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
2026-10-18 16:31:52 +08:00
parent 2cff58ca6a
commit 75a48f55d2
8 changed files with 1263 additions and 4 deletions
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"""战略地图 API"""
from fastapi import APIRouter, Depends, HTTPException, Query
from sqlalchemy import text
from sqlalchemy.orm import Session
from typing import Optional
from datetime import date, datetime, timedelta
@@ -1227,3 +1228,320 @@ def get_review_record(
raise HTTPException(404, "复盘记录不存在")
return review_to_dict(r)
# ── 战略地图「活看板」(只读)────────────────────────────────────────
# 任务:finance-20261011-strategy-map-frontend-fullstack(任总 2026-10-11 19:07「收口」)
# 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)
# 只读:本端点不写任何表;entity_id 严格取 token → 博海 e2 天然隔离。
# kpi_targets.target_type 取值:兼容期读两形(不阻塞渲染)
# - 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)
# - P0 修正单 finance-20261011-kpi-targets-targettype-fix-dama 会把它们改成 `yearly`
# - 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`
_PERIOD_TYPES = ("yearly", "annual")
def _sb_resolve_bindings(db: Session, entity_id: int, objs: list) -> tuple[dict, dict]:
"""节点 ↔ KPI 绑定:优先 `map_objectives.kpis`(收口单已回填),缺失时按名称回查。
返回 (bindings, sources):``bindings[obj.id] = (kpi_id, kpi_code)``;
``sources[obj.id]`` ∈ {kpis, kpis_code, name, note, none} —— 供复核方判断
是否已用上 19 条回填绑定(回填前 name/note 兜底)。
"""
from app.models import KPIDefinition
bindings: dict = {}
sources: dict = {}
declared_codes: dict = {}
for obj in objs:
raw = obj.kpis
if isinstance(raw, str):
try:
raw = json.loads(raw)
except Exception:
raw = None
if isinstance(raw, dict):
raw = [raw]
if not isinstance(raw, list):
continue
for item in raw:
if isinstance(item, dict):
kid, code = item.get("kpi_id"), item.get("kpi_code") or item.get("code")
if kid:
bindings[obj.id] = (int(kid), code)
sources[obj.id] = "kpis"
break
if code:
declared_codes[obj.id] = code
break
elif isinstance(item, str):
declared_codes[obj.id] = item
break
def _def_by_code(code: str, cache: dict):
if code in cache:
return cache[code]
row = db.query(KPIDefinition).filter(
KPIDefinition.entity_id == entity_id,
KPIDefinition.kpi_code == code,
).first()
cache[code] = row
return row
code_cache: dict = {}
for oid, code in declared_codes.items():
row = _def_by_code(code, code_cache)
if row:
bindings[oid] = (row.id, row.kpi_code)
sources[oid] = "kpis_code"
# 兜底:按节点名回查 KPI 名 / kpi_targets.note("名称 · 期间")
for obj in objs:
if obj.id in bindings:
continue
row = db.query(KPIDefinition).filter(
KPIDefinition.entity_id == entity_id,
KPIDefinition.kpi_name == obj.name,
).first()
if row:
bindings[obj.id] = (row.id, row.kpi_code)
sources[obj.id] = "name"
continue
hit = db.execute(text(
"SELECT kpi_id FROM kpi_targets "
"WHERE entity_id = :e AND target_type IN ('yearly', 'annual') AND note LIKE :pat "
"ORDER BY period LIMIT 1"
), {"e": entity_id, "pat": f"{obj.name} · %"}).first()
if hit:
bindings[obj.id] = (int(hit[0]), None)
sources[obj.id] = "note"
else:
sources[obj.id] = "none"
return bindings, sources
@router.get("/{map_id}/strategy-board")
def get_strategy_board(
map_id: int,
period: Optional[str] = Query(None, description="期间 2027/2028/2029,默认取最小可用期间"),
db: Session = Depends(get_db),
entity_id: int = Depends(get_entity_id),
):
"""战略地图活看板(只读):19 节点分层 + 达成率色阶 + 因果箭头。
- 目标值:`kpi_targets`(`target_type` 兼容 `yearly`/`annual` 两形,按 period)
- 实际值:`kpi_values` **实测区**最新期(`kpi_value_scope.actual_only_clause`)
- 色阶:r = 实际/目标;≥1.0 success / ≥0.8 warning / <0.8 danger / 无实际值 info
- 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
"""
from app.models import KPIValue, KPICausality, KPIDefinition
from app.utils.strategy_board import (
INVERSE_KPI_IDS, LAYER_DISPLAY_ORDER, LAYER_META, LEVEL_COLORS, STATUS_UNIT,
compute_level, layer_meta, period_rank, pick_latest,
)
warnings: list = []
m = db.query(StrategicMap).filter(
StrategicMap.id == map_id, StrategicMap.entity_id == entity_id,
).first()
if not m:
raise HTTPException(404, "战略地图不存在")
objs = db.query(MapObjective).filter(
MapObjective.map_id == map_id, MapObjective.entity_id == entity_id,
).order_by(MapObjective.sort_order, MapObjective.id).all()
if not objs:
warnings.append("该地图下无 map_objectives 节点(map_objectives 为空)")
bindings, sources = _sb_resolve_bindings(db, entity_id, objs)
kpi_ids = sorted({v[0] for v in bindings.values() if v and v[0]})
kpi_defs = {}
if kpi_ids:
for k in db.query(KPIDefinition).filter(
KPIDefinition.entity_id == entity_id, KPIDefinition.id.in_(kpi_ids),
).all():
kpi_defs[k.id] = k
# ── 目标值(kpi_targets 无 ORM 模型,用只读 text() 取)──
targets: dict = {}
periods: list = []
if kpi_ids:
id_list = ",".join(str(int(i)) for i in kpi_ids) # 已 int 化,无注入面
ttype = ",".join("'%s'" % t for t in _PERIOD_TYPES)
rows = db.execute(text(
"SELECT kpi_id, period, target_type, target_value FROM kpi_targets "
f"WHERE entity_id = :e AND target_type IN ({ttype}) AND kpi_id IN ({id_list})"
), {"e": entity_id}).fetchall()
# 同 (kpi_id, period) 两形并存(兼容期)⇒ 取 `_PERIOD_TYPES` 中序更靠前者(yearly 优先)
_type_rank = {t: i for i, t in enumerate(_PERIOD_TYPES)}
best: dict = {}
for r in rows:
kid, per, ttype_row, tv = int(r[0]), str(r[1]), str(r[2]), r[3]
rank = _type_rank.get(ttype_row, len(_PERIOD_TYPES))
if (kid, per) in best and best[(kid, per)][0] <= rank:
continue
best[(kid, per)] = (rank, float(tv) if tv is not None else None)
for (kid, per) in best:
targets[(kid, per)] = best[(kid, per)][1]
if per not in periods:
periods.append(per)
periods.sort(key=period_rank)
# `direction` 列在 ORM 模型里未映射(库内有、模型无);判色**不依赖**它
# (逆指标用显式白名单,见 strategy_board.INVERSE_KPI_IDS),此处仅为回执留证
directions: dict = {}
if kpi_ids:
id_list_d = ",".join(str(int(i)) for i in kpi_ids)
for r in db.execute(text(
f"SELECT id, direction FROM kpi_definitions WHERE id IN ({id_list_d})"
)).fetchall():
directions[int(r[0])] = r[1]
# ── 实际值:实测区最新期(每 KPI 一条)──
currents: dict = {}
if kpi_ids:
vrows = db.query(KPIValue).filter(
KPIValue.entity_id == entity_id,
KPIValue.kpi_id.in_(kpi_ids),
actual_only_clause(),
).all()
by_kpi: dict = {}
for v in vrows:
by_kpi.setdefault(v.kpi_id, []).append(v)
for kid, rows_k in by_kpi.items():
currents[kid] = pick_latest(rows_k)
# ── 因果箭头(先按本单 source_type,为空则退回该实体全部)──
edges_raw = db.query(KPICausality).filter(
KPICausality.entity_id == entity_id,
KPICausality.source_type == "strategy-2027",
).all()
if not edges_raw:
edges_raw = db.query(KPICausality).filter(KPICausality.entity_id == entity_id).all()
if edges_raw:
warnings.append("未命中 source_type='strategy-2027' 的因果链,已退回该实体全部因果链")
chosen_period = period if period else (periods[0] if periods else None)
obj_by_kpi = {v[0]: k for k, v in bindings.items() if v and v[0]}
nodes: list = []
for obj in objs:
kid, code = bindings.get(obj.id, (None, None))
kdef = kpi_defs.get(kid) if kid else None
unit = (kdef.unit if kdef else None) or None
target = targets.get((kid, chosen_period)) if kid else None
vrow = currents.get(kid) if kid else None
cur = float(vrow.actual_value) if (vrow and vrow.actual_value is not None) else None
calc = compute_level(kpi_id=kid, unit=unit, current=cur, target=target)
lmeta = layer_meta(obj.dimension_key)
owner = None
if kdef:
owner = getattr(kdef, "responsible_user", None) or getattr(kdef, "data_owner", None)
dept = getattr(kdef, "responsible_dept", None)
if dept and owner:
owner = f"{dept}·{owner}"
elif dept:
owner = dept
nodes.append({
"id": obj.id,
"name": obj.name,
"dimension_key": obj.dimension_key,
"layer_name": lmeta["name"],
"layer_color": lmeta["color"],
"icon": obj.icon,
"sort_order": obj.sort_order,
"description": obj.description,
"kpi_id": kid,
"kpi_code": code or (kdef.kpi_code if kdef else None),
"kpi_name": kdef.kpi_name if kdef else None,
"unit": unit,
"direction": directions.get(kid),
"owner": owner,
"binding_source": sources.get(obj.id, "none"),
"current": cur,
"current_period": (vrow.period if vrow else None),
"current_data_status": (vrow.data_status if vrow else None),
"current_source_type": (vrow.source_type if vrow else None),
"target": target,
"rate": calc["rate"],
"level": calc["level"],
"color": calc["color"],
"mode": calc["mode"],
"reason": calc["reason"],
})
if obj.id not in bindings or not kid:
warnings.append(f"节点「{obj.name}」未绑定 KPI(map_objectives.kpis 为空且回查未命中)")
elif code is None and kdef:
code = kdef.kpi_code
layer_buckets: dict = {k: [] for k in LAYER_DISPLAY_ORDER}
for n in nodes:
layer_buckets.setdefault(n["dimension_key"] if n["dimension_key"] in LAYER_META else "unknown", []).append(n)
layers: list = []
for key in LAYER_DISPLAY_ORDER:
lmeta = LAYER_META[key]
layers.append({"key": key, "name": lmeta["name"], "color": lmeta["color"],
"nodes": layer_buckets.get(key, [])})
for key, bucket in layer_buckets.items():
if key not in LAYER_META and bucket:
layers.append({"key": key, "name": key, "color": LEVEL_COLORS["info"], "nodes": bucket})
warnings.append(f"存在规范外 dimension_key='{key}'({len(bucket)} 个节点)")
edges: list = []
dropped = 0
for e in edges_raw:
sid, tid = obj_by_kpi.get(e.source_kpi_id), obj_by_kpi.get(e.target_kpi_id)
if sid is None or tid is None:
dropped += 1
continue
edges.append({
"id": e.id,
"source_node_id": sid, "target_node_id": tid,
"source_kpi_id": e.source_kpi_id, "target_kpi_id": e.target_kpi_id,
"strength": float(e.strength) if e.strength is not None else None,
"lag_months": e.lag_months,
"direction": e.direction,
"formula": e.formula,
})
if dropped:
warnings.append(f"{dropped} 条因果链端点不在本图 19 节点内,已剔除")
asof = None
asof_rank = -1
for v in currents.values():
if period_rank(v.period) > asof_rank:
asof, asof_rank = v.period, period_rank(v.period)
with_actual = sum(1 for n in nodes if n["current"] is not None)
return {
"map": {
"id": m.id, "entity_id": m.entity_id, "title": m.title,
"version": m.version, "status": m.status,
"updated_at": m.updated_at.isoformat() if getattr(m, "updated_at", None) else None,
},
"period": chosen_period,
"periods": periods,
"data_asof": asof,
"layers": layers,
"edges": edges,
"stats": {
"nodes": len(nodes),
"with_actual": with_actual,
"missing_actual": len(nodes) - with_actual,
"edges": len(edges),
"by_level": {lv: sum(1 for n in nodes if n["level"] == lv) for lv in LEVEL_COLORS},
},
"caliber": {
"source": "app/utils/strategy_board.py",
"level_rule": "r=actual/target;>=1.0 success;>=0.8 warning;<0.8 danger;no actual info",
"inverse_whitelist": sorted(INVERSE_KPI_IDS),
"status_unit": STATUS_UNIT,
"actual_scope": "kpi_values 实测区(排除 estimated/forecast)最新期",
"zero_guard": "target 0/缺失 ⇒ info,禁 NaN/Inf",
},
"warnings": warnings,
}
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# -*- coding: utf-8 -*-
"""战略地图「活看板」色阶口径 —— 单一事实源(任务 finance-20261011-strategy-map-frontend-fullstack)
口径依据(逐字,来源见任务件 §三/§四 与 D1 裁定):
| 层 | dimension_key | 层色 |
|---|---|---|
| 财务(滞后) | finance | #F56C6C |
| 客户(过渡) | customer | #409EFF |
| 流程(领先) | process | #67C23A |
| 学习(根本驱动) | learning | #E6A23C |
色阶(§四):
r = 实际值 / 目标值
r >= 1.0 -> success #16A34A
r >= 0.8 -> warning #EAB308
r < 0.8 -> danger #DC2626
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"]}
@@ -0,0 +1,123 @@
# -*- coding: utf-8 -*-
"""`map_objectives.kpis` 读端形态兼容回归(承接 dama 知会件 2026-10-11 19:1x)
背景:map_id=65 的 19 行 `kpis` 现为 NULL;库内唯一非空先例是**编码字符串数组**
(map 53);finance 拟回填的是**对象数组**且未通过形态核验。
因此读端(`_sb_resolve_bindings`)必须对四种形态都不抛错、且两形都能正确绑定:
| 形态 | 样例 | 期望来源 |
|---|---|---|
| 甲 编码字符串数组 | `["F_REVENUE"]` | kpis_code(按 code 查 kpi_definitions) |
| 丙 同上但为 JSON 字符串 | `'["F_REVENUE"]'` | kpis_code |
| 乙 对象数组 | `[{"kpi_id":1,"kpi_code":"F_REVENUE"}]` | kpis(直取 kpi_id) |
| 乙' 对象数组仅 code | `[{"kpi_code":"F_REVENUE"}]` | kpis_code |
| 丁 NULL / [] / 异形 | `None` / `[]` / `"not-json"` | 兜底(name / note / none),不得抛错 |
同时断言:**不按 status='active' 过滤** kpi_definitions
(15 条新建定义 status=NULL,#11 inactive、#230 archived,按 active 过滤会漏)。
纯桩测试(FakeDB),不连库、不触生产。
"""
import json
from types import SimpleNamespace
from typing import Any
import pytest
from app.api.maps import _sb_resolve_bindings
from app.models import KPIDefinition
DEFS = [
SimpleNamespace(id=1, entity_id=1, kpi_code="F_REVENUE", kpi_name="营业收入"),
SimpleNamespace(id=35, entity_id=1, kpi_code="F_NET_PROFIT", kpi_name="净利润"),
# status 刻意置 None:读端不得按 status 过滤
SimpleNamespace(id=504, entity_id=1, kpi_code="F_CCC", kpi_name="现金转换周期", status=None),
]
TARGETS = [(35, "净利润 · 2027")]
def _db() -> Any:
"""桩:仅供单测,不连库(运行时鸭子类型,Session 的极小子集)"""
return _DB()
def _col_val(arg):
try:
return arg.left.key, arg.right.value
except Exception:
return None, None
class _Q:
def __init__(self, model, store):
self.model, self.store, self.eq = model, store, {}
def filter(self, *args):
for a in args:
k, v = _col_val(a)
if k:
self.eq[k] = v
return self
def first(self):
for r in self.store.get(self.model, []):
if all(getattr(r, k, None) == v for k, v in self.eq.items()):
return r
return None
class _DB:
def __init__(self):
self.store = {KPIDefinition: DEFS}
def query(self, model):
return _Q(model, self.store)
def execute(self, stmt, params):
pat = params.get("pat") or ""
class _R:
def first(self):
return next((t for t in TARGETS if pat and t[1].startswith(pat[:-2])), None)
return _R()
def _obj(oid, name, kpis):
return SimpleNamespace(id=oid, name=name, kpis=kpis, dimension_key="finance")
@pytest.mark.parametrize("kpis,expect_id,expect_src", [
(["F_REVENUE"], 1, "kpis_code"), # 甲
(json.dumps(["F_CCC"]), 504, "kpis_code"), # 丙
([{"kpi_id": 35, "kpi_code": "F_NET_PROFIT"}], 35, "kpis"), # 乙
([{"kpi_code": "F_NET_PROFIT"}], 35, "kpis_code"), # 乙'
([{"code": "F_REVENUE"}], 1, "kpis_code"), # 乙''(code 别名)
({"kpi_id": 35}, 35, "kpis"), # 单对象(非数组)
])
def test_kpis_forms_bind_correctly(kpis, expect_id, expect_src):
o = _obj(2001, "任意节点名", kpis)
b, s = _sb_resolve_bindings(_db(), 1, [o])
assert b.get(2001, (None,))[0] == expect_id, f"form={kpis!r} got={b.get(2001)}"
assert s.get(2001) == expect_src, f"form={kpis!r} source={s.get(2001)}"
@pytest.mark.parametrize("kpis", [None, [], "not-json", 12345])
def test_kpis_degenerate_forms_fall_back_and_never_raise(kpis):
"""丁:NULL / 空 / 异形 —— 走 name/note 兜底或 none,绝不抛异常"""
o = _obj(2002, "净利润", kpis) # 名称可回查 + note 兜底均命中 id=35
b, s = _sb_resolve_bindings(_db(), 1, [o])
assert b.get(2002, (None,))[0] == 35
assert s.get(2002) in ("name", "note")
def test_null_kpis_unmatched_node_reports_none_not_crash():
"""19 行全 NULL 时:节点仍须在结果里(source=none),不得丢节点/抛错"""
o = _obj(2003, "图上没有对应 KPI 的节点", None)
b, s = _sb_resolve_bindings(_db(), 1, [o])
assert o.id not in b and s.get(o.id) == "none"
def test_no_status_active_filter_on_kpi_definitions():
"""status=None 的定义(15 条新建 KPI 形态)必须能被读到 —— 读端不得按 status 过滤"""
o = _obj(2004, "现金转换周期", [{"kpi_code": "F_CCC"}])
b, _s = _sb_resolve_bindings(_db(), 1, [o])
assert b.get(2004, (None,))[0] == 504, "status=None 的定义被过滤掉了(应命中)"
@@ -0,0 +1,174 @@
# -*- coding: utf-8 -*-
"""战略地图活看板色阶口径回归(任务 finance-20261011-strategy-map-frontend-fullstack)
覆盖件 §四/§4.1/§4.2/§4.3 与 §七「可直接复用的对照值」(2026-01~08 现取)。
纯函数测试:不连库、不依赖 FastAPI。
"""
import pytest
from app.utils.strategy_board import (
INVERSE_KPI_IDS, LAYER_META, LEVEL_COLORS, STATUS_UNIT,
compute_level, is_inverse_kpi, is_status_kpi, layer_meta, period_rank, pick_latest,
)
# ── §七 对照值(前端自测用,逐条断言期望色)──────────────────────────
@pytest.mark.parametrize("name,kpi_id,unit,current,target,expect", [
("营业收入", 1, "万元", 808.80, 1050, "danger"), # r=0.77
("CM 率", 503, "%", 16.83, 43, "danger"),
("CCC(逆)", 504, "天", 206.4, 150, "danger"), # r=0.727 取倒数
("货币资金", 505, "万元", 5.31, 60, "danger"),
("高贡献线收入占比", 506, "%", 47.81, 55, "warning"), # r=0.87
])
def test_spec_section7_fixtures(name, kpi_id, unit, current, target, expect):
got = compute_level(kpi_id=kpi_id, unit=unit, current=current, target=target)
assert got["level"] == expect, f"{name}: {got}"
def test_inverse_ccc_rate_is_reciprocal():
"""§4.1 CCC 206.4 → 目标 150:r = 150/206.4 = 0.7267(不是 206.4/150=1.376 的绿灯)"""
got = compute_level(kpi_id=504, unit="天", current=206.4, target=150)
assert got["mode"] == "inverse"
assert got["rate"] == pytest.approx(0.7267, abs=1e-4)
assert got["level"] == "danger"
# 若误按正向算会得到 success —— 这正是本回归要拦住的假绿
assert compute_level(kpi_id=9999, unit="天", current=206.4, target=150)["level"] == "success"
def test_inverse_whitelist_is_explicit_not_direction_based():
"""§4.1 逆指标=显式白名单;#230/#23 库内 direction 为 NULL 也不得漏"""
assert INVERSE_KPI_IDS == frozenset({504, 511, 230, 23})
for kid in (504, 511, 230, 23):
assert is_inverse_kpi(kid) is True
for kid in (1, 11, 502, 503, 505, 506, 507, 508, 509, 510, 512, 513, 514, 515, 516):
assert is_inverse_kpi(kid) is False
# 短期借款 #230:unit=元、direction=NULL ⇒ 逆指标(不能因 direction 缺失判成状态类/正向)
got = compute_level(kpi_id=230, unit="元", current=211.5, target=211.5)
assert got["mode"] == "inverse"
assert got["level"] == "success"
# ── §4.2 状态类:按 unit 判,1=绿 / 0=NULL=红,且绝不做除法 ──────────
@pytest.mark.parametrize("kpi_id,current,expect", [
(512, 1, "success"),
(512, 0, "danger"),
(512, None, "danger"), # 件 §4.2 逐字:0 / NULL = 未达成 ⇒ 红
(513, 1, "success"),
(515, 1, "success"),
(516, 0, "danger"),
])
def test_status_class_by_unit(kpi_id, current, expect):
unit = STATUS_UNIT # '状态'
got = compute_level(kpi_id=kpi_id, unit=unit, current=current, target=1)
assert got["mode"] == "status"
assert got["level"] == expect
assert got["rate"] is None, "状态类不得产出达成率"
def test_status_class_never_divides():
"""状态类 + 目标 0/缺失 ⇒ 依然按 1/0 判色,不触发除零"""
for target in (None, 0):
got = compute_level(kpi_id=512, unit="状态", current=0, target=target)
assert got["level"] == "danger" and got["rate"] is None
assert is_status_kpi("状态") is True
assert is_status_kpi("状态数") is False # 精确匹配,不用 startswith
assert is_status_kpi(None) is False
def test_status_not_inferred_from_null_direction():
"""`direction IS NULL` 不等于状态类:#230/#23 同为 NULL 但不走状态分支"""
for kid, unit in ((230, "元"), (23, "%")):
assert compute_level(kpi_id=kid, unit=unit, current=10, target=10)["mode"] == "inverse"
for kid in (512, 513, 515, 516):
assert compute_level(kpi_id=kid, unit=STATUS_UNIT, current=1, target=1)["mode"] == "status"
# ── §4.3 零点保护 / 空值 ────────────────────────────────────────────
@pytest.mark.parametrize("current,target,reason", [
(None, 150, "无实际值"),
(206.4, None, "目标值缺失或为 0"),
(206.4, 0, "目标值缺失或为 0"),
(0, 150, "逆指标现值为 0(倒数无定义)"),
])
def test_zero_guard_returns_info(current, target, reason):
got = compute_level(kpi_id=504, unit="天", current=current, target=target)
assert got["level"] == "info"
assert got["color"] == LEVEL_COLORS["info"]
assert got["rate"] is None
assert got["reason"] == reason
def test_never_nan_or_inf_or_raise():
"""历史教训:`{{ current.cover.toFixed(1) }}` 对 null 无守卫崩卡 —— 后端必须不产出 NaN/Inf"""
bad_inputs = [
(None, None), (None, 0), ("", ""), ("abc", "def"), (float("nan"), 100),
(100, float("nan")), (float("inf"), 100), (100, float("inf")),
("206.4", "150"), (False, 1), ([], {}),
]
for cur, tgt in bad_inputs:
got = compute_level(kpi_id=504, unit="天", current=cur, target=tgt)
assert got["rate"] is None or got["rate"] == got["rate"]
assert got["rate"] not in (float("inf"), float("-inf"))
assert got["level"] in LEVEL_COLORS
# 字符串数字可按数值处理(Excel/JSON 常见)
assert compute_level(kpi_id=1, unit="万元", current="808.80", target="1050")["rate"] == pytest.approx(0.7703, abs=1e-4)
# ── 阈值边界 ────────────────────────────────────────────────────────
@pytest.mark.parametrize("current,target,expect", [
(100, 100, "success"), (120, 100, "success"),
(80, 100, "warning"), (99.9, 100, "warning"),
(79.99, 100, "danger"), (0.01, 100, "danger"),
])
def test_threshold_boundaries(current, target, expect):
assert compute_level(kpi_id=1, unit="万元", current=current, target=target)["level"] == expect
# ── 期间排序 / 取最新(实测区取值口径)─────────────────────────────
@pytest.mark.parametrize("a,b", [
("2026-08", "2026-H1"), ("2026-Q4", "2026-09"), ("2027", "2026-H2"),
("2026-12", "2026-01"), ("2026-Q3", "2026-Q2"),
])
def test_period_rank_order(a, b):
assert period_rank(a) > period_rank(b)
def test_period_rank_unparsable_is_zero():
for bad in (None, "", "未知", "abc", "2026-13"):
assert period_rank(bad) == 0
class _Row:
def __init__(self, period, data_status, actual_value, id):
self.period, self.data_status, self.actual_value, self.id = period, data_status, actual_value, id
def test_pick_latest_prefers_newer_period_then_verified():
rows = [
_Row("2026-01", "verified", 180.87, 1),
_Row("2026-08", "error", 14.45, 9),
_Row("2026-08", "verified", 14.45, 8),
_Row("2026-H1", "verified", 713.27, 10),
]
got = pick_latest(rows)
assert got.period == "2026-08"
assert got.data_status == "verified", "同期间内必须取 verified(不被 error 行顶掉)"
assert pick_latest([]) is None
# ── 层色规范(§三,固定)─────────────────────────────────────────────
def test_layer_colors_fixed():
assert LAYER_META["finance"]["color"] == "#F56C6C"
assert LAYER_META["customer"]["color"] == "#409EFF"
assert LAYER_META["process"]["color"] == "#67C23A"
assert LAYER_META["learning"]["color"] == "#E6A23C"
# 未知/缺失 dimension_key 不抛错、不丢节点(置灰占位)
assert layer_meta(None)["color"] == LEVEL_COLORS["info"]
assert layer_meta("mystery")["color"] == LEVEL_COLORS["info"]
def test_level_colors_fixed():
assert LEVEL_COLORS["success"] == "#16A34A"
assert LEVEL_COLORS["warning"] == "#EAB308"
assert LEVEL_COLORS["danger"] == "#DC2626"
assert LEVEL_COLORS["info"] == "#94A3B8"