Boost Your Python Skills with Type Annotations: A Beginner's Guide
A step-by-step guide to using type annotations in Python
We have all been using Python without specifying types of variables. For example, we would set a variable as a=10 and not int a =10. In more technical jargon, we call this as Python being a dynamically typed language, meaning that the variable type is determined at runtime based on the value it is assigned. So, if a variable is assigned a value of 10, Python will interpret it as an integer, while if a variable is assigned a value of 10.5 Python will consider it as a float, and so on.
For most purposes, it works great and allows for great flexibility and simplicity in writing Python programs. But, it can make it challenging to understand the behavior of a program, especially when dealing with complex or large codebases.
To address this issue, Python introduced type annotations in version 3.5, which allows developers to specify the type of a variable, function, or class in the source code.
In this blog post, I will take a closer look at type annotations in Python and explain how they are used to improve the readability and reliability of your Python programs.
