Many of Python syntax is sugar for underlying methods especially in data access.
It means that if you define a _add_ method for one of your classes you will make all sorts of things happen when you include instances of them together. It is similar as calling int._add_(4, 4). The expression 4 + 4 is syntactic sugar for calling the _add_ method of the integer type. If it walks like a duck and quacks like a duck, it must be a duck.
In Python we have to permit the object to describe what it to be included. Duck typing is type safety checks for complex types.
Attempt to include different types of objects together and the compiler will tell you that you’re not permitted. Although most languages will let you a chance to add an integer to a floating point number – resulting in a floating point number. After all, there is a reason that so many newer languages allow this functionality. Alternatively, duck typing has plenty of positives. With duck typing, errors are discovered during runtime, which makes it harder to go back and fix past mistakes. A few types of object can be included – typically only to objects of the similar type. find bugs faster and making them much easier to fix.
Example, in a statically typed language we have a concept of including.
Abstract base classes complement duck-typing by providing a way to define interfaces.
#DUCK TYPING CODE#
There is another idea in typing lark which is a characteristics of dynamic languages. See 2to3 - Automated Python 2 to 3 code translation.
Parts of the standard library in python suppose to use I/O like objects with read or write methods, yet you will pass anything that executes these, without having to inherit from anything.
Duck typing is the “type” of the object is a matter of concern only at runtime and you don’t require mentioning the type of the object before you execute any kind of operation on that object.