running python as a dameon

[Sean Davis]

On Sep 5, 5:55 pm, peyman <peymanfara... at gmail.com> wrote:
> Hi
>
> I have a Natural Language Processing (NLP) code written in python that
> reads into memory a large training file and then given a sentence tags
> it, using the training data. I want to put this NLP code on a server
> which handles all incoming client http requests via PHP. What I want
> to do is to provide the python NLP program as a service to any other
> PHP/Java/Ruby process request. So the mapping is
>
> http -> apache -> PHP/Java/Ruby/... -> Python NLP

Why not use a simple CGI script or wsgi application?  You could make
the service online and interactive and with the same application and
code make an XMLRPC web service.  So, things would look more like:

http -> apache -> Python (running NLP and serving requests)

You can use apache to proxy requests to any one of a dozen or so
python-based webservers.  You could also use mod_wsgi to interface
with a wsgi application.

Sean

>
> I can not provide this service as a shell script because of the
> inefficiencies of having to load into memory a large training data to
> every service request. So what I want to do is to provide the NLP
> service to other application processes as a python daemon
>
> http -> apache -> PHP/Java/Ruby/... -> Python Dameon -> Python NLP
>
> The daemon loads into memory the training data once. then every
> service request event invokes the appropriate NLP code in the python
> program. I've tried to use play around with twisted but am not making
> too much of a headway. What I've done in the NLP code is to do this:
>
> # filename: NLP.py
> def parse(sentence):
>     structure=getentities(sentence)
>     print 'subject: \t',' '.join(structure[0])
>     print 'predicate: \t',' '.join(structure[1])
>     print 'TE: \t\t',' '.join(structure[2])
>
> class TLogicClass():
>     def __init__(self,prop):
>         return parse(prop)
>
> then in the dameon code done this
>
> # filename: dameon.py
> from twisted.application import service
> import NLP
>
> application=service.Application("nlp")
> ParseService=NLP.TLogicClass("time flies like an arrow")
> ParseService.setServiceParent(application)
>
> but I get the following error when I run twistd -y daemon.py
>
> >> Failed to load application: TLogicClass instance has no attribute 'setServiceParent'
>
> I suspect I need to put twisted in the NLP.py but I don't know what I
> need to do in order to get what I want to do which is:
>
> to load into memory only once a large training data that can then be
> queried by another (non-python) event based process  (I need "reactor"
> class?).
>
> thank you in advance for your help