![Cover logo](https://raw.githubusercontent.com/InstantDomain/instant-segment/main/cover.svg) # Instant Segment: fast English word segmentation in Rust [![Documentation](https://docs.rs/instant-segment/badge.svg)](https://docs.rs/instant-segment/) [![Crates.io](https://img.shields.io/crates/v/instant-segment.svg)](https://crates.io/crates/instant-segment) [![PyPI](https://img.shields.io/pypi/v/instant-segment)](https://pypi.org/project/instant-segment/) [![Build status](https://github.com/InstantDomainSearch/instant-segment/workflows/CI/badge.svg)](https://github.com/InstantDomainSearch/instant-segment/actions?query=workflow%3ACI) [![License: Apache 2.0](https://img.shields.io/badge/License-Apache%202.0-blue.svg)](LICENSE-APACHE) Instant Segment is a fast Apache-2.0 library for English word segmentation. It is based on the Python [wordsegment][python] project written by Grant Jenks, which is in turn based on code from Peter Norvig's chapter [Natural Language Corpus Data][chapter] from the book [Beautiful Data][book] (Segaran and Hammerbacher, 2009). For the microbenchmark included in this repository, Instant Segment is ~100x faster than the Python implementation. The API was carefully constructed so that multiple segmentations can share the underlying state to allow parallel usage. ## How it works Instant Segment works by segmenting a string into words by selecting the splits with the highest probability given a corpus of words and their occurrences. For instance, provided that `choose` and `spain` occur more frequently than `chooses` and `pain`, and that the pair `choose spain` occurs more frequently than `chooses pain`, Instant Segment can help identify the domain `choosespain.com` as `ChooseSpain.com` which more likely matches user intent. Read about [how we built and improved][story] Instant Segment for use in production at [Instant Domain Search](https://instantdomainsearch.com/) to help our users find relevant domains they can register. ## Using the library ### Python **(>= 3.9)** ```sh pip install instant-segment ``` ### Rust ```toml [dependencies] instant-segment = "0.8.1" ``` ### Examples The following examples expect `unigrams` and `bigrams` to exist. See the examples ([Rust](./instant-segment/examples/contrived.rs), [Python](./instant-segment-py/examples/contrived.py)) to see how to construct these objects. ```python import instant_segment segmenter = instant_segment.Segmenter(unigrams, bigrams) search = instant_segment.Search() segmenter.segment("instantdomainsearch", search) print([word for word in search]) --> ['instant', 'domain', 'search'] ``` ```rust use instant_segment::{Search, Segmenter}; use std::collections::HashMap; let segmenter = Segmenter::from_maps(unigrams, bigrams); let mut search = Search::default(); let words = segmenter .segment("instantdomainsearch", &mut search) .unwrap(); println!("{:?}", words.collect::>()) --> ["instant", "domain", "search"] ``` Check out the tests for more thorough examples: [Rust](./instant-segment/src/test_cases.rs), [Python](./instant-segment-py/test/test.py) ## Testing To run the tests run the following: ``` cargo t -p instant-segment --all-features ``` You can also test the Python bindings with: ``` make test-python ``` [python]: https://github.com/grantjenks/python-wordsegment [chapter]: http://norvig.com/ngrams/ [story]: https://instantdomainsearch.com/engineering/instant-word-segmentation-with-rust [book]: http://oreilly.com/catalog/9780596157111/ [distributed]: https://catalog.ldc.upenn.edu/LDC2006T13 [issues]: https://github.com/InstantDomainSearch/instant-segment/issues