def review_hits(self, print_assignment):
"""Interactively reject/approve all HITs associated with this task."""
hits = list(self.get_reviewable_hits())
worker_to_assignments = defaultdict(list)
assignments_batch = parallel_call(self._mtc.get_assignments, [hit.HITId for hit in hits])
for assignments in assignments_batch:
for assignment in assignments:
worker_to_assignments[assignment.WorkerId].append(assignment)
def approve(assignment):
self._mtc.approve_assignment(assignment.AssignmentId)
try:
self._mtc.dispose_hit(assignment.HITId)
except MTurkRequestError:
print('Failed to dispose HIT {}'.format(assignment.HITId))
raise
total_workers = len(worker_to_assignments)
for i, (worker, assignments) in enumerate(worker_to_assignments.items()):
print("Answers of worker {} ({} of {}, completed {} HITs):".format(worker, i+1, total_workers,
len(assignments)))
while True:
assignment = random.choice(assignments)
print_assignment(assignment)
answer = self._prompt_yes_no_more()
if answer == "y":
parallel_call(approve, assignments)
print("Approved all assignments for this worker")
break
elif answer == "n":
print("Did not approve assignments for this worker")
break
print("\n----- ----- ----- ----- ----- ----- ----- ----- ----- ----- \n")
def disable_hits(self):
"""Disable all HITs associated with this task.
WARNING: approves all submitted assignments that have not already been approved or rejected.
"""
hits = list(self.get_hits())
hit_ids = [hit.HITId for hit in hits]
parallel_call(self._mtc.disable_hit, hit_ids)
def expire_hits(self):
"""Expire all HITs associated with this task.
The task will no longer appear in the marketplace.
But the HITs and their assignments will still exist on MTurk, awaiting approval/rejection.
"""
hits = list(self.get_hits())
hit_ids = [hit.HITId for hit in hits]
parallel_call(self._mtc.expire_hit, hit_ids)
def launch(self, example_uids):
"""Launch task.
Args:
example_uids (list[str]): list of example_uids to launch the task with
"""
batches = list(chunks(example_uids, self._batch_size))
total_hits = len(batches)
assert isinstance(self._price_per_hit, float)
total_cost = total_hits * self._price_per_hit
print('Launching {} HITs (${}). Type Enter to continue.'.format(total_hits, total_cost))
input()
parallel_call(self.create_hit, batches)
def get_all_assignments(self, hits=[]):
assignments = []
assignments_batch = parallel_call(self._mtc.get_assignments,
[hit.HITId for hit in hits])
for assignments in assignments_batch:
for assignment in assignments:
assignments.append(assignments)
return assignments
