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For example, one could define a dictionary having a string "toast" mapped to the integer 42 or vice versa. The keys in a dictionary must be of an immutable Python type, such as an integer or a string, because under the hood they are implemented via a hash function. This makes for much faster lookup times, but requires keys not change.
This creational pattern [1] is frequently used for numbers and strings in different programming languages. In many object-oriented languages such as Python, even primitive types such as integer numbers are objects. To avoid the overhead of constructing a large number of integer objects, these objects get reused through interning. [2]
In computer science, an integer literal is a kind of literal for an integer whose value is directly represented in source code.For example, in the assignment statement x = 1, the string 1 is an integer literal indicating the value 1, while in the statement x = 0x10 the string 0x10 is an integer literal indicating the value 16, which is represented by 10 in hexadecimal (indicated by the 0x prefix).
There are two types of divisions in Python: floor division (or integer division) // and floating-point / division. [103] Python uses the ** operator for exponentiation. Python uses the + operator for string concatenation. Python uses the * operator for duplicating a string a specified number of times.
String interning also reduces memory usage if there are many instances of the same string value; for instance, it is read from a network or from storage. Such strings may include magic numbers or network protocol information. For example, XML parsers may intern names of tags and attributes to save memory.
COBOL uses the STRING statement to concatenate string variables. MATLAB and Octave use the syntax "[x y]" to concatenate x and y. Visual Basic and Visual Basic .NET can also use the "+" sign but at the risk of ambiguity if a string representing a number and a number are together. Microsoft Excel allows both "&" and the function "=CONCATENATE(X,Y)".
In Python, if a name is intended to be "private", it is prefixed by one or two underscores. Private variables are enforced in Python only by convention. Names can also be suffixed with an underscore to prevent conflict with Python keywords. Prefixing with double underscores changes behaviour in classes with regard to name mangling.
Python's runtime does not restrict access to such attributes, the mangling only prevents name collisions if a derived class defines an attribute with the same name. On encountering name mangled attributes, Python transforms these names by prepending a single underscore and the name of the enclosing class, for example: >>>