Topics

• Flexible, Maintainable Python: A Gentle Intro to Dependency Injection
  By: Paul Zuradzki
  Experience Level: Intermediate
  Length: 30 Minutes
  Description:

  Dependency injection (DI) isn’t just for enterprise Java. DI is a simple, versatile design technique that can help you write less coupled, more modular, and more testable code. By the end of this talk, you'll be able to:

  • Spot implicit dependencies in your code

  • Understand what dependency injection is and why it matters

  • Apply simple DI in your Python code using functions or parameters

  • Know when not to use it

   

  Outline

  • Motivation: Good Design and Why DI

  • Recognizing Dependencies

  • What is Dependency Injection (DI)

  • Dependency Injection (DI) vs Dependency Inversion Principle (DIP)

  • Practical Examples

  • Styles of Dependency Injection

  • DI for Testing

  • DI for Decoupling

  • DI for Flexibility

  • Composition Root: Where to Wire Dependencies

  • When Not to Use DI

  • Patterns that Use DI

  • Strategy

  • Factory

  • Service, Repository, and Domain

  • DI and Python Idioms

  • DI Containers and Frameworks for Large or Complex Projects

   

• To pickle or not to pickle
  By: Joshua Herman
  Experience Level: Intermediate
  Length: 45 Minutes
  Description:

  We will go over the implications of how deciding a serialization format (also known as a data interchange format) can have on your performance, security and readability. We will study JSON, pickle and safetensors and understand the decision making and the specifications of those formats have and why you should choose one over the other. We will also show the implications of how others have used and when these formats while are a good idea before start to change in such a manner where you need to migrate to a format for the previous reasons mentioned (performance, security and readability). Also, at the end there will be a security demo derived from a blogpost.