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binary real values are represented in a binary format that includes the mantissa, the base (2, 8, or 16), and the exponent; the special values NaN, -INF, +INF , and negative zero are also supported Multiple valid types ( VisibleString, PrintableString, GeneralString, UniversalString, UTF8String )
A fixed-point data type uses the same, implied, denominator for all numbers. The denominator is usually a power of two.For example, in a hypothetical fixed-point system that uses the denominator 65,536 (2 16), the hexadecimal number 0x12345678 (0x1234.5678 with sixteen fractional bits to the right of the assumed radix point) means 0x12345678/65536 or 305419896/65536, 4660 + the fractional ...
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 ...
For function that manipulate strings, modern object-oriented languages, like C# and Java have immutable strings and return a copy (in newly allocated dynamic memory), while others, like C manipulate the original string unless the programmer copies data to a new string.
The nebulous JSON 'number' type is strictly defined in Ion to be one of int: Signed integers of arbitrary size; float: 64-bit IEEE binary-encoded floating point numbers; decimal: Decimal-encoded real numbers of arbitrary precision; Ion adds these types: timestamp: Date/time/time zone moments of arbitrary precision
Transformation languages serve the purpose of transforming (translating) source code specified in a certain formal language into a defined destination format code. It is most commonly used in intermediate components of more complex super-systems in order to adopt internal results for input into a succeeding processing routine.
Introduced in Python 2.2 as an optional feature and finalized in version 2.3, generators are Python's mechanism for lazy evaluation of a function that would otherwise return a space-prohibitive or computationally intensive list. This is an example to lazily generate the prime numbers:
The XML format supports non-ASCII characters and storing NSValue objects (which, unlike GNUstep's ASCII property list format, Apple's ASCII property list format does not support). [10] Since XML files, however, are not the most space-efficient means of storage, Mac OS X 10.2 introduced a new format where property list files are stored as binary ...