Merge develop into master

.env_sample

@@ -59,6 +59,14 @@ AWS_STORAGE_PRIVATE_BUCKET_NAME=private
 AWS_S3_ENDPOINT_URL=http://minio:9000/
 AWS_QUERYSTRING_AUTH=False
 
+# -----------------------------------------------------------------------------
+# Limit for re-running submission
+# This is used to limit users to rerun submissions
+# on default queue when number of submissions are < RERUN_SUBMISSION_LIMIT
+# -----------------------------------------------------------------------------
+RERUN_SUBMISSION_LIMIT=30
+
+
 # # S3 storage example
 # STORAGE_TYPE=s3
 # AWS_ACCESS_KEY_ID=12312312312312312331223

compute_worker/compute_worker.py

@@ -26,9 +26,12 @@
 from kombu import Queue, Exchange
 from urllib3 import Retry
 
-
 logger = logging.getLogger()
 
+
+# -----------------------------------------------
+# Celery + Rabbit MQ
+# -----------------------------------------------
 # Init celery + rabbit queue definitions
 app = Celery()
 app.config_from_object('celery_config')  # grabs celery_config.py
@@ -38,13 +41,20 @@
 ]
 
 
+# -----------------------------------------------
+# Directories
+# -----------------------------------------------
 # Setup base directories used by all submissions
 # note: we need to pass this directory to docker-compose so it knows where to store things!
 HOST_DIRECTORY = os.environ.get("HOST_DIRECTORY", "/tmp/codabench/")
 BASE_DIR = "/codabench/"  # base directory inside the container
 CACHE_DIR = os.path.join(BASE_DIR, "cache")
 MAX_CACHE_DIR_SIZE_GB = float(os.environ.get('MAX_CACHE_DIR_SIZE_GB', 10))
 
+
+# -----------------------------------------------
+# Submission status
+# -----------------------------------------------
 # Status options for submissions
 STATUS_NONE = "None"
 STATUS_SUBMITTING = "Submitting"
@@ -65,6 +75,10 @@
     STATUS_FAILED,
 )
 
+
+# -----------------------------------------------
+# Container Engine
+# -----------------------------------------------
 # Setup the container engine that we are using
 if os.environ.get("CONTAINER_ENGINE_EXECUTABLE"):
     CONTAINER_ENGINE_EXECUTABLE = os.environ.get("CONTAINER_ENGINE_EXECUTABLE")
@@ -75,9 +89,18 @@
     CONTAINER_ENGINE_EXECUTABLE = "docker"
 
 
+# -----------------------------------------------
+# Exceptions
+# -----------------------------------------------
 class SubmissionException(Exception):
     pass
 
+class DockerImagePullException(Exception):
+    pass
+
+class ExecutionTimeLimitExceeded(Exception):
+    pass
+
 
 # -----------------------------------------------------------------------------
 # The main compute worker entrypoint, this is how a job is ran at the highest
@@ -94,6 +117,8 @@ def run_wrapper(run_args):
         if run.is_scoring:
             run.push_scores()
         run.push_output()
+    except DockerImagePullException as e:
+        run._update_status(STATUS_FAILED, str(e))
     except SubmissionException as e:
         run._update_status(STATUS_FAILED, str(e))
     except SoftTimeLimitExceeded:
@@ -160,14 +185,14 @@ def is_valid_zip(zip_path):
         return False
 
 
-class ExecutionTimeLimitExceeded(Exception):
-    pass
-
-
 def alarm_handler(signum, frame):
     raise ExecutionTimeLimitExceeded
 
 
+# -----------------------------------------------
+# Class Run
+# Respnosible for running a submission inside a docker container
+# -----------------------------------------------
 class Run:
     """A "Run" in Codalab is composed of some program, some data to work with, and some signed URLs to upload results
     to. There is also a secret key to do special commands for just this submission.
@@ -340,8 +365,55 @@ def _get_container_image(self, image_name):
             container_engine_pull = check_output(cmd)
             logger.info("Pull complete for image: {0} with output of {1}".format(image_name, container_engine_pull))
         except CalledProcessError:
-            logger.info("Pull for image: {} returned a non-zero exit code!")
-            raise SubmissionException(f"Pull for {image_name} failed!")
+            error_message = f"Pull for image: {image_name} returned a non-zero exit code! Check if the docker image exists on docker hub."
+            logger.info(error_message)
+            # Prepare data to be sent to submissions api
+            docker_pull_fail_data = {
+                "type": "Docker_Image_Pull_Fail",
+                "error_message": error_message,
+            }
+            # Send data to be written to ingestion logs
+            self._update_submission(docker_pull_fail_data)
+            # Send error through web socket to the frontend
+            asyncio.run(self._send_data_through_socket(error_message))
+            raise DockerImagePullException(f"Pull for {image_name} failed!")
+
+    async def _send_data_through_socket(self, error_message):
+        """
+        This function gets an error messages and sends it through a web socket. This function is used for sending
+        - Docker image pull failure logs
+        - Execution time limit exceeded logs
+        """
+        logger.info(f"Connecting to {self.websocket_url} to send docker image pull error")
+
+        # connect to web socket
+        websocket = await websockets.connect(self.websocket_url)
+
+        # define websocket errors
+        websocket_errors = (socket.gaierror, websockets.WebSocketException, websockets.ConnectionClosedError, ConnectionRefusedError)
+
+        try:
+            # send message
+            await websocket.send(json.dumps({
+                "kind": "stderr",
+                "message": error_message
+            }))
+
+        except websocket_errors:
+            # handle websocket errors
+            logger.info(f"Error sending failed through websocket")
+            try:
+                await websocket.close()
+            except Exception as e:
+                logger.error(e)
+        else:
+            # no error in websocket message sending
+            logger.info(f"Error sent successfully through websocket")
+
+        logger.info(f"Disconnecting from websocket {self.websocket_url}")
+
+        # close websocket
+        await websocket.close()
 
     def _get_bundle(self, url, destination, cache=True):
         """Downloads zip from url and unzips into destination. If cache=True then url is hashed and checked
@@ -384,7 +456,7 @@ def _get_bundle(self, url, destination, cache=True):
                     raise  # Re-raise the last caught BadZipFile exception
                 else:
                     logger.info("Failed. Retrying in 60 seconds...")
-                    time.sleep(60) # Wait 60 seconds before retrying
+                    time.sleep(60)  # Wait 60 seconds before retrying
         # Return the zip file path for other uses, e.g. for creating a MD5 hash to identify it
         return bundle_file
 
@@ -627,7 +699,7 @@ def _put_file(self, url, file=None, raw_data=None, content_type='application/zip
         """
         if file and raw_data:
             raise Exception("Cannot put both a file and raw_data")
-        
+
         headers = {
             # For Azure only, other systems ignore these headers
             'x-ms-blob-type': 'BlockBlob',
@@ -731,7 +803,19 @@ def start(self):
         try:
             loop.run_until_complete(gathered_tasks)
         except ExecutionTimeLimitExceeded:
-            raise SubmissionException(f"Execution Time Limit exceeded. Limit was {self.execution_time_limit} seconds")
+            error_message = f"Execution Time Limit exceeded. Limit was {self.execution_time_limit} seconds"
+            logger.info(error_message)
+            # Prepare data to be sent to submissions api
+            execution_time_limit_exceeded_data = {
+                "type": "Execution_Time_Limit_Exceeded",
+                "error_message": error_message,
+                "is_scoring": self.is_scoring
+            }
+            # Send data to be written to ingestion/scoring std_err
+            self._update_submission(execution_time_limit_exceeded_data)
+            # Send error through web socket to the frontend
+            asyncio.run(self._send_data_through_socket(error_message))
+            raise SubmissionException(error_message)
         finally:
             self.watch = False
             for kind, logs in self.logs.items():

docker-compose.yml

@@ -126,7 +126,7 @@ services:
   #   Rabbitmq & Flower monitoring tool
   #-----------------------------------------------
   rabbit:
-    image: rabbitmq:3.6-management
+    image: rabbitmq:management
     # setting hostname here makes data persist properly between
     # containers being destroyed..!
     hostname: rabbit

requirements.txt

@@ -26,6 +26,7 @@ bleach==3.1.4
 # Heroku staging debug tools
 django-debug-toolbar==3.2
 django-querycount==0.7.0
+blessings==1.7
 
 # User impersonation
 django-su==0.9.0

src/apps/api/serializers/tasks.py

@@ -138,6 +138,7 @@ class Meta:
         fields = (
             'id',
             'created_when',
+            'created_by',
             'key',
             'name',
             'solutions',

src/apps/api/views/competitions.py

@@ -38,6 +38,7 @@
 from api.permissions import IsOrganizerOrCollaborator
 from datetime import datetime
 from django.db import transaction
+from django.conf import settings
 
 
 class CompetitionViewSet(ModelViewSet):
@@ -614,15 +615,56 @@ def manually_migrate(self, request, pk):
 
     @action(detail=True, url_name='rerun_submissions')
     def rerun_submissions(self, request, pk):
+
         phase = self.get_object()
         comp = phase.competition
-        if request.user not in comp.all_organizers and not request.user.is_superuser:
-            raise PermissionDenied('You do not have permission to re-run submissions')
+
+        # Get submissions
         submissions = phase.submissions.all()
-        for submission in submissions:
-            submission.re_run()
-        rerun_count = len(submissions)
-        return Response({"count": rerun_count})
+
+        can_re_run_submissions = False
+        error_message = ""
+
+        # Super admin can rerun without any restrictions
+        if request.user.is_superuser:
+            can_re_run_submissions = True
+
+        # competition admin can run only if
+        elif request.user in comp.all_organizers:
+
+            # submissions are in limit
+            if len(submissions) <= int(settings.RERUN_SUBMISSION_LIMIT):
+                can_re_run_submissions = True
+
+            # submissions are not in limit
+            else:
+                # Codabemch public queue
+                if comp.queue is None:
+                    can_re_run_submissions = False
+                    error_message = f"You cannot rerun more than {settings.RERUN_SUBMISSION_LIMIT} submissions on Codabench public queue! Contact us on `info@codalab.org` to request a rerun."
+
+                # Other queue where user is not owner and not organizer
+                elif request.user != comp.queue.owner and request.user not in comp.queue.organizers.all():
+                    can_re_run_submissions = False
+                    error_message = f"You cannot rerun more than {settings.RERUN_SUBMISSION_LIMIT} submissions on a queue which is not yours! Contact us on `info@codalab.org` to request a rerun."
+
+                # User can rerun submissions where he is owner or organizer
+                else:
+                    can_re_run_submissions = True
+
+        else:
+            can_re_run_submissions = False
+            error_message = 'You do not have permission to re-run submissions'
+
+        # error when user is not super user or admin of the competition
+        if can_re_run_submissions:
+            # rerun all submissions
+            for submission in submissions:
+                submission.re_run()
+            rerun_count = len(submissions)
+            return Response({"count": rerun_count})
+        else:
+            raise PermissionDenied(error_message)
 
     @swagger_auto_schema(responses={200: PhaseResultsSerializer})
     @action(detail=True, methods=['GET'])

src/apps/api/views/submissions.py

@@ -1,5 +1,6 @@
 import json
 import uuid
+import logging
 
 from django.db.models import Q
 from django_filters.rest_framework import DjangoFilterBackend
@@ -14,14 +15,17 @@
 from rest_framework.settings import api_settings
 from rest_framework.viewsets import ModelViewSet
 from rest_framework_csv import renderers
+from django.core.files.base import ContentFile
 
 from profiles.models import Organization, Membership
 from tasks.models import Task
 from api.serializers.submissions import SubmissionCreationSerializer, SubmissionSerializer, SubmissionFilesSerializer
-from competitions.models import Submission, Phase, CompetitionParticipant
+from competitions.models import Submission, SubmissionDetails, Phase, CompetitionParticipant
 from leaderboards.strategies import put_on_leaderboard_by_submission_rule
 from leaderboards.models import SubmissionScore, Column, Leaderboard
 
+logger = logging.getLogger()
+
 
 class SubmissionViewSet(ModelViewSet):
     queryset = Submission.objects.all().order_by('-pk')
@@ -50,6 +54,44 @@ def check_object_permissions(self, request, obj):
                     hostname = request.data['status_details'].replace('scoring_hostname-', '')
                     obj.scoring_worker_hostname = hostname
                     obj.save()
+
+            # check if type is in request data. type can have the following values
+            # - Docker_Image_Pull_Fail
+            # - Execution_Time_Limit_Exceeded
+            if "type" in self.request.data.keys():
+
+                if request.data["type"] in ["Docker_Image_Pull_Fail", "Execution_Time_Limit_Exceeded"]:
+
+                    # Get the error message
+                    error_message = request.data['error_message']
+
+                    # Set file name to ingestion std error as default
+                    error_file_name = "prediction_ingestion_stderr"
+
+                    # Change error file name when error comes from execution time limit
+                    # and error occured during scoring
+                    if request.data["type"] == "Execution_Time_Limit_Exceeded" and request.data['is_scoring'] == "True":
+                        error_file_name = "scoring_stderr"
+
+                    try:
+                        # Get submission detail for this submission
+                        submission_detail = SubmissionDetails.objects.get(
+                            name=error_file_name,
+                            submission=obj,
+                        )
+
+                        # Read the existing content from the file
+                        existing_content = submission_detail.data_file.read().decode("utf-8")
+
+                        # Append the new error message to the existing content
+                        modified_content = existing_content + "\n" + error_message
+
+                        # write error message to the file
+                        submission_detail.data_file.save(submission_detail.data_file.name, ContentFile(modified_content.encode("utf-8")))
+
+                    except SubmissionDetails.DoesNotExist:
+                        logger.warning("SubmissionDetails object not found.")
+
             not_bot_user = self.request.user.is_authenticated and not self.request.user.is_bot
 
             if self.action in ['update_fact_sheet', 're_run_submission']:

src/settings/base.py

@@ -450,3 +450,10 @@
 # Django-Su (User impersonation)
 SU_LOGIN_CALLBACK = 'profiles.admin.su_login_callback'
 AJAX_LOOKUP_CHANNELS = {'django_su': dict(model='profiles.User', search_field='username')}
+
+# =============================================================================
+# Limit for re-running submission
+# This is used to limit users to rerun submissions
+# on default queue when number of submissions are < RERUN_SUBMISSION_LIMIT
+# =============================================================================
+RERUN_SUBMISSION_LIMIT = os.environ.get('RERUN_SUBMISSION_LIMIT', 30)

src/static/riot/competitions/detail/_tabs.tag

@@ -60,7 +60,12 @@
                                         <th>Phase</th>
                                         <th>Task</th>
                                         <th>Type</th>
-                                        <th>Available</th>
+                                        <th>Available <span class="ui mini circular icon button"
+                                                          data-tooltip="Available for download to participants."
+                                                          data-position="top center">
+                                                          <i class="question icon"></i>
+                                                      </span>
+                                        </th>
                                         <th>Size</th>
                                     </tr>
                                     </thead>