This tutorial is for Python developers of any level who write applications that interact with databases and want to learn how to leverage a tool like SQLAlchemy to seamlessly interact with a database and manage data in a Pythonic way.

You’ll walk out of this interactive tutorial having learned how to:

• Use SQLAlchemy for database operations in Python, enhancing the readability and maintainability of the code
• Build Python classes (ORMs) that represent the database tables
• Experiment with different relationship-loading techniques to improve querying performance
• Utilize SQLAlchemy’s asyncio extension to interact with databases asynchronously

To give more detail, we’ll be covering the following:

• Introduction
  • What is SQLAlchemy?
  • Why use SQLAlchemy and advantages?
  • Components Overview such as engine, dialect, connection pool, etc.
• Initial setup for the hands-on workshop with GitHub Codespaces
  • Run and explore example service that has database queries with raw SQL
• Adding SQLAlchemy to the example service
  • Set up SQLAlchemy
    • Set up engine & dialect to connect with the DB
    • Use SQLAlchemy Core to query the DB
  • Add ORMs
    • What are ORMs?
    • How to represent a basic table?
    • Modeling different relationships (e.g., 1-1 and 1-many) between the classes
    • Using ORMs to query the DB
  • Convert other queries using SQLAlchemy
• Improve performance by changing relationship loading techniques
  • Consequences of certain models: Talk about N+1 problem and bidirectional relationships
  • Discuss different loading techniques, such as lazy loading and eager loading
• The SQLAlchemy.asyncio extension
  • Brief description of asyncio
    • What are coroutines?
    • Scheduling tasks on the asyncio event loop
  • A hands-on walkthrough of SQLAlchemy’s asyncio extension
    • Setting up SQLAlchemy in async mode
    • Performing a query and inserting it into the database
    • Using ORMs in queries using asyncio