def post(self):
if experiment_grouping_already_started(
self.experiment): # be idempotent
return
cycle = Cycle(range(self.experiment.cohort_count))
workers, peer_workers = [], {}
for worker in Worker.all().filter('experiment = ', self.experiment):
worker.cohort_index = cycle.next()
workers.append(worker)
if peer_workers.has_key(worker.cohort_index):
peer_workers[worker.cohort_index].append(worker)
else:
peer_workers[worker.cohort_index] = [worker]
for worker in workers:
previous_cohort_index = index_decr(worker.cohort_index,
self.experiment.cohort_count)
previous_cohort = peer_workers[previous_cohort_index]
worker.peer_worker = previous_cohort.pop(
random.randrange(len(previous_cohort)))
worker.put()
if worker.cohort_index == 0:
taskqueue.add(queue_name='worker-notification',
params={'key': worker.key()})
def post(self):
if experiment_grouping_already_started(self.experiment): # be idempotent
return
cycle = Cycle(range(self.experiment.cohort_count))
workers, peer_workers = [], {}
for worker in Worker.all().filter('experiment = ', self.experiment):
worker.cohort_index = cycle.next()
workers.append(worker)
if peer_workers.has_key(worker.cohort_index):
peer_workers[worker.cohort_index].append(worker)
else:
peer_workers[worker.cohort_index] = [worker]
for worker in workers:
previous_cohort_index = index_decr(worker.cohort_index, self.experiment.cohort_count)
previous_cohort = peer_workers[previous_cohort_index]
worker.peer_worker = previous_cohort.pop(random.randrange(len(previous_cohort)))
worker.put()
if worker.cohort_index == 0:
taskqueue.add(queue_name='worker-notification', params={'key': worker.key()})
def _fn(self, *args, **kwargs):
self.token = self.request.get('token')
self.worker = Worker.all().filter('nonce = ', self.token).get()
if self.worker:
return fn(self, *args, **kwargs)
else:
self.bad_request()
def _fn(self, *args, **kwargs):
self.token = self.request.get('token')
self.worker = Worker.all().filter('nonce = ', self.token).get()
if self.worker:
return fn(self, *args, **kwargs)
else:
self.bad_request()
def post(self):
labeling = Labeling()
labeling.image_url = self.image_url(self.worker)
labeling.worker = self.worker
labeling.labels = self.request.get_all('label')
labeling.time = int(self.request.get('time'))
labeling.put()
evaluator = Worker.all().filter('peer_worker = ', self.worker).get()
taskqueue.add(queue_name='worker-notification', params={'key': evaluator.key()})
self.redirect(self.mturk_submit_url())
def post(self):
labeling = Labeling()
labeling.image_url = self.image_url(self.worker)
labeling.worker = self.worker
labeling.labels = self.request.get_all('label')
labeling.time = int(self.request.get('time'))
labeling.put()
evaluator = Worker.all().filter('peer_worker = ', self.worker).get()
taskqueue.add(queue_name='worker-notification',
params={'key': evaluator.key()})
self.redirect(self.mturk_submit_url())
def get(self):
experiments = Experiment.all().filter('second_stage_started = ', None)
for experiment in experiments:
worker_count = 0
for worker in Worker.all().filter('experiment = ', experiment):
if worker.has_labeled_an_image():
worker_count += 1
if worker_count == experiment.cohort_size * experiment.cohort_count:
taskqueue.add(queue_name='worker-grouping', params={'key': experiment.key()})
experiment.second_stage_started = datetime.now()
experiment.put()
def get(self):
experiments = Experiment.all().filter('second_stage_started = ', None)
for experiment in experiments:
worker_count = 0
for worker in Worker.all().filter('experiment = ', experiment):
if worker.has_labeled_an_image():
worker_count += 1
if worker_count == experiment.cohort_size * experiment.cohort_count:
taskqueue.add(queue_name='worker-grouping',
params={'key': experiment.key()})
experiment.second_stage_started = datetime.now()
experiment.put()