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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 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 ...
The array, set and dictionary binary types are made up of pointers - the objref and keyref entries - that index into an object table in the file. This means that binary plists can capture the fact that - for example - a separate array and dictionary serialized into a file both have the same data element stored in them.
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.
It can convert a wide range of complex data structures, including dict, array, numpy ndarray, into JData representations and export the data as JSON or UBJSON files. The BJData Python module, pybj, [4] enabling reading/writing BJData/UBJSON files, is also available on PyPI, Debian/Ubuntu and GitHub.
Python dictionaries (a form of associative array) can also be directly iterated over, when the dictionary keys are returned; or the items() method of a dictionary can be iterated over where it yields corresponding key,value pairs as a tuple:
Construct is a Python library for the construction and deconstruction of data structures in a declarative fashion. In this context, construction, or building, refers to the process of converting (serializing) a programmatic object into a binary representation.
To avoid installing the large SciPy package just to get an array object, this new package was separated and called NumPy. Support for Python 3 was added in 2011 with NumPy version 1.5.0. [15] In 2011, PyPy started development on an implementation of the NumPy API for PyPy. [16] As of 2023, it is not yet fully compatible with NumPy. [17]