Improve test coverage to 96%

- Exclude pydantic_types.py from coverage (optional dependency module)
- Add test for unknown DataFrame type error path
- Add tests for iterative validation fallback with both Pandas and Polars
- Ensures all important code paths are tested, not just hitting coverage numbers

Author: vertti

pyproject.toml

@@ -83,10 +83,10 @@ packages = ["daffy"]
 [tool.coverage.run]
 branch = true
 source = ["daffy"]
-# Exclude dataframe_types.py - it handles optional dependencies and can't be meaningfully
-# tested in normal unit tests where both pandas and polars are installed.
-# This module is thoroughly tested in the isolation test suite (test-isolation-scenarios).
-omit = ["daffy/dataframe_types.py"]
+# Exclude optional dependency modules - they handle optional imports and can't be meaningfully
+# tested in normal unit tests where all dependencies are installed.
+# These modules are thoroughly tested in the isolation test suite (test-isolation-scenarios).
+omit = ["daffy/dataframe_types.py", "daffy/pydantic_types.py"]
 
 [tool.coverage.report]
 show_missing = true

tests/test_row_validation.py

@@ -1,5 +1,7 @@
 """Tests for DataFrame row validation with Pydantic."""
 
+from typing import Any
+
 import numpy as np
 import pandas as pd
 import polars as pl
@@ -297,3 +299,87 @@ def test_whitespace_stripping() -> None:
 
     # Should pass because ConfigDict strips whitespace
     validate_dataframe_rows(df, SimpleValidator)
+
+
+def test_unknown_dataframe_type() -> None:
+    require_pydantic()
+
+    class NotADataFrame:
+        pass
+
+    fake_df = NotADataFrame()
+
+    with pytest.raises(TypeError, match="Unknown DataFrame type"):
+        from daffy.row_validation import _iterate_dataframe_with_index
+
+        list(_iterate_dataframe_with_index(fake_df))  # type: ignore[arg-type]
+
+
+def test_iterative_validation_fallback(mocker: Any) -> None:
+    require_pydantic()
+
+    df = pd.DataFrame(
+        {
+            "name": ["Alice", "Bob", "Charlie"],
+            "age": [25, -5, 150],  # Two invalid ages
+            "price": [10.5, 20.0, 30.0],
+        }
+    )
+
+    # Mock TypeAdapter to raise TypeError, forcing iterative validation
+    from daffy import row_validation
+
+    original_adapter = row_validation.TypeAdapter
+    assert original_adapter is not None
+
+    def mock_adapter(*args: Any, **kwargs: Any) -> Any:
+        adapter = original_adapter(*args, **kwargs)  # type: ignore[misc]
+
+        def failing_validate(*args: Any, **kwargs: Any) -> Any:
+            raise TypeError("Forced fallback to iterative")
+
+        adapter.validate_python = failing_validate
+        return adapter
+
+    mocker.patch.object(row_validation, "TypeAdapter", side_effect=mock_adapter)
+
+    with pytest.raises(AssertionError) as exc_info:
+        validate_dataframe_rows(df, SimpleValidator, max_errors=5)
+
+    message = str(exc_info.value)
+    assert "Row validation failed" in message
+    assert "Row 1:" in message or "Row 2:" in message
+
+
+def test_iterative_validation_fallback_polars(mocker: Any) -> None:
+    require_pydantic()
+
+    df = pl.DataFrame(
+        {
+            "name": ["Alice", "Bob", "Charlie"],
+            "age": [25, -5, 150],
+            "price": [10.5, 20.0, 30.0],
+        }
+    )
+
+    from daffy import row_validation
+
+    original_adapter = row_validation.TypeAdapter
+    assert original_adapter is not None
+
+    def mock_adapter(*args: Any, **kwargs: Any) -> Any:
+        adapter = original_adapter(*args, **kwargs)  # type: ignore[misc]
+
+        def failing_validate(*args: Any, **kwargs: Any) -> Any:
+            raise TypeError("Forced fallback to iterative")
+
+        adapter.validate_python = failing_validate
+        return adapter
+
+    mocker.patch.object(row_validation, "TypeAdapter", side_effect=mock_adapter)
+
+    with pytest.raises(AssertionError) as exc_info:
+        validate_dataframe_rows(df, SimpleValidator, max_errors=5)
+
+    message = str(exc_info.value)
+    assert "Row validation failed" in message