To optimize database queries in Python, use indexing, limit the data retrieved with `SELECT` statements, and consider using ORM features like lazy loading. Analyze query performance with tools like EXPLAIN.

Optimizing database queries is crucial for enhancing the performance of Python applications that rely on database interactions. Start by examining the structure of your queries; using indexes on frequently queried columns can significantly speed up data retrieval. Ensure that your database tables are indexed appropriately for the types of queries you are executing. Additionally, limit the data retrieved by using SELECT statements that specify only the necessary columns rather than using SELECT *, which can lead to unnecessary data transfer. In Python, if you’re using an Object-Relational Mapping (ORM) framework like SQLAlchemy or Django ORM, leverage features such as lazy loading to minimize the amount of data loaded into memory. Additionally, you can analyze query performance using the EXPLAIN command, which provides insights into how the database executes your queries. This information can help you identify slow queries and optimize them further. By combining these strategies, you can improve the efficiency of database queries in your Python applications.