Type annotation for A strongly and dynamically typed Python.

Python is a dynamically-typed language. That means that variable types are dynamically set at run-time, upon assignment of a value to a variable.

For example, in

def fn(a, b):
    return a + b        

The types of?a?and?b?are not known at build-time, only when?a?and?b?are assigned values at run-time.

Hence, calling

fn("a", 1)        

somewhere in your code will not raise an exception until the code is actually executed and the function is called:

>>> fn("a", 1)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
TypeError: can only concatenate str (not "int") to str        

In Python 3, type annotations do not change this. Python is still a dynamically-typed language. Type annotations serve the following purpose:

• Code documentation: thanks to them, a developer reading type-annotated code (his own or someone else’s) will know exactly what type each variables is supposed to be. This helps reduce bugs and exceptions and accelerate the development cycle.
• Linting and validation: code editors and continuous integration (CI) pipelines can be configured to automatically validate type-annotated code at build-time and catch bugs before they make it to production.