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Python sets are very much like mathematical sets, and support operations like set intersection and union. Python also features a frozenset class for immutable sets, see Collection types. Dictionaries (class dict) are mutable mappings tying keys and corresponding values. Python has special syntax to create dictionaries ({key: value})
A singly-linked list structure, implementing a list with three integer elements. The term list is also used for several concrete data structures that can be used to implement abstract lists, especially linked lists and arrays. In some contexts, such as in Lisp programming, the term list may refer specifically to a linked list rather than an array.
Python has built-in set and frozenset types since 2.4, and since Python 3.0 and 2.7, supports non-empty set literals using a curly-bracket syntax, e.g.: {x, y, z}; empty sets must be created using set(), because Python uses {} to represent the empty dictionary.
A more involved example is the Boom hierarchy of the binary tree, list, bag and set abstract data types. [10] All these data types can be declared by three operations: null , which constructs the empty container, single , which constructs a container from a single element and append , which combines two containers of the same type.
In this example of a simple class representing a student with only the name stored, one can see the variable name is private, i.e. only visible from the Student class, and the "setter" and "getter" are public, namely the "getName()" and "setName(name)" methods.
Here, the list [0..] represents , x^2>3 represents the predicate, and 2*x represents the output expression.. List comprehensions give results in a defined order (unlike the members of sets); and list comprehensions may generate the members of a list in order, rather than produce the entirety of the list thus allowing, for example, the previous Haskell definition of the members of an infinite list.
In Python, the metaclass - type - controls these details of Car's behavior. They can be overridden by using a different metaclass instead of type. The above example contains some redundant code to do with the four attributes make, model, year, and color. It is possible to eliminate some of this redundancy using a custom metaclass.
A forest f consists of a list of trees, while a tree t consists of a pair of a value v and a forest f (its children). This definition is elegant and easy to work with abstractly (such as when proving theorems about properties of trees), as it expresses a tree in simple terms: a list of one type, and a pair of two types.