Python bindings for the yake-rust crate.
Project description
yake-rust
This package contains the yake-rust crate with python bindings.
Yake is a language agnostic statistical keyword extractor weighing several factors such as acronyms, position in paragraph, capitalization, how many sentences the keyword appears in, stopwords, punctuation and more. For details, see these papers: brief, extended.
This crate is ported and is as close as possible in results to the reference implementation. The input text is split into sentences and tokens via the segtok crate.
By implementing the keyword extraction in rust instead of native python, yake-rust has the advantage of
- speed - in tests, it typically outperforms the reference implementation.
- concurrency - yake_rust releases the GIL so that multiple threads can perform keyword extraction concurrently on multicore systems.
Furthermore, yake-rust is fully typed.
Installation
For example, to install it with pip:
pip install yake-rust
Usage
Create an instance of yake_rust.Yake with the desired configuration
and call its get_n_best method to get the n best keywords from a text.
(Note that n is a keyword-only argument for the purpose of clarity.)
>>>from yake_rust import Yake
>>>yake = Yake(language="en")
>>>yake.get_n_best("News from the inauguration!", n=1)
[('inauguration', 0.15831692877998726)]
The yake_rust.Yake constructor requires one (and only one) of two mandatory keyword-only arguments,
language- ISO 639 two-letter abbreviation for a language, e.g.,language="en"for English.stopwords-set[str]of custom stopwords to use. Iflanguageis used, a default set of stopwords for that language will be used.
In addition, it has the following keyword-only arguments for customizability:
ngrams-intspecifying the maximum number of ngrams per keyword.punctuation-set[str]with punctuation symbols.window_size-intdetermining the size of the "window" around a word when considering how it appears in context.remove_duplicates-boolsaying whether to remove keywords which are considered duplicates of other keywords, as determined by the Levenshtein distance and the deduplication threshold.deduplication threshold-floatwhich determines the threshold of considering two keywords to be duplicates of each other. Does nothing ifremove_duplicatesisFalse.strict_capital-boolthat whenTrue(default), consider the casing of a term by counting capitalized terms without intermediate uppercase letters. Thus,Paypalis counted whilePayPalis not. The reference implementation sticks withTrue.only_alphanumeric_and_hyphen-boolthat can be turned on the drop keywords that contain characters other than alphanumerical characters and hyphens.minimum_chars-intfor the minimum number of characters in a keyword; shorter keywords will be dropped. By default, there is no such limit.
Leaving the defaults should bring you as close as possible to the reference implementation. For more information and precise defaults, see the rust crate.
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