https://github.com/jaidevd/numerizer

A Python module to convert natural language numerics into ints and floats.
https://github.com/jaidevd/numerizer

information-extraction nlp regular-expressions spacy spacy-extension

Last synced: 7 days ago
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A Python module to convert natural language numerics into ints and floats.

• Host: GitHub
• URL: https://github.com/jaidevd/numerizer
• Owner: jaidevd
• License: mit
• Created: 2019-12-02T07:00:34.000Z (about 5 years ago)
• Default Branch: master
• Last Pushed: 2024-09-26T08:33:18.000Z (4 months ago)
• Last Synced: 2025-01-11T03:06:54.375Z (14 days ago)
• Topics: information-extraction, nlp, regular-expressions, spacy, spacy-extension
• Language: Python
• Homepage:
• Size: 50.8 KB
• Stars: 226
• Watchers: 8
• Forks: 24
• Open Issues: 6
• Metadata Files:
  • Readme: README.rst
  • License: LICENSE

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README

        
numerizer

=========

A Python module to convert natural language numerics into ints and floats.

This is a port of the Ruby gem `numerizer

`_

Numerizer has been tested on Python 3.9, 3.10 and 3.11.

Installation

------------

The numerizer library can be installed from PyPI as follows:

.. code:: bash

    $ pip install numerizer

Usage

-----

.. code:: python

    >>> from numerizer import numerize

    >>> numerize('forty two')

    '42'

    >>> numerize('forty-two')

    '42'

    >>> numerize('four hundred and sixty two')

    '462'

    >>> numerize('one fifty')

    '150'

    >>> numerize('twelve hundred')

    '1200'

    >>> numerize('twenty one thousand four hundred and seventy three')

    '21473'

    >>> numerize('one million two hundred and fifty thousand and seven')

    '1250007'

    >>> numerize('one billion and one')

    '1000000001'

    >>> numerize('nine and three quarters')

    '9.75'

    >>> numerize('platform nine and three quarters')

    'platform 9.75'

Using the SpaCy extension

^^^^^^^^^^^^^^^^^^^^^^^^^

Since version 0.2, numerizer is available as a `SpaCy extension `_.

Any named entities of a quantitative nature within a SpaCy document can be numerized as follows:

.. code:: python

    >>> from spacy import load

    >>> nlp = load('en_core_web_sm')  # or load any other spaCy model

    >>> doc = nlp('The projected revenue for the next quarter is over two million dollars.')

    >>> doc._.numerize()

    {the next quarter: 'the next 1/4', over two million dollars: 'over 2000000 dollars'}

Users can specify which entity types are to be numerized, by using the `labels` argument in the extension function, as follows:

.. code:: python

    >>> doc._.numerize(labels=['MONEY'])  # only numerize entities of type 'MONEY'

    {over two million dollars: 'over 2000000 dollars'}

The extension is available for tokens and spans as well.

.. code:: python

    >>> two_million = doc[-4:-2]  # span corresponding to "two million"

    >>> two_million._.numerize()

    '2000000'

    >>> quarter = doc[6]  # token corresponding to "quarter"

    >>> quarter._.numerized

    '1/4'

Extras

------

For R users, a wrapper library has been developed by `@amrrs `_. Try it out `here `_.