Metadata-Version: 2.2
Name: number-parser
Version: 0.2.1
Summary: parse numbers written in natural language
Home-page: https://github.com/arnavkapoor/number-parser
Author: Arnav Kapoor
Author-email: arnavk805@gmail.com
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: BSD License
Classifier: Natural Language :: English
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
License-File: LICENSE
Requires-Dist: attrs>=17.3.0
Dynamic: author
Dynamic: author-email
Dynamic: classifier
Dynamic: description
Dynamic: home-page
Dynamic: requires-dist
Dynamic: summary

=============
number-parser
=============
.. image:: https://img.shields.io/pypi/pyversions/price-parser.svg
   :target: https://pypi.python.org/pypi/price-parser
   :alt: Supported Python Versions

``number-parser`` is a simple library that allows you to convert numbers written in the natural
language to it's equivalent numeric forms. It currently supports cardinal numbers in the following 
languages - English, Hindi, Spanish and Russian and ordinal numbers in English.

Installation
============
::

    pip install number-parser

number-parser requires Python 3.6+.

Usage
=====

The library provides three major APIs which corresponds to the following common usages.

Interface #1: Multiple numbers 
------------------------------

Identifying the numbers in a text string, converting them to corresponding numeric values while ignoring non-numeric words.
This also supports ordinal number conversion (for English only).

>>> from number_parser import parse
>>> parse("I have two hats and thirty seven coats")
'I have 2 hats and 37 coats'
>>> parse("One, Two, Three go")
'1, 2, 3 go'
>>> parse("First day of year two thousand")
'1 day of year 2000'


Interface #2: Single number 
--------------------------------
Converting a single number written in words to it's corresponding integer. 

>>> from number_parser import parse_number
>>> parse_number("two thousand and twenty")
2020
>>> parse_number("not_a_number")


Interface #3: Single number Ordinal
-------------------------------------

Converting a single ordinal number written in words to it's corresponding integer. (Support for only English)

>>> from number_parser import parse_ordinal
>>> parse_ordinal("twenty third")
23
>>> parse_ordinal("seventy fifth")
75


Language Support
----------------

The default language is English, you can pass the language parameter with corresponding locale for other languages.
It currently supports cardinal numbers in the following 
languages - English, Hindi, Spanish and Russian and ordinal numbers in English.

>>> from number_parser import parse, parse_number
>>> parse("Hay tres gallinas y veintitrés patos", language='es')
'Hay 3 gallinas y 23 patos'
>>> parse_number("चौदह लाख बत्तीस हज़ार पाँच सौ चौबीस", language='hi')
1432524

Supported cases
---------------

The library has extensive tests.
Some of the supported cases are described below.

Accurately handling usage of conjunction while forming the number. 

>>> parse("doscientos cincuenta y doscientos treinta y uno y doce", language='es')
'250 y 231 y 12'


Handling ambiguous cases without proper separators.

>>> parse("two thousand thousand")
'2000 1000'
>>> parse_number("two thousand two million")
2002000000


Handling nuances in the languag ith different forms of the same number. 

>>> parse_number("пятисот девяноста шести", language='ru')
596
>>> parse_number("пятистам девяноста шести", language='ru')
596
>>> parse_number("пятьсот девяносто шесть", language='ru')
596

Contributing
============

* Source code: https://github.com/arnavkapoor/number-parser
* Issue tracker: https://github.com/arnavkapoor/number-parser/issues


Changes
=======
0.1.0 (2020-07-30)
------------------

Initial release.

0.2.0 (2020-08-18)
------------------

Ordinal Number Support


0.2.1 (2020-08-25)
------------------

Fix tokenization bug - Hindi
