"""Tests for data loaders."""

import pandas as pd
import pytest

from src.core.enums import Timeframe
from src.data.loaders import CSVLoader, ParquetLoader


@pytest.fixture
def sample_ohlcv_data():
    """Create sample OHLCV DataFrame."""
    dates = pd.date_range("2024-01-01 03:00", periods=100, freq="1min")
    return pd.DataFrame(
        {
            "timestamp": dates,
            "open": [100.0 + i * 0.1 for i in range(100)],
            "high": [100.5 + i * 0.1 for i in range(100)],
            "low": [99.5 + i * 0.1 for i in range(100)],
            "close": [100.2 + i * 0.1 for i in range(100)],
            "volume": [1000] * 100,
        }
    )


@pytest.fixture
def csv_file(sample_ohlcv_data, tmp_path):
    """Create temporary CSV file."""
    csv_path = tmp_path / "test_data.csv"
    sample_ohlcv_data.to_csv(csv_path, index=False)
    return csv_path


@pytest.fixture
def parquet_file(sample_ohlcv_data, tmp_path):
    """Create temporary Parquet file."""
    parquet_path = tmp_path / "test_data.parquet"
    sample_ohlcv_data.to_parquet(parquet_path, index=False)
    return parquet_path


def test_csv_loader(csv_file):
    """Test CSV loader."""
    loader = CSVLoader()
    df = loader.load(str(csv_file), symbol="DAX", timeframe=Timeframe.M1)

    assert len(df) == 100
    assert "symbol" in df.columns
    assert "timeframe" in df.columns
    assert df["symbol"].iloc[0] == "DAX"
    assert df["timeframe"].iloc[0] == "1min"


def test_csv_loader_missing_file():
    """Test CSV loader with missing file."""
    loader = CSVLoader()
    with pytest.raises(Exception):  # Should raise DataError
        loader.load("nonexistent.csv")


def test_parquet_loader(parquet_file):
    """Test Parquet loader."""
    loader = ParquetLoader()
    df = loader.load(str(parquet_file), symbol="DAX", timeframe=Timeframe.M1)

    assert len(df) == 100
    assert "symbol" in df.columns
    assert "timeframe" in df.columns


def test_load_and_preprocess(csv_file):
    """Test load_and_preprocess function."""
    from src.data.loaders import load_and_preprocess

    df = load_and_preprocess(
        str(csv_file),
        loader_type="csv",
        validate=True,
        preprocess=True,
    )

    assert len(df) == 100
    assert "timestamp" in df.columns