"""Tests for data validators."""

import pandas as pd
import pytest

from src.core.enums import Timeframe
from src.data.validators import check_continuity, detect_outliers, validate_ohlcv


@pytest.fixture
def valid_ohlcv_data():
    """Create valid 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 invalid_ohlcv_data():
    """Create invalid OHLCV DataFrame."""
    dates = pd.date_range("2024-01-01 03:00", periods=10, freq="1min")
    df = pd.DataFrame(
        {
            "timestamp": dates,
            "open": [100.0] * 10,
            "high": [99.0] * 10,  # Invalid: high < low
            "low": [99.5] * 10,
            "close": [100.2] * 10,
        }
    )
    return df


def test_validate_ohlcv_valid(valid_ohlcv_data):
    """Test validation with valid data."""
    df = validate_ohlcv(valid_ohlcv_data)
    assert len(df) == 100


def test_validate_ohlcv_invalid(invalid_ohlcv_data):
    """Test validation with invalid data."""
    with pytest.raises(Exception):  # Should raise ValidationError
        validate_ohlcv(invalid_ohlcv_data)


def test_validate_ohlcv_missing_columns():
    """Test validation with missing columns."""
    df = pd.DataFrame({"timestamp": pd.date_range("2024-01-01", periods=10)})
    with pytest.raises(Exception):  # Should raise ValidationError
        validate_ohlcv(df)


def test_check_continuity(valid_ohlcv_data):
    """Test continuity check."""
    is_continuous, gaps = check_continuity(valid_ohlcv_data, Timeframe.M1)
    assert is_continuous
    assert len(gaps) == 0


def test_check_continuity_with_gaps():
    """Test continuity check with gaps."""
    # Create data with gaps
    dates = pd.date_range("2024-01-01 03:00", periods=10, freq="1min")
    # Remove some dates to create gaps
    dates = dates[[0, 1, 2, 5, 6, 7, 8, 9]]  # Gap between index 2 and 5

    df = pd.DataFrame(
        {
            "timestamp": dates,
            "open": [100.0] * len(dates),
            "high": [100.5] * len(dates),
            "low": [99.5] * len(dates),
            "close": [100.2] * len(dates),
        }
    )

    is_continuous, gaps = check_continuity(df, Timeframe.M1)
    assert not is_continuous
    assert len(gaps) > 0


def test_detect_outliers(valid_ohlcv_data):
    """Test outlier detection."""
    # Add an outlier
    df = valid_ohlcv_data.copy()
    df.loc[50, "close"] = 200.0  # Extreme value

    outliers = detect_outliers(df, columns=["close"], method="iqr", threshold=3.0)
    assert outliers["is_outlier"].sum() > 0