tests/test_settings_upload.py

"""Comprehensive tests for settings CSV upload functionality.

This module tests edge cases and error scenarios for the settings upload feature,
including:
- read_settings event handler behavior
- CSV format edge cases (empty, malformed, encoding issues)
- File object edge cases
- Error recovery scenarios
"""

import tempfile
from pathlib import Path
from unittest.mock import Mock, patch, MagicMock
import pandas as pd
import pytest


class TestReadSettingsHandler:
    """Test the read_settings event handler directly."""

    def test_read_settings_with_none_returns_none(self):
        """Test read_settings handler logic returns None when file is None."""
        # Test the handler logic directly
        # Simulate the read_settings function from app.py
        def read_settings(file):
            if file is None:
                return None
            from mosaic.ui.utils import load_settings
            df = load_settings(file.name if hasattr(file, "name") else file)
            return df  # In actual app, returns gr.Dataframe(df, visible=True)

        result = read_settings(None)
        assert result is None

    def test_read_settings_with_file_object_with_name(self):
        """Test read_settings handles file object with .name attribute."""
        from mosaic.ui.utils import load_settings

        # Create temporary CSV
        with tempfile.NamedTemporaryFile(mode="w", suffix=".csv", delete=False) as f:
            f.write("Slide,Site Type,Sex,Cancer Subtype\n")
            f.write("slide1.svs,Primary,Male,Unknown\n")
            f.flush()
            temp_path = f.name

        try:
            # Create mock file object with .name attribute
            mock_file = Mock()
            mock_file.name = temp_path

            # Simulate read_settings handler
            def read_settings(file):
                if file is None:
                    return None
                df = load_settings(file.name if hasattr(file, "name") else file)
                return df

            result = read_settings(mock_file)

            # Verify DataFrame was loaded
            assert isinstance(result, pd.DataFrame)
            assert len(result) == 1
            assert result["Slide"].iloc[0] == "slide1.svs"
        finally:
            Path(temp_path).unlink(missing_ok=True)

    def test_read_settings_with_file_path_string(self):
        """Test read_settings handles direct file path string."""
        from mosaic.ui.utils import load_settings

        # Create temporary CSV
        with tempfile.NamedTemporaryFile(mode="w", suffix=".csv", delete=False) as f:
            f.write("Slide,Site Type,Sex,Cancer Subtype\n")
            f.write("slide1.svs,Primary,Male,Unknown\n")
            f.flush()
            temp_path = f.name

        try:
            # Simulate read_settings handler with direct path
            def read_settings(file):
                if file is None:
                    return None
                df = load_settings(file.name if hasattr(file, "name") else file)
                return df

            result = read_settings(temp_path)

            # Verify DataFrame was loaded
            assert isinstance(result, pd.DataFrame)
            assert len(result) == 1
            assert result["Slide"].iloc[0] == "slide1.svs"
        finally:
            Path(temp_path).unlink(missing_ok=True)

    def test_read_settings_with_file_object_without_name_attribute(self):
        """Test read_settings handles file-like object without .name attribute."""
        from mosaic.ui.utils import load_settings

        # Create temporary CSV
        with tempfile.NamedTemporaryFile(mode="w", suffix=".csv", delete=False) as f:
            f.write("Slide,Site Type,Sex,Cancer Subtype\n")
            f.write("slide1.svs,Primary,Male,Unknown\n")
            f.flush()
            temp_path = f.name

        try:
            # Simulate read_settings handler (file without .name falls back to using file directly)
            def read_settings(file):
                if file is None:
                    return None
                df = load_settings(file.name if hasattr(file, "name") else file)
                return df

            # When file doesn't have .name, the function uses the file object directly
            # In practice, Gradio always provides .name, but test the fallback
            result = read_settings(temp_path)

            assert isinstance(result, pd.DataFrame)
            assert len(result) == 1
        finally:
            Path(temp_path).unlink(missing_ok=True)


class TestCsvFormatEdgeCases:
    """Test CSV format edge cases and error handling."""

    def test_load_settings_empty_csv_file(self):
        """Test loading completely empty CSV file."""
        from mosaic.ui.utils import load_settings

        with tempfile.NamedTemporaryFile(mode="w", suffix=".csv", delete=False) as f:
            # Write nothing - completely empty file
            f.flush()
            temp_path = f.name

        try:
            # Empty CSV should raise an error
            with pytest.raises(Exception):  # Could be pd.errors.EmptyDataError or ValueError
                load_settings(temp_path)
        finally:
            Path(temp_path).unlink(missing_ok=True)

    def test_load_settings_headers_only_csv(self):
        """Test CSV with only headers but no data rows."""
        from mosaic.ui.utils import load_settings

        with tempfile.NamedTemporaryFile(mode="w", suffix=".csv", delete=False) as f:
            f.write("Slide,Site Type,Sex,Cancer Subtype\n")
            # No data rows
            f.flush()
            temp_path = f.name

        try:
            df = load_settings(temp_path)

            # Should return empty DataFrame with correct columns
            assert isinstance(df, pd.DataFrame)
            assert len(df) == 0
            assert "Slide" in df.columns
            assert "Site Type" in df.columns
        finally:
            Path(temp_path).unlink(missing_ok=True)

    def test_load_settings_csv_with_extra_columns(self):
        """Test CSV with extra unknown columns (should be filtered)."""
        from mosaic.ui.utils import load_settings, SETTINGS_COLUMNS

        with tempfile.NamedTemporaryFile(mode="w", suffix=".csv", delete=False) as f:
            f.write("Slide,Site Type,Sex,Cancer Subtype,ExtraColumn1,ExtraColumn2\n")
            f.write("slide1.svs,Primary,Male,Unknown,extra_value1,extra_value2\n")
            f.flush()
            temp_path = f.name

        try:
            df = load_settings(temp_path)

            # Extra columns should be filtered out
            assert "ExtraColumn1" not in df.columns
            assert "ExtraColumn2" not in df.columns

            # Only SETTINGS_COLUMNS should remain
            assert list(df.columns) == SETTINGS_COLUMNS
        finally:
            Path(temp_path).unlink(missing_ok=True)

    def test_load_settings_csv_with_special_characters(self):
        """Test CSV with special characters in values."""
        from mosaic.ui.utils import load_settings

        with tempfile.NamedTemporaryFile(mode="w", suffix=".csv", delete=False) as f:
            f.write("Slide,Site Type,Sex,Cancer Subtype\n")
            # Special characters in slide name
            f.write("slide-1_test@2024.svs,Primary,Unknown\n")
            f.flush()
            temp_path = f.name

        try:
            df = load_settings(temp_path)

            # Should handle special characters correctly
            assert isinstance(df, pd.DataFrame)
            assert len(df) == 1
            assert df["Slide"].iloc[0] == "slide-1_test@2024.svs"
        finally:
            Path(temp_path).unlink(missing_ok=True)

    def test_load_settings_csv_with_quotes_in_values(self):
        """Test CSV with quoted values."""
        from mosaic.ui.utils import load_settings

        with tempfile.NamedTemporaryFile(mode="w", suffix=".csv", delete=False) as f:
            f.write("Slide,Site Type,Sex,Cancer Subtype\n")
            # Value with comma inside quotes
            f.write('"slide1,with,commas.svs",Primary,Unknown\n')
            f.flush()
            temp_path = f.name

        try:
            df = load_settings(temp_path)

            # Should parse quoted values correctly
            assert isinstance(df, pd.DataFrame)
            assert len(df) == 1
            assert df["Slide"].iloc[0] == "slide1,with,commas.svs"
        finally:
            Path(temp_path).unlink(missing_ok=True)

    def test_load_settings_csv_with_missing_values(self):
        """Test CSV with missing/empty values in optional columns."""
        from mosaic.ui.utils import load_settings

        with tempfile.NamedTemporaryFile(mode="w", suffix=".csv", delete=False) as f:
            f.write("Slide,Site Type,Sex,Cancer Subtype,IHC Subtype,Segmentation Config\n")
            # Empty values for optional columns
            f.write("slide1.svs,Primary,Male,Unknown,,\n")
            f.flush()
            temp_path = f.name

        try:
            df = load_settings(temp_path)

            # Should load CSV with empty values preserved
            assert isinstance(df, pd.DataFrame)
            assert len(df) == 1
            # Empty strings should be preserved (validation will handle defaults later)
            assert df["Segmentation Config"].iloc[0] == ""
            assert df["IHC Subtype"].iloc[0] == ""
        finally:
            Path(temp_path).unlink(missing_ok=True)

    def test_load_settings_csv_with_whitespace(self):
        """Test CSV with extra whitespace around values."""
        from mosaic.ui.utils import load_settings

        with tempfile.NamedTemporaryFile(mode="w", suffix=".csv", delete=False) as f:
            f.write("Slide,Site Type,Sex,Cancer Subtype\n")
            # Values with leading/trailing whitespace
            f.write(" slide1.svs , Primary , Male , Unknown \n")
            f.flush()
            temp_path = f.name

        try:
            df = load_settings(temp_path)

            # pandas should handle whitespace
            assert isinstance(df, pd.DataFrame)
            assert len(df) == 1
            # Check if whitespace is preserved or stripped (depends on pandas behavior)
            slide_value = df["Slide"].iloc[0]
            assert "slide1.svs" in slide_value
        finally:
            Path(temp_path).unlink(missing_ok=True)

    def test_load_settings_csv_with_different_line_endings(self):
        """Test CSV with different line ending styles (CRLF, LF)."""
        from mosaic.ui.utils import load_settings

        # Test with CRLF (Windows style)
        with tempfile.NamedTemporaryFile(mode="wb", suffix=".csv", delete=False) as f:
            f.write(b"Slide,Site Type,Sex,Cancer Subtype\r\n")
            f.write(b"slide1.svs,Primary,Male,Unknown\r\n")
            f.flush()
            temp_path = f.name

        try:
            df = load_settings(temp_path)

            assert isinstance(df, pd.DataFrame)
            assert len(df) == 1
            assert df["Slide"].iloc[0] == "slide1.svs"
        finally:
            Path(temp_path).unlink(missing_ok=True)

    def test_load_settings_csv_with_tab_delimiter_fails(self):
        """Test that TSV (tab-delimited) file raises error."""
        from mosaic.ui.utils import load_settings

        with tempfile.NamedTemporaryFile(mode="w", suffix=".csv", delete=False) as f:
            # Use tabs instead of commas
            f.write("Slide\tSite Type\tCancer Subtype\n")
            f.write("slide1.svs\tPrimary\tUnknown\n")
            f.flush()
            temp_path = f.name

        try:
            # Should fail because columns won't be parsed correctly
            with pytest.raises(ValueError, match="Missing required column"):
                load_settings(temp_path)
        finally:
            Path(temp_path).unlink(missing_ok=True)

    def test_load_settings_large_csv(self):
        """Test loading CSV with many rows (performance test)."""
        from mosaic.ui.utils import load_settings

        num_rows = 1000

        with tempfile.NamedTemporaryFile(mode="w", suffix=".csv", delete=False) as f:
            f.write("Slide,Site Type,Sex,Cancer Subtype\n")
            for i in range(num_rows):
                f.write(f"slide{i}.svs,Primary,Male,Unknown\n")
            f.flush()
            temp_path = f.name

        try:
            df = load_settings(temp_path)

            # Should handle large CSV without issues
            assert isinstance(df, pd.DataFrame)
            assert len(df) == num_rows
        finally:
            Path(temp_path).unlink(missing_ok=True)


class TestEncodingEdgeCases:
    """Test CSV encoding edge cases."""

    def test_load_settings_utf8_csv(self):
        """Test loading UTF-8 encoded CSV (should work)."""
        from mosaic.ui.utils import load_settings

        with tempfile.NamedTemporaryFile(mode="w", encoding="utf-8", suffix=".csv", delete=False) as f:
            f.write("Slide,Site Type,Sex,Cancer Subtype\n")
            f.write("slide1.svs,Primary,Male,Unknown\n")
            f.flush()
            temp_path = f.name

        try:
            df = load_settings(temp_path)
            assert isinstance(df, pd.DataFrame)
            assert len(df) == 1
        finally:
            Path(temp_path).unlink(missing_ok=True)

    def test_load_settings_csv_with_unicode_characters(self):
        """Test CSV with Unicode characters in values."""
        from mosaic.ui.utils import load_settings

        with tempfile.NamedTemporaryFile(mode="w", encoding="utf-8", suffix=".csv", delete=False) as f:
            f.write("Slide,Site Type,Sex,Cancer Subtype\n")
            # Unicode characters in slide name
            f.write("slide_café_™_测试.svs,Primary,Unknown\n")
            f.flush()
            temp_path = f.name

        try:
            df = load_settings(temp_path)

            # Should handle Unicode correctly
            assert isinstance(df, pd.DataFrame)
            assert len(df) == 1
            assert "café" in df["Slide"].iloc[0]
        finally:
            Path(temp_path).unlink(missing_ok=True)


class TestErrorRecoveryScenarios:
    """Test error recovery and user experience flows."""

    def test_consecutive_csv_uploads(self):
        """Test uploading multiple CSVs consecutively."""
        from mosaic.ui.utils import load_settings

        # First CSV
        with tempfile.NamedTemporaryFile(mode="w", suffix=".csv", delete=False) as f:
            f.write("Slide,Site Type,Sex,Cancer Subtype\n")
            f.write("slide1.svs,Primary,Male,Unknown\n")
            f.flush()
            temp_path1 = f.name

        # Second CSV (different data)
        with tempfile.NamedTemporaryFile(mode="w", suffix=".csv", delete=False) as f:
            f.write("Slide,Site Type,Sex,Cancer Subtype\n")
            f.write("slide2.svs,Metastatic,Female,LUAD\n")
            f.write("slide3.svs,Primary,Male,BRCA\n")
            f.flush()
            temp_path2 = f.name

        try:
            # Load first CSV
            df1 = load_settings(temp_path1)
            assert len(df1) == 1
            assert df1["Slide"].iloc[0] == "slide1.svs"

            # Load second CSV (should completely replace)
            df2 = load_settings(temp_path2)
            assert len(df2) == 2
            assert df2["Slide"].iloc[0] == "slide2.svs"
            assert df2["Slide"].iloc[1] == "slide3.svs"

            # Should be independent DataFrames
            assert len(df1) == 1  # df1 unchanged
        finally:
            Path(temp_path1).unlink(missing_ok=True)
            Path(temp_path2).unlink(missing_ok=True)

    def test_load_settings_after_failed_upload(self):
        """Test successful load after a failed upload attempt."""
        from mosaic.ui.utils import load_settings

        # First attempt: invalid CSV (missing required columns)
        with tempfile.NamedTemporaryFile(mode="w", suffix=".csv", delete=False) as f:
            f.write("InvalidColumn\n")
            f.write("value\n")
            f.flush()
            invalid_path = f.name

        # Second attempt: valid CSV
        with tempfile.NamedTemporaryFile(mode="w", suffix=".csv", delete=False) as f:
            f.write("Slide,Site Type,Sex,Cancer Subtype\n")
            f.write("slide1.svs,Primary,Male,Unknown\n")
            f.flush()
            valid_path = f.name

        try:
            # First load should fail
            with pytest.raises(ValueError, match="Missing required column"):
                load_settings(invalid_path)

            # Second load should succeed
            df = load_settings(valid_path)
            assert isinstance(df, pd.DataFrame)
            assert len(df) == 1
            assert df["Slide"].iloc[0] == "slide1.svs"
        finally:
            Path(invalid_path).unlink(missing_ok=True)
            Path(valid_path).unlink(missing_ok=True)

    def test_load_settings_with_file_permission_error(self):
        """Test behavior when file cannot be read due to permissions."""
        from mosaic.ui.utils import load_settings
        import os

        if os.name == 'nt':
            # Skip on Windows due to different permission model
            pytest.skip("Permission test not applicable on Windows")

        with tempfile.NamedTemporaryFile(mode="w", suffix=".csv", delete=False) as f:
            f.write("Slide,Site Type,Sex,Cancer Subtype\n")
            f.write("slide1.svs,Primary,Male,Unknown\n")
            f.flush()
            temp_path = f.name

        try:
            # Remove read permissions
            os.chmod(temp_path, 0o000)

            # Should raise permission error
            with pytest.raises(PermissionError):
                load_settings(temp_path)
        finally:
            # Restore permissions for cleanup
            os.chmod(temp_path, 0o644)
            Path(temp_path).unlink(missing_ok=True)

    def test_load_settings_nonexistent_file(self):
        """Test loading from non-existent file path."""
        from mosaic.ui.utils import load_settings

        nonexistent_path = "/tmp/this_file_does_not_exist_12345.csv"

        # Should raise FileNotFoundError
        with pytest.raises(FileNotFoundError):
            load_settings(nonexistent_path)


class TestValidationWithUpload:
    """Test validation integration with CSV upload."""

    def test_csv_upload_triggers_validation(self, mock_cancer_subtype_maps):
        """Test that uploaded CSV is automatically validated."""
        from mosaic.ui.utils import load_settings, validate_settings

        cancer_subtype_name_map, reversed_map, cancer_subtypes = mock_cancer_subtype_maps

        # Create CSV with invalid values
        with tempfile.NamedTemporaryFile(mode="w", suffix=".csv", delete=False) as f:
            f.write("Slide,Site Type,Sex,Cancer Subtype,Segmentation Config\n")
            f.write("slide1.svs,InvalidSite,Male,InvalidSubtype,InvalidConfig\n")
            f.flush()
            temp_path = f.name

        try:
            # Load and validate
            df = load_settings(temp_path)
            validated_df = validate_settings(
                df, cancer_subtype_name_map, cancer_subtypes, reversed_map
            )

            # Should apply defaults for invalid values
            assert validated_df["Site Type"].iloc[0] == "Primary"
            assert validated_df["Cancer Subtype"].iloc[0] == "Unknown"
            assert validated_df["Segmentation Config"].iloc[0] == "Biopsy"
        finally:
            Path(temp_path).unlink(missing_ok=True)

    def test_csv_upload_with_partial_invalid_data(self, mock_cancer_subtype_maps):
        """Test CSV with mix of valid and invalid rows."""
        from mosaic.ui.utils import load_settings, validate_settings

        cancer_subtype_name_map, reversed_map, cancer_subtypes = mock_cancer_subtype_maps

        with tempfile.NamedTemporaryFile(mode="w", suffix=".csv", delete=False) as f:
            f.write("Slide,Site Type,Sex,Cancer Subtype\n")
            f.write("slide1.svs,Primary,Male,Unknown\n")  # Valid
            f.write("slide2.svs,InvalidSite,Female,InvalidSubtype\n")  # Invalid
            f.write("slide3.svs,Metastatic,Male,LUAD\n")  # Valid
            f.flush()
            temp_path = f.name

        try:
            df = load_settings(temp_path)
            validated_df = validate_settings(
                df, cancer_subtype_name_map, cancer_subtypes, reversed_map
            )

            # All rows should be present
            assert len(validated_df) == 3

            # Valid rows unchanged
            assert validated_df.iloc[0]["Site Type"] == "Primary"
            assert validated_df.iloc[2]["Site Type"] == "Metastatic"

            # Invalid row corrected with defaults
            assert validated_df.iloc[1]["Site Type"] == "Primary"
            assert validated_df.iloc[1]["Cancer Subtype"] == "Unknown"
        finally:
            Path(temp_path).unlink(missing_ok=True)