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Python supports most object oriented programming (OOP) techniques. It allows polymorphism, not only within a class hierarchy but also by duck typing. Any object can be used for any type, and it will work so long as it has the proper methods and attributes. And everything in Python is an object, including classes, functions, numbers and modules.
This class allows assignments between any two objects. A copy of the key object is made before it is inserted into NSMutableDictionary, therefore the keys must conform to the NSCopying protocol. When being inserted to a dictionary, the value object receives a retain message to increase its reference count.
In computer programming, lazy initialization is the tactic of delaying the creation of an object, the calculation of a value, or some other expensive process until the first time it is needed.
Circular references can appear in computer programming when one piece of code requires the result from another, but that code needs the result from the first. For example, the two functions, posn and plus1 in the following Python program comprise a circular reference: [further explanation needed]
In computer science, an associative array, map, symbol table, or dictionary is an abstract data type that stores a collection of (key, value) pairs, such that each possible key appears at most once in the collection. In mathematical terms, an associative array is a function with finite domain. [1] It supports 'lookup', 'remove', and 'insert ...
An internal iterator is a higher order function (often taking anonymous functions) that traverses a collection while applying a function to each element. For example, Python's map function applies a caller-defined function to each element:
A lazy copy is an implementation of a deep copy. When initially copying an object, a (fast) shallow copy is used. A counter is also used to track how many objects share the data. When the program wants to modify an object, it can determine if the data is shared (by examining the counter) and can do a deep copy if needed.
This is a generalization of single-dispatch polymorphism where a function or method call is dynamically dispatched based on the derived type of the object on which the method has been called. Multiple dispatch routes the dynamic dispatch to the implementing function or method using the combined characteristics of one or more arguments.