
||
for r in rev_rows:
|
||
a = r["assistant"]; mid = int(r["member_id"]); mk = r["month_key"]
|
||
rev_idx.setdefault(a, {}).setdefault(mid, {})[mk] = d(r["revenue_amount"])
|
||
|
||
rech_idx = {a: {} for a in assistants}
|
||
for r in rech_rows:
|
||
a = r["assistant"]; mid = int(r["member_id"]); mk = r["month_key"]
|
||
rech_idx.setdefault(a, {}).setdefault(mid, {})[mk] = d(r["recharge_amount"])
|
||
|
||
for a in assistants:
|
||
safe = sanitize_filename(a)
|
||
csv_path = OUT_DIR / f"助教详情_{safe}.csv"
|
||
md_path = OUT_DIR / f"助教详情_{safe}.md"
|
||
|
||
# 评价（简短）
|
||
base_total = sum((svc_map[mk][a]["base"] for mk,_,_ in MONTHS), Decimal('0'))
|
||
extra_total = sum((svc_map[mk][a]["extra"] for mk,_,_ in MONTHS), Decimal('0'))
|
||
rev_total = sum((revenue_map[mk][a] for mk,_,_ in MONTHS), Decimal('0'))
|
||
rech_total = sum((recharge_map[mk][a] for mk,_,_ in MONTHS), Decimal('0'))
|
||
|
||
# 头部客户 Top100（按12月消费业绩）
|
||
members = set(rev_idx.get(a, {}).keys()) | set(svc_idx.get(a, {}).keys()) | set(rech_idx.get(a, {}).keys())
|
||
def rev_dec(mid: int) -> Decimal:
|
||
return rev_idx.get(a, {}).get(mid, {}).get('2025-12', Decimal('0'))
|
||
top_members = sorted(members, key=lambda mid: rev_dec(mid), reverse=True)[:100]
|
||
|
||
top3 = '、'.join([(member_name.get(mid) or str(mid)) for mid in top_members[:3]])
|
||
assistant_review = (
|
||
f"评价：基础{fmt_hours(base_total,1)}，附加{fmt_hours(extra_total,1)}；"
|
||
f"客户流水¥{rev_total:.2f}，充值归因¥{rech_total:.2f}；"
|
||
f"头部客户(12月)Top3：{top3 or '无'}。"
|
||
)
|
||
|
||
# Part1-4
|
||
part1=[]; part2=[]; part3=[]; part4=[]
|
||
for mk, mcn, _ in MONTHS:
|
||
base_v = svc_map[mk][a]["base"]
|
||
extra_v = svc_map[mk][a]["extra"]
|
||
rev_v = revenue_map[mk][a]
|
||
rech_v = recharge_map[mk][a]
|
||
|
||
base_all = {x: svc_map[mk][x]["base"] for x in assistants}
|
||
extra_all = {x: svc_map[mk][x]["extra"] for x in assistants}
|
||
rev_all = {x: revenue_map[mk][x] for x in assistants}
|
||
rech_all = {x: recharge_map[mk][x] for x in assistants}
|
||
|
||
base_rank = dense_rank_desc(base_all).get(a, 0)
|
||
extra_rank = dense_rank_desc(extra_all).get(a, 0)
|
||
rev_rank = dense_rank_desc(rev_all).get(a, 0)
|
||
rech_rank = dense_rank_desc(rech_all).get(a, 0)
|
||
|
||
base_da, base_dm = calc_diff(base_all, base_v)
|
||
extra_da, extra_dm = calc_diff(extra_all, extra_v)
|
||
rev_da, rev_dm = calc_diff(rev_all, rev_v)
|
||
rech_da, rech_dm = calc_diff(rech_all, rech_v)
|
||
|
||
part1.append([mcn, fmt_hours(base_v,2), base_rank or "", fmt_hours(base_da,2), fmt_hours(base_dm,2)])
|
||
part2.append([mcn, fmt_hours(extra_v,2), extra_rank or "", fmt_hours(extra_da,2), fmt_hours(extra_dm,2)])
|
||
part3.append([mcn, fmt_money(rev_v), rev_rank or "", fmt_money(rev_da), fmt_money(rev_dm)])
|
||
part4.append([mcn, fmt_money(rech_v), rech_rank or "", fmt_money(rech_da), fmt_money(rech_dm)])
|
||
|
||
# Part5 rows
|
||
part5=[]
|
||
for i, mid in enumerate(top_members, start=1):
|
||
def h_pair(month_key: str) -> str:
|
||
v = svc_idx.get(a, {}).get(mid, {}).get(month_key, {})
|
||
return f"{fmt_hours(v.get('base',Decimal('0')),1)} / {fmt_hours(v.get('extra',Decimal('0')),1)}"
|
||
def rev_m(month_key: str) -> Decimal:
|
||
return rev_idx.get(a, {}).get(mid, {}).get(month_key, Decimal('0'))
|
||
def rech_m(month_key: str) -> Decimal:
|
||
return rech_idx.get(a, {}).get(mid, {}).get(month_key, Decimal('0'))
|
||
name = member_name.get(mid) or str(mid)
|
||
part5.append([
|
||
i,
|
||
name,
|
||
h_pair('2025-12'), fmt_money(rev_m('2025-12')), fmt_money(rech_m('2025-12')),
|
||
h_pair('2025-11'), fmt_money(rev_m('2025-11')), fmt_money(rech_m('2025-11')),
|
||
h_pair('2025-10'), fmt_money(rev_m('2025-10')), fmt_money(rech_m('2025-10')),
|
||
])
|
||
|
||
title = f"助教详情：{a}（2025年10-12月）"
|
||
desc = (
|
||
"本表包含5个部分：基础课业绩、附加课业绩、客户消费业绩、客户充值业绩、头部客户情况。"
|
||
"均值/中位数差值对比集合为当月该指标>0的助教。"
|
||
"充值/客户流水多助教与多订单命中均按全额复制计入，故汇总可能大于门店总额。"
|
||
)
|
||
|
||
rows=[]
|
||
rows += [["一、基础课业绩"], ["说明：" + assistant_review], []]
|
||
rows += [["月份", "基础课业绩", "基础课业绩", "基础课业绩", "基础课业绩"], ["月份", "小时数", "排名", "平均值差值小时数", "中位数值差值小时数"]]
|
||
rows += part1
|
||
rows += [[], ["二、附加课业绩"], ["说明：附加课=order_assistant_type=2。"], []]
|
||
rows += [["月份", "附加课业绩", "附加课业绩", "附加课业绩", "附加课业绩"], ["月份", "小时数", "排名", "平均值差值小时数", "中位数值差值小时数"]]
|
||
rows += part2
|
||
rows += [[], ["三、客户消费业绩"], ["说明：订单台费+助教+商品应付金额全额计入订单内助教。"], []]
|
||
rows += [["月份", "客户消费业绩", "客户消费业绩", "客户消费业绩", "客户消费业绩"], ["月份", "合计元", "排名", "平均值差值元", "中位数值差值元"]]
|
||
rows += part3
|
||
rows += [[], ["四、客户充值业绩"], ["说明：充值命中消费窗口±30分钟且有助教则归因；全额复制。"], []]
|
||
rows += [["月份", "客户充值业绩", "客户充值业绩", "客户充值业绩", "客户充值业绩"], ["月份", "合计元", "排名", "平均值差值元", "中位数值差值元"]]
|
||
rows += part4
|
||
rows += [[], ["五、头部客户（按12月消费业绩排序，Top100）"], ["说明：基础/附加课时=基础h/附加h。"], []]
|
||
rows += [["排名", "客户名称", "12月", "12月", "12月", "11月", "11月", "11月", "10月", "10月", "10月"],
|
||
["排名", "客户名称", "基础/附加课时", "消费业绩(元)", "客户充值(元)", "基础/附加课时", "消费业绩(元)", "客户充值(元)", "基础/附加课时", "消费业绩(元)", "客户充值(元)"]]
|
||
rows += part5
|
||
|
||
write_csv_sections(csv_path, title, desc, rows)
|
||
write_md(
|
||
md_path,
|
||
title,
|
||
"按模板拆分5部分输出；月度排名采用dense_rank；均值/中位数在当月该指标>0助教集合上计算。",
|
||
desc + "\n" + assistant_review,
|
||
[
|
||
SqlBlock("服务时长（助教-客户-月份）", sql_svc),
|
||
SqlBlock("客户流水（助教-客户-月份）", sql_rev),
|
||
SqlBlock("充值归因（助教-客户-月份）", sql_rech),
|
||
],
|
||
)
|
||
|
||
print(f"完成：{OUT_DIR}")
|
||
|
||
|
||
if __name__ == "__main__":
|
||
main()
|