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DICT is a dictionary network protocol created by the DICT Development Group [1] in 1997, described by RFC 2229. [2] Its goal is to surpass the Webster protocol to allow clients to access a variety of dictionaries via a uniform interface.
The dictionary problem is the classic problem of designing efficient data structures that implement associative arrays. [2] The two major solutions to the dictionary problem are hash tables and search trees .
[1] [2] In compiling a dictionary, a lexicographer decides whether the evidence of use is sufficient to justify an entry in the dictionary. This decision is not the same as determining whether the word exists. [citation needed] The green background means a given dictionary is the largest in a given language.
Python's built-in dict implements a hash table in the form of a type. [54] Ruby's built-in Hash uses the open addressing model from Ruby 2.4 onwards. [55] Rust programming language includes HashMap, HashSet as part of the Rust Standard Library. [56]
The #ifexist function selects one of two alternatives depending on whether a page exists at the specified title. {{#ifexist: page title | value if page exists | value if page doesn't exist}} The page can be in any namespace, so it can be an article or "content page", an image or other media file, a category, etc.
Introduced in Python 2.2 as an optional feature and finalized in version 2.3, generators are Python's mechanism for lazy evaluation of a function that would otherwise return a space-prohibitive or computationally intensive list. This is an example to lazily generate the prime numbers:
Python 2.0 was released in 2000. Python 3.0, released in 2008, was a major revision not completely backward-compatible with earlier versions. Python 2.7.18, released in 2020, was the last release of Python 2. [37] Python consistently ranks as one of the most popular programming languages, and has gained widespread use in the machine learning ...
In this example, we will consider a dictionary consisting of the following words: {a, ab, bab, bc, bca, c, caa}. The graph below is the Aho–Corasick data structure constructed from the specified dictionary, with each row in the table representing a node in the trie, with the column path indicating the (unique) sequence of characters from the root to the node.