Ngram-based indexing of strings into a binary file

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  • License: MIT License (MIT)
  • Author: Remi Rampin
  • Tags ngram, indexing, full-text, text-search, full-text-search
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Project description

This library allows indexing many strings into a file, and then efficiently fuzzy-matching strings against what’s been indexed.

Currently, the structure is built from the Rust program in memory before being written to the file, so that phase uses a lot of RAM. You cannot create/change an index from Python.

String search is done from the file and requires little memory.

The index is a trie structure in which trigrams can be looked up; results for each trigrams of the input are matched and sorted to get the most similar strings.

Example:

>>> from ngram_search import Ngrams
>>> ngrams = Ngrams(path)
>>> ngrams.search("ham", 0.24)
[(0, 1.0), (2, 0.25)]
>>> ngrams.search("spa", 0.2)
[(0, 0.375)]

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  • License: MIT License (MIT)
  • Author: Remi Rampin
  • Tags ngram, indexing, full-text, text-search, full-text-search
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