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The decorator pattern is a design pattern used in statically-typed object-oriented programming languages to allow functionality to be added to objects at run time; Python decorators add functionality to functions and methods at definition time, and thus are a higher-level construct than decorator-pattern classes.
Python is a high-level, general-purpose programming language. Its design philosophy emphasizes code readability with the use of significant indentation. [33] Python is dynamically type-checked and garbage-collected. It supports multiple programming paradigms, including structured (particularly procedural), object-oriented and functional ...
An n-tuple can be formally defined as the image of a function that has the set of the n first natural numbers as its domain. Tuples may be also defined from ordered pairs by a recurrence starting from ordered pairs ; indeed, an n -tuple can be identified with the ordered pair of its ( n − 1) first elements and its n th element.
A function call using named parameters differs from a regular function call in that the arguments are passed by associating each one with a parameter name, instead of providing an ordered list of arguments. For example, consider this Java or C# method call that doesn't use named parameters:
While a variable or function may be declared many times, it is typically defined once (in C++, this is known as the One Definition Rule or ODR). Dynamic languages such as JavaScript or Python generally allow functions to be redefined, that is, re-bound; a function is a variable much like any other, with a name and a value (the definition).
In Python, auxiliary variables in generator expressions and list comprehensions (in Python 3) have expression scope. In C, variable names in a function prototype have expression scope, known in this context as function protocol scope. As the variable names in the prototype are not referred to (they may be different in the actual definition ...
The standard type hierarchy of Python 3. In computer science and computer programming, a data type (or simply type) is a collection or grouping of data values, usually specified by a set of possible values, a set of allowed operations on these values, and/or a representation of these values as machine types. [1]
In object-oriented (OO) and functional programming, an immutable object (unchangeable [1] object) is an object whose state cannot be modified after it is created. [2] This is in contrast to a mutable object (changeable object), which can be modified after it is created. [3]