# =============================================================================
# AWOOOI Statistics API 單元測試
# =============================================================================
# Phase 6.5: 測試統計分析 API 端點
#
# 測試項目:
# - /stats/incidents/summary
# - /stats/incidents/resolution
# - /stats/incidents/trends
# - /stats/ai-performance
# - /stats/services/affected
# - /stats/feedback/summary
# =============================================================================

import pytest
from datetime import datetime, timedelta
from unittest.mock import AsyncMock, MagicMock, patch

from src.api.v1.stats import (
    get_incident_summary,
    get_resolution_stats,
    get_incident_trends,
    get_ai_performance,
    get_affected_services,
    get_feedback_summary,
    IncidentSummary,
    ResolutionStats,
    IncidentTrends,
    AIPerformance,
    ServiceImpact,
    FeedbackSummary,
)


class TestIncidentSummary:
    """事件總覽統計測試"""

    @pytest.mark.asyncio
    async def test_empty_database_returns_zero_counts(self):
        """空資料庫應返回零計數"""
        mock_db = AsyncMock()
        mock_db.execute = AsyncMock(return_value=MagicMock(
            scalar=MagicMock(return_value=0),
            all=MagicMock(return_value=[])
        ))

        result = await get_incident_summary(days=30, db=mock_db)

        assert result.total_incidents == 0
        assert result.resolved_rate == 0.0
        assert len(result.status_distribution) == 0
        assert len(result.severity_distribution) == 0

    @pytest.mark.asyncio
    async def test_resolved_rate_calculation(self):
        """解決率計算正確"""
        # 10 總數，3 已解決 = 30%
        mock_db = AsyncMock()
        call_count = 0

        def mock_execute(*args, **kwargs):
            nonlocal call_count
            call_count += 1
            result = MagicMock()
            if call_count == 1:  # 總數
                result.scalar.return_value = 10
            elif call_count == 2:  # 狀態分佈
                result.all.return_value = []
            elif call_count == 3:  # 嚴重度分佈
                result.all.return_value = []
            elif call_count == 4:  # 已解決數
                result.scalar.return_value = 3
            else:  # 平均 signals
                result.scalar.return_value = 2.5
            return result

        mock_db.execute = AsyncMock(side_effect=mock_execute)

        result = await get_incident_summary(days=30, db=mock_db)

        assert result.total_incidents == 10
        assert result.resolved_rate == 30.0


class TestResolutionStats:
    """解決時間統計測試"""

    @pytest.mark.asyncio
    async def test_empty_results_return_none(self):
        """無已解決事件應返回 None"""
        mock_db = AsyncMock()
        mock_db.execute = AsyncMock(return_value=MagicMock(
            all=MagicMock(return_value=[])
        ))

        result = await get_resolution_stats(days=30, db=mock_db)

        assert result.avg_minutes is None
        assert result.p50_minutes is None
        assert result.p95_minutes is None
        assert result.sample_size == 0


class TestIncidentTrends:
    """事件趨勢測試"""

    @pytest.mark.asyncio
    async def test_empty_data_returns_empty_list(self):
        """無資料應返回空列表"""
        mock_db = AsyncMock()
        mock_db.execute = AsyncMock(return_value=MagicMock(
            all=MagicMock(return_value=[])
        ))

        result = await get_incident_trends(days=30, period="daily", db=mock_db)

        assert result.period == "daily"
        assert len(result.data) == 0

    @pytest.mark.asyncio
    async def test_period_validation(self):
        """週期參數驗證"""
        mock_db = AsyncMock()
        mock_db.execute = AsyncMock(return_value=MagicMock(
            all=MagicMock(return_value=[])
        ))

        for period in ["daily", "weekly", "monthly"]:
            result = await get_incident_trends(days=30, period=period, db=mock_db)
            assert result.period == period


class TestAIPerformance:
    """AI 效能統計測試"""

    @pytest.mark.asyncio
    async def test_empty_outcomes(self):
        """無 outcome 資料應返回零"""
        mock_db = AsyncMock()
        mock_db.execute = AsyncMock(return_value=MagicMock(
            all=MagicMock(return_value=[])
        ))

        result = await get_ai_performance(days=30, db=mock_db)

        assert result.total_proposals == 0
        assert result.executed_count == 0
        assert result.execution_rate == 0.0
        assert result.success_rate == 0.0
        assert result.avg_effectiveness is None

    @pytest.mark.asyncio
    async def test_effectiveness_distribution_initialized(self):
        """有效性評分分佈初始化正確"""
        mock_db = AsyncMock()
        mock_db.execute = AsyncMock(return_value=MagicMock(
            all=MagicMock(return_value=[])
        ))

        result = await get_ai_performance(days=30, db=mock_db)

        # 應該有 1-5 的所有評分
        assert set(result.effectiveness_distribution.keys()) == {1, 2, 3, 4, 5}


class TestAffectedServices:
    """受影響服務統計測試"""

    @pytest.mark.asyncio
    async def test_empty_results(self):
        """無資料應返回空列表"""
        mock_db = AsyncMock()
        mock_db.execute = AsyncMock(return_value=MagicMock(
            all=MagicMock(return_value=[])
        ))

        result = await get_affected_services(days=30, limit=10, db=mock_db)

        assert len(result) == 0

    @pytest.mark.asyncio
    async def test_limit_parameter(self):
        """limit 參數應限制結果數量"""
        mock_db = AsyncMock()
        # 模擬 5 個服務的資料
        mock_db.execute = AsyncMock(return_value=MagicMock(
            all=MagicMock(return_value=[
                (["svc1"], "P0"),
                (["svc2"], "P1"),
                (["svc3"], "P2"),
                (["svc1"], "P0"),  # svc1 重複
                (["svc2"], "P1"),  # svc2 重複
            ])
        ))

        result = await get_affected_services(days=30, limit=2, db=mock_db)

        # 應該只返回前 2 個 (按計數排序)
        assert len(result) <= 2


class TestFeedbackSummary:
    """人類回饋摘要測試"""

    @pytest.mark.asyncio
    async def test_empty_feedback(self):
        """無回饋應返回零計數"""
        mock_db = AsyncMock()
        mock_db.execute = AsyncMock(return_value=MagicMock(
            all=MagicMock(return_value=[])
        ))

        result = await get_feedback_summary(days=30, db=mock_db)

        assert result.total_feedback == 0
        assert result.positive_count == 0
        assert result.neutral_count == 0
        assert result.negative_count == 0
        assert len(result.common_themes) == 0

    @pytest.mark.asyncio
    async def test_score_categorization(self):
        """評分分類正確 (>=4 正面, =3 中性, <=2 負面)"""
        mock_db = AsyncMock()
        mock_db.execute = AsyncMock(return_value=MagicMock(
            all=MagicMock(return_value=[
                ({"effectiveness_score": 5},),  # 正面
                ({"effectiveness_score": 4},),  # 正面
                ({"effectiveness_score": 3},),  # 中性
                ({"effectiveness_score": 2},),  # 負面
                ({"effectiveness_score": 1},),  # 負面
            ])
        ))

        result = await get_feedback_summary(days=30, db=mock_db)

        assert result.positive_count == 2
        assert result.neutral_count == 1
        assert result.negative_count == 2
        assert result.total_feedback == 5

    @pytest.mark.asyncio
    async def test_theme_extraction(self):
        """主題萃取包含關鍵字"""
        mock_db = AsyncMock()
        mock_db.execute = AsyncMock(return_value=MagicMock(
            all=MagicMock(return_value=[
                ({"learning_notes": "Connection timeout issue"},),
                ({"learning_notes": "Memory leak detected"},),
                ({"learning_notes": "timeout again"},),
            ])
        ))

        result = await get_feedback_summary(days=30, db=mock_db)

        # timeout 出現 2 次，應該在常見主題中
        assert "timeout" in result.common_themes or "connection" in result.common_themes