def tasks(self, request, pk=None):
"""
get:
Get task list for view
Retrieve a list of tasks with pagination for a specific view using filters and ordering.
"""
view = self.get_object()
queryset = self.get_task_queryset(request, view)
context = {'proxy': bool_from_request(request.GET, 'proxy', True), 'resolve_uri': True, 'request': request}
project = view.project
# paginated tasks
self.pagination_class = TaskPagination
page = self.paginate_queryset(queryset)
if page is not None:
# retrieve ML predictions if tasks don't have them
if project.evaluate_predictions_automatically:
ids = [task.id for task in page] # page is a list already
tasks_for_predictions = Task.objects.filter(id__in=ids, predictions__isnull=True)
evaluate_predictions(tasks_for_predictions)
serializer = self.task_serializer_class(page, many=True, context=context)
return self.get_paginated_response(serializer.data)
# all tasks
if project.evaluate_predictions_automatically:
evaluate_predictions(queryset.filter(predictions__isnull=True))
serializer = self.task_serializer_class(queryset, many=True, context=context)
return Response(serializer.data)
def get(self, request, pk):
"""
get:
Task by ID
Retrieve a specific task by ID.
"""
task = Task.prepared.get(id=pk)
context = {
'proxy': bool_from_request(request.GET, 'proxy', True),
'resolve_uri': True,
'completed_by': 'full',
'request': request
}
# get prediction
if task.project.evaluate_predictions_automatically and not task.predictions.exists(
):
evaluate_predictions([task])
serializer = self.get_serializer_class()(task,
many=False,
context=context)
data = serializer.data
return Response(data)
def test_core_bool_from_request(param, result):
params = {'test': param} if param is not None else {}
# incorrect param should call exception
if result is None:
error = False
try:
bool_from_request(params, 'test', 0)
except:
error = True
assert error
# everything ok
else:
assert bool_from_request(params, 'test', 0) == result
def tasks(self, request, pk=None):
"""
get:
Get task list for view
Retrieve a list of tasks with pagination for a specific view using filters and ordering.
"""
view = self.get_object()
queryset = Task.prepared.all(
prepare_params=view.get_prepare_tasks_params())
context = {
'proxy': bool_from_request(request.GET, 'proxy', True),
'resolve_uri': True
}
# paginated tasks
self.pagination_class = TaskPagination
page = self.paginate_queryset(queryset)
if page is not None:
self.evaluate_predictions(page)
serializer = self.task_serializer_class(page,
many=True,
context=context)
return self.get_paginated_response(serializer.data)
# all tasks
self.evaluate_predictions(queryset)
serializer = self.task_serializer_class(queryset,
many=True,
context=context)
return Response(serializer.data)
def perform_create(self, ser):
task = get_object_with_check_and_log(self.request,
Task,
pk=self.kwargs['pk'])
# annotator has write access only to annotations and it can't be checked it after serializer.save()
user = self.request.user
# updates history
result = ser.validated_data.get('result')
extra_args = {'task_id': self.kwargs['pk']}
# save stats about how well annotator annotations coincide with current prediction
# only for finished task annotations
if result is not None:
prediction = Prediction.objects.filter(
task=task, model_version=task.project.model_version)
if prediction.exists():
prediction = prediction.first()
prediction_ser = PredictionSerializer(prediction).data
else:
logger.debug(
f'User={self.request.user}: there are no predictions for task={task}'
)
prediction_ser = {}
# serialize annotation
extra_args.update({
'prediction': prediction_ser,
})
if 'was_cancelled' in self.request.GET:
extra_args['was_cancelled'] = bool_from_request(
self.request.GET, 'was_cancelled', False)
if 'completed_by' not in ser.validated_data:
extra_args['completed_by'] = self.request.user
# create annotation
logger.debug(f'User={self.request.user}: save annotation')
annotation = ser.save(**extra_args)
logger.debug(f'Save activity for user={self.request.user}')
self.request.user.activity_at = timezone.now()
self.request.user.save()
# Release task if it has been taken at work (it should be taken by the same user, or it makes sentry error
logger.debug(f'User={user} releases task={task}')
task.release_lock(user)
# if annotation created from draft - remove this draft
draft_id = self.request.data.get('draft_id')
if draft_id is not None:
logger.debug(
f'Remove draft {draft_id} after creating annotation {annotation.id}'
)
AnnotationDraft.objects.filter(id=draft_id).delete()
if self.request.data.get('ground_truth'):
annotation.task.ensure_unique_groundtruth(
annotation_id=annotation.id)
return annotation
def _make_response(self, next_task, request, use_task_lock=True):
"""Once next task has chosen, this function triggers inference and prepare the API response"""
user = request.user
project = next_task.project
if use_task_lock:
# set lock for the task with TTL 3x time more then current average lead time (or 1 hour by default)
next_task.set_lock(request.user)
# call machine learning api and format response
if project.show_collab_predictions:
for ml_backend in project.ml_backends.all():
ml_backend.predict_one_task(next_task)
# serialize task
context = {
'request': request,
'project': project,
'resolve_uri': True,
'proxy': bool_from_request(request.GET, 'proxy', True)
}
serializer = TaskWithAnnotationsAndPredictionsAndDraftsSerializer(
next_task, context=context)
response = serializer.data
annotations = []
for c in response.get('annotations', []):
if c.get('completed_by') == user.id and not (c.get('ground_truth')
or c.get('honeypot')):
annotations.append(c)
response['annotations'] = annotations
return Response(response)
def retrieve(self, request, *args, **kwargs):
task = self.get_object()
result = self.get_serializer(task).data
# use proxy inlining to task data (for credential access)
proxy = bool_from_request(request.GET, 'proxy', True)
result['data'] = task.resolve_uri(result['data'], proxy=proxy)
return Response(result)
def get_serializer_context(request):
return {
'proxy': bool_from_request(request.GET, 'proxy', True),
'resolve_uri': True,
'completed_by': 'full',
'drafts': True,
'predictions': True,
'annotations': True,
'request': request
}
def create(self, request, *args, **kwargs):
start = time.time()
files_as_tasks_list = bool_from_request(request.data,
'files_as_tasks_list', True)
file_upload_ids = self.request.data.get('file_upload_ids')
# check project permissions
project = generics.get_object_or_404(Project.objects.for_user(
self.request.user),
pk=self.kwargs['pk'])
if not file_upload_ids:
return Response(
{
'task_count': 0,
'annotation_count': 0,
'prediction_count': 0,
'duration': 0,
'file_upload_ids': [],
'found_formats': {},
'data_columns': []
},
status=status.HTTP_204_NO_CONTENT)
tasks, found_formats, data_columns = FileUpload.load_tasks_from_uploaded_files(
project, file_upload_ids, files_as_tasks_list=files_as_tasks_list)
with transaction.atomic():
project.remove_tasks_by_file_uploads(file_upload_ids)
tasks, serializer = self._save(tasks)
duration = time.time() - start
# Update task states if there are related settings in project
# after bulk create we can bulk update task stats with
# flag_update_stats=True but they are already updated with signal in same transaction
# so just update tasks_number_changed
project.update_tasks_states(maximum_annotations_changed=False,
overlap_cohort_percentage_changed=False,
tasks_number_changed=True)
logger.info('Tasks bulk_update finished')
project.summary.update_data_columns(tasks)
# TODO: project.summary.update_created_annotations_and_labels
return Response(
{
'task_count': len(tasks),
'annotation_count': len(serializer.db_annotations),
'prediction_count': len(serializer.db_predictions),
'duration': duration,
'file_upload_ids': file_upload_ids,
'found_formats': found_formats,
'data_columns': data_columns
},
status=status.HTTP_201_CREATED)
def get(self, request, *args, **kwargs):
project = self.get_object()
export_type = (request.GET.get('exportType', 'JSON')
if 'exportType' in request.GET else request.GET.get(
'export_type', 'JSON'))
only_finished = not bool_from_request(request.GET,
'download_all_tasks', False)
tasks_ids = request.GET.getlist('ids[]')
if 'download_resources' in request.GET:
download_resources = bool_from_request(request.GET,
'download_resources', True)
else:
download_resources = settings.CONVERTER_DOWNLOAD_RESOURCES
logger.debug('Get tasks')
tasks = Task.objects.filter(project=project)
if tasks_ids and len(tasks_ids) > 0:
logger.debug(f'Select only subset of {len(tasks_ids)} tasks')
tasks = tasks.filter(id__in=tasks_ids)
query = tasks.select_related('project').prefetch_related(
'annotations', 'predictions')
if only_finished:
query = query.filter(annotations__isnull=False).distinct()
task_ids = query.values_list('id', flat=True)
logger.debug('Serialize tasks for export')
tasks = []
for _task_ids in batch(task_ids, 1000):
tasks += ExportDataSerializer(query.filter(id__in=_task_ids),
many=True,
expand=['drafts']).data
logger.debug('Prepare export files')
export_stream, content_type, filename = DataExport.generate_export_file(
project, tasks, export_type, download_resources, request.GET)
response = HttpResponse(File(export_stream), content_type=content_type)
response[
'Content-Disposition'] = 'attachment; filename="%s"' % filename
response['filename'] = filename
return response
def create(self, request, *args, **kwargs):
start = time.time()
commit_to_project = bool_from_request(request.query_params,
'commit_to_project', True)
# check project permissions
project = generics.get_object_or_404(Project.objects.for_user(
self.request.user),
pk=self.kwargs['pk'])
# upload files from request, and parse all tasks
parsed_data, file_upload_ids, could_be_tasks_lists, found_formats, data_columns = load_tasks(
request, project)
if commit_to_project:
# Immediately create project tasks and update project states and counters
tasks, serializer = self._save(parsed_data)
task_count = len(tasks)
annotation_count = len(serializer.db_annotations)
prediction_count = len(serializer.db_predictions)
# Update tasks states if there are related settings in project
# after bulk create we can bulk update tasks stats with
# flag_update_stats=True but they are already updated with signal in same transaction
# so just update tasks_number_changed
project.update_tasks_states(
maximum_annotations_changed=False,
overlap_cohort_percentage_changed=False,
tasks_number_changed=True)
logger.info('Tasks bulk_update finished')
project.summary.update_data_columns(parsed_data)
# TODO: project.summary.update_created_annotations_and_labels
else:
# Do nothing - just output file upload ids for further use
task_count = len(parsed_data)
annotation_count = None
prediction_count = None
duration = time.time() - start
return Response(
{
'task_count': task_count,
'annotation_count': annotation_count,
'prediction_count': prediction_count,
'duration': duration,
'file_upload_ids': file_upload_ids,
'could_be_tasks_list': could_be_tasks_lists,
'found_formats': found_formats,
'data_columns': data_columns
},
status=status.HTTP_201_CREATED)
def get(self, request, *args, **kwargs):
project = get_object_with_permissions(request, Project, kwargs['pk'], 'projects.change_project')
title = request.GET.get('title', '')
title = project.title if not title else title
title = generate_unique_title(request.user, title)
duplicate_tasks = bool_from_request(request.GET, 'duplicate_tasks', default=False)
try:
project = duplicate_project(project, title, duplicate_tasks, request.user)
except Exception as e:
raise ValueError(f"Can't duplicate project: {e}")
return Response({'id': project.pk}, status=status.HTTP_200_OK)
def retrieve(self, request, *args, **kwargs):
task = self.get_object()
# call machine learning api and format response
if task.project.evaluate_predictions_automatically:
for ml_backend in task.project.ml_backends.all():
ml_backend.predict_one_task(task)
result = self.get_serializer(task).data
# use proxy inlining to task data (for credential access)
proxy = bool_from_request(request.GET, 'proxy', True)
result['data'] = task.resolve_uri(result['data'], proxy=proxy)
return Response(result)
def get(self, request, pk):
"""
get:
Task by ID
Retrieve a specific task by ID.
"""
queryset = Task.prepared.get(id=pk)
context = {
'proxy': bool_from_request(request.GET, 'proxy', True),
'resolve_uri': True,
'completed_by': 'full'
}
serializer = self.serializer_class(queryset, many=False, context=context)
return Response(serializer.data)
def get_queryset(self):
review = bool_from_request(self.request.GET, 'review', False)
selected = {"all": False, "included": [self.kwargs.get("pk")]}
if review:
kwargs = {'fields_for_evaluation': ['annotators', 'reviewed']}
else:
kwargs = {'all_fields': True}
project = self.request.query_params.get(
'project') or self.request.data.get('project')
if not project:
project = Task.objects.get(
id=self.request.parser_context['kwargs'].get('pk')).project.id
return self.prefetch(
Task.prepared.get_queryset(prepare_params=PrepareParams(
project=project, selectedItems=selected),
**kwargs))
def get(self, request, *args, **kwargs):
project = self.get_object()
export_type = request.GET.get('exportType')
is_labeled = not bool_from_request(request.GET, 'download_all_tasks', False)
logger.debug('Get tasks')
query = Task.objects.filter(project=project, is_labeled=is_labeled)
logger.debug('Serialize tasks for export')
tasks = ExportDataSerializer(query, many=True).data
logger.debug('Prepare export files')
export_stream, content_type, filename = DataExport.generate_export_file(project, tasks, export_type, request.GET)
response = HttpResponse(File(export_stream), content_type=content_type)
response['Content-Disposition'] = 'attachment; filename="%s"' % filename
response['filename'] = filename
return response
def get_task_serializer_context(request, project):
storage = find_first_many_to_one_related_field_by_prefix(
project, '.*io_storages.*')
resolve_uri = True
if not storage and not project.task_data_login and not project.task_data_password:
resolve_uri = False
all_fields = request.GET.get('fields',
None) == 'all' # false by default
return {
'proxy': bool_from_request(request.GET, 'proxy', True),
'resolve_uri': resolve_uri,
'request': request,
'project': project,
'drafts': all_fields,
'predictions': all_fields,
'annotations': all_fields
}
def get(self, request, *args, **kwargs):
project = self.get_object()
export_type = request.GET.get('exportType')
only_finished = not bool_from_request(request.GET, 'download_all_tasks', False)
logger.debug('Get tasks')
query = Task.objects.filter(project=project).select_related('project').prefetch_related('annotations', 'predictions')
if only_finished:
query = query.filter(annotations__isnull=False).distinct()
task_ids = query.values_list('id', flat=True)
logger.debug('Serialize tasks for export')
tasks = []
for _task_ids in batch(task_ids, 1000):
tasks += ExportDataSerializer(query.filter(id__in=_task_ids), many=True).data
logger.debug('Prepare export files')
export_stream, content_type, filename = DataExport.generate_export_file(project, tasks, export_type, request.GET)
response = HttpResponse(File(export_stream), content_type=content_type)
response['Content-Disposition'] = 'attachment; filename="%s"' % filename
response['filename'] = filename
return response
def get(self, request):
# get project
view_pk = int_from_request(request.GET, 'view', 0) or int_from_request(request.data, 'view', 0)
project_pk = int_from_request(request.GET, 'project', 0) or int_from_request(request.data, 'project', 0)
if project_pk:
project = get_object_with_check_and_log(request, Project, pk=project_pk)
self.check_object_permissions(request, project)
elif view_pk:
view = get_object_with_check_and_log(request, View, pk=view_pk)
project = view.project
self.check_object_permissions(request, project)
else:
return Response({'detail': 'Neither project nor view id specified'}, status=404)
# get prepare params (from view or from payload directly)
prepare_params = get_prepare_params(request, project)
queryset = self.get_task_queryset(request, prepare_params)
context = self.get_task_serializer_context(self.request, project)
# paginated tasks
self.pagination_class = TaskPagination
page = self.paginate_queryset(queryset)
all_fields = 'all' if request.GET.get('fields', None) == 'all' else None
fields_for_evaluation = get_fields_for_evaluation(prepare_params, request.user)
review = bool_from_request(self.request.GET, 'review', False)
if review:
fields_for_evaluation = ['annotators', 'reviewed']
all_fields = None
if page is not None:
ids = [task.id for task in page] # page is a list already
tasks = list(
self.prefetch(
Task.prepared.annotate_queryset(
Task.objects.filter(id__in=ids),
fields_for_evaluation=fields_for_evaluation,
all_fields=all_fields,
)
)
)
tasks_by_ids = {task.id: task for task in tasks}
# keep ids ordering
page = [tasks_by_ids[_id] for _id in ids]
# retrieve ML predictions if tasks don't have them
if not review and project.evaluate_predictions_automatically:
tasks_for_predictions = Task.objects.filter(id__in=ids, predictions__isnull=True)
evaluate_predictions(tasks_for_predictions)
serializer = self.task_serializer_class(page, many=True, context=context)
return self.get_paginated_response(serializer.data)
# all tasks
if project.evaluate_predictions_automatically:
evaluate_predictions(queryset.filter(predictions__isnull=True))
queryset = Task.prepared.annotate_queryset(
queryset, fields_for_evaluation=fields_for_evaluation, all_fields=all_fields
)
serializer = self.task_serializer_class(queryset, many=True, context=context)
return Response(serializer.data)
