def post(self, request_id):
user = users.get_current_user()
request = models.read(request_id)
for q in request.questions:
feedback = self.request.POST.get(q)
if not feedback:
continue
saved_feedback = models.feedback(user, request, q, feedback)
saved_feedback.feedback = feedback
saved_feedback.put()
return webapp2.redirect('/request/{0}?status=saved'.format(request_id))
def api_put(request):
"""
响应PUT
"""
data = request_util.get_fields_to_be_save(request)
feedback = app_models.feedback(**data)
feedback.save()
error_msg = None
data = json.loads(feedback.to_json())
data['id'] = data['_id']['$oid']
if error_msg:
data['error_msg'] = error_msg
response = create_response(200)
response.data = data
return response.get_response()
def addfeedback(request):
res = {'code': 1, 'message': ''}
try:
uid = request.GET['uid']
txt = request.GET['txt']
except:
return HttpResponse(json.dumps(res))
#if True:
try:
feed = feedback()
feed.uid = uid
feed.txt = txt
feed.save()
#else:
except:
return HttpResponse(json.dumps(res))
res['code'] = 0
res['message'] = 'ok'
return HttpResponse(json.dumps(res))
def addfeedback(request):
res={'code':1,'message':''}
try:
uid=request.GET['uid']
txt=request.GET['txt']
except:
return HttpResponse(json.dumps(res))
#if True:
try:
feed=feedback()
feed.uid=uid
feed.txt=txt
feed.save()
#else:
except:
return HttpResponse(json.dumps(res))
res['code']=0
res['message']='ok'
return HttpResponse(json.dumps(res))
score = raw_input('Enter target score:')
threshold = raw_input(
'Enter threshold for word importance:')
input_scale = raw_input(
'Choose 1 for 0-1 scale, 2 for 0-5 scale:')
if int(input_scale) == 1:
score = float(score) * 5
testSet = [[goldA], [studA], [float(score)]]
result = app.test(usedModels, classifier, testSet)
# Covert result into required grading scale.
result = post_process(result)
print result
#feedback_model.build_vocab([sentA, sentB], tokenize=True)
keywords = models.feedback(feedm.feedback_model, goldA,
float(threshold))
#print 'keywords:', keywords
sent = nltk.word_tokenize(studA)
sent = [word.lower() for word in sent]
#print 'sent', sent
feedback = set(keywords) - set(sent) - set(['<s>', '</s>'])
print 'Hey there, you missed following keywords:\n', list(
feedback)
elif BATCH_MODE:
input_path = raw_input(
'Enter the complete file path for test data. \n')
trainSet, devSet, testSet = app.load_data_nosplit(
input_path)
result = app.test([feedm, fbm], classifier, testSet)
result = post_process(result)