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Some collections maintain a linear ordering of items – with access to one or both ends. The data structure implementing such a collection need not be linear. For example, a priority queue is often implemented as a heap, which is a kind of tree. Notable linear collections include: list; stack; queue; priority queue; double-ended queue
Considered a sequential collection, a stack has one end which is the only position at which the push and pop operations may occur, the top of the stack, and is fixed at the other end, the bottom. A stack may be implemented as, for example, a singly linked list with a pointer to the top element. A stack may be implemented to have a bounded capacity.
This is a list of well-known data structures. For a wider list of terms, see list of terms relating to algorithms and data structures. For a comparison of running times for a subset of this list see comparison of data structures.
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})
This behavior can be axiomatized in various ways. For example, a common VDM (Vienna Development Method) description of a stack defines top (peek) and remove as atomic, where top returns the top value (without modifying the stack), and remove modifies the stack (without returning a value). [1] In this case pop is defined in terms of top and remove.
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In computer science, a container is a class or a data structure [1] [2] whose instances are collections of other objects. In other words, they store objects in an organized way that follows specific access rules. The size of the container depends on the number of objects (elements) it contains.
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