Imported from mikesvoboda/nemotron-v3-home-security-intelligence (backend/tests/unit/api/schemas/AGENTS.md). Install upstream with npx skills add mikesvoboda/nemotron-v3-home-security-intelligence --skill schemas. Copyright stays with the author.

Unit Tests - API Schemas

Purpose

The backend/tests/unit/api/schemas/ directory contains unit tests for Pydantic schema validation. These tests verify request/response data validation, serialization, and field constraints.

Directory Structure

backend/tests/unit/api/schemas/
├── AGENTS.md                         # This file
├── __init__.py                       # Package initialization
├── test_detections.py                # Detection schema validation
├── test_enrichment_data_validation.py# Enrichment data schemas
├── test_llm_response.py              # LLM response schema validation
├── test_performance_schemas.py       # Performance schema models
└── test_system.py                    # System schema validation

Test Files (5 files)

Running Tests

# All schema tests
uv run pytest backend/tests/unit/api/schemas/ -v

# Single test file
uv run pytest backend/tests/unit/api/schemas/test_detections.py -v

# With coverage
uv run pytest backend/tests/unit/api/schemas/ -v --cov=backend/api/schemas

Test Categories

Field Validation Tests

• Required field presence
• Optional field defaults
• Type coercion and validation
• String length constraints
• Numeric range validation
• Enum value validation

Serialization Tests

• JSON serialization roundtrip
• Date/datetime formatting
• UUID handling
• Nested object serialization

Edge Case Tests

• Empty values handling
• Null vs missing fields
• Extra fields rejection/ignoring
• Unicode and special characters

Common Test Patterns

Valid Schema Test

def test_valid_schema():
    data = {"id": "abc123", "confidence": 0.95, "label": "person"}
    schema = DetectionSchema(**data)
    assert schema.id == "abc123"
    assert schema.confidence == 0.95

Invalid Schema Test

def test_invalid_confidence():
    with pytest.raises(ValidationError) as exc_info:
        DetectionSchema(
            id="abc123",
            confidence=1.5,  # Invalid: > 1.0
            label="person",
        )
    assert "confidence" in str(exc_info.value)

Serialization Test

def test_serialization():
    schema = DetectionSchema(id="abc123", confidence=0.95, label="person")
    data = schema.model_dump()
    assert isinstance(data, dict)
    assert data["id"] == "abc123"

JSON Roundtrip Test

def test_json_roundtrip():
    original = DetectionSchema(id="abc123", confidence=0.95, label="person")
    json_str = original.model_dump_json()
    restored = DetectionSchema.model_validate_json(json_str)
    assert original == restored

Related Documentation

• /backend/api/schemas/AGENTS.md - Schema implementation docs
• /backend/tests/unit/AGENTS.md - Unit test patterns
• /backend/tests/unit/api/AGENTS.md - API layer test overview