g-laz77 / apertium-python

Apertium + Python

Introduction

• The code-base is in development for the Gsoc '18 project called Apertium API in Python
• The Apertium core modules are written in C++.
• This project is an attempt to make the Apertium modules available in python, which because of it's simplicity is more appealing to users.

About the Exisiting Code Base

• The exisiting code base has the subprocess implementation of the basic functions of Apertium.
• A branch called the windows has the implementation for the windows support and will soon be available on master. Detailed instructions can be found here

Major things to do

• Subprocess implementation of the C++ functions in Apertium. To make the wrapper thinner.
• Other small issues can be found here

Usage of library

Analysis

Performing Morphological Analysis

Method 1: One can create Analyzer objects on which analyze() function can be run.

In [1]: import apertium
In [2]: a = apertium.Analyzer('en')
In [3]: a.analyze('cats')
Out[3]: [cats/cat<n><pl>, ./.<sent>]

Method 2: Alternatively, the library provides an option to directly run the analyze method.

In [1]: import apertium
In [2]: apertium.analyze('en', 'cats')
Out[2]: cats/cat<n><pl>

Generation

Performing Morphological Generation

Method 1: Just like the Analyzer, One can create Generator objects on which generate() function can be run.

In [1]: import apertium
In [2]: g = apertium.Generator('en')
In [3]: g.generate('^cat<n><pl>$')
Out[3]: 'cats'

Method 2: Running generate() directly.

In [1]: import apertium
In [2]: apertium.generate('en', '^cat<n><pl>$')
Out[2]: 'cats'

Installing more modes from other language data

One can also install modes by providing the path to the lang-data using this simple function

In [1]: import apertium
In [2]: apertium.append_pair_path('..')

Translation

Performing Translations

In [1]: import apertium
In [2]: t = apertium.Translator('eng', 'spa')
In [3]: t.translate('cats')
Out[3]: 'Gatos'