feat(strategy-map): live board reading map_objectives + kpi_targets (read-only)
Task: finance-20261011-strategy-map-frontend-fullstack (P2, read-only integration)
- backend/app/utils/strategy_board.py: single source of truth for the level
caliber (layer colors, inverse-kpi explicit whitelist, status class by
unit, zero guard, period ranking, latest-actual picking). Pure functions.
- backend/app/api/maps.py: GET /api/cma/maps/{map_id}/strategy-board
- nodes straight from map_objectives (sorted by sort_order, id)
- node<->kpi binding with 4-step fallback, binding_source echoed back
- targets from kpi_targets (target_type compatible: yearly + annual),
deduped per (kpi_id, period) with yearly preferred
- actuals from kpi_values actual-only scope, latest period
- causality edges from kpi_causality, out-of-map endpoints dropped+counted
- entity_id taken from the token only (no cross-tenant reads)
- zero writes; nothing is persisted by this endpoint
- frontend/src/views/StrategyMap.vue: /strategy-map live board (4 swim lanes
bottom-up, node cards, 20 causality arrows in SVG, period switch, A3 print).
No emoji, null guards everywhere (no toFixed on null).
- api/index.ts + router/index.ts + permission.ts: route + menu registration
(/strategy-map, zone A read-only, roles ceo/finance/business/it).
- backend/tests/test_strategy_board_20261011.py: 33 cases (spec section 4 /
4.1 / 4.2 / 4.3 + section 7 fixtures + threshold boundaries + period rank).
- backend/tests/test_map_objectives_kpis_form_20261011.py: 14 cases for the
four kpis column shapes (list, json string, object list, NULL/[]/weird).
Not included: push + backend restart (production write, separate gate).
(cherry picked from commit c675bde6b4beaf1d8a9d02a80f5434203a53f348)
This commit is contained in:
Hermes CI Fix
@@ -1,5 +1,6 @@
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"""战略地图 API"""
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from fastapi import APIRouter, Depends, HTTPException, Query
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from sqlalchemy import text
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from sqlalchemy.orm import Session
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from typing import Optional
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from datetime import date, datetime, timedelta
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@@ -1227,3 +1228,320 @@ def get_review_record(
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raise HTTPException(404, "复盘记录不存在")
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return review_to_dict(r)
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# ── 战略地图「活看板」（只读）────────────────────────────────────────
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# 任务：finance-20261011-strategy-map-frontend-fullstack（任总 2026-10-11 19:07「收口」）
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# 口径单一源：app/utils/strategy_board.py（色阶/逆指标白名单/状态类/零点保护）
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# 只读：本端点不写任何表；entity_id 严格取 token → 博海 e2 天然隔离。
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# kpi_targets.target_type 取值：兼容期读两形（不阻塞渲染）
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# - 现状（2026-10-11 只读实测）：全库仅 `annual: 57`（e1 战略框架同步写入，值域外）
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# - P0 修正单 finance-20261011-kpi-targets-targettype-fix-dama 会把它们改成 `yearly`
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# - 两形都读 ⇒ 修正前后同一份代码都取得到数；同 (kpi_id, period) 重复时偏好 `yearly`
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_PERIOD_TYPES = ("yearly", "annual")
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def _sb_resolve_bindings(db: Session, entity_id: int, objs: list) -> tuple[dict, dict]:
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"""节点 ↔ KPI 绑定：优先 `map_objectives.kpis`（收口单已回填），缺失时按名称回查。
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返回 (bindings, sources)：``bindings[obj.id] = (kpi_id, kpi_code)``；
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``sources[obj.id]`` ∈ {kpis, kpis_code, name, note, none} —— 供复核方判断
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是否已用上 19 条回填绑定（回填前 name/note 兜底）。
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"""
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from app.models import KPIDefinition
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bindings: dict = {}
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sources: dict = {}
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declared_codes: dict = {}
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for obj in objs:
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raw = obj.kpis
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if isinstance(raw, str):
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try:
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raw = json.loads(raw)
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except Exception:
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raw = None
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if isinstance(raw, dict):
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raw = [raw]
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if not isinstance(raw, list):
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continue
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for item in raw:
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if isinstance(item, dict):
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kid, code = item.get("kpi_id"), item.get("kpi_code") or item.get("code")
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if kid:
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bindings[obj.id] = (int(kid), code)
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sources[obj.id] = "kpis"
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break
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if code:
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declared_codes[obj.id] = code
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break
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elif isinstance(item, str):
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declared_codes[obj.id] = item
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break
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def _def_by_code(code: str, cache: dict):
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if code in cache:
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return cache[code]
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row = db.query(KPIDefinition).filter(
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KPIDefinition.entity_id == entity_id,
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KPIDefinition.kpi_code == code,
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).first()
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cache[code] = row
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return row
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code_cache: dict = {}
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for oid, code in declared_codes.items():
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row = _def_by_code(code, code_cache)
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if row:
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bindings[oid] = (row.id, row.kpi_code)
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sources[oid] = "kpis_code"
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# 兜底：按节点名回查 KPI 名 / kpi_targets.note（"名称 · 期间"）
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for obj in objs:
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if obj.id in bindings:
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continue
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row = db.query(KPIDefinition).filter(
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KPIDefinition.entity_id == entity_id,
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KPIDefinition.kpi_name == obj.name,
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).first()
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if row:
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bindings[obj.id] = (row.id, row.kpi_code)
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sources[obj.id] = "name"
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continue
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hit = db.execute(text(
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"SELECT kpi_id FROM kpi_targets "
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"WHERE entity_id = :e AND target_type IN ('yearly', 'annual') AND note LIKE :pat "
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"ORDER BY period LIMIT 1"
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), {"e": entity_id, "pat": f"{obj.name} · %"}).first()
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if hit:
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bindings[obj.id] = (int(hit[0]), None)
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sources[obj.id] = "note"
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else:
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sources[obj.id] = "none"
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return bindings, sources
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@router.get("/{map_id}/strategy-board")
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def get_strategy_board(
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map_id: int,
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period: Optional[str] = Query(None, description="期间 2027/2028/2029，默认取最小可用期间"),
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db: Session = Depends(get_db),
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entity_id: int = Depends(get_entity_id),
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):
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"""战略地图活看板（只读）：19 节点分层 + 达成率色阶 + 因果箭头。
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- 目标值：`kpi_targets`（`target_type` 兼容 `yearly`/`annual` 两形，按 period）
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- 实际值：`kpi_values` **实测区**最新期（`kpi_value_scope.actual_only_clause`）
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- 色阶：r = 实际/目标；≥1.0 success / ≥0.8 warning / <0.8 danger / 无实际值 info
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- 逆指标（显式白名单 504/511/230/23）取倒数；状态类（unit='状态'）按 1/0 判色
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"""
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from app.models import KPIValue, KPICausality, KPIDefinition
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from app.utils.strategy_board import (
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INVERSE_KPI_IDS, LAYER_DISPLAY_ORDER, LAYER_META, LEVEL_COLORS, STATUS_UNIT,
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compute_level, layer_meta, period_rank, pick_latest,
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)
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warnings: list = []
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m = db.query(StrategicMap).filter(
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StrategicMap.id == map_id, StrategicMap.entity_id == entity_id,
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).first()
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if not m:
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raise HTTPException(404, "战略地图不存在")
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objs = db.query(MapObjective).filter(
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MapObjective.map_id == map_id, MapObjective.entity_id == entity_id,
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).order_by(MapObjective.sort_order, MapObjective.id).all()
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if not objs:
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warnings.append("该地图下无 map_objectives 节点（map_objectives 为空）")
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bindings, sources = _sb_resolve_bindings(db, entity_id, objs)
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kpi_ids = sorted({v[0] for v in bindings.values() if v and v[0]})
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kpi_defs = {}
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if kpi_ids:
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for k in db.query(KPIDefinition).filter(
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KPIDefinition.entity_id == entity_id, KPIDefinition.id.in_(kpi_ids),
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).all():
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kpi_defs[k.id] = k
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# ── 目标值（kpi_targets 无 ORM 模型，用只读 text() 取）──
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targets: dict = {}
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periods: list = []
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if kpi_ids:
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id_list = ",".join(str(int(i)) for i in kpi_ids) # 已 int 化，无注入面
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ttype = ",".join("'%s'" % t for t in _PERIOD_TYPES)
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rows = db.execute(text(
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"SELECT kpi_id, period, target_type, target_value FROM kpi_targets "
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f"WHERE entity_id = :e AND target_type IN ({ttype}) AND kpi_id IN ({id_list})"
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), {"e": entity_id}).fetchall()
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# 同 (kpi_id, period) 两形并存（兼容期）⇒ 取 `_PERIOD_TYPES` 中序更靠前者（yearly 优先）
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_type_rank = {t: i for i, t in enumerate(_PERIOD_TYPES)}
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best: dict = {}
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for r in rows:
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kid, per, ttype_row, tv = int(r[0]), str(r[1]), str(r[2]), r[3]
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rank = _type_rank.get(ttype_row, len(_PERIOD_TYPES))
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if (kid, per) in best and best[(kid, per)][0] <= rank:
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continue
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best[(kid, per)] = (rank, float(tv) if tv is not None else None)
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for (kid, per) in best:
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targets[(kid, per)] = best[(kid, per)][1]
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if per not in periods:
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periods.append(per)
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periods.sort(key=period_rank)
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# `direction` 列在 ORM 模型里未映射（库内有、模型无）；判色**不依赖**它
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# （逆指标用显式白名单，见 strategy_board.INVERSE_KPI_IDS），此处仅为回执留证
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directions: dict = {}
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if kpi_ids:
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id_list_d = ",".join(str(int(i)) for i in kpi_ids)
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for r in db.execute(text(
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f"SELECT id, direction FROM kpi_definitions WHERE id IN ({id_list_d})"
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)).fetchall():
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directions[int(r[0])] = r[1]
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# ── 实际值：实测区最新期（每 KPI 一条）──
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currents: dict = {}
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if kpi_ids:
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vrows = db.query(KPIValue).filter(
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KPIValue.entity_id == entity_id,
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KPIValue.kpi_id.in_(kpi_ids),
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actual_only_clause(),
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).all()
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by_kpi: dict = {}
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for v in vrows:
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by_kpi.setdefault(v.kpi_id, []).append(v)
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for kid, rows_k in by_kpi.items():
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currents[kid] = pick_latest(rows_k)
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# ── 因果箭头（先按本单 source_type，为空则退回该实体全部）──
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edges_raw = db.query(KPICausality).filter(
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KPICausality.entity_id == entity_id,
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KPICausality.source_type == "strategy-2027",
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).all()
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if not edges_raw:
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edges_raw = db.query(KPICausality).filter(KPICausality.entity_id == entity_id).all()
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if edges_raw:
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warnings.append("未命中 source_type='strategy-2027' 的因果链，已退回该实体全部因果链")
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chosen_period = period if period else (periods[0] if periods else None)
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obj_by_kpi = {v[0]: k for k, v in bindings.items() if v and v[0]}
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nodes: list = []
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for obj in objs:
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kid, code = bindings.get(obj.id, (None, None))
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kdef = kpi_defs.get(kid) if kid else None
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unit = (kdef.unit if kdef else None) or None
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target = targets.get((kid, chosen_period)) if kid else None
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vrow = currents.get(kid) if kid else None
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cur = float(vrow.actual_value) if (vrow and vrow.actual_value is not None) else None
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calc = compute_level(kpi_id=kid, unit=unit, current=cur, target=target)
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lmeta = layer_meta(obj.dimension_key)
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owner = None
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if kdef:
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owner = getattr(kdef, "responsible_user", None) or getattr(kdef, "data_owner", None)
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dept = getattr(kdef, "responsible_dept", None)
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if dept and owner:
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owner = f"{dept}·{owner}"
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elif dept:
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owner = dept
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nodes.append({
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"id": obj.id,
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"name": obj.name,
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"dimension_key": obj.dimension_key,
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"layer_name": lmeta["name"],
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"layer_color": lmeta["color"],
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"icon": obj.icon,
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"sort_order": obj.sort_order,
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"description": obj.description,
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"kpi_id": kid,
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"kpi_code": code or (kdef.kpi_code if kdef else None),
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"kpi_name": kdef.kpi_name if kdef else None,
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"unit": unit,
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"direction": directions.get(kid),
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"owner": owner,
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"binding_source": sources.get(obj.id, "none"),
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"current": cur,
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"current_period": (vrow.period if vrow else None),
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"current_data_status": (vrow.data_status if vrow else None),
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"current_source_type": (vrow.source_type if vrow else None),
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"target": target,
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"rate": calc["rate"],
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"level": calc["level"],
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"color": calc["color"],
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"mode": calc["mode"],
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"reason": calc["reason"],
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})
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if obj.id not in bindings or not kid:
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warnings.append(f"节点「{obj.name}」未绑定 KPI（map_objectives.kpis 为空且回查未命中）")
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elif code is None and kdef:
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code = kdef.kpi_code
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layer_buckets: dict = {k: [] for k in LAYER_DISPLAY_ORDER}
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for n in nodes:
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layer_buckets.setdefault(n["dimension_key"] if n["dimension_key"] in LAYER_META else "unknown", []).append(n)
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layers: list = []
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for key in LAYER_DISPLAY_ORDER:
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lmeta = LAYER_META[key]
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layers.append({"key": key, "name": lmeta["name"], "color": lmeta["color"],
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"nodes": layer_buckets.get(key, [])})
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for key, bucket in layer_buckets.items():
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if key not in LAYER_META and bucket:
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layers.append({"key": key, "name": key, "color": LEVEL_COLORS["info"], "nodes": bucket})
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warnings.append(f"存在规范外 dimension_key='{key}'（{len(bucket)} 个节点）")
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edges: list = []
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dropped = 0
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for e in edges_raw:
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sid, tid = obj_by_kpi.get(e.source_kpi_id), obj_by_kpi.get(e.target_kpi_id)
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if sid is None or tid is None:
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dropped += 1
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continue
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edges.append({
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"id": e.id,
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"source_node_id": sid, "target_node_id": tid,
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"source_kpi_id": e.source_kpi_id, "target_kpi_id": e.target_kpi_id,
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"strength": float(e.strength) if e.strength is not None else None,
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"lag_months": e.lag_months,
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"direction": e.direction,
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"formula": e.formula,
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})
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if dropped:
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warnings.append(f"{dropped} 条因果链端点不在本图 19 节点内，已剔除")
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asof = None
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asof_rank = -1
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for v in currents.values():
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if period_rank(v.period) > asof_rank:
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asof, asof_rank = v.period, period_rank(v.period)
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with_actual = sum(1 for n in nodes if n["current"] is not None)
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return {
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"map": {
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"id": m.id, "entity_id": m.entity_id, "title": m.title,
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"version": m.version, "status": m.status,
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"updated_at": m.updated_at.isoformat() if getattr(m, "updated_at", None) else None,
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},
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"period": chosen_period,
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"periods": periods,
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"data_asof": asof,
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"layers": layers,
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"edges": edges,
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"stats": {
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"nodes": len(nodes),
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"with_actual": with_actual,
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"missing_actual": len(nodes) - with_actual,
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"edges": len(edges),
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"by_level": {lv: sum(1 for n in nodes if n["level"] == lv) for lv in LEVEL_COLORS},
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},
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"caliber": {
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"source": "app/utils/strategy_board.py",
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"level_rule": "r=actual/target;>=1.0 success;>=0.8 warning;<0.8 danger;no actual info",
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"inverse_whitelist": sorted(INVERSE_KPI_IDS),
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"status_unit": STATUS_UNIT,
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"actual_scope": "kpi_values 实测区（排除 estimated/forecast）最新期",
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"zero_guard": "target 0/缺失 ⇒ info，禁 NaN/Inf",
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},
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"warnings": warnings,
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}
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@@ -0,0 +1,228 @@
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# -*- coding: utf-8 -*-
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"""战略地图「活看板」色阶口径 —— 单一事实源（任务 finance-20261011-strategy-map-frontend-fullstack）
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口径依据（逐字，来源见任务件 §三/§四 与 D1 裁定）：
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| 层 | dimension_key | 层色 |
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|---|---|---|
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| 财务（滞后） | finance | #F56C6C |
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| 客户（过渡） | customer | #409EFF |
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| 流程（领先） | process | #67C23A |
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| 学习（根本驱动） | learning | #E6A23C |
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色阶（§四）：
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r = 实际值 / 目标值
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r >= 1.0 -> success #16A34A
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r >= 0.8 -> warning #EAB308
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r < 0.8 -> danger #DC2626
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无实际值 -> info #94A3B8
|
||||
|
||||
特例（**必须**按此三类处理，不要按 direction 字段过滤）：
|
||||
|
||||
- §4.1 逆指标 ⇒ 取倒数再算：`INVERSE_KPI_IDS` **显式 code/ID 白名单**。
|
||||
不用 `direction='lower_better'` 过滤 —— 库内 `#230 EXT_139` / `#23 C_CUST_CONCENTRATION`
|
||||
的 `direction` 为 **NULL**（dama 知会件 `dama-20261011-strategy-map-direction-contract-fyi`），
|
||||
照 direction 过滤会把这两条逆指标错算成正向。
|
||||
- §4.2 状态类 ⇒ 不走达成率：判据是 **`unit == '状态'`**（不是 `direction IS NULL`，
|
||||
逆指标 #230/#23 的 direction 同样是 NULL）。约定 **1 ⇒ success；0 / NULL ⇒ danger**，
|
||||
并且**绝不**做 `current / target`（避免除零）。
|
||||
- §4.3 零点保护：目标值 0 / 缺失 ⇒ info（灰），禁止 NaN / Infinity / 除零崩溃。
|
||||
|
||||
本模块为纯函数（无 DB / 无框架依赖），供 `api/maps.py` 与单测共用。
|
||||
"""
|
||||
from __future__ import annotations
|
||||
|
||||
from typing import Any, Iterable, Optional
|
||||
|
||||
# ── 层色规范（§三，固定，不可自定义）────────────────────────────
|
||||
LAYER_META: dict[str, dict[str, str]] = {
|
||||
"finance": {"key": "finance", "name": "财务（滞后）", "color": "#F56C6C"},
|
||||
"customer": {"key": "customer", "name": "客户（过渡）", "color": "#409EFF"},
|
||||
"process": {"key": "process", "name": "流程（领先）", "color": "#67C23A"},
|
||||
"learning": {"key": "learning", "name": "学习（根本驱动）", "color": "#E6A23C"},
|
||||
}
|
||||
|
||||
#: 展示顺序：自下而上 学习 → 流程 → 客户 → 财务（§五.1）
|
||||
LAYER_DISPLAY_ORDER: tuple[str, ...] = ("learning", "process", "customer", "finance")
|
||||
|
||||
#: 色阶四级色（§四）
|
||||
LEVEL_COLORS: dict[str, str] = {
|
||||
"success": "#16A34A",
|
||||
"warning": "#EAB308",
|
||||
"danger": "#DC2626",
|
||||
"info": "#94A3B8",
|
||||
}
|
||||
|
||||
#: 逆指标白名单（§4.1 + D1 裁定 §二：CCC(504) / 库存(511) / 短期借款 EXT_139(230) / 客户集中度(23)）
|
||||
#: 显式写死，不从 direction 推导（理由见模块 docstring）
|
||||
INVERSE_KPI_IDS: frozenset[int] = frozenset({504, 511, 230, 23})
|
||||
|
||||
#: 状态类判据（§4.2：按 unit 判，不按 direction 判）
|
||||
STATUS_UNIT = "状态"
|
||||
|
||||
#: 达成率阈值（§四）
|
||||
WARNING_RATE = 0.8
|
||||
SUCCESS_RATE = 1.0
|
||||
|
||||
#: 取值状态优先级（同期多行时取更可信的一条）
|
||||
STATUS_RANK: dict[str, int] = {"verified": 3, "calculated": 2, "pending": 1}
|
||||
|
||||
_SUB_PERIOD_MONTHS = {"Q1": 3, "Q2": 6, "Q3": 9, "Q4": 12, "H1": 6, "H2": 12}
|
||||
|
||||
|
||||
class StrategyBoardError(ValueError):
|
||||
"""口径层显式错误（不静默兜底）"""
|
||||
|
||||
|
||||
def period_rank(period: Optional[str]) -> int:
|
||||
"""期间可比排序键：统一折成「年内月序」再比，避免字典序把 `2026-H1` 排在 `2026-08` 之后。
|
||||
|
||||
- ``YYYY-MM`` → year*12 + MM
|
||||
- ``YYYY-Qn`` → year*12 + 3n
|
||||
- ``YYYY-Hn`` → year*12 + 6n
|
||||
- ``YYYY`` → year*12 + 12
|
||||
无法解析 → 0（排在所有可解析期间之前，不参与「最新期」竞争）。
|
||||
"""
|
||||
if not period:
|
||||
return 0
|
||||
raw = str(period).strip()
|
||||
parts = raw.replace("/", "-").split("-")
|
||||
try:
|
||||
year = int(parts[0])
|
||||
except (ValueError, IndexError):
|
||||
return 0
|
||||
if len(parts) < 2:
|
||||
return year * 12 + 12
|
||||
sub = parts[1].strip().upper()
|
||||
if sub.isdigit():
|
||||
month = int(sub)
|
||||
if 1 <= month <= 12:
|
||||
return year * 12 + month
|
||||
return 0
|
||||
return year * 12 + _SUB_PERIOD_MONTHS.get(sub, 0)
|
||||
|
||||
|
||||
def status_rank(data_status: Optional[str]) -> int:
|
||||
"""取值状态优先级（同一期间多行时优先 verified）"""
|
||||
return STATUS_RANK.get((data_status or "").strip().lower(), 0)
|
||||
|
||||
|
||||
def pick_latest(rows: Iterable[Any], *, period_attr: str = "period",
|
||||
status_attr: str = "data_status", id_attr: str = "id") -> Optional[Any]:
|
||||
"""从（已按口径过滤的）实测区行里挑「最新期 + 同期间内最可信」的一条。
|
||||
|
||||
排序键 = (期间序, 取值状态序, id)。全部无法解析期间时退回 id，绝不返回随机行。
|
||||
"""
|
||||
best = None
|
||||
best_key = None
|
||||
for row in rows:
|
||||
key = (
|
||||
period_rank(getattr(row, period_attr, None)),
|
||||
status_rank(getattr(row, status_attr, None)),
|
||||
getattr(row, id_attr, 0) or 0,
|
||||
)
|
||||
if best_key is None or key > best_key:
|
||||
best, best_key = row, key
|
||||
return best
|
||||
|
||||
|
||||
def is_status_kpi(unit: Optional[str]) -> bool:
|
||||
"""状态类判据：unit == '状态'（§4.2）"""
|
||||
return (unit or "").strip() == STATUS_UNIT
|
||||
|
||||
|
||||
def is_inverse_kpi(kpi_id: Optional[int]) -> bool:
|
||||
"""逆指标判据：显式白名单（§4.1）"""
|
||||
return kpi_id is not None and int(kpi_id) in INVERSE_KPI_IDS
|
||||
|
||||
|
||||
def compute_level(
|
||||
*,
|
||||
kpi_id: Any = None,
|
||||
unit: Any = None,
|
||||
current: Any = None,
|
||||
target: Any = None,
|
||||
) -> dict[str, Any]:
|
||||
"""算单节点色阶。返回 ``{level, color, rate, mode, reason}``。
|
||||
|
||||
- ``mode``：``status`` / ``inverse`` / ``normal``
|
||||
- ``rate``：达成率（状态类与灰灯为 ``None``）
|
||||
- ``reason``：灰灯/非达成率的原因（供前端 tooltip 与复核用）
|
||||
|
||||
任何入参形态（None / 0 / 负数 / 非数值字符串）都不得抛异常、不得返回 NaN/Inf。
|
||||
"""
|
||||
mode = "status" if is_status_kpi(unit) else ("inverse" if is_inverse_kpi(kpi_id) else "normal")
|
||||
out: dict[str, Any] = {"level": "info", "color": LEVEL_COLORS["info"], "rate": None,
|
||||
"mode": mode, "reason": None}
|
||||
|
||||
# ── §4.2 状态类：不走达成率 ──
|
||||
if mode == "status":
|
||||
if current is None:
|
||||
# 件 §4.2 逐字：「0 / NULL = 未达成 ⇒ 红」
|
||||
out.update(level="danger", color=LEVEL_COLORS["danger"], reason="状态未填报（NULL ⇒ 未达成）")
|
||||
return out
|
||||
try:
|
||||
val = float(current)
|
||||
except (TypeError, ValueError):
|
||||
out.update(level="danger", color=LEVEL_COLORS["danger"], reason="状态值非法 ⇒ 未达成")
|
||||
return out
|
||||
if val == 1:
|
||||
out.update(level="success", color=LEVEL_COLORS["success"], reason="状态=1（已达成）")
|
||||
else:
|
||||
out.update(level="danger", color=LEVEL_COLORS["danger"], reason=f"状态={val:g}（未达成）")
|
||||
return out
|
||||
|
||||
cur = _to_finite(current)
|
||||
tgt = _to_finite(target)
|
||||
|
||||
# ── §4.3 零点保护 / 无实际值 ──
|
||||
if cur is None:
|
||||
out["reason"] = "无实际值"
|
||||
return out
|
||||
if tgt is None or tgt == 0:
|
||||
out["reason"] = "目标值缺失或为 0"
|
||||
return out
|
||||
|
||||
if mode == "inverse":
|
||||
if cur == 0:
|
||||
# 逆指标现值为 0 ⇒ 倒数无定义，按零点保护置灰（禁除零）
|
||||
out["reason"] = "逆指标现值为 0（倒数无定义）"
|
||||
return out
|
||||
rate = tgt / cur
|
||||
else:
|
||||
rate = cur / tgt
|
||||
|
||||
if rate != rate or rate in (float("inf"), float("-inf")): # NaN / Inf 双保险
|
||||
out["reason"] = "达成率不可计算"
|
||||
return out
|
||||
|
||||
out["rate"] = round(rate, 4)
|
||||
if rate >= SUCCESS_RATE:
|
||||
out.update(level="success", color=LEVEL_COLORS["success"])
|
||||
elif rate >= WARNING_RATE:
|
||||
out.update(level="warning", color=LEVEL_COLORS["warning"])
|
||||
else:
|
||||
out.update(level="danger", color=LEVEL_COLORS["danger"])
|
||||
return out
|
||||
|
||||
|
||||
def _to_finite(value: Any) -> Optional[float]:
|
||||
"""容错取数：None / 空串 / 非数值 → None；NaN / Inf → None（禁入算）"""
|
||||
if value is None or value == "":
|
||||
return None
|
||||
try:
|
||||
num = float(value)
|
||||
except (TypeError, ValueError):
|
||||
return None
|
||||
if num != num or num in (float("inf"), float("-inf")):
|
||||
return None
|
||||
return num
|
||||
|
||||
|
||||
def layer_meta(dimension_key: Optional[str]) -> dict[str, str]:
|
||||
"""层元信息；未知 dimension_key 归入 info 灰的「未分层」占位（不抛错、不丢节点）"""
|
||||
key = (dimension_key or "").strip()
|
||||
if key in LAYER_META:
|
||||
return LAYER_META[key]
|
||||
return {"key": key or "unknown", "name": key or "未分层", "color": LEVEL_COLORS["info"]}
|
||||
Reference in New Issue
Block a user