Type annotations have had a convoluted history with Python - but have recently experienced a Renaissance. We'll cover how to effectively use Python typing.
Type annotations - also known as type signatures - are used to indicate the datatypes of variables and input/outputs of functions and methods.
In many languages, datatypes are explicitly stated. In these languages, if you don't declare your datatype - the code will not run.
Type annotations have a long and convoluted history with Python, going all the way back to the first release of Python 3 with the initial implementation of function annotations.
Type annotations in Python are not make-or-break like in other languages (like C). They're optional chunks of syntax that we can add to make our code more explicit.
Erroneous type annotations will do nothing more than highlight the incorrect annotation in our code editor - no errors are ever raised due to annotations.
So, if type annotations are not enforced, why use them?
Well, as we touched upon already - declaring types makes our code more explicit, and if done well, easier to read - both for ourselves and others.
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In the programming world, Data types play an important role. Each Variable is stored in different data types and responsible for various functions. Python had two different objects, and They are mutable and immutable objects.
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