- Python is both a strongly typed and a dynamically typed language.
- Strong typing means that variables do have a type and that the type matters when performing operations on a variable. Dynamic typing means that the type of the variable is determined only during runtime.
- Due to strong typing, types need to be compatible with respect to the operand when performing operations. For example Python allows one to add an integer and a floating point number, but adding an integer to a string produces error.
- Python is a dynamically typed language. This means that the Python interpreter does type checking only as code runs, and the type of a variable is allowed to change over its lifetime.
Obs: just for comparison, JavaScript is dynamically and weakly typed
Python Object-oriented programming
- Everything in Python is an object
- Every object is defined by being an instance of at least one class. What's the distinction between class and type? The class statement lets us define new types
- When we check the type of a variable with
type(), we see the type of the object the variable currently references - While the hints consume some storage, they have no runtime impact. Python politely ignores these hints; this means they're optional. People reading your code, however, will be more than delighted to see them. They are a great way to inform the reader of your intent. You can omit them while you're learning, but you'll love them when you go back to expand something you wrote earlier
- The one difference, syntactically, between methods of classes and functions outside classes is
that methods have one required argument. This argument is conventionally named
self - All Python classes are subclasses of the special built-in class named object