
Building Data Science Applications with FastAPI
By :

In the first section of this chapter, we said that Python was a dynamically typed language: the interpreter doesn't check types at compile time but rather at runtime. This makes the language a bit more flexible and the developer a bit more efficient. However, if you are experienced with that kind of language, you probably know that it's easy to produce errors and bugs in this context: forgetting arguments and type mismatch.
This is why Python introduced type hinting starting with version 3.5. The goal is to provide a syntax to annotate the source code with type annotations: each variable, function, and class can be annotated to give indications about the types they expect. This doesn't mean that Python becomes a statically typed language. Those annotations remain completely optional and are ignored by the interpreter. However, those annotations can be used by static-type checkers, which will check whether your code is valid...