feat(v0.2.0): data pipeline

tests/unit/test_data/test_loaders.py

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+"""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