PyRuSH
=========



PyRuSH is the python implementation of `RuSH <https://github.com/jianlins/RuSH>`_ (**Ru** le-based sentence **S** egmenter using **H** ashing), which is originally developed using Java. RuSH is an efficient, reliable, and easy adaptable rule-based sentence segmentation solution. It is specifically designed to handle the telegraphic written text in clinical note. It leverages a nested hash table to execute simultaneous rule processing, which reduces the impact of the rule-base growth on execution time and eliminates the effect of rule order on accuracy.

If you wish to cite RuSH in a publication, please use:

Jianlin Shi ; Danielle Mowery ; Kristina M. Doing-Harris ; John F. Hurdle.RuSH: a Rule-based Segmentation Tool Using Hashing for Extremely Accurate Sentence Segmentation of Clinical Text. AMIA Annu Symp Proc. 2016: 1587.

The full text can be found `here <https://knowledge.amia.org/amia-63300-1.3360278/t005-1.3362920/f005-1.3362921/2495498-1.3363244/2495498-1.3363247?timeStamp=1479743941616>`_.



Installation
------------

    pip install PyRuSH


How to use
------------

A standalone RuSH class is available to be directly used in your code. From 1.0.4, pyRush adopt spaCy 3.x api to initiate an component.

    >>> from PyRuSH import RuSH
    >>> input_str = "The patient was admitted on 03/26/08\n and was started on IV antibiotics elevation" +\
    >>>              ", was also counseled to minimizing the cigarette smoking. The patient had edema\n\n" +\
    >>>              "\n of his bilateral lower extremities. The hospital consult was also obtained to " +\
    >>>              "address edema issue question was related to his liver hepatitis C. Hospital consult" +\
    >>>              " was obtained. This included an ultrasound of his abdomen, which showed just mild " +\
    >>>              "cirrhosis. "
    >>> rush = RuSH('../conf/rush_rules.tsv')
    >>> sentences=rush.segToSentenceSpans(input_str)
    >>> for sentence in sentences:
    >>>     print("Sentence({0}-{1}):\t>{2}<".format(sentence.begin, sentence.end, input_str[sentence.begin:sentence.end]))
    
Spacy Componentized PyRuSH
---------------------------
Start from version 1.0.3, PyRuSH adds Spacy compatible Sentencizer component: PyRuSHSentencizer.

    >>> from PyRuSH import PyRuSHSentencizer
    >>> from spacy.lang.en import English
    >>> nlp = English()
    >>> nlp.add_pipe("medspacy_pyrush")
    >>> doc = nlp("This is a sentence. This is another sentence.")
    >>> print('\n'.join([str(s) for s in doc.sents]))
    

    
A Colab Notebook Demo
---------------------------
Feel free to try this runnable `Colab notebook Demo <https://colab.research.google.com/drive/1gX9MzZTQiPw8G3x_vUwZbiSXGtbI0uIX?usp=sharing>`_

Revision History
----------------

**1.0.11 (2025-09-02)**

- Improved sentence splitting logic: Sentences are now split at the last token before exceeding the max length, ensuring no chunk exceeds the specified limit.
- Edge case handling: Trailing whitespaces (caused by spacy sentence labeling mechanism) can be optionally split into a separate sentence (merge_gaps=False) to avoid necessarily long sentences.

**1.0.9 (2024-10-27)**

- Initial release with spaCy 3.x compatibility and core RuSH logic.
- Added Spacy-compatible PyRuSHSentencizer component.
