"""
v2.2 K 线服务单元测试
测试覆盖率目标: >80%
"""
import pytest
from datetime import datetime, date, timedelta
from unittest.mock import Mock, AsyncMock, patch, MagicMock
from decimal import Decimal

# 导入被测试模块
from app.models.kline import (
    Frequency, AdjustType,
    StockKLineItem, StockKLineData, StockSymbolInfo, StockAdjustFactor,
    FuturesKLineItem, FuturesKLineData, FuturesSymbolInfo, FuturesContractInfo
)
from app.services.kline.stock_service import StockKLineService, STOCK_FREQUENCIES
from app.services.kline.futures_service import FuturesKLineService, FUTURES_FREQUENCIES
from app.services.kline.adjustment_service import AdjustmentService
from app.repositories.kline.stock_repository import StockKLineRepository
from app.repositories.kline.futures_repository import FuturesKLineRepository


# ==================== 测试 fixtures ====================

@pytest.fixture
def mock_db():
    """模拟数据库会话"""
    return Mock()


@pytest.fixture
def stock_repository(mock_db):
    """股票仓库实例"""
    return StockKLineRepository(mock_db)


@pytest.fixture
def futures_repository(mock_db):
    """期货仓库实例"""
    return FuturesKLineRepository(mock_db)


@pytest.fixture
def stock_service(mock_db):
    """股票服务实例"""
    return StockKLineService(mock_db)


@pytest.fixture
def futures_service(mock_db):
    """期货服务实例"""
    return FuturesKLineService(mock_db)


@pytest.fixture
def adjustment_service(mock_db):
    """复权服务实例"""
    return AdjustmentService(mock_db)


@pytest.fixture
def sample_stock_kline_items():
    """示例股票K线数据"""
    return [
        StockKLineItem(
            symbol="000001.SZ",
            time=datetime(2026, 4, 1, 9, 30),
            open=10.50,
            high=10.80,
            low=10.40,
            close=10.65,
            volume=1500000,
            amount=15975000.00,
            trade_date=date(2026, 4, 1),
            is_limit_up=False,
            is_limit_down=False,
            total_market_cap=250000000000.00,
            float_market_cap=200000000000.00
        ),
        StockKLineItem(
            symbol="000001.SZ",
            time=datetime(2026, 4, 2, 9, 30),
            open=10.60,
            high=10.90,
            low=10.55,
            close=10.75,
            volume=1600000,
            amount=17120000.00,
            trade_date=date(2026, 4, 2),
            is_limit_up=False,
            is_limit_down=False
        ),
    ]


@pytest.fixture
def sample_futures_kline_items():
    """示例期货K线数据"""
    return [
        FuturesKLineItem(
            symbol="IF2406",
            time=datetime(2026, 4, 1, 9, 30),
            open=3850.0,
            high=3880.0,
            low=3840.0,
            close=3870.0,
            volume=125000,
            open_interest=85000,
            settlement_price=3865.0,
            trade_date=date(2026, 4, 1)
        ),
        FuturesKLineItem(
            symbol="IF2406",
            time=datetime(2026, 4, 2, 9, 30),
            open=3870.0,
            high=3890.0,
            low=3860.0,
            close=3880.0,
            volume=130000,
            open_interest=88000,
            settlement_price=3875.0,
            trade_date=date(2026, 4, 2)
        ),
    ]


@pytest.fixture
def sample_adjust_factors():
    """示例复权因子"""
    return [
        StockAdjustFactor(
            symbol="000001.SZ",
            ex_date=date(2025, 6, 1),
            adjust_factor=1.1,
            dividend_ratio=0.5,
            split_ratio=1.0
        ),
        StockAdjustFactor(
            symbol="000001.SZ",
            ex_date=date(2024, 6, 1),
            adjust_factor=1.2,
            dividend_ratio=0.8,
            split_ratio=1.0
        ),
    ]


# ==================== 枚举测试 ====================

class TestEnums:
    """枚举类型测试"""
    
    def test_frequency_values(self):
        """测试周期枚举值"""
        assert Frequency.FREQ_1M.value == "1m"
        assert Frequency.FREQ_5M.value == "5m"
        assert Frequency.FREQ_1D.value == "1d"
        assert Frequency.FREQ_1W.value == "1w"
        assert Frequency.FREQ_1MONTH.value == "1month"
    
    def test_adjust_type_values(self):
        """测试复权类型枚举值"""
        assert AdjustType.NONE.value == ""
        assert AdjustType.QFQ.value == "qfq"
        assert AdjustType.HFQ.value == "hfq"
    
    def test_stock_frequencies_count(self):
        """测试股票支持的周期数量"""
        assert len(STOCK_FREQUENCIES) == 8
    
    def test_futures_frequencies_count(self):
        """测试期货支持的周期数量"""
        assert len(FUTURES_FREQUENCIES) == 8


# ==================== 数据模型测试 ====================

class TestModels:
    """数据模型测试"""
    
    def test_stock_kline_item_creation(self, sample_stock_kline_items):
        """测试股票K线项创建"""
        item = sample_stock_kline_items[0]
        assert item.symbol == "000001.SZ"
        assert item.open == 10.50
        assert item.high == 10.80
        assert item.low == 10.40
        assert item.close == 10.65
        assert item.volume == 1500000
    
    def test_futures_kline_item_creation(self, sample_futures_kline_items):
        """测试期货K线项创建"""
        item = sample_futures_kline_items[0]
        assert item.symbol == "IF2406"
        assert item.open_interest == 85000
        assert item.settlement_price == 3865.0
    
    def test_stock_kline_data_creation(self, sample_stock_kline_items):
        """测试股票K线数据响应创建"""
        data = StockKLineData(
            symbol="000001.SZ",
            name="平安银行",
            freq=Frequency.FREQ_1D,
            adjust=AdjustType.NONE,
            count=len(sample_stock_kline_items),
            items=sample_stock_kline_items
        )
        assert data.symbol == "000001.SZ"
        assert data.count == 2
    
    def test_futures_kline_data_creation(self, sample_futures_kline_items):
        """测试期货K线数据响应创建"""
        data = FuturesKLineData(
            symbol="IF2406",
            name="股指期货2406",
            freq=Frequency.FREQ_1D,
            count=len(sample_futures_kline_items),
            items=sample_futures_kline_items
        )
        assert data.symbol == "IF2406"
        assert data.count == 2


# ==================== 股票仓库测试 ====================

class TestStockRepository:
    """股票数据仓库测试"""
    
    def test_table_map_exists(self, stock_repository):
        """测试表映射存在"""
        assert Frequency.FREQ_1D in stock_repository.TABLE_MAP
        assert stock_repository.TABLE_MAP[Frequency.FREQ_1D] == "stock_klines_1d"
    
    def test_get_klines_empty_result(self, stock_repository, mock_db):
        """测试查询空结果"""
        mock_db.execute.return_value = []
        items = stock_repository.get_klines(
            "000001.SZ",
            Frequency.FREQ_1D,
            datetime(2026, 4, 1),
            datetime(2026, 4, 5)
        )
        assert items == []
    
    def test_get_klines_with_data(self, stock_repository, mock_db, sample_stock_kline_items):
        """测试查询有数据"""
        # 模拟数据库返回
        mock_result = [
            Mock(
                symbol_id="000001.SZ",
                ts=datetime(2026, 4, 1),
                open=Decimal("10.50"),
                high=Decimal("10.80"),
                low=Decimal("10.40"),
                close=Decimal("10.65"),
                volume=1500000,
                amount=Decimal("15975000.00"),
                trade_date=date(2026, 4, 1),
                is_limit_up=False,
                is_limit_down=False,
                total_market_cap=None,
                float_market_cap=None,
                inst_holding_ratio=None,
                trading_days=None
            )
        ]
        mock_db.execute.return_value = mock_result
        
        items = stock_repository.get_klines(
            "000001.SZ",
            Frequency.FREQ_1D,
            datetime(2026, 4, 1),
            datetime(2026, 4, 5)
        )
        
        assert len(items) >= 0  # 根据mock实现可能返回不同结果
    
    def test_unsupported_frequency(self, stock_repository):
        """测试不支持的周期"""
        # Frequency 枚举中没有这个值的情况
        result = stock_repository.get_klines(
            "000001.SZ",
            Frequency.FREQ_1D,
            datetime(2026, 4, 1),
            datetime(2026, 4, 5)
        )
        # 应该返回结果（表映射存在）
        assert isinstance(result, list)


# ==================== 期货仓库测试 ====================

class TestFuturesRepository:
    """期货数据仓库测试"""
    
    def test_table_map_exists(self, futures_repository):
        """测试表映射存在"""
        assert Frequency.FREQ_1D in futures_repository.TABLE_MAP
        assert futures_repository.TABLE_MAP[Frequency.FREQ_1D] == "futures_klines_1d"
    
    def test_get_klines_empty(self, futures_repository, mock_db):
        """测试查询空结果"""
        mock_db.execute.return_value = []
        items = futures_repository.get_klines(
            "IF2406",
            Frequency.FREQ_1D,
            datetime(2026, 4, 1),
            datetime(2026, 4, 5)
        )
        assert items == []
    
    def test_get_main_contract_none(self, futures_repository, mock_db):
        """测试无主力合约"""
        mock_db.execute.return_value.first.return_value = None
        result = futures_repository.get_main_contract("IF")
        assert result is None


# ==================== 股票服务测试 ====================

class TestStockService:
    """股票K线服务测试"""
    
    def test_service_creation(self, stock_service):
        """测试服务创建"""
        assert stock_service is not None
        assert stock_service.repository is not None
    
    def test_validate_params_empty_symbol(self, stock_service):
        """测试空代码验证"""
        with pytest.raises(ValueError, match="股票代码不能为空"):
            stock_service._validate_params(
                "",
                Frequency.FREQ_1D,
                datetime(2026, 4, 1),
                datetime(2026, 4, 5)
            )
    
    def test_validate_params_invalid_time_range(self, stock_service):
        """测试无效时间范围"""
        with pytest.raises(ValueError, match="开始时间必须早于结束时间"):
            stock_service._validate_params(
                "000001.SZ",
                Frequency.FREQ_1D,
                datetime(2026, 4, 5),
                datetime(2026, 4, 1)
            )
    
    def test_validate_params_exceeds_max_days(self, stock_service):
        """测试超过最大天数"""
        start = datetime(2020, 1, 1)
        end = datetime(2026, 4, 1)
        # 1分钟周期最大30天
        with pytest.raises(ValueError, match="最多查询"):
            stock_service._validate_params(
                "000001.SZ",
                Frequency.FREQ_1M,
                start,
                end
            )
    
    @pytest.mark.asyncio
    async def test_query_klines_unsupported_freq(self, stock_service):
        """测试不支持的周期"""
        # 创建一个不在 STOCK_FREQUENCIES 中的周期
        with pytest.raises(ValueError, match="不支持的股票"):
            await stock_service.query_klines(
                "000001.SZ",
                Frequency.FREQ_1M,  # 这个在 STOCK_FREQUENCIES 中
                datetime(2026, 4, 1),
                datetime(2026, 4, 5)
            )


# ==================== 期货服务测试 ====================

class TestFuturesService:
    """期货K线服务测试"""
    
    def test_service_creation(self, futures_service):
        """测试服务创建"""
        assert futures_service is not None
        assert futures_service.repository is not None
    
    def test_validate_params_empty_symbol(self, futures_service):
        """测试空代码验证"""
        with pytest.raises(ValueError, match="合约代码不能为空"):
            futures_service._validate_params(
                "",
                Frequency.FREQ_1D,
                datetime(2026, 4, 1),
                datetime(2026, 4, 5)
            )
    
    def test_validate_params_invalid_time_range(self, futures_service):
        """测试无效时间范围"""
        with pytest.raises(ValueError, match="开始时间必须早于结束时间"):
            futures_service._validate_params(
                "IF2406",
                Frequency.FREQ_1D,
                datetime(2026, 4, 5),
                datetime(2026, 4, 1)
            )
    
    def test_batch_limit(self, futures_service):
        """测试批量查询限制"""
        symbols = [f"IF{i}" for i in range(101)]
        with pytest.raises(ValueError, match="最多支持 100"):
            futures_service._validate_params(
                symbols[0],
                Frequency.FREQ_1D,
                datetime(2026, 4, 1),
                datetime(2026, 4, 5)
            )


# ==================== 复权服务测试 ====================

class TestAdjustmentService:
    """复权计算服务测试"""
    
    def test_service_creation(self, adjustment_service):
        """测试服务创建"""
        assert adjustment_service is not None
    
    def test_no_adjustment(self, adjustment_service, sample_stock_kline_items):
        """测试不复权"""
        result = adjustment_service.apply_adjustment(
            "000001.SZ",
            sample_stock_kline_items,
            AdjustType.NONE,
            []
        )
        assert result == sample_stock_kline_items
    
    def test_no_factors(self, adjustment_service, sample_stock_kline_items):
        """测试无复权因子"""
        result = adjustment_service.apply_adjustment(
            "000001.SZ",
            sample_stock_kline_items,
            AdjustType.QFQ,
            []
        )
        # 无因子时返回原始数据
        assert result == sample_stock_kline_items
    
    def test_adjust_price_none(self, adjustment_service):
        """测试空价格调整"""
        result = adjustment_service._adjust_price(None, 1.5)
        assert result is None
    
    def test_adjust_price_value(self, adjustment_service):
        """测试价格调整"""
        result = adjustment_service._adjust_price(10.0, 1.5)
        assert result == 15.0
    
    def test_calculate_adjust_factor_dividend(self, adjustment_service):
        """测试分红因子计算"""
        # 分红0.5元，前收盘价10元
        factor = adjustment_service.calculate_adjust_factor(
            dividend_ratio=0.5,
            前收盘价=10.0
        )
        assert factor == 0.95  # (10 - 0.5) / 10
    
    def test_calculate_adjust_factor_split(self, adjustment_service):
        """测试拆股因子计算"""
        # 1股拆成2股
        factor = adjustment_service.calculate_adjust_factor(
            split_ratio=2.0,
            前收盘价=10.0
        )
        assert factor == 0.5  # 1 / 2
    
    def test_build_factor_map(self, adjustment_service, sample_adjust_factors):
        """测试因子映射构建"""
        factor_map = adjustment_service._build_factor_map(sample_adjust_factors)
        assert date(2025, 6, 1) in factor_map
        assert date(2024, 6, 1) in factor_map
        assert factor_map[date(2025, 6, 1)].adjust_factor == 1.1
    
    def test_qfq_cumulative_factors(self, adjustment_service, sample_adjust_factors):
        """测试前复权累计因子计算"""
        cumulative = adjustment_service._calculate_qfq_cumulative_factors(
            sample_adjust_factors
        )
        # 应该有累计因子
        assert len(cumulative) > 0
    
    def test_hfq_cumulative_factors(self, adjustment_service, sample_adjust_factors):
        """测试后复权累计因子计算"""
        cumulative = adjustment_service._calculate_hfq_cumulative_factors(
            sample_adjust_factors
        )
        # 应该有累计因子
        assert len(cumulative) > 0


# ==================== API 测试 ====================

class TestAPIEndpoints:
    """API 接口测试"""
    
    @pytest.mark.asyncio
    async def test_health_endpoint(self):
        """测试健康检查"""
        from app.api.v2.kline_v2_2 import health_check
        result = await health_check()
        assert result.code == 0
        assert result.data["status"] == "healthy"
        assert result.data["version"] == "2.2.0"
    
    @pytest.mark.asyncio
    async def test_freqs_endpoint(self):
        """测试周期列表"""
        from app.api.v2.kline_v2_2 import get_supported_freqs
        result = await get_supported_freqs()
        assert result.code == 0
        assert len(result.data["stock"]) == 8
        assert len(result.data["futures"]) == 8


# ==================== 集成测试 ====================

class TestIntegration:
    """集成测试"""
    
    @pytest.mark.asyncio
    async def test_full_stock_kline_flow(self, mock_db):
        """测试完整股票K线流程"""
        # 创建服务
        service = StockKLineService(mock_db)
        
        # 模拟仓库返回空数据
        service.repository.get_klines = Mock(return_value=[])
        service.repository.get_symbol_info = Mock(return_value=None)
        
        # 验证参数
        try:
            service._validate_params(
                "000001.SZ",
                Frequency.FREQ_1D,
                datetime(2026, 4, 1),
                datetime(2026, 4, 5)
            )
            # 参数验证应该通过
            assert True
        except ValueError:
            pytest.fail("参数验证不应失败")
    
    @pytest.mark.asyncio
    async def test_full_futures_kline_flow(self, mock_db):
        """测试完整期货K线流程"""
        service = FuturesKLineService(mock_db)
        
        # 验证参数
        try:
            service._validate_params(
                "IF2406",
                Frequency.FREQ_1D,
                datetime(2026, 4, 1),
                datetime(2026, 4, 5)
            )
            assert True
        except ValueError:
            pytest.fail("参数验证不应失败")


# ==================== 边界测试 ====================

class TestBoundaryCases:
    """边界条件测试"""
    
    def test_zero_price(self, adjustment_service):
        """测试零价格"""
        # 前收盘价为0时返回1.0
        factor = adjustment_service.calculate_adjust_factor(前收盘价=0)
        assert factor == 1.0
    
    def test_empty_items_list(self, adjustment_service):
        """测试空数据列表"""
        result = adjustment_service.apply_adjustment(
            "000001.SZ",
            [],
            AdjustType.QFQ,
            []
        )
        assert result == []
    
    def test_large_volume(self):
        """测试大成交量"""
        item = StockKLineItem(
            symbol="000001.SZ",
            time=datetime(2026, 4, 1),
            open=10.0,
            high=10.5,
            low=9.5,
            close=10.2,
            volume=9999999999999,  # 超大成交量
            amount=100000000000000,
            trade_date=date(2026, 4, 1)
        )
        assert item.volume == 9999999999999
    
    def test_negative_price_not_allowed(self):
        """测试负价格（应该被数据验证拒绝）"""
        # Pydantic 模型通常允许负值，但业务逻辑应该验证
        # 这里测试模型是否能创建（实际业务中应该有验证）
        item = StockKLineItem(
            symbol="000001.SZ",
            time=datetime(2026, 4, 1),
            open=-10.0,  # 负价格
            high=-10.5,
            low=-9.5,
            close=-10.2,
            volume=1000,
            amount=10000,
            trade_date=date(2026, 4, 1)
        )
        # 模型允许创建，业务验证应该在服务层
        assert item.open == -10.0


# ==================== 性能测试 ====================

class TestPerformance:
    """性能相关测试"""
    
    def test_large_batch_items(self):
        """测试大批量数据处理"""
        items = []
        for i in range(1000):
            items.append(StockKLineItem(
                symbol="000001.SZ",
                time=datetime(2026, 4, 1) + timedelta(days=i),
                open=10.0 + i * 0.01,
                high=10.5 + i * 0.01,
                low=9.5 + i * 0.01,
                close=10.2 + i * 0.01,
                volume=1000000,
                amount=10000000,
                trade_date=date(2026, 4, 1) + timedelta(days=i)
            ))
        assert len(items) == 1000
    
    def test_adjustment_performance(self, adjustment_service):
        """测试复权计算性能"""
        # 创建1000条测试数据
        items = []
        for i in range(100):
            items.append(StockKLineItem(
                symbol="000001.SZ",
                time=datetime(2025, 1, 1) + timedelta(days=i),
                open=10.0,
                high=10.5,
                low=9.5,
                close=10.2,
                volume=1000000,
                amount=10000000,
                trade_date=date(2025, 1, 1) + timedelta(days=i)
            ))
        
        # 应用复权
        factors = [
            StockAdjustFactor(
                symbol="000001.SZ",
                ex_date=date(2025, 6, 1),
                adjust_factor=1.1,
                dividend_ratio=0.5,
                split_ratio=1.0
            )
        ]
        
        result = adjustment_service.apply_adjustment(
            "000001.SZ",
            items,
            AdjustType.QFQ,
            factors
        )
        
        assert len(result) == 100


# ==================== 运行测试 ====================

if __name__ == "__main__":
    pytest.main([__file__, "-v", "--tb=short"])