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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})
The keys and values can be of any type, except nil. The following focuses on non-numerical indexes. A table literal is written as { value, key = value, [index] = value, ["non id string"] = value }. For example:
add a new (,) pair to the collection, mapping the key to its new value. Any existing mapping is overwritten. The arguments to this operation are the key and the value. Remove or delete remove a (,) pair from the collection, unmapping a given key from its value. The argument to this operation is the key.
A lookup table, which contains, as keys, the case values and, as values, the part under the case statement. (In some languages, only actual data types are allowed as values in the lookup table. In other languages, it is also possible to assign functions as lookup table values, gaining the same flexibility as a real switch statement.
Example of a web form with name-value pairs. A name–value pair, also called an attribute–value pair, key–value pair, or field–value pair, is a fundamental data representation in computing systems and applications. Designers often desire an open-ended data structure that allows for future extension without modifying existing code or data.
Variables are prefixed with a dollar symbol and a type does not need to be specified in advance. Unlike function and class names, variable names are case-sensitive. Both double-quoted ("") and heredoc strings allow the ability to embed a variable's value into the string. [13]
LUTs differ from hash tables in a way that, to retrieve a value with key , a hash table would store the value in the slot () where is a hash function i.e. is used to compute the slot, while in the case of LUT, the value is stored in slot , thus directly addressable.
The term closure is often used as a synonym for anonymous function, though strictly, an anonymous function is a function literal without a name, while a closure is an instance of a function, a value, whose non-local variables have been bound either to values or to storage locations (depending on the language; see the lexical environment section below).