Metadata-Version: 1.1
Name: CLAM
Version: 0.9.13.2
Summary: Computational Linguistics Application Mediator. Turn command-line NLP tools into fully-fledged RESTful webservices.
Home-page: http://proycon.github.com/clam
Author: Maarten van Gompel
Author-email: proycon@anaproy.nl
License: GPL
Description: =======================================================
        CLAM: Computational Linguistics Application Mediator
        =======================================================
        
        .. image:: https://travis-ci.org/proycon/clam.svg?branch=master
            :target: https://travis-ci.org/proycon/clam
        
        *by Maarten van Gompel, Centre for Language Studies, Radboud University Nijmegen*
        
        *Licensed under GPLv3*
        		
        **Website:** http://proycon.github.io/clam 
        **Source repository:** https://github.com/proycon/clam/
        
        CLAM allows you to quickly and transparently transform your Natural Language
        Processing application into a RESTful webservice, with which both human
        end-users as well as automated clients can interact. CLAM takes a description
        of your system and wraps itself around the system, allowing end-users or
        automated clients to upload input files to your application, start your
        application with specific parameters of their choice, and download and view the
        output of the application once it is completed.
        
        CLAM is set up in a universal fashion, requiring minimal effort on the part of
        the service developer. Your actual NLP application is treated as a black box,
        of which only the parameters, input formats and output formats need to be
        described. Your application itself needs not be network aware in any way, nor
        aware of CLAM, and the handling and validation of input can be taken care of by
        CLAM.
        
        CLAM is entirely written in Python, runs on UNIX-derived systems, and is
        available as open source under the GNU Public License (v3). It is set up in a
        modular fashion, and offers an API, and as such is easily extendable. CLAM
        communicates in a transparent XML format, and using XSL transformation offers a
        full web 2.0 web-interface for human end users. 
        
        Installation instruction can be found below. For full documentation see the
        manual in ``docs/clam_manual.pdf`` , also accessible through the CLAM website
        at http://proycon.github.io/clam . It is recommended to read this prior to
        starting with CLAM. 
        
        
        Installation
        ----------------
        
        IMPORTANT NOTICE: It's discouraged to download the zip packages or tarballs
        from github, install CLAM from the `Python
        Package Index <http://pypi.python.org/pypi/CLAM>`_ or use git properly.
        
        Installation On Linux 
        ~~~~~~~~~~~~~~~~~~~~~~~~
        
        Easy install is part of the Python setup tools and can install CLAM globally on
        your system for you from the Python Package Index. This is the easiest method
        of installing CLAM, as it will automatically fetch and install any
        dependencies.  This procedure downloads CLAM for you automatically.
        Alternatively, you can use ``pip`` (usually part  of the ``python-pip``
        package). We recommend to use a virtual environment (``virtualenv``) if you
        want to install CLAM locally as a user, if you want to install globally,
        prepend the following commands with ``sudo``:
        
         $ easy_install clam
        
        If you already downloaded CLAM manually (from github), you can do::
        
         $ ./setup.py install
        
        If easy_install is not yet installed on your system, install it using: 
         on debian-based linux systems (including Ubuntu)::
        
          $ apt-get install python-setuptools 
          
        on RPM-based linux systems::
        
          $ yum install python-setuptools
        
        on MacOS X: (follow the manual steps further down this document)
        
        Note that sudo/root access is needed to install globally. Ask your system administrator
        to install it.  Alternatively, you can install in a local custom path  using the
        -d flag, this however complicates matters as you need to take care to add these
        local directories to your python library path:
        
         $ easy_install -d /path/to/dir clam
        
        
        Installation on Mac OS X
        ~~~~~~~~~~~~~~~~~~~~~~~~~~~
        
        Install a Python distribution such as `Anaconda <http://continuum.io/>`_ and follow the Linux instructions above.
        
        
        Installation on Windows
        ~~~~~~~~~~~~~~~~~~~~~~~~~~
        
         Not supported, delete Windows and install a decent OS ;)
         
        
        Running a test webservice
        ~~~~~~~~~~~~~~~~~~~~~~~~~~~
        
        If you installed CLAM using the above method, then you can launch a clam test
        webservice using the development server as follows:
        
        $ clamservice -H localhost -p 8080 clam.config.textstats
         
        Navigate your browser to http://localhost:8080 and verify everything works
        
        If any problems occur during installation regarding pycurl, then install the
        pycurl package supplied by your distribution (python-pycurl on Debian/ubuntu)
        
        Note: It is important to regularly keep CLAM up to date as fixes and
        improvements are implemented on a regular basis. Update CLAM using::
        
         $ easy_install -U clam
        
        or if you used pip::
        
         $ pip install -U clam
        
        
        Installing a particular clam webservice for production use
        ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
        
        When installating a particular CLAM webservice on a new server, it is first
        necessary to edit the service configuration file of the webservice and make
        sure all the paths in there are set correctly for the new server. Of interest
        is in particular the ROOT path, which is where user data will be stored, this
        directory must exist and be writable by the webserver.
        
        For testing, the built-in development server can be used. Suppose the
        webservice configuration is in /path/to/mywebservice/ and is called
        mywebservice.py, then the development server can be started as follows::
        
         $ clamservice -P /path/to/mywebservice mywebservice
        
        For production, however, it is strongly recommended to embed CLAM in Apache.
        This is the typically task of a system administrator, as certain skills are
        necessary and assumed.
        
        Embedding CLAM in Apache is accomplished through WSGI, for which you need to
        have the package libapache2-mod-wsgi installed (Debian/Ubuntu).  Next it
        involves the writing of a small WSGI script and adaptation of the Apache
        configuration to load this script. All this is explained in detail in the CLAM
        Manual, obtainable from http://proycon.github.io/clam/ . 
        
        
        
        
        
        
Keywords: clam webservice rest nlp computational_linguistics rest
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Topic :: Internet :: WWW/HTTP :: WSGI :: Application
Classifier: Topic :: Text Processing :: Linguistic
Classifier: Programming Language :: Python :: 2.6
Classifier: Operating System :: POSIX
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
