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=== GSoC Proposal : Python API/library for Apertium ===





== BASIC DETAILS ==

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Name


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Arghya Bhattacharya


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EMail Address


Alternate EMail Address


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[[arghya.b@research.iiit.ac.in]]


arghyatiger@gmail.com


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IRC nick


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arghya


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Mobile


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+91 9831325363


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TimeZone


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UTC + 5:30


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Link to Github


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[[https://github.com/arghyatiger/]]


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== Why am I interested in Machine Translation ? ==

'''The broader perspective:'''

Being from a diverse country like India, with over 22 officially registered languages and over 1500 mother tongue languages (150 of them are sizeable), I&rsquo;ve always been curious as to how
languages serve as the basic entity of interaction. As a kid, I&rsquo;ve lived in various places in India and hence i&rsquo;ve had the chance to closely interact with people of different lingual
backgrounds and in the process i ended up learning quite a fewlanguages including Hindi, Bengali, English, Tamil, Oriya. The language diversity in my country is fascinating, but with it comes
a lot of problems and i believe <nowiki>Insert non-formatted text here</nowiki>that efficient machine translation can aid solving a lot of these problems and breaking the &ldquo;language barrier&rdquo;
across the country and the globe and connect people better.


'''Academic Interests:'''

I am currently pursuing my B.Tech in Computer Science + M.S by Research in Computational Linguistics Dual Degree program at IIIT-Hyderabad, India. A good portion of our academic focus is on Machine Translation and I really find it an interesting area to work on. So working with apertium will help me nurture my Computational Linguistics skills as well as give me a chance to help the community with whatever contribution i&rsquo;m capable of making.



== Why is it that I am interested in Apertium ? ==

Being a student, with primary academic focus on Computational Linguistics, Apertium happens to be one of the important tools that I use for my university assignments.The Apertium projects have a nice blend of Linguistic and Coding tasks and that makes the projects interesting to me. Also as a part of the long term goal of contributing to the community, I think contributions to Apertium would make a significant impact on the Computational Linguistics community all around the globe and that further motivates me to work for Apertium



== Which of the published tasks am I interested in? ==

To me all the published tasks seem to be interesting and hence it becomes difficult to choose only one. But I have been able to narrow down to the project called Python API/library for Apertium



== Why should Google and Apertium sponsor the project of Python API for Apertium ? ==

The Apertium code base is primarily written in C++. While C++ has a fairly high performance, supports low level systems programming and is fairly available everywhere and reasonably well standardized, however, there are a few shortcomings to it as well. Some of them include the non-interactiveness of c++, the compile/debug/nap cycle and the endless difficulties in extending and modifying the modules. Also, Once the development of a module is done with, certain improvements like writing User-Interfaces and systems integration become really cumbersome in C++. Python on the other hand has a lot of features that c++ doesn&rsquo;t have. Python has a interpreted high level programming environment. And hence a python wrapper can provide flexibility, interactivity to Apertium&rsquo;s code base. Also a lot of other features like ease of debugging, ease of testing, and rapid prototyping.



== How and Who will benefit from this project? ==

The project would bring a lot of developers at ease as python is a high level language with a lot of features that make it easier to grasp for developers, and would increase the scalability of apertium in the future, also a lot of people like to use jupyter notebooks and python, and hence I believe that if apertium has a python API, it would be helpful to a large community of developers, linguists, computational linguistics and all people keen on using a wide range of linguistic tools.



== Detailed project plan and workflow ==

'''1. Detailed Project Goal:'''

The Goal of the project is to create structured python wrappers for the core modules of apertium, namely:

* [[Apertium/Lttoolbox]]
* [[Apertium/Apertium]]

a.) The modules should be python importable,the pythonic usage would be as follows:
* from apertium.lttoolbox import trasducer
b.) The modules should be nested
* apertium.lttoolbox.transducer
c.) The internal usage of the functions should be as follows:
* import apertium.transducer.internal
* t = apertium.transducer.internal.Transducer().insertSingleTransduction()

'''2. Tool to be used: '''

For the project, I plan on using SWIG to bind the C++ code. SWIG is a software development tool that simplifies the task of interfacing different languages to C and C++ programs. SWIG is a compiler that takes C declarations and creates the wrappers needed to access those declarations from other languages. Among the other options that I explored for the project are Pyrex, ctypes, SIP, Boost.python.But for projects of the scale of this one, SWIG seems to be the most convenient due to a lot of features explained later in the proposal.

'''3. Timeline :'''


Goals for the various phases:
{|class="wikitable" style="width:100%"
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<center>'''PHASE'''</center>


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<center>'''OBJECTIVE'''</center>


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<center>COMMUNITY BONDING PERIOD</center>


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<center>Good Understanding of all the modules, all the intricacies of binding each module and a detailed report of the modules</center>


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<center>CODING PHASE 1</center>


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<center>Binding/Testing the Lttoolbox Module</center>


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<center>CODING PHASE 2</center>


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<center>Binding/Testing the Apertium Module</center>


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<center>CODING PHASE 3</center>


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<center>Documentation of usage of the python modules and library organization of the modules made in previous phases</center>
|}


Week-Wise Goals:

{|class="wikitable"
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<center>'''TIME PERIOD'''</center>


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<center>'''TASK PLAN'''</center>


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<center>COMMUNITY BONDING PERIOD</center>

<center>DATES:</center>
* START : April 23rd
* END : May 13th


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* Playing around with the lttoolbox and apertium modules and using every function and understanding all the flags and arguments of the functions.
* Reading up on the details of SWIG.
* Taking inputs from various apertium users on what would be the ideal implementation that they would want.

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<center>WEEK ONE:</center>
* Lttoolbox setup

<center>DATES:</center>
* START : May 14th
* END : May 20th


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* Setting up Disutils for the lttoolbox module and making the basic layout importable in Python.

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<center>WEEK TWO:</center>
* Variable handling in SWIG for Lttoolbox module

<center>DATES:</center>
* START : May 21st
* END : May 27th


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* Making explicit declarations of Constants and Enumerations of the module in SWIG interface
* Testing all pointer based data manipulation for any errors. (A common problem that might occur with swig bindings)
* Looking for Data Members that need to be made read-only and making necessary changes in the interface file
* Identifying Static Class members,Python classes had no support for static methods and no version of Python supports static member variables in a manner that SWIG can utilize. Therefore, SWIG generates wrappers that try to work around some of these issues , but the other issues have to be taken care of manually.
* Resolving namespace problem of SWIG manually(occurs if there are multiple namespaces)

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<center>WEEK THREE:</center>
* Templating and Object Handling for Lttoolbox module

<center>DATES:</center>
* START : May 28th
* END : June 3rd


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* In order to create wrappers, one has to tell SWIG to create wrappers for a particular template instantiation. Hence all the templates have to be explicitly declared specific to the data being manipulated in them.
* C++ Reference Counted Objects: Referencing and Dereferencing of objects have to be taken care of so that no error occurs, another place where SWIG isn&rsquo;t smart enough.

* Handling C++ overloaded functions: Overloading support is not quite as flexible as in C++. Sometimes there are methods that SWIG can&#39;t disambiguate, if such errors appear then they have to be taken care of manually in the interface file of the wrapper.

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<center>WEEK FOUR:</center>
* Testing and improving cross language polymorphism
* Making the module more Pythonistic
* Exception Handling

<center>DATES:</center>
* START : June 4th
* END : June 10th


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* Implement Director Classes: No mechanism exists to pass method calls down the inheritance chain from C++ to Python. In particular, if a C++ class has been extended in Python, these extensions will not be visible from C++ code. Virtual method calls from C++ are thus not able access the lowest implementation in the inheritance chain. There exists a feature implemented in SWIG called directors, The job of the directors is to route method calls correctly, either to C++ implementations higher in the inheritance chain or to Python implementations lower in the inheritance chain.
* Writing c++ helper functions: Sometimes the SWIG module misses bits of functionality because there is no easy way to construct and manipulate a suitable datatype, for those cases c++ helper functions need to be written.
* Writing High Level Python function to provide a high-level Python interface built on top of low-level helper functions.
* Error Handling: If C++ throws an erro then it is better to convert it into a python exception.

|-
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<center>WEEK FIVE: </center>
* Apertium setup

<center>DATES:</center>
* START : June 11th
* END : June 17th


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* Ref : week1

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<center>WEEK SIX:</center>
* Variable handling in SWIG for Apertium module

<center>DATES:</center>
* START : June 18th
* END : June 24th


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* Ref : week2

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<center>WEEK SEVEN:</center>
* Templating and Object Handling for Lttoolbox module

<center>DATES:</center>
* START : June 25th
* END : July 1st


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* Ref : week3

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<center>WEEK EIGHT:</center>
* Testing and improving cross language polymorphism
* Making the module more pythonistic
* Exception Handling

<center>DATES:</center>
* START : July 2nd
* END : July 8th


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* Ref : week4

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<center>WEEK NINE:</center>
* Extensive alpha testing of modules built

<center>DATES:</center>
* START : July 9th
* END : July 15th


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* Testing the modules built and starting the documentation.

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<center>WEEK TEN:</center>
* Finishing Documentation

<center>DATES:</center>
* START : July 16th
* END : July 22nd


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* Finishing the documentation of the module and distribute for Beta testing

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<center>WEEK ELEVEN:</center>
* Beta testing and changes(if any)

<center>DATES:</center>
* START : July 23rd
* END : July 29th


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* Taking reviews of beta testing and implementing changes if any.

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<center>WEEK TWELVE:</center>
* Deciding on the library structure
* Making module pip installable

<center>DATES:</center>
* START : July 30th
* END : August 5th


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* Making the super wrapper for the modules.
* Making the module pip installable
* Update Documentation

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<center>WEEK THIRTEEN: </center>
* Final reviews and bug report analysis

<center>DATES:</center>
* START : August 6th
* END : August 14th


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* Analyse and make bug report for the bugs in the code.
* Make Final documentation
* Release Final Module

|}


== Coding Challenge ==

1.)Make the Transducer model python importable



== About me: Education and Experience ==

I am a sophomore at IIIT-Hyderabad, India, pursing my Dual-Degree in Computer Science and Computational Linguistics. I&rsquo;ve worked with C++ and Python closely in a lot of projects and I take keen interest in machine learning as well.I usually love building fun applications. The details of my work experience can be found [[here]].

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Latest revision as of 09:19, 27 March 2018