def getSentsByOntology():
owlfile = "..\..\jobaly\ontology\web_dev.owl"
ontology = OntologyLib(owlfile)
terms = [ " "+ x.lower()+" " for x in ontology.getLabelList()]
terms.extend([" "+x.lower()+" " for x in ontology.getAllClassNames()])
srcBbClient = DbClient('localhost', 27017, "jobaly_daily_test")
newCol = srcBbClient.getCollection("daily_job_webdev")
collection = newCol
matchingSents = []
for job in collection.find():
# print "\n\n\n======",job["_id"],"============================\n"
jobDesc = JobDescParser.parseJobDesc(job)
sents = jobDesc.listAllSentences()
jid = job["_id"]
for sent in sents:
c = 0
sent = " "+sent.lower()+" "
for term in terms:
if sent.find(term) != -1:
c+=1
if c==3 :
print sent.encode("GBK", "ignore")
matchingSents.append((jid, sent))
break
sortedsents = sorted(matchingSents, key=lambda x: len(x[1]) )
dumpTwo(sortedsents, "term3" , ( lambda x: x[0] + ":" + x[1] ) )
def getDisMatrixFromColletion():
srcBbClient = DbClient('localhost', 27017, "jobaly_daily_test")
collection = srcBbClient.getCollection("daily_job_webdev")
f = open('sents.txt','w')
# python will convert \n to os.linesep
docs = []
for job in collection.find():
# print "\n\n\n======",job["_id"],"============================\n"
# f.write(job["summary"].encode("GBK", "ignore")+"\n")
jobDesc = JobDescParser.parseJobDesc(job)
sents = jobDesc.listAllSentences()
doc =[]
for sent in sents:
# print sent.encode("GBK", "ignore")
f.write(sent.encode("GBK", "ignore")+"\n")
tokens = [ token.lower() for token in word_tokenize(sent)]
for token in tokens:
if token == 'c':
# print token
pass
doc.extend(tokens)
docs.append(doc)
f.close()
terms=["javascript", "jquery", "html", "css", "java", "python", "ruby", "mysql", "jdbc" , "cpp" ]
# terms=["javascript", "jquery", "html", "css", "java", "jsp", "python", "ruby", "ror" ]
# terms=["java","jdbc","spring","hibernate","mysql","oracle"]
matrix = getDistanceMatrix(docs, terms)
printDisMatrix(terms, matrix)
matrix_dump = json.dumps(matrix)
print matrix_dump
def getAllSentsInColl(collection):
allSents = []
for job in collection.find():
print "\n\n\n======",job["_id"],"============================\n"
jobDesc = JobDescParser.parseJobDesc(job)
sents = [ ( jobDesc._id, sent ) for sent in jobDesc.listAllSentences() ]
allSents.extend(sents)
return allSents
def preprocess( job ):
jobDesc = JobDescParser.parseJobDesc(job)
sents = jobDesc.listAllSentences()
sents2 = []
for line in sents:
sents2.append( processLine(line) )
return sents2
def getAllSentsInColl(collection):
allSents = []
for job in collection.find():
print "\n\n\n======", job["_id"], "============================\n"
jobDesc = JobDescParser.parseJobDesc(job)
sents = [(jobDesc._id, sent) for sent in jobDesc.listAllSentences()]
allSents.extend(sents)
return allSents
def getSentenceByTerm(collection, term, outputPath):
matchingSents = []
for job in collection.find():
# print "\n\n\n======",job["_id"],"============================\n"
jobDesc = JobDescParser.parseJobDesc(job)
sents = jobDesc.listAllSentences()
jid = job["_id"]
for sent in sents:
tokens = [ token.lower() for token in word_tokenize(sent)]
if term in tokens :
matchingSents.append((jid, sent))
print sent.encode("GBK", "ignore")
sortedsents = sorted(matchingSents, key=lambda x: len(x[1]) )
dumpTwo(sortedsents, outputPath , ( lambda x: x[0] + ":" + x[1] ) )
def getJavaScipt():
srcBbClient = DbClient('localhost', 27017, "jobaly_daily_test")
newCol = srcBbClient.getCollection("daily_job_webdev")
collection = newCol
term = "javascript"
matchingSents = []
for job in collection.find():
# print "\n\n\n======",job["_id"],"============================\n"
jobDesc = JobDescParser.parseJobDesc(job)
sents = jobDesc.listAllSentences()
jid = job["_id"]
for sent in sents:
tokens = [ token.lower() for token in word_tokenize(sent)]
if term in tokens :
matchingSents.append((jid, sent))
print sent.encode("GBK", "ignore")
sortedsents = sorted(matchingSents, key=lambda x: len(x[1]) )
dumpTwo(sortedsents, "..\skill\output\javascript" , ( lambda x: x[0] + ":" + x[1] ) )
def createDocs():
srcBbClient = DbClient('localhost', 27017, "jobaly_daily_test")
collection = srcBbClient.getCollection("daily_job_webdev")
maxnum =99999
docs = []
i= 0
for job in collection.find():
i+=1
if i == maxnum:
break
# print "\n\n\n======",job["_id"],"============================\n"
jobDesc = JobDescParser.parseJobDesc(job)
sents = jobDesc.listAllSentences()
doc =[]
for sent in sents:
tokens = [ token.lower() for token in word_tokenize(sent)]
doc.extend(tokens)
docs.append(doc)
return docs
def getDisMatrixFromColletion():
srcBbClient = DbClient('localhost', 27017, "jobaly_daily_test")
collection = srcBbClient.getCollection("daily_job_webdev")
f = open('sents.txt', 'w')
# python will convert \n to os.linesep
docs = []
for job in collection.find():
# print "\n\n\n======",job["_id"],"============================\n"
# f.write(job["summary"].encode("GBK", "ignore")+"\n")
jobDesc = JobDescParser.parseJobDesc(job)
sents = jobDesc.listAllSentences()
doc = []
for sent in sents:
# print sent.encode("GBK", "ignore")
f.write(sent.encode("GBK", "ignore") + "\n")
tokens = [token.lower() for token in word_tokenize(sent)]
for token in tokens:
if token == 'c':
# print token
pass
doc.extend(tokens)
docs.append(doc)
f.close()
terms = [
"javascript", "jquery", "html", "css", "java", "python", "ruby",
"mysql", "jdbc", "cpp"
]
# terms=["javascript", "jquery", "html", "css", "java", "jsp", "python", "ruby", "ror" ]
# terms=["java","jdbc","spring","hibernate","mysql","oracle"]
matrix = getDistanceMatrix(docs, terms)
printDisMatrix(terms, matrix)
matrix_dump = json.dumps(matrix)
print matrix_dump
