backend/app/services/forecasting/confidence_engine.py

@@ -375,6 +375,7 @@ def compute_report_confidence(
     *,
     component_confidences: list[Confidence] | None = None,
     deal_count: int | None = None,
+    deal_count_months: int | None = None,
     analog_count: int | None = None,
     domrf_coverage: float | None = None,
     history_months: int | None = None,
@@ -403,6 +404,8 @@ def compute_report_confidence(
         component_confidences: per-service confidence (#950/#952/#985/#986…), None/[]→
             нет вкладывающих компонентов.
         deal_count: число сделок за окно (None → нет данных, тянет в low).
+        deal_count_months: окно наблюдения для deal_count (мес) — добавляет «за N мес»
+            в ноту фактора («7 сделок за 6 мес — мало»). None → нота без периода.
         analog_count: число ЖК-аналогов в выборке (= market_metrics.obj_count).
         domrf_coverage: доля domrf↔objective ∈ [0,1] (главный sparse-риск проекта).
         history_months: глубина ряда (мес).
@@ -417,6 +420,7 @@ def compute_report_confidence(
 
     # ── 1. Сырые счётчики качества данных → факторы (только заданные) ──────────
     if deal_count is not None:
+        _deal_suffix = f"за {deal_count_months} мес" if deal_count_months is not None else ""
         factors.append(
             _factor_from_count(
                 _F_DEAL_COUNT,
@@ -424,6 +428,7 @@ def compute_report_confidence(
                 high_at=_DEAL_COUNT_HIGH,
                 low_below=_DEAL_COUNT_LOW,
                 unit="сделок",
+                suffix=_deal_suffix,
             )
         )
     if analog_count is not None:

backend/app/services/forecasting/report_assembler.py

@@ -189,10 +189,10 @@ def _domrf_coverage(analyze: dict[str, Any], supply_layers: dict[str, Any] | Non
     """
     if supply_layers is not None:
         coverage = supply_layers.get("domrf_coverage")
-        if isinstance(coverage, (int, float)) and not isinstance(coverage, bool):
+        if isinstance(coverage, int | float) and not isinstance(coverage, bool):
             return _clamp_fraction(float(coverage))
     pct = analyze.get("market_data_coverage_pct")
-    if isinstance(pct, (int, float)) and not isinstance(pct, bool):
+    if isinstance(pct, int | float) and not isinstance(pct, bool):
         return _clamp_fraction(float(pct) / 100.0)
     return None
 
@@ -223,6 +223,19 @@ def _history_months(
     return None
 
 
+def _deal_count_months(market_metrics: dict[str, Any] | None) -> int | None:
+    """Окно наблюдения для deal_count (мес) — для deal_count_months #990. PURE.
+
+    Читает тот же `market_metrics.window_months` (§9.2), что и `_history_months` —
+    именно за это окно считается n_sold. Нет → None (#990 пропускает суффикс «за N мес»).
+    """
+    if market_metrics is not None:
+        window = market_metrics.get("window_months")
+        if isinstance(window, int) and window > 0:
+            return window
+    return None
+
+
 def _confounded(forecasts: Sequence[dict[str, Any]]) -> bool:
     """Пересекает ли окно прогноза шок-период — для confounded #990. PURE.
 
@@ -293,10 +306,10 @@ def _primary_deficit_index(forecasts: Sequence[dict[str, Any]]) -> float | None:
     )
     if primary is not None and primary.get("deficit_index") is not None:
         di = primary["deficit_index"]
-        return float(di) if isinstance(di, (int, float)) and not isinstance(di, bool) else None
+        return float(di) if isinstance(di, int | float) and not isinstance(di, bool) else None
     for f in forecasts:
         di = f.get("deficit_index")
-        if isinstance(di, (int, float)) and not isinstance(di, bool):
+        if isinstance(di, int | float) and not isinstance(di, bool):
             return float(di)
     return None
 
@@ -314,10 +327,10 @@ def _primary_months_of_inventory(forecasts: Sequence[dict[str, Any]]) -> float |
     )
     if primary is not None and primary.get("months_of_inventory") is not None:
         moi = primary["months_of_inventory"]
-        return float(moi) if isinstance(moi, (int, float)) and not isinstance(moi, bool) else None
+        return float(moi) if isinstance(moi, int | float) and not isinstance(moi, bool) else None
     for f in forecasts:
         moi = f.get("months_of_inventory")
-        if isinstance(moi, (int, float)) and not isinstance(moi, bool):
+        if isinstance(moi, int | float) and not isinstance(moi, bool):
             return float(moi)
     return None
 
@@ -342,7 +355,7 @@ def _overall_score(product_scores: dict[str, Any] | None) -> float | None:
     if not isinstance(product_scores, dict):
         return None
     overall = product_scores.get("overall")
-    if isinstance(overall, (int, float)) and not isinstance(overall, bool):
+    if isinstance(overall, int | float) and not isinstance(overall, bool):
         return float(overall)
     return None
 
@@ -388,10 +401,10 @@ def _market_now_summary(
     parts: list[str] = []
     if market_metrics is not None:
         velocity = market_metrics.get("unit_velocity")
-        if isinstance(velocity, (int, float)) and not isinstance(velocity, bool):
+        if isinstance(velocity, int | float) and not isinstance(velocity, bool):
             parts.append(f"абсорбция ~{round(float(velocity), 1)} ед./мес")
     avg_price = analyze.get("market_avg_price_per_m2")
-    if isinstance(avg_price, (int, float)) and not isinstance(avg_price, bool):
+    if isinstance(avg_price, int | float) and not isinstance(avg_price, bool):
         parts.append(f"средняя цена ~{round(float(avg_price)):,} ₽/м²".replace(",", " "))
     # #1634: НЕ через _analog_count — он отдаёт market_metrics.obj_count (число ЖК во
     # всей district-wide/микрорайонной выборке §9.2), что НЕ равно «конкурентов рядом».
@@ -618,6 +631,7 @@ def _build_confidence(
             market_metrics, future_supply, forecasts, product_scores, special_indices
         ),
         deal_count=_deal_count(analyze, market_metrics),
+        deal_count_months=_deal_count_months(market_metrics),
         analog_count=_analog_count(analyze, market_metrics),
         domrf_coverage=_domrf_coverage(analyze, supply_layers),
         history_months=_history_months(market_metrics, forecasts),

backend/tests/services/forecasting/test_confidence_engine.py

@@ -342,6 +342,26 @@ class TestComputeReportConfidence:
         # Полностью JSON-сериализуем (контракт для экспортёров/чата).
         assert json.loads(json.dumps(d, ensure_ascii=False)) == d
 
+    def test_deal_count_note_carries_window_months(self) -> None:
+        # #1637: deal_count_months → нота «за N мес» в факторе (и в rationale).
+        res = compute_report_confidence(
+            deal_count=7,
+            deal_count_months=6,
+            advisory=False,
+        )
+        dc_factor = next(f for f in res.factors if f.name == "deal_count")
+        assert "за 6 мес" in dc_factor.note
+        assert "7 сделок" in dc_factor.note
+        # Структурная причина тоже содержит период (через ноту фактора-виновника).
+        assert "за 6 мес" in res.rationale
+
+    def test_deal_count_note_without_window_has_no_period(self) -> None:
+        # deal_count_months=None (по умолчанию) → нота без «за N мес» (backward compat).
+        res = compute_report_confidence(deal_count=7, advisory=False)
+        dc_factor = next(f for f in res.factors if f.name == "deal_count")
+        assert "7 сделок" in dc_factor.note
+        assert "за" not in dc_factor.note
+
     def test_ignores_garbage_component_confidence(self) -> None:
         # Мусорный component-уровень не учитывается (whitelist), не роняет искусственно.
         res = compute_report_confidence(