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So, PHP can have non-consecutively numerically indexed arrays. The keys have to be of integer (floating point numbers are truncated to integer) or string type, while values can be of arbitrary types, including other arrays and objects. The arrays are heterogeneous: a single array can have keys of different types.
An array data structure can be mathematically modeled as an abstract data structure (an abstract array) with two operations get(A, I): the data stored in the element of the array A whose indices are the integer tuple I. set(A, I, V): the array that results by setting the value of that element to V. These operations are required to satisfy the ...
In Miranda, this right-fold, from Hughes (1989:5-6), has the same semantics (by example) as the Scheme implementation above, for two arguments. append a b = reduce cons b a Where reduce is Miranda's name for fold, and cons constructs a list from two values or lists. For example,
JSON (JavaScript Object Notation, pronounced / ˈ dʒ eɪ s ən / or / ˈ dʒ eɪ ˌ s ɒ n /) is an open standard file format and data interchange format that uses human-readable text to store and transmit data objects consisting of name–value pairs and arrays (or other serializable values).
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 ...
JSON streaming comprises communications protocols to delimit JSON objects built upon lower-level stream-oriented protocols (such as TCP), that ensures individual JSON objects are recognized, when the server and clients use the same one (e.g. implicitly coded in). This is necessary as JSON is a non-concatenative protocol (the concatenation of ...
Flow diagram. In computing, serialization (or serialisation, also referred to as pickling in Python) is the process of translating a data structure or object state into a format that can be stored (e.g. files in secondary storage devices, data buffers in primary storage devices) or transmitted (e.g. data streams over computer networks) and reconstructed later (possibly in a different computer ...
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]