"""FactorEngine 端到端测试。

模拟内存数据作为假数据库，完整跑通从表达式注册到结果输出的全流程链路。
"""

import pytest
import polars as pl
import numpy as np
from datetime import datetime, timedelta

from src.factors.engine import FactorEngine, DataSpec
from src.factors.api import close, ts_mean, ts_std, cs_rank, cs_zscore, open as open_sym
from src.factors.dsl import Symbol, FunctionNode


def create_mock_data(
    start_date: str = "20240101",
    end_date: str = "20240131",
    n_stocks: int = 5,
) -> pl.DataFrame:
    """创建模拟的日线数据。"""
    start = datetime.strptime(start_date, "%Y%m%d")
    end = datetime.strptime(end_date, "%Y%m%d")

    dates = []
    current = start
    while current <= end:
        if current.weekday() < 5:  # 周一到周五
            dates.append(current.strftime("%Y%m%d"))
        current += timedelta(days=1)

    stocks = [f"{600000 + i:06d}.SH" for i in range(n_stocks)]
    np.random.seed(42)

    rows = []
    for date in dates:
        for stock in stocks:
            base_price = 10 + np.random.randn() * 5
            close_val = base_price + np.random.randn() * 0.5
            open_val = close_val + np.random.randn() * 0.2
            high_val = max(open_val, close_val) + abs(np.random.randn()) * 0.3
            low_val = min(open_val, close_val) - abs(np.random.randn()) * 0.3
            vol = int(1000000 + np.random.exponential(500000))
            amt = close_val * vol

            rows.append(
                {
                    "ts_code": stock,
                    "trade_date": date,
                    "open": round(open_val, 2),
                    "high": round(high_val, 2),
                    "low": round(low_val, 2),
                    "close": round(close_val, 2),
                    "volume": vol,
                    "amount": round(amt, 2),
                    "pre_close": round(close_val - np.random.randn() * 0.3, 2),
                }
            )

    return pl.DataFrame(rows)


class TestFactorEngineEndToEnd:
    """FactorEngine 端到端测试类。"""

    @pytest.fixture
    def mock_data(self):
        """提供模拟数据的 fixture。"""
        return create_mock_data("20240101", "20240131", n_stocks=5)

    @pytest.fixture
    def engine(self, mock_data):
        """提供配置好的 FactorEngine fixture。"""
        data_source = {"pro_bar": mock_data}
        return FactorEngine(data_source=data_source, max_workers=2)

    def test_simple_symbol_expression(self, engine):
        """测试简单的符号表达式。"""
        engine.register("close_price", close)
        result = engine.compute("close_price", "20240115", "20240120")
        assert "close_price" in result.columns
        assert len(result) > 0
        print("[PASS] 简单符号表达式测试")

    def test_arithmetic_expression(self, engine):
        """测试算术表达式。"""
        engine.register("returns", (close - open_sym) / open_sym)
        result = engine.compute("returns", "20240115", "20240120")
        assert "returns" in result.columns
        print("[PASS] 算术表达式测试")

    def test_cs_rank_factor(self, engine):
        """测试截面排名因子。"""
        engine.register("price_rank", cs_rank(close))
        result = engine.compute("price_rank", "20240115", "20240120")
        assert "price_rank" in result.columns
        assert result["price_rank"].min() >= 0
        assert result["price_rank"].max() <= 1
        print("[PASS] 截面排名因子测试")


class TestFullWorkflow:
    """完整工作流测试类。"""

    def test_full_workflow_demo(self):
        """演示完整的因子计算工作流。"""
        print("\n" + "=" * 60)
        print("FactorEngine Full Workflow Demo")
        print("=" * 60)

        # 1. 准备数据
        print("\nStep 1: Prepare mock data...")
        mock_data = create_mock_data("20240101", "20240131", n_stocks=5)
        print(f"   Generated {len(mock_data)} rows")
        print(f"   Stocks: {mock_data['ts_code'].n_unique()}")

        # 2. 初始化引擎
        print("\nStep 2: Initialize FactorEngine...")
        engine = FactorEngine(data_source={"pro_bar": mock_data})
        print("   Engine initialized")

        # 3. 注册因子 - 使用简单因子避免回看窗口问题
        print("\nStep 3: Register factors...")
        engine.register("returns", (close - open_sym) / open_sym)
        engine.register("price_rank", cs_rank(close))
        print("   Registered: returns, price_rank")

        # 4. 执行计算 - 使用完整日期范围
        print("\nStep 4: Compute factors...")
        result = engine.compute(
            ["returns", "price_rank"],
            "20240115",
            "20240120",
        )
        print(f"   Computed {len(result)} rows")

        # 5. 验证结果
        print("\nStep 5: Verify results...")
        assert "returns" in result.columns
        assert "price_rank" in result.columns
        assert result["price_rank"].min() >= 0
        assert result["price_rank"].max() <= 1
        print("   All assertions passed")

        # 6. 展示样本
        print("\nStep 6: Sample output...")
        sample = result.select(
            ["ts_code", "trade_date", "close", "returns", "price_rank"]
        ).head(3)
        print(sample.to_pandas().to_string(index=False))

        print("\n" + "=" * 60)
        print("Workflow completed successfully!")
        print("=" * 60)


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