Gradual Typing in Python
Dynamically typed languages let you write a larger variety of programs than those with static types. Unfortunately, a lot of those are invalid. From version 3.5 onwards, Python has had a standardised system for adding types to your Python programs so you can increase your confidence in your code.
By gradually adding types to your Python programs you can get the best of both worlds - add static types where they're useful, but retain the flexibility of dynamic typing where you want it. The talk covers a little of the history of typechecking in Python, some short demos, and a brief report on adding types to an existing project.
By gradually adding types to your Python programs you can get the best of both worlds - add static types where they're useful, but retain the flexibility of dynamic typing where you want it. The talk covers a little of the history of typechecking in Python, some short demos, and a brief report on adding types to an existing project.
Presented by
Taylor Manderson
Taylor is currently studying Software Engineering and Mathematics at the University of Queensland, while working in development and devops roles at Polymathian, an industrial mathematics company. As a Pythonista by day and a Haskeller by night, she loves any way she can put maths into his software - by types, functional programming, or just writing mathematical code.
