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In computer programming, a null-terminated string is a character string stored as an array containing the characters and terminated with a null character (a character with an internal value of zero, called "NUL" in this article, not same as the glyph zero).
Numeric literals in Python are of the normal sort, e.g. 0, -1, 3.4, 3.5e-8. Python has arbitrary-length integers and automatically increases their storage size as necessary. Prior to Python 3, there were two kinds of integral numbers: traditional fixed size integers and "long" integers of arbitrary size.
In computer character encodings, there is a normal general-purpose space (Unicode character U+0020) whose width will vary according to the design of the typeface. Typical values range from 1/5 em to 1/3 em (in digital typography an em is equal to the nominal size of the font, so for a 10-point font the space will probably be between 2 and 3.3 ...
The empty string is a syntactically valid representation of zero in positional notation (in any base), which does not contain leading zeros.Since the empty string does not have a standard visual representation outside of formal language theory, the number zero is traditionally represented by a single decimal digit 0 instead.
A second common application of non-breaking spaces is in plain text file formats such as SGML, HTML, TeX and LaTeX, whose rendering engines are programmed to treat sequences of whitespace characters (space, newline, tab, form feed, etc.) as if they were a single character (but this behavior can be overridden).
Whitespace defines a command as a sequences of whitespace characters. For example, [Tab][Space][Space][Space] performs arithmetic addition of the top two elements on the stack. A command is written as an instruction modification parameter (IMP) followed by an operation and then any parameters. [1] IMP sequences include:
Objects, when deposited in an Object Space are passive, i.e., their methods cannot be invoked while the objects are in the Object Space. Instead, the accessing process must retrieve it from the Object Space into its local memory, use the service provided by the object, update the state of the object and place it back into the Object Space.
In linguistics, the Levenshtein distance is used as a metric to quantify the linguistic distance, or how different two languages are from one another. [3] It is related to mutual intelligibility : the higher the linguistic distance, the lower the mutual intelligibility, and the lower the linguistic distance, the higher the mutual intelligibility.