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
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
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