bf8a641654
git-svn-id: svn://svn.cy55.de/Zope3/src/loops/trunk@2071 fd906abe-77d9-0310-91a1-e0d9ade77398
113 lines
3.5 KiB
Text
113 lines
3.5 KiB
Text
===============================================================
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loops - Linked Objects for Organization and Processing Services
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===============================================================
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Automatic classification of resources.
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($Id$)
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Setting up a loops Site and Utilities
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=====================================
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Let's do some basic set up
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>>> from zope import component, interface
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>>> from zope.traversing.api import getName
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>>> from zope.app.testing.setup import placefulSetUp, placefulTearDown
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>>> site = placefulSetUp(True)
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and build a simple loops site with a concept manager and some concepts
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(with a relation registry, a catalog, and all the type machinery - what
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in real life is done via standard ZCML setup or via local utility
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configuration):
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>>> from loops.classifier.testsetup import TestSite
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>>> t = TestSite(site)
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>>> concepts, resources, views = t.setup()
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>>> len(concepts), len(resources)
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(20, 0)
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Let's now add an external collection that reads in a set of resources
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from external files so we have something to work with.
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>>> from loops.concept import Concept
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>>> from loops.setup import addObject
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>>> from loops.common import adapted
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>>> from loops.classifier.testsetup import dataDir
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>>> tExternalCollection = concepts['extcollection']
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>>> coll01 = addObject(concepts, Concept, 'coll01',
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... title=u'Collection One', conceptType=tExternalCollection)
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>>> aColl01 = adapted(coll01)
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>>> aColl01.baseAddress = dataDir
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>>> aColl01.address = ''
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>>> aColl01.update()
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>>> len(resources)
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7
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>>> rnames = list(sorted(resources.keys()))
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>>> rnames[0]
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u'cust_im_contract_webbg_20071015.txt'
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Filename-based Classification
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=============================
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Let's first look at the external address (i.e. the file name) of the
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resource we want to classify.
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>>> r1 = resources[rnames[0]]
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>>> adapted(r1)
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<loops.resource.ExternalFileAdapter object ...>
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>>> adapted(r1).externalAddress
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'cust_im_contract_webbg_20071015.txt'
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OK, that's what we need. So we get the preconfigured classifier
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(see testsetup.py) and let it classify the resource.
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>>> classifier = adapted(concepts['fileclassifier'])
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Before just processing the resource we'll have a look at the details
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and follow the classifier step by step.
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>>> from loops.classifier.base import InformationSet
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>>> from loops.classifier.interfaces import IExtractor, IAnalyzer
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>>> infoSet = InformationSet()
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>>> for name in classifier.extractors.split():
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... print 'extractor:', name
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... extractor = component.getAdapter(adapted(r1), IExtractor, name=name)
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... infoSet.update(extractor.extractInformationSet())
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extractor: filename
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>>> infoSet
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{'filename': 'cust_im_contract_webbg_20071015.txt'}
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>>> analyzer = component.getUtility(IAnalyzer, name=classifier.analyzer)
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>>> statements = analyzer.extractStatements(infoSet, classifier)
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>>> statements
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[]
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So there seems to be something missing - we have to create concepts
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that may be identified as being candidates for classification.
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>>> tInstitution = addObject(concepts, Concept, 'institution',
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... title=u'Institution', conceptType=concepts['type'])
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>>> cust_im = addObject(concepts, Concept, 'im_editors',
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... title=u'im Editors', conceptType=tInstitution)
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>>> t.indexAll(concepts, resources)
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>>> statements = analyzer.extractStatements(infoSet, classifier)
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>>> len(statements)
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1
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So we are now ready to have the whole stuff run in one call.
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>>> classifier.process(r1)
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Fin de partie
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=============
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>>> placefulTearDown()
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