WIP

tests/domain/test_document_classifier.py

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+"""
+Tests for DocumentClassifier - TDD RED phase.
+
+Test document type classification based on extracted fields.
+"""
+import pytest
+
+from backend.domain.document_classifier import DocumentClassifier, ClassificationResult
+
+
+class TestDocumentClassifier:
+    """Test document classification logic."""
+
+    @pytest.fixture
+    def classifier(self) -> DocumentClassifier:
+        """Create classifier instance."""
+        return DocumentClassifier()
+
+    # ==================== Invoice Detection Tests ====================
+
+    def test_classify_with_payment_line_returns_invoice(
+        self, classifier: DocumentClassifier
+    ) -> None:
+        """Payment line is the strongest invoice indicator."""
+        fields = {"payment_line": "# 123456 # 100 00 5 > 308-2963#"}
+
+        result = classifier.classify(fields)
+
+        assert result.document_type == "invoice"
+        assert result.confidence >= 0.9
+        assert "payment_line" in result.reason
+
+    def test_classify_with_multiple_indicators_returns_invoice(
+        self, classifier: DocumentClassifier
+    ) -> None:
+        """Multiple invoice indicators -> invoice with medium confidence."""
+        fields = {
+            "Amount": "1200.00",
+            "Bankgiro": "123-4567",
+            "payment_line": None,
+        }
+
+        result = classifier.classify(fields)
+
+        assert result.document_type == "invoice"
+        assert result.confidence >= 0.7
+
+    def test_classify_with_ocr_and_amount_returns_invoice(
+        self, classifier: DocumentClassifier
+    ) -> None:
+        """OCR + Amount is typical invoice pattern."""
+        fields = {
+            "OCR": "123456789012",
+            "Amount": "500.00",
+        }
+
+        result = classifier.classify(fields)
+
+        assert result.document_type == "invoice"
+        assert result.confidence >= 0.7
+
+    def test_classify_with_single_indicator_returns_invoice_lower_confidence(
+        self, classifier: DocumentClassifier
+    ) -> None:
+        """Single indicator -> invoice but lower confidence."""
+        fields = {"Amount": "100.00"}
+
+        result = classifier.classify(fields)
+
+        assert result.document_type == "invoice"
+        assert 0.5 <= result.confidence < 0.8
+
+    def test_classify_with_invoice_number_only(
+        self, classifier: DocumentClassifier
+    ) -> None:
+        """Invoice number alone suggests invoice."""
+        fields = {"InvoiceNumber": "INV-2024-001"}
+
+        result = classifier.classify(fields)
+
+        assert result.document_type == "invoice"
+
+    # ==================== Letter Detection Tests ====================
+
+    def test_classify_with_no_indicators_returns_letter(
+        self, classifier: DocumentClassifier
+    ) -> None:
+        """No invoice indicators -> letter."""
+        fields: dict[str, str | None] = {}
+
+        result = classifier.classify(fields)
+
+        assert result.document_type == "letter"
+        assert result.confidence >= 0.5
+
+    def test_classify_with_empty_fields_returns_letter(
+        self, classifier: DocumentClassifier
+    ) -> None:
+        """All fields empty or None -> letter."""
+        fields = {
+            "payment_line": None,
+            "OCR": None,
+            "Amount": None,
+            "Bankgiro": None,
+        }
+
+        result = classifier.classify(fields)
+
+        assert result.document_type == "letter"
+
+    def test_classify_with_only_non_indicator_fields_returns_letter(
+        self, classifier: DocumentClassifier
+    ) -> None:
+        """Fields that don't indicate invoice -> letter."""
+        fields = {
+            "CustomerNumber": "C12345",
+            "SupplierOrgNumber": "556677-8899",
+        }
+
+        result = classifier.classify(fields)
+
+        assert result.document_type == "letter"
+
+    # ==================== Edge Cases ====================
+
+    def test_classify_with_empty_string_fields_returns_letter(
+        self, classifier: DocumentClassifier
+    ) -> None:
+        """Empty strings should be treated as missing."""
+        fields = {
+            "payment_line": "",
+            "Amount": "",
+        }
+
+        result = classifier.classify(fields)
+
+        assert result.document_type == "letter"
+
+    def test_classify_with_whitespace_only_fields_returns_letter(
+        self, classifier: DocumentClassifier
+    ) -> None:
+        """Whitespace-only strings should be treated as missing."""
+        fields = {
+            "payment_line": "   ",
+            "Amount": "\t\n",
+        }
+
+        result = classifier.classify(fields)
+
+        assert result.document_type == "letter"
+
+    # ==================== ClassificationResult Immutability ====================
+
+    def test_classification_result_is_immutable(
+        self, classifier: DocumentClassifier
+    ) -> None:
+        """ClassificationResult should be a frozen dataclass."""
+        fields = {"payment_line": "test"}
+        result = classifier.classify(fields)
+
+        with pytest.raises((AttributeError, TypeError)):
+            result.document_type = "modified"  # type: ignore
+
+    def test_classification_result_has_required_fields(
+        self, classifier: DocumentClassifier
+    ) -> None:
+        """ClassificationResult must have document_type, confidence, reason."""
+        fields = {"Amount": "100.00"}
+        result = classifier.classify(fields)
+
+        assert hasattr(result, "document_type")
+        assert hasattr(result, "confidence")
+        assert hasattr(result, "reason")
+        assert isinstance(result.document_type, str)
+        assert isinstance(result.confidence, float)
+        assert isinstance(result.reason, str)