# Fixture Quality Review

## Summary
- Files reviewed: 4 conftest files
- Key fixtures analyzed: 5
- Overall quality: 4.0/5

## Main conftest.py Analysis (`tests/conftest.py`)

### Fixtures Reviewed

#### 1. `clear_type_caches` (session scope, autouse)
| Criterion | Score | Notes |
|-----------|-------|-------|
| Scope | 5 | Appropriately session-scoped for expensive cache clearing |
| Documentation | 4 | Good docstring explaining purpose |
| Safety | 5 | Proper yield pattern with cleanup |
| Performance | 5 | Session scope prevents unnecessary repeated clearing |

**Good**: Uses session scope to minimize cache clearing overhead.

#### 2. `clear_registry` (function scope, autouse)
| Criterion | Score | Notes |
|-----------|-------|-------|
| Scope | 5 | Function scope appropriate for isolation |
| Documentation | 5 | Excellent docstring with optimization explanation |
| Safety | 5 | Conditional clearing based on test markers |
| Performance | 5 | Smart optimization - only clears for tests needing isolation |

**Good**: Marker-based conditional clearing (`database`, `integration`, `e2e`, `forked`, `slow`, `enterprise`) is an excellent optimization pattern.

#### 3. `use_snake_case` (function scope)
| Criterion | Score | Notes |
|-----------|-------|-------|
| Scope | 5 | Function scope for config changes |
| Documentation | 3 | Basic docstring |
| Safety | 5 | Saves and restores original config |
| Performance | 5 | Lightweight fixture |

**Good**: Properly saves and restores original config.

### Fixture Organization

The main conftest uses modular imports:
```python
from tests.fixtures.examples.conftest_examples import *
from tests.fixtures.database.database_conftest import *
from tests.fixtures.auth.conftest_auth import *
from tests.fixtures.cascade.conftest import *
```

**Strengths**:
- Graceful fallback when dependencies unavailable
- Logical grouping by domain
- `FRAISEQL_AVAILABLE` flag for conditional execution

**Issues**:
- Star imports (`*`) make fixture discovery harder
- No explicit list of imported fixtures

### `pytest_collection_modifyitems` Hook

| Criterion | Score | Notes |
|-----------|-------|-------|
| Purpose | 5 | Skip Rust tests when FRAISEQL_SKIP_RUST=1 |
| Implementation | 4 | Checks markers and filepath |
| Performance | 5 | Lightweight string checks |

## Issues Found

### P1 - High Priority
1. **Star imports from fixture modules** - Hard to track which fixtures come from where
   - Recommendation: Use explicit imports or `__all__` in fixture modules

### P2 - Medium Priority
2. **Missing fixture documentation** - Some fixtures lack type hints or detailed docs
   - Recommendation: Add return type hints and param descriptions

3. **No fixture usage tracking** - Unclear which fixtures are used by which tests
   - Recommendation: Add fixture usage matrix or documentation

### P3 - Low Priority
4. **No fixture caching for expensive operations** - Some fixtures could benefit from `@lru_cache`
   - Recommendation: Profile and add caching where beneficial

## Recommendations

1. **Replace star imports with explicit imports**:
   ```python
   from tests.fixtures.database.database_conftest import (
       db_pool,
       test_connection,
       # ... explicit list
   )
   ```

2. **Add fixture docstrings with parameter types**:
   ```python
   @pytest.fixture
   def use_snake_case() -> Generator[None, None, None]:
       """Configure schema for snake_case field names.

       Yields:
           None

       Note:
           Restores original config after test.
       """
   ```

3. **Create fixture dependency graph** in documentation for complex test scenarios

4. **Consider using `pytest-lazy-fixture`** for parametrized fixtures where applicable

## Overall Assessment

The fixture design is solid with good use of:
- Session vs function scope optimization
- Marker-based conditional execution
- Proper cleanup with yield patterns
- Graceful degradation when dependencies unavailable

Main improvement area is explicit imports and better documentation.
