357 lines
16 KiB
Python
357 lines
16 KiB
Python
"""Unit-тесты §15 движка отчётной уверенности (#990, 955-A4).
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Чистые тесты — БЕЗ БД (движок PURE: берёт уже-посчитанные входы, ничего не считает
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из §9.x и не ходит в БД):
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• _level_from_value / _factor_from_count — каждый порог-бэнд (high/medium/low) +
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RU-нота с РЕАЛЬНЫМ числом и оценочным словом; None → low + «нет данных».
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• _coverage_factor — покрытие domrf↔objective в % в ноте (структурный §15-пример).
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• _aggregate — weakest-link MIN (один low → общий low); пустой → low.
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• _cap — advisory-потолок опускает high → medium.
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• _build_rationale — называет тянущий-вниз фактор с его числом, «Low потому что N…»;
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advisory-cap проговаривается; пусто → «недостаточно данных».
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• compute_report_confidence — смешанные факторы → правильный level + структурная
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причина; advisory НИКОГДА не отдаёт high; all-None → low + «недостаточно данных»;
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as_dict() ложится в слот ReportConfidence (#987) и JSON-сериализуем.
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Детерминированно, без LLM, без сети. DATABASE_URL до импорта app-модулей (зеркало
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соседних тестов — на случай side-effect'ов импорта пакета forecasting).
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"""
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from __future__ import annotations
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import json
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import os
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os.environ.setdefault("DATABASE_URL", "postgresql+psycopg://test:test@localhost:5432/test")
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from app.services.forecasting.confidence_engine import (
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_ANALOG_COUNT_HIGH,
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_DEAL_COUNT_HIGH,
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_DEAL_COUNT_LOW,
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_HISTORY_MONTHS_HIGH,
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ConfidenceFactor,
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ReportConfidenceResult,
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_aggregate,
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_build_rationale,
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_cap,
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_coverage_factor,
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_factor_from_count,
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_level_from_value,
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compute_report_confidence,
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)
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def _factor(name: str, level: str) -> ConfidenceFactor:
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"""Лёгкий фактор фиксированного уровня (для агрегатных/причинных тестов)."""
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return ConfidenceFactor(name=name, value=None, level=level, note=f"{name}:{level}") # type: ignore[arg-type]
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# ── _level_from_value — пороговые бэнды ────────────────────────────────────────
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class TestLevelFromValue:
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def test_high_band(self) -> None:
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assert _level_from_value(50, high_at=50, low_below=15) == "high"
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assert _level_from_value(120, high_at=50, low_below=15) == "high"
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def test_medium_band(self) -> None:
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# Между low_below (вкл.) и high_at (искл.) → medium.
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assert _level_from_value(15, high_at=50, low_below=15) == "medium"
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assert _level_from_value(30, high_at=50, low_below=15) == "medium"
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def test_low_band(self) -> None:
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assert _level_from_value(14, high_at=50, low_below=15) == "low"
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assert _level_from_value(0, high_at=50, low_below=15) == "low"
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def test_none_is_low(self) -> None:
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# Нет сигнала ≠ хороший сигнал.
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assert _level_from_value(None, high_at=50, low_below=15) == "low"
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# ── _factor_from_count — бэнды + RU-нота с числом ──────────────────────────────
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class TestFactorFromCount:
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def test_low_count_note_has_number_and_word(self) -> None:
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f = _factor_from_count(
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"deal_count",
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7,
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high_at=_DEAL_COUNT_HIGH,
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low_below=_DEAL_COUNT_LOW,
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unit="сделок",
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suffix="за 6 мес",
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)
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assert f.level == "low"
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assert f.value == 7
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# Структурный §15-стиль: реальное число + контекст + оценка.
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assert "7 сделок" in f.note
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assert "за 6 мес" in f.note
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assert "мало" in f.note
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def test_medium_count_band(self) -> None:
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f = _factor_from_count(
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"deal_count", 20, high_at=_DEAL_COUNT_HIGH, low_below=_DEAL_COUNT_LOW, unit="сделок"
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)
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assert f.level == "medium"
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assert "20 сделок" in f.note
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assert "умеренно" in f.note
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def test_high_count_band(self) -> None:
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f = _factor_from_count(
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"deal_count", 80, high_at=_DEAL_COUNT_HIGH, low_below=_DEAL_COUNT_LOW, unit="сделок"
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)
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assert f.level == "high"
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assert "80 сделок" in f.note
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assert "достаточно" in f.note
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def test_one_analog_is_low_with_number(self) -> None:
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# ТЗ §15-пример «только 1 ЖК» — 1 аналог обязан давать low с числом в ноте.
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f = _factor_from_count(
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"analog_count", 1, high_at=_ANALOG_COUNT_HIGH, low_below=2, unit="ЖК-аналога"
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)
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assert f.level == "low"
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assert "1 ЖК-аналога" in f.note
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def test_none_count_low_no_data_note(self) -> None:
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f = _factor_from_count(
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"deal_count", None, high_at=_DEAL_COUNT_HIGH, low_below=_DEAL_COUNT_LOW, unit="сделок"
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)
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assert f.level == "low"
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assert f.value is None
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assert "нет данных" in f.note
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def test_float_count_rendered_compactly(self) -> None:
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# Целое-как-float → без хвоста; дробное → 1 знак.
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f_int = _factor_from_count(
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"history_months", 12.0, high_at=_HISTORY_MONTHS_HIGH, low_below=12, unit="мес истории"
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)
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assert "12 мес истории" in f_int.note # не "12.0"
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f_frac = _factor_from_count(
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"history_months", 12.5, high_at=_HISTORY_MONTHS_HIGH, low_below=12, unit="мес истории"
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)
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assert "12.5 мес истории" in f_frac.note
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# ── _coverage_factor — покрытие domrf↔objective в % ────────────────────────────
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class TestCoverageFactor:
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def test_low_coverage_percent_in_note(self) -> None:
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# Главный sparse-риск проекта: 2.5% покрытие → low, % в ноте (структурный §15).
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f = _coverage_factor(0.025)
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assert f.level == "low"
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assert f.value == 0.025
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assert "2.5%" in f.note
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assert "domrf↔objective" in f.note
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def test_high_coverage(self) -> None:
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f = _coverage_factor(0.75)
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assert f.level == "high"
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assert "75.0%" in f.note
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def test_none_coverage_low(self) -> None:
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f = _coverage_factor(None)
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assert f.level == "low"
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assert "неизвестно" in f.note
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# ── _aggregate — weakest-link MIN ──────────────────────────────────────────────
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class TestAggregate:
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def test_one_low_drags_overall_to_low(self) -> None:
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factors = [_factor("a", "high"), _factor("b", "medium"), _factor("c", "low")]
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assert _aggregate(factors) == "low"
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def test_all_high_stays_high(self) -> None:
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assert _aggregate([_factor("a", "high"), _factor("b", "high")]) == "high"
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def test_medium_floor_when_no_low(self) -> None:
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assert _aggregate([_factor("a", "high"), _factor("b", "medium")]) == "medium"
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def test_empty_is_low(self) -> None:
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# Нет ни одного сигнала → low (graceful).
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assert _aggregate([]) == "low"
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# ── _cap — advisory-потолок ────────────────────────────────────────────────────
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class TestCap:
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def test_high_capped_to_medium(self) -> None:
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assert _cap("high", "medium") == "medium"
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def test_low_unchanged_below_ceiling(self) -> None:
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assert _cap("low", "medium") == "low"
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def test_medium_unchanged_at_ceiling(self) -> None:
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assert _cap("medium", "medium") == "medium"
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# ── _build_rationale — структурная §15-причина ─────────────────────────────────
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class TestBuildRationale:
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def test_low_names_dragging_factor_with_number(self) -> None:
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# «Low потому что 7 сделок …» — называет виновника с его числом.
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deal = _factor_from_count(
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"deal_count",
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7,
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high_at=_DEAL_COUNT_HIGH,
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low_below=_DEAL_COUNT_LOW,
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unit="сделок",
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suffix="за 6 мес",
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)
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good = _factor("history_months", "high")
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text = _build_rationale("low", [deal, good], advisory_capped=False)
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assert text.startswith("Low потому что")
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assert "7 сделок" in text
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# Не-тянущий (high) фактор НЕ называется.
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assert "history_months" not in text
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def test_low_lists_multiple_dragging_factors(self) -> None:
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deal = _factor_from_count(
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"deal_count", 7, high_at=_DEAL_COUNT_HIGH, low_below=_DEAL_COUNT_LOW, unit="сделок"
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)
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analog = _factor_from_count(
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"analog_count", 1, high_at=_ANALOG_COUNT_HIGH, low_below=2, unit="ЖК-аналога"
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)
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cov = _coverage_factor(0.025)
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text = _build_rationale("low", [deal, analog, cov], advisory_capped=False)
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assert "7 сделок" in text
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assert "1 ЖК-аналога" in text
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assert "2.5%" in text
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assert " / " in text # перечисление виновников
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def test_advisory_cap_spoken_in_rationale(self) -> None:
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# Уровень упёрся в advisory-потолок (не данные) → причина это проговаривает.
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text = _build_rationale("medium", [_factor("x", "medium")], advisory_capped=True)
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assert "советующий" in text
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assert "medium" in text
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def test_empty_factors_insufficient(self) -> None:
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assert "недостаточно данных" in _build_rationale("low", [], advisory_capped=False)
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# ── compute_report_confidence — интеграция (PURE, без БД) ──────────────────────
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class TestComputeReportConfidence:
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def test_mixed_factors_weakest_link_low(self) -> None:
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# Сильная история, но 7 сделок и 1 ЖК → weakest-link low; причина структурная.
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res = compute_report_confidence(
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component_confidences=["medium", "high"],
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deal_count=7,
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analog_count=1,
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domrf_coverage=0.4,
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history_months=36,
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confounded=False,
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advisory=True,
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)
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assert isinstance(res, ReportConfidenceResult)
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assert res.level == "low"
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assert res.rationale.startswith("Low потому что")
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assert "7 сделок" in res.rationale
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assert "1 ЖК-аналога" in res.rationale
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def test_advisory_never_high(self) -> None:
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# Все сигналы отличные, но advisory=True → НИКОГДА не high (потолок medium).
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res = compute_report_confidence(
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component_confidences=["high", "high"],
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deal_count=200,
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analog_count=10,
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domrf_coverage=0.9,
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history_months=48,
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confounded=False,
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advisory=True,
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)
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assert res.level == "medium"
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assert res.advisory_capped is True
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assert "советующий" in res.rationale
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def test_non_advisory_allows_high(self) -> None:
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# advisory=False (гипотетически провалидированный стек) → high достижим.
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res = compute_report_confidence(
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component_confidences=["high"],
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deal_count=200,
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analog_count=10,
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domrf_coverage=0.9,
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history_months=48,
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confounded=False,
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advisory=False,
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)
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assert res.level == "high"
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assert res.advisory_capped is False
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def test_confounded_window_drags_down(self) -> None:
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# Шок-окно → low даже при прочих хороших сигналах; названо в причине.
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res = compute_report_confidence(
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component_confidences=["high"],
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deal_count=200,
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analog_count=10,
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domrf_coverage=0.9,
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history_months=48,
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confounded=True,
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advisory=True,
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)
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assert res.level == "low"
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assert "шок" in res.rationale
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def test_all_none_is_low_insufficient(self) -> None:
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# Граничный graceful: ни одного входа → low + «недостаточно данных».
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res = compute_report_confidence()
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assert res.level == "low"
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assert "недостаточно данных" in res.rationale
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assert res.factors == []
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assert res.advisory_capped is False
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def test_clean_inputs_medium_under_advisory(self) -> None:
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# Рабочие (medium-бэнд) счётчики без low-факторов → medium под advisory-cap.
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res = compute_report_confidence(
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component_confidences=["medium"],
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deal_count=20,
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analog_count=2,
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domrf_coverage=0.4,
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history_months=18,
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advisory=True,
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)
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assert res.level == "medium"
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# Здесь потолок не понижал (raw уже medium) → не помечаем capped.
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assert res.advisory_capped is False
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def test_as_dict_fits_report_confidence_slot(self) -> None:
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# as_dict() ложится в слот ReportConfidence (#987): {level, rationale, factors}.
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res = compute_report_confidence(deal_count=7, analog_count=1, advisory=True)
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d = res.as_dict()
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assert set(d.keys()) == {"level", "rationale", "factors"}
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assert d["level"] == "low"
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assert isinstance(d["rationale"], str)
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assert isinstance(d["factors"], dict)
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# Факторы по именам + флаг advisory_capped внутри.
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assert "deal_count" in d["factors"]
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assert d["factors"]["deal_count"]["value"] == 7
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assert "advisory_capped" in d["factors"]
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# Полностью JSON-сериализуем (контракт для экспортёров/чата).
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assert json.loads(json.dumps(d, ensure_ascii=False)) == d
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def test_ignores_garbage_component_confidence(self) -> None:
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# Мусорный component-уровень не учитывается (whitelist), не роняет искусственно.
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res = compute_report_confidence(
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component_confidences=["high", "bogus"], # type: ignore[list-item]
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deal_count=200,
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analog_count=10,
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domrf_coverage=0.9,
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history_months=48,
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advisory=False,
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)
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assert res.level == "high"
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def test_as_dict_keeps_all_component_factors(self) -> None:
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# Несколько component-факторов не теряются в плоском dict (суффиксуются).
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res = compute_report_confidence(
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component_confidences=["high", "medium", "low"], advisory=False
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)
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d = res.as_dict()
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component_keys = [k for k in d["factors"] if k.startswith("component")]
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assert len(component_keys) == 3 # ни один не перезаписан
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assert json.loads(json.dumps(d, ensure_ascii=False)) == d
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