test: 移除 Mock 測試 (統帥鐵律)
全面禁止 Mock 測試，所有測試必須使用真實資料庫。 移除 test_stats_api.py (Mock-based unit tests) Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
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# =============================================================================
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# AWOOOI Statistics API 單元測試
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# =============================================================================
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# Phase 6.5: 測試統計分析 API 端點
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#
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# 測試項目:
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# - /stats/incidents/summary
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# - /stats/incidents/resolution
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# - /stats/incidents/trends
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# - /stats/ai-performance
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# - /stats/services/affected
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# - /stats/feedback/summary
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# =============================================================================
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import pytest
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from datetime import datetime, timedelta
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from unittest.mock import AsyncMock, MagicMock, patch
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from src.api.v1.stats import (
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get_incident_summary,
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get_resolution_stats,
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get_incident_trends,
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get_ai_performance,
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get_affected_services,
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get_feedback_summary,
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IncidentSummary,
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ResolutionStats,
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IncidentTrends,
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AIPerformance,
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ServiceImpact,
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FeedbackSummary,
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)
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class TestIncidentSummary:
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"""事件總覽統計測試"""
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@pytest.mark.asyncio
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async def test_empty_database_returns_zero_counts(self):
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"""空資料庫應返回零計數"""
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mock_db = AsyncMock()
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mock_db.execute = AsyncMock(return_value=MagicMock(
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scalar=MagicMock(return_value=0),
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all=MagicMock(return_value=[])
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))
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result = await get_incident_summary(days=30, db=mock_db)
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assert result.total_incidents == 0
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assert result.resolved_rate == 0.0
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assert len(result.status_distribution) == 0
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assert len(result.severity_distribution) == 0
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@pytest.mark.asyncio
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async def test_resolved_rate_calculation(self):
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"""解決率計算正確"""
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# 10 總數，3 已解決 = 30%
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mock_db = AsyncMock()
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call_count = 0
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def mock_execute(*args, **kwargs):
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nonlocal call_count
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call_count += 1
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result = MagicMock()
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if call_count == 1: # 總數
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result.scalar.return_value = 10
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elif call_count == 2: # 狀態分佈
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result.all.return_value = []
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elif call_count == 3: # 嚴重度分佈
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result.all.return_value = []
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elif call_count == 4: # 已解決數
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result.scalar.return_value = 3
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else: # 平均 signals
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result.scalar.return_value = 2.5
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return result
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mock_db.execute = AsyncMock(side_effect=mock_execute)
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result = await get_incident_summary(days=30, db=mock_db)
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assert result.total_incidents == 10
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assert result.resolved_rate == 30.0
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class TestResolutionStats:
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"""解決時間統計測試"""
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@pytest.mark.asyncio
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async def test_empty_results_return_none(self):
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"""無已解決事件應返回 None"""
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mock_db = AsyncMock()
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mock_db.execute = AsyncMock(return_value=MagicMock(
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all=MagicMock(return_value=[])
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))
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result = await get_resolution_stats(days=30, db=mock_db)
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assert result.avg_minutes is None
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assert result.p50_minutes is None
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assert result.p95_minutes is None
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assert result.sample_size == 0
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class TestIncidentTrends:
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"""事件趨勢測試"""
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@pytest.mark.asyncio
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async def test_empty_data_returns_empty_list(self):
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"""無資料應返回空列表"""
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mock_db = AsyncMock()
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mock_db.execute = AsyncMock(return_value=MagicMock(
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all=MagicMock(return_value=[])
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))
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result = await get_incident_trends(days=30, period="daily", db=mock_db)
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assert result.period == "daily"
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assert len(result.data) == 0
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@pytest.mark.asyncio
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async def test_period_validation(self):
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"""週期參數驗證"""
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mock_db = AsyncMock()
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mock_db.execute = AsyncMock(return_value=MagicMock(
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all=MagicMock(return_value=[])
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))
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for period in ["daily", "weekly", "monthly"]:
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result = await get_incident_trends(days=30, period=period, db=mock_db)
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assert result.period == period
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class TestAIPerformance:
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"""AI 效能統計測試"""
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@pytest.mark.asyncio
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async def test_empty_outcomes(self):
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"""無 outcome 資料應返回零"""
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mock_db = AsyncMock()
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mock_db.execute = AsyncMock(return_value=MagicMock(
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all=MagicMock(return_value=[])
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))
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result = await get_ai_performance(days=30, db=mock_db)
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assert result.total_proposals == 0
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assert result.executed_count == 0
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assert result.execution_rate == 0.0
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assert result.success_rate == 0.0
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assert result.avg_effectiveness is None
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@pytest.mark.asyncio
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async def test_effectiveness_distribution_initialized(self):
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"""有效性評分分佈初始化正確"""
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mock_db = AsyncMock()
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mock_db.execute = AsyncMock(return_value=MagicMock(
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all=MagicMock(return_value=[])
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))
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result = await get_ai_performance(days=30, db=mock_db)
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# 應該有 1-5 的所有評分
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assert set(result.effectiveness_distribution.keys()) == {1, 2, 3, 4, 5}
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class TestAffectedServices:
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"""受影響服務統計測試"""
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@pytest.mark.asyncio
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async def test_empty_results(self):
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"""無資料應返回空列表"""
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mock_db = AsyncMock()
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mock_db.execute = AsyncMock(return_value=MagicMock(
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all=MagicMock(return_value=[])
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))
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result = await get_affected_services(days=30, limit=10, db=mock_db)
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assert len(result) == 0
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@pytest.mark.asyncio
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async def test_limit_parameter(self):
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"""limit 參數應限制結果數量"""
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mock_db = AsyncMock()
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# 模擬 5 個服務的資料
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mock_db.execute = AsyncMock(return_value=MagicMock(
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all=MagicMock(return_value=[
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(["svc1"], "P0"),
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(["svc2"], "P1"),
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(["svc3"], "P2"),
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(["svc1"], "P0"), # svc1 重複
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(["svc2"], "P1"), # svc2 重複
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])
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))
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result = await get_affected_services(days=30, limit=2, db=mock_db)
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# 應該只返回前 2 個 (按計數排序)
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assert len(result) <= 2
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class TestFeedbackSummary:
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"""人類回饋摘要測試"""
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@pytest.mark.asyncio
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async def test_empty_feedback(self):
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"""無回饋應返回零計數"""
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mock_db = AsyncMock()
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mock_db.execute = AsyncMock(return_value=MagicMock(
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all=MagicMock(return_value=[])
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))
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result = await get_feedback_summary(days=30, db=mock_db)
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assert result.total_feedback == 0
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assert result.positive_count == 0
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assert result.neutral_count == 0
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assert result.negative_count == 0
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assert len(result.common_themes) == 0
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@pytest.mark.asyncio
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async def test_score_categorization(self):
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"""評分分類正確 (>=4 正面, =3 中性, <=2 負面)"""
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mock_db = AsyncMock()
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mock_db.execute = AsyncMock(return_value=MagicMock(
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all=MagicMock(return_value=[
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({"effectiveness_score": 5},), # 正面
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({"effectiveness_score": 4},), # 正面
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({"effectiveness_score": 3},), # 中性
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({"effectiveness_score": 2},), # 負面
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({"effectiveness_score": 1},), # 負面
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])
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))
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result = await get_feedback_summary(days=30, db=mock_db)
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assert result.positive_count == 2
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assert result.neutral_count == 1
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assert result.negative_count == 2
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assert result.total_feedback == 5
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@pytest.mark.asyncio
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async def test_theme_extraction(self):
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"""主題萃取包含關鍵字"""
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mock_db = AsyncMock()
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mock_db.execute = AsyncMock(return_value=MagicMock(
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all=MagicMock(return_value=[
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({"learning_notes": "Connection timeout issue"},),
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({"learning_notes": "Memory leak detected"},),
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({"learning_notes": "timeout again"},),
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])
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))
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result = await get_feedback_summary(days=30, db=mock_db)
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# timeout 出現 2 次，應該在常見主題中
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assert "timeout" in result.common_themes or "connection" in result.common_themes
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