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Python package for lexicon; Trie and DAWG implementation.

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aosingh/lexpy

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lexpyDownloadsPyPI version

Python 3.7Python 3.8Python 3.9Python 3.10Python 3.11Python 3.12

PyPy3.7PyPy3.8PyPy3.9

  • A lexicon is a data-structure which stores a set of words. The difference betweena dictionary and a lexicon is that in a lexicon there areno values associated with the words.

  • A lexicon is similar to a list or a set of words, but the internal representation is different and optimizedfor faster searches of words, prefixes and wildcard patterns.

  • Given a word, precisely, the search time is O(W) where W is the length of the word.

  • 2 important lexicon data-structures areTrie andDirected Acyclic Word Graph (DAWG).

Install

lexpy can be installed via Python Package Index(PyPI) usingpip. The only installation requirement is that you need Python 3.7 or higher.

pip install lexpy

Interface

Interface DescriptionTrieDAWG
Add a single wordadd('apple', count=2)add('apple', count=2)
Add multiple wordsadd_all(['advantage', 'courage'])add_all(['advantage', 'courage'])
Check if exists?in operatorin operator
Search using wildcard expressionsearch('a?b*', with_count=True)search('a?b*, with_count=True)
Search for prefix matchessearch_with_prefix('bar', with_count=True)search_with_prefix('bar')
Search for similar words within given edit distance. Here, the notion of edit distance is same as Levenshtein distancesearch_within_distance('apble', dist=1, with_count=True)search_within_distance('apble', dist=1, with_count=True)
Get the number of nodes in the automatonlen(trie)len(dawg)

Examples

Trie

Build from an input list, set, or tuple of words.

fromlexpyimportTrietrie=Trie()input_words= ['ampyx','abuzz','athie','athie','athie','amato','amato','aneto','aneto','aruba','arrow','agony','altai','alisa','acorn','abhor','aurum','albay','arbil','albin','almug','artha','algin','auric','sore','quilt','psychotic','eyes','cap','suit','tank','common','lonely','likeable''language','shock','look','pet','dime','small''dusty','accept','nasty','thrill','foot','steel','steel','steel','steel','abuzz']trie.add_all(input_words)# You can pass any sequence types or a file-like object hereprint(trie.get_word_count())>>>48

Build from a file or file path.

In the file, words should be newline separated.

fromlexpyimportTrie# Eithertrie=Trie()trie.add_all('/path/to/file.txt')# Orwithopen('/path/to/file.txt','r')asinfile:trie.add_all(infile)

Check if exists using thein operator

print('ampyx'intrie)>>>True

Prefix search

print(trie.search_with_prefix('ab'))>>> ['abhor','abuzz']
print(trie.search_with_prefix('ab',with_count=True))>>> [('abuzz',2), ('abhor',1)]

Wildcard search using? and*

  • ? = 0 or 1 occurrence of any character

  • * = 0 or more occurrence of any character

print(trie.search('a*o*'))>>> ['amato','abhor','aneto','arrow','agony','acorn']print(trie.search('a*o*',with_count=True))>>> [('amato',2), ('abhor',1), ('aneto',2), ('arrow',1), ('agony',1), ('acorn',1)]print(trie.search('su?t'))>>> ['suit']print(trie.search('su?t',with_count=True))>>> [('suit',1)]

Search for similar words using the notion of Levenshtein distance

print(trie.search_within_distance('arie',dist=2))>>> ['athie','arbil','auric']print(trie.search_within_distance('arie',dist=2,with_count=True))>>> [('athie',3), ('arbil',1), ('auric',1)]

Increment word count

  • You can either add a new word or increment the counter for an existing word.
trie.add('athie',count=1000)print(trie.search_within_distance('arie',dist=2,with_count=True))>>> [('athie',1003), ('arbil',1), ('auric',1)]

Directed Acyclic Word Graph (DAWG)

  • DAWG supports the same set of operations as a Trie. The difference is the number of nodes in a DAWG is alwaysless than or equal to the number of nodes in Trie.

  • They both are Deterministic Finite State Automata. However, DAWG is a minimized version of the Trie DFA.

  • In a Trie, prefix redundancy is removed. In a DAWG, both prefix and suffix redundancies are removed.

  • In the current implementation of DAWG, the insertion order of the words should bealphabetical.

  • The implementation idea of DAWG is borrowed fromhttp://stevehanov.ca/blog/?id=115

fromlexpyimportTrie,DAWGtrie=Trie()trie.add_all(['advantageous','courageous'])dawg=DAWG()dawg.add_all(['advantageous','courageous'])len(trie)# Number of Nodes in Trie23dawg.reduce()# Perform DFA minimization. Call this every time a chunk of words are uploaded in DAWG.len(dawg)# Number of nodes in DAWG21

DAWG

The APIs are exactly same as the Trie APIs

Build a DAWG

fromlexpyimportDAWGdawg=DAWG()input_words= ['ampyx','abuzz','athie','athie','athie','amato','amato','aneto','aneto','aruba','arrow','agony','altai','alisa','acorn','abhor','aurum','albay','arbil','albin','almug','artha','algin','auric','sore','quilt','psychotic','eyes','cap','suit','tank','common','lonely','likeable''language','shock','look','pet','dime','small''dusty','accept','nasty','thrill','foot','steel','steel','steel','steel','abuzz']dawg.add_all(input_words)dawg.reduce()dawg.get_word_count()>>>48

Check if exists using thein operator

print('ampyx'indawg)>>>True

Prefix search

print(dawg.search_with_prefix('ab'))>>> ['abhor','abuzz']
print(dawg.search_with_prefix('ab',with_count=True))>>> [('abuzz',2), ('abhor',1)]

Wildcard search using? and*

? = 0 or 1 occurance of any character

* = 0 or more occurance of any character

print(dawg.search('a*o*'))>>> ['amato','abhor','aneto','arrow','agony','acorn']print(dawg.search('a*o*',with_count=True))>>> [('amato',2), ('abhor',1), ('aneto',2), ('arrow',1), ('agony',1), ('acorn',1)]print(dawg.search('su?t'))>>> ['suit']print(dawg.search('su?t',with_count=True))>>> [('suit',1)]

Search for similar words using the notion of Levenshtein distance

print(dawg.search_within_distance('arie',dist=2))>>> ['athie','arbil','auric']print(dawg.search_within_distance('arie',dist=2,with_count=True))>>> [('athie',3), ('arbil',1), ('auric',1)]

Alphabetical order insertion

If you insert a word which is lexicographically out-of-order,ValueError will be raised.

dawg.add('athie',count=1000)

ValueError

ValueError: Words should be inserted in Alphabetical order. <Previous word - thrill>, <Current word - athie>

Increment the word count

  • You can either add an alphabetically greater word with a specific count or increment the count of the previous added word.
dawg.add_all(['thrill']*20000)# or dawg.add('thrill', count=20000)print(dawg.search('thrill',with_count=True))>> [('thrill',20001)]

Special Characters

Special characters, except? and*, are matched literally.

fromlexpyimportTriet=Trie()t.add('a©')
t.search('a©')>> ['a©']
t.search('a?')>> ['a©']
t.search('?©')>> ['a©']

Trie vs DAWG

Number of nodes comparison

Build time comparison

Future Work

These are some ideas which I would love to work on next in that order. Pull requests or discussions are invited.

  • Merge trie and DAWG features in one data structure
    • Support all functionalities and still be as compressed as possible.
  • Serialization / Deserialization
    • Pickle is definitely an option.
  • Server (TCP or HTTP) to serve queries over the network.

Fun Facts

  1. The 45-letter word pneumonoultramicroscopicsilicovolcanoconiosis is the longest English word that appears in a major dictionary.So for all english words, the search time is bounded by O(45).
  2. The longest technical word(not in dictionary) is the name of a protein called astitin. It has 189,819letters and it is disputed whether it is a word.

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