Describe your experience with optimizing and processing complex SQL queries.

Optimizing complex SQL queries in Python typically involves analyzing the execution plan, using indexes, and minimizing database access. When working with ORM (such as SQLAlchemy or Django ORM), it is important to avoid the "N+1" problem, use eager loading, and write queries with aggregations or subqueries.

Example of optimization with SQLAlchemy:

from sqlalchemy.orm import joinedload

# Instead of lazy loading related objects
session.query(Parent).options(joinedload(Parent.children)).all()

It is also useful to profile queries and, if necessary, write raw SQL for performance-critical sections.