public code v1

test/data_reader/test_data_reader.py

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+import pytest
+import pandas as pd
+import numpy as np
+import tempfile
+import os
+from unittest.mock import patch
+from pygrex.data_reader.data_reader import DataReader
+
+
+@pytest.fixture
+def valid_df():
+    """Fixture providing a valid test DataFrame."""
+    return pd.DataFrame(
+        {
+            "userId": [1, 2, 3, 1],
+            "itemId": [100, 200, 300, 400],
+            "rating": [4.5, 3.0, 5.0, 2.0],
+            "timestamp": [1000, 2000, 3000, 4000],
+        }
+    )
+
+
+@pytest.fixture
+def test_csv_path(valid_df):
+    """Fixture providing a temporary CSV file with valid data."""
+    with tempfile.TemporaryDirectory() as temp_dir:
+        test_csv_path = os.path.join(temp_dir, "test_data.csv")
+        valid_df.to_csv(test_csv_path, sep=",", index=False)
+        yield test_csv_path
+
+
+def test_init_with_dataframe(valid_df):
+    """Test initialization with a DataFrame."""
+    reader = DataReader(dataframe=valid_df)
+    pd.testing.assert_frame_equal(reader.dataset, valid_df)
+    assert reader.num_user == 3
+    assert reader.num_item == 4
+
+
+def test_init_with_filepath(test_csv_path):
+    """Test initialization with filepath."""
+    reader = DataReader(
+        filepath_or_buffer=test_csv_path,
+        sep=",",
+        names=["userId", "itemId", "rating", "timestamp"],
+        skiprows=1,  # Skip header
+    )
+    # Check that dataset was loaded correctly
+    assert reader.num_user == 3
+    assert reader.num_item == 4
+
+
+def test_dataset_loading_file_not_found():
+    """Test exception when file is not found."""
+    with pytest.raises(FileNotFoundError):
+        DataReader(
+            filepath_or_buffer="nonexistent.csv",
+            sep=",",
+            names=["userId", "itemId", "rating", "timestamp"],
+        )
+
+
+def test_dataset_validation_invalid_columns():
+    """Test validation for invalid columns."""
+    # Create a DataFrame with non-numeric userId
+    invalid_df = pd.DataFrame(
+        {
+            "userId": ["user1", "user2", "user3"],
+            "itemId": [100, 200, 300],
+            "rating": [4.5, 3.0, 5.0],
+            "timestamp": [1000, 2000, 3000],
+        }
+    )
+
+    with pytest.raises(ValueError) as excinfo:
+        DataReader(dataframe=invalid_df)
+    assert "cannot be converted to a numeric type" in str(excinfo.value)
+
+
+def test_dataset_validation_empty():
+    """Test validation for empty DataFrame."""
+    empty_df = pd.DataFrame(columns=["userId", "itemId", "rating", "timestamp"])
+    with pytest.raises(ValueError) as excinfo:
+        DataReader(dataframe=empty_df)
+    assert "DataFrame cannot be empty" in str(excinfo.value)
+
+
+def test_dataset_validation_invalid_types():
+    """Test validation for invalid data types."""
+    # Create DataFrame with invalid rating (string)
+    invalid_types_df = pd.DataFrame(
+        {
+            "userId": [1, 2, 3],
+            "itemId": [100, 200, 300],
+            "rating": ["high", "medium", "low"],
+            "timestamp": [1000, 2000, 3000],
+        }
+    )
+
+    with pytest.raises(ValueError) as excinfo:
+        DataReader(dataframe=invalid_types_df)
+    assert "cannot be converted to a numeric type" in str(excinfo.value)
+
+
+def test_dataset_validation_missing_values():
+    """Test validation for missing values."""
+    # Create DataFrame with NaN values
+    missing_values_df = pd.DataFrame(
+        {
+            "userId": [1, 2, np.nan],
+            "itemId": [100, 200, 300],
+            "rating": [4.5, 3.0, 5.0],
+            "timestamp": [1000, 2000, 3000],
+        }
+    )
+
+    with pytest.raises(ValueError) as excinfo:
+        DataReader(dataframe=missing_values_df)
+    assert "contains missing values" in str(excinfo.value)
+
+
+def test_get_raw_dataset_not_set():
+    """Test get_raw_dataset when not set."""
+    # Mock pandas.read_csv to raise FileNotFoundError
+    with patch(
+        "pandas.read_csv", side_effect=FileNotFoundError("File not found: dummy.csv")
+    ):
+        with pytest.raises(FileNotFoundError):
+            reader = DataReader(
+                filepath_or_buffer="dummy.csv",
+                sep=",",
+                names=["userId", "itemId", "rating", "timestamp"],
+            )
+
+
+def test_make_consecutive_ids_in_dataset(valid_df):
+    """Test making IDs consecutive."""
+    # Create a DataFrame with non-consecutive IDs
+    df = pd.DataFrame(
+        {
+            "userId": [100, 200, 300, 100],
+            "itemId": [500, 600, 700, 800],
+            "rating": [4.5, 3.0, 5.0, 2.0],
+            "timestamp": [1000, 2000, 3000, 4000],
+        }
+    )
+
+    reader = DataReader(dataframe=df)
+    reader.make_consecutive_ids_in_dataset()
+
+    # Check that IDs are now consecutive
+    assert set(reader.dataset["userId"]) == {0, 1, 2}
+    assert set(reader.dataset["itemId"]) == {0, 1, 2, 3}
+
+    # Check mapping
+    assert reader.get_original_user_id(0) == 100
+    assert reader.get_original_item_id(0) == 500
+
+
+def test_make_consecutive_ids_not_set():
+    """Test make_consecutive_ids_in_dataset when dataset is not set."""
+    with patch(
+        "pandas.read_csv", side_effect=FileNotFoundError("File not found: dummy.csv")
+    ):
+        with pytest.raises(FileNotFoundError):
+            reader = DataReader(
+                filepath_or_buffer="dummy.csv",
+                sep=",",
+                names=["userId", "itemId", "rating", "timestamp"],
+            )
+
+
+def test_binarize(valid_df):
+    """Test binarization of ratings."""
+    reader = DataReader(dataframe=valid_df)
+    reader.binarize(binary_threshold=3.5)
+
+    # Check that ratings are binarized
+    expected = [1, 0, 1, 0]  # 4.5 > 3.5, 3.0 <= 3.5, 5.0 > 3.5, 2.0 <= 3.5
+    assert list(reader.dataset["rating"]) == expected
+
+
+def test_binarize_not_set():
+    """Test binarize when dataset is not set."""
+    with patch(
+        "pandas.read_csv", side_effect=FileNotFoundError("File not found: dummy.csv")
+    ):
+        with pytest.raises(FileNotFoundError):
+            reader = DataReader(
+                filepath_or_buffer="dummy.csv",
+                sep=",",
+                names=["userId", "itemId", "rating", "timestamp"],
+            )
+
+
+def test_get_original_user_id_not_set(valid_df):
+    """Test get_original_user_id when mapping is not set."""
+    # Create reader without calling make_consecutive_ids_in_dataset
+    reader = DataReader(dataframe=valid_df)
+    with pytest.raises(ValueError) as excinfo:
+        reader.get_original_user_id(0)
+    assert "ID mapping not set" in str(excinfo.value)