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Implementation of edit distance calculation.

Project description

Fast calculation of Edit Distance (ED)

A implementation of edit distance with improved runtime. Implemented using C and cython.

Highlight:

This edit distance calculation is significantly faster than most of existing python package. It enables a max edit distance search, specifically, if you have a query sequence and wanted to find the most similar item in a long list, you could set a maximum edit distance and enable a fast search.

Installation:

Install using pip:

pip install fast-edit-distance

or build from source

git clone https://github.com/youyupei/fast_edit_distance.git
cd fast_edit_distance
python3 setup.py build
python3 setup.py install --user

Usage:

from fast_edit_distance import edit_distance

# example
edit_distance(string1, string2, max_ed=5)

Compare with Levenshtein.distance

The fast_edit_distance.edit_distance has the same function as Levenshtein.distance with significantly improved runtime. Especially when people need to identied pair of strings whose ED are smaller than a number (set max_ed in fast_edit_distance.edit_distance). Here is the runtime test with some random sequence (Run the test/test.py to reproduce this comparison):

Runtime test no max ed cutoff(1_000_000 iteration):
Levenshtein.distance: 46.49s
fast_edit_distance.edit_distance: 12.75s

Runtime test with max ed cutoff 1 (1_000_000 iteration):
Levenshtein.distance: 46.45s
fast_edit_distance.edit_distance: 0.50s

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