Build SQLAlchemy queries that are both efficient and deterministic to prevent unpredictable results and improve performance. When writing database queries:

1. Use SQLAlchemy’s native operators instead of Python’s bitwise operators for better readability: ```python

   Instead of this:

   query.where((DagFavorite.dag_id == DagModel.dag_id) & (DagFavorite.user_id == self.user_id))

Use this:

query.where(and_(DagFavorite.dag_id == DagModel.dag_id, DagFavorite.user_id == self.user_id))

2. **Build queries with explicit control flow** for complex conditions:
```python
# Instead of adding a complex boolean expression:
query = ...
since_running = Log.dttm > last_running_time if last_running_time else True
query = query.where(Log.event == EVENT, since_running)

# Prefer explicit conditional logic:
query = query.where(Log.event == EVENT)
if last_running_time:
    query = query.where(Log.dttm > last_running_time)

1. Always ensure deterministic ordering by including a unique identifier (typically the primary key) as a secondary sort criterion: ```python

   Instead of:

   query.order_by(AssetEvent.timestamp.asc())

Use:

query.order_by(AssetEvent.timestamp.asc(), AssetEvent.id.asc()) ```

1. Review query filters carefully to avoid overly restrictive WHERE clauses that might unintentionally exclude valid records. Consider the complete range of valid states and values that should be included in your results.