numerizer · PyPI

Python module for converting natural language numbers into ints and floats.

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Project description

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:

$ pip install numerizer

Usage

>>> 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:

>>> 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:

>>> 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.

>>> 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.