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In Haskell, the polymorphic function map :: (a -> b) -> [a] -> [b] is generalized to a polytypic function fmap :: Functor f => (a -> b) -> f a -> f b, which applies to any type belonging the Functor type class. The type constructor of lists [] can be defined as an instance of the Functor type class using the map function from the previous example:
However, since the code only uses methods common to the interface Map, a self-balancing binary tree could be used by calling the constructor of the TreeMap class (which implements the subinterface SortedMap), without changing the definition of the phoneBook variable, or the rest of the code, or using other underlying data structures that ...
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C++ programmers expect the latter on every major implementation of C++; it includes aggregate types (vectors, lists, maps, sets, queues, stacks, arrays, tuples), algorithms (find, for_each, binary_search, random_shuffle, etc.), input/output facilities (iostream, for reading from and writing to the console and files), filesystem library ...
A map, sometimes referred to as a dictionary, consists of a key/value pair. The key is used to order the sequence, and the value is somehow associated with that key. For example, a map might contain keys representing every unique word in a text and values representing the number of times that word appears in the text.
In computer science, a multimap (sometimes also multihash, multidict or multidictionary) is a generalization of a map or associative array abstract data type in which more than one value may be associated with and returned for a given key. Both map and multimap are particular cases of containers (for example, see C++ Standard Template Library ...
The code using such classes doesn't depend on the exact location the data is read from or is written to. For example, such code could write data to a file, a memory buffer or a web socket without a recompilation. The implementation classes inherit the abstraction classes and provide an implementation for concrete type of data source or sink.
Standard examples of data-driven languages are the text-processing languages sed and AWK, [1] and the document transformation language XSLT, where the data is a sequence of lines in an input stream – these are thus also known as line-oriented languages – and pattern matching is primarily done via regular expressions or line numbers.