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In object-oriented languages, string functions are often implemented as properties and methods of string objects. In functional and list-based languages a string is represented as a list (of character codes), therefore all list-manipulation procedures could be considered string functions.
Note that Python allows negative list indices. The index -1 represents the last element, -2 the penultimate element, etc. Python also allows a step property by appending an extra colon and a value. For example:
Single document window splitting: window can be split to simultaneously view different areas of a file. MDI: Overlappable windows: each opened document gets its own fully movable window inside the editor environment. MDI: Tabbed document interface: multiple documents can be viewed as tabs in a single window.
In Raku, a sister language to Perl, for must be used to traverse elements of a list (foreach is not allowed). The expression which denotes the collection to loop over is evaluated in list-context, but not flattened by default, and each item of the resulting list is, in turn, aliased to the loop variable(s). List literal example:
Beyond syntactic requirements of C/C++, implicit concatenation is a form of syntactic sugar, making it simpler to split string literals across several lines, avoiding the need for line continuation (via backslashes) and allowing one to add comments to parts of strings. For example, in Python, one can comment a regular expression in this way: [21]
''Title of list:'' example 1, example 2, example 3 Title of list: example 1, example 2, example 3 This style requires less space on the page, and is preferred if there are only a few entries in the list, it can be read easily, and a direct edit point is not required. The list items should start with a lowercase letter unless they are proper nouns.
A training data set is a data set of examples used during the learning process and is used to fit the parameters (e.g., weights) of, for example, a classifier. [9] [10]For classification tasks, a supervised learning algorithm looks at the training data set to determine, or learn, the optimal combinations of variables that will generate a good predictive model. [11]
The Ruby programming language interpreter offers an eval function similar to Python or Perl, and also allows a scope, or binding, to be specified. Aside from specifying a function's binding, eval may also be used to evaluate an expression within a specific class definition binding or object instance binding, allowing classes to be extended with ...