def build_job(self, session):
"""Produce the Job for this operation.
Return the Job object that has to be sent to Workers to have
them perform the operation this object describes.
session (Session): the database session to use to fetch objects
if necessary.
return (Job): the job encoding of the operation, as understood
by Workers and TaskTypes.
"""
result = None
dataset = Dataset.get_from_id(self.dataset_id, session)
if self.type_ == ESOperation.COMPILATION:
submission = Submission.get_from_id(self.object_id, session)
result = CompilationJob.from_submission(submission, dataset)
elif self.type_ == ESOperation.EVALUATION:
submission = Submission.get_from_id(self.object_id, session)
result = EvaluationJob.from_submission(
submission, dataset, self.testcase_codename)
elif self.type_ == ESOperation.USER_TEST_COMPILATION:
user_test = UserTest.get_from_id(self.object_id, session)
result = CompilationJob.from_user_test(user_test, dataset)
elif self.type_ == ESOperation.USER_TEST_EVALUATION:
user_test = UserTest.get_from_id(self.object_id, session)
result = EvaluationJob.from_user_test(user_test, dataset)
return result
def submission_tokened(self, submission_id):
"""Notice that a submission has been tokened.
Usually called by ContestWebServer when it's processing a token
request of an user. Since we don't trust anyone we verify that,
and then send data about the token to the rankings.
submission_id (int): the id of the submission that changed.
"""
with SessionGen() as session:
submission = Submission.get_from_id(submission_id, session)
if submission is None:
logger.error("[submission_tokened] Received token request for "
"unexistent submission id %s." % submission_id)
raise KeyError("Submission not found.")
if submission.user.hidden:
logger.info("[submission_tokened] Token for submission %d "
"not sent because user is hidden." % submission_id)
return
# Update RWS.
self.send_token(submission)
def submission_scored(self, submission_id):
"""Notice that a submission has been scored.
Usually called by ScoringService when it's done with scoring a
submission result. Since we don't trust anyone we verify that,
and then send data about the score to the rankings.
submission_id (int): the id of the submission that changed.
dataset_id (int): the id of the dataset to use.
"""
with SessionGen() as session:
submission = Submission.get_from_id(submission_id, session)
if submission is None:
logger.error("[submission_scored] Received score request for "
"unexistent submission id %s." % submission_id)
raise KeyError("Submission not found.")
if submission.user.hidden:
logger.info("[submission_scored] Score for submission %d "
"not sent because user is hidden." % submission_id)
return
# Update RWS.
self.send_score(submission)
def execute(self, entry):
"""Assign a score to a submission result.
This is the core of ScoringService: here we retrieve the result
from the database, check if it is in the correct status,
instantiate its ScoreType, compute its score, store it back in
the database and tell ProxyService to update RWS if needed.
entry (QueueEntry): entry containing the operation to perform.
"""
operation = entry.item
with SessionGen() as session:
# Obtain submission.
submission = Submission.get_from_id(operation.submission_id, session)
if submission is None:
raise ValueError("Submission %d not found in the database." % operation.submission_id)
# Obtain dataset.
dataset = Dataset.get_from_id(operation.dataset_id, session)
if dataset is None:
raise ValueError("Dataset %d not found in the database." % operation.dataset_id)
# Obtain submission result.
submission_result = submission.get_result(dataset)
# It means it was not even compiled (for some reason).
if submission_result is None:
raise ValueError(
"Submission result %d(%d) was not found." % (operation.submission_id, operation.dataset_id)
)
# Check if it's ready to be scored.
if not submission_result.needs_scoring():
if submission_result.scored():
logger.info(
"Submission result %d(%d) is already scored.", operation.submission_id, operation.dataset_id
)
return
else:
raise ValueError(
"The state of the submission result "
"%d(%d) doesn't allow scoring." % (operation.submission_id, operation.dataset_id)
)
# Instantiate the score type.
score_type = get_score_type(dataset=dataset)
# Compute score and fill it in the database.
submission_result.score, submission_result.score_details, submission_result.public_score, submission_result.public_score_details, submission_result.ranking_score_details = score_type.compute_score(
submission_result
)
# Store it.
session.commit()
# If dataset is the active one, update RWS.
if dataset is submission.task.active_dataset:
self.proxy_service.submission_scored(submission_id=submission.id)
def acquire_worker(self, operations):
"""Tries to assign an operation to an available worker. If no workers
are available then this returns None, otherwise this returns
the chosen worker.
operations ([ESOperation]): the operations to assign to a worker.
return (int|None): None if no workers are available, the worker
assigned to the operation otherwise.
"""
# We look for an available worker.
try:
shard = self.find_worker(WorkerPool.WORKER_INACTIVE,
require_connection=True,
random_worker=True)
except LookupError:
self._workers_available_event.clear()
return None
# Then we fill the info for future memory.
self._add_operations(shard, operations)
logger.debug("Worker %s acquired.", shard)
self._start_time[shard] = make_datetime()
with SessionGen() as session:
jobs = []
datasets = {}
submissions = {}
user_tests = {}
for operation in operations:
if operation.dataset_id not in datasets:
datasets[operation.dataset_id] = Dataset.get_from_id(
operation.dataset_id, session)
object_ = None
if operation.for_submission():
if operation.object_id not in submissions:
submissions[operation.object_id] = \
Submission.get_from_id(
operation.object_id, session)
object_ = submissions[operation.object_id]
else:
if operation.object_id not in user_tests:
user_tests[operation.object_id] = \
UserTest.get_from_id(operation.object_id, session)
object_ = user_tests[operation.object_id]
logger.info("Asking worker %s to `%s'.", shard, operation)
jobs.append(Job.from_operation(
operation, object_, datasets[operation.dataset_id]))
job_group_dict = JobGroup(jobs).export_to_dict()
self._worker[shard].execute_job_group(
job_group_dict=job_group_dict,
callback=self._service.action_finished,
plus=shard)
return shard
def new_submission(self, submission_id):
"""This RPC prompts ES of the existence of a new
submission. ES takes the right countermeasures, i.e., it
schedules it for compilation.
submission_id (int): the id of the new submission.
"""
with SessionGen() as session:
submission = Submission.get_from_id(submission_id, session)
if submission is None:
logger.error("[new_submission] Couldn't find submission "
"%d in the database.", submission_id)
return
self.submission_enqueue_operations(submission)
session.commit()
def submission_tokened(self, submission_id):
"""This RPC inform ScoringService that the user has played the
token on a submission.
submission_id (int): the id of the submission that changed.
timestamp (int): the time of the token.
"""
with SessionGen(commit=False) as session:
submission = Submission.get_from_id(submission_id, session)
if submission is None:
logger.error("[submission_tokened] Received token request for "
"unexistent submission id %s." % submission_id)
raise KeyError
if submission.user.hidden:
logger.info("[submission_tokened] Token for submission %d "
"not sent because user is hidden." % submission_id)
return
# Update RWS.
self.rankings_send_token(submission)
def write_results(self, items):
"""Receive worker results from the cache and writes them to the DB.
Grouping results together by object (i.e., submission result
or user test result) and type (compilation or evaluation)
allows this method to talk less to the DB, for example by
retrieving datasets and submission results only once instead
of once for every result.
items ([(operation, Result)]): the results received by ES but
not yet written to the db.
"""
logger.info("Starting commit process...")
# Reorganize the results by submission/usertest result and
# operation type (i.e., group together the testcase
# evaluations for the same submission and dataset).
by_object_and_type = defaultdict(list)
for operation, result in items:
t = (operation.type_, operation.object_id, operation.dataset_id)
by_object_and_type[t].append((operation, result))
with SessionGen() as session:
# Dictionary holding the objects we use repeatedly,
# indexed by id, to avoid querying them multiple times.
# TODO: this pattern is used in WorkerPool and should be
# abstracted away.
datasets = dict()
subs = dict()
srs = dict()
for key, operation_results in iteritems(by_object_and_type):
type_, object_id, dataset_id = key
# Get dataset.
if dataset_id not in datasets:
datasets[dataset_id] = session.query(Dataset)\
.filter(Dataset.id == dataset_id)\
.options(joinedload(Dataset.testcases))\
.first()
dataset = datasets[dataset_id]
if dataset is None:
logger.error("Could not find dataset %d in the database.",
dataset_id)
continue
# Get submission or user test, and their results.
if type_ in [ESOperation.COMPILATION, ESOperation.EVALUATION]:
if object_id not in subs:
subs[object_id] = \
Submission.get_from_id(object_id, session)
object_ = subs[object_id]
if object_ is None:
logger.error("Could not find submission %d "
"in the database.", object_id)
continue
result_id = (object_id, dataset_id)
if result_id not in srs:
srs[result_id] = object_.get_result_or_create(dataset)
object_result = srs[result_id]
else:
# We do not cache user tests as they can come up
# only once.
object_ = UserTest.get_from_id(object_id, session)
object_result = object_.get_result_or_create(dataset)
self.write_results_one_object_and_type(
session, object_result, operation_results)
logger.info("Committing evaluations...")
session.commit()
for type_, object_id, dataset_id in by_object_and_type:
if type_ == ESOperation.EVALUATION:
submission_result = srs[(object_id, dataset_id)]
dataset = datasets[dataset_id]
if len(submission_result.evaluations) == \
len(dataset.testcases):
submission_result.set_evaluation_outcome()
logger.info("Committing evaluation outcomes...")
session.commit()
logger.info("Ending operations for %s objects...",
len(by_object_and_type))
for type_, object_id, dataset_id in by_object_and_type:
if type_ == ESOperation.COMPILATION:
submission_result = srs[(object_id, dataset_id)]
self.compilation_ended(submission_result)
elif type_ == ESOperation.EVALUATION:
submission_result = srs[(object_id, dataset_id)]
if submission_result.evaluated():
self.evaluation_ended(submission_result)
elif type_ == ESOperation.USER_TEST_COMPILATION:
user_test_result = UserTest\
.get_from_id(object_id, session)\
.get_result(datasets[dataset_id])
self.user_test_compilation_ended(user_test_result)
elif type_ == ESOperation.USER_TEST_EVALUATION:
user_test_result = UserTest\
.get_from_id(object_id, session)\
.get_result(datasets[dataset_id])
self.user_test_evaluation_ended(user_test_result)
logger.info("Done")
def execute(self, entry):
"""Assign a score to a submission result.
This is the core of ScoringService: here we retrieve the result
from the database, check if it is in the correct status,
instantiate its ScoreType, compute its score, store it back in
the database and tell ProxyService to update RWS if needed.
entry (QueueEntry): entry containing the operation to perform.
"""
operation = entry.item
with SessionGen() as session:
# Obtain submission.
submission = Submission.get_from_id(operation.submission_id,
session)
if submission is None:
raise ValueError("Submission %d not found in the database." %
operation.submission_id)
# Obtain dataset.
dataset = Dataset.get_from_id(operation.dataset_id, session)
if dataset is None:
raise ValueError("Dataset %d not found in the database." %
operation.dataset_id)
# Obtain submission result.
submission_result = submission.get_result(dataset)
# It means it was not even compiled (for some reason).
if submission_result is None:
raise ValueError("Submission result %d(%d) was not found." %
(operation.submission_id,
operation.dataset_id))
# Check if it's ready to be scored.
if not submission_result.needs_scoring():
if submission_result.scored():
logger.info("Submission result %d(%d) is already scored.",
operation.submission_id, operation.dataset_id)
return
else:
raise ValueError("The state of the submission result "
"%d(%d) doesn't allow scoring." %
(operation.submission_id,
operation.dataset_id))
# Instantiate the score type.
score_type = get_score_type(dataset=dataset)
# Compute score and fill it in the database.
submission_result.score, \
submission_result.score_details, \
submission_result.public_score, \
submission_result.public_score_details, \
submission_result.ranking_score_details = \
score_type.compute_score(submission_result)
# Round submission score to 2 decimal places
submission_result.score = round(submission_result.score, 2)
# Store it.
session.commit()
# Update statistics and access level
score = submission_result.score
taskscore = session.query(TaskScore)\
.filter(TaskScore.user_id == submission.user_id)\
.filter(TaskScore.task_id == submission.task_id).first()
if taskscore is None:
taskscore = TaskScore()
taskscore.task_id = submission.task_id
taskscore.user_id = submission.user_id
session.add(taskscore)
mtime = max([0] + [e.execution_time
for e in submission_result.evaluations])
if score > taskscore.score:
taskscore.score = score
taskscore.time = mtime
elif score == taskscore.score and mtime < taskscore.time:
taskscore.time = mtime
submission.task.nsubscorrect = session.query(Submission)\
.filter(Submission.task_id == submission.task_id)\
.filter(Submission.results.any(
SubmissionResult.score == 100)).count()
submission.task.nuserscorrect = session.query(TaskScore)\
.filter(TaskScore.task_id == submission.task_id)\
.filter(TaskScore.score == 100).count()
submission.user.score = sum([
t.score for t in session.query(TaskScore)
.filter(TaskScore.user_id == submission.user_id).all()])
if submission.user.score >= 300 and \
submission.user.access_level == 6:
submission.user.access_level = 5
submission.task.nsubs = session.query(Submission)\
.filter(Submission.task_id == submission.task_id).count()
submission.task.nusers = session.query(TaskScore)\
.filter(TaskScore.task_id == submission.task_id).count()
session.commit()
# If dataset is the active one, update RWS.
if dataset is submission.task.active_dataset:
self.proxy_service.submission_scored(
submission_id=submission.id)
def new_evaluation(self, submission_id, dataset_id):
"""This RPC inform ScoringService that ES finished the work on
a submission (either because it has been evaluated, or because
the compilation failed).
submission_id (int): the id of the submission that changed.
dataset_id (int): the id of the dataset to use.
"""
with SessionGen(commit=True) as session:
submission = Submission.get_from_id(submission_id, session)
if submission is None:
logger.error("[new_evaluation] Couldn't find submission %d "
"in the database." % submission_id)
raise ValueError
if submission.user.hidden:
logger.info("[new_evaluation] Submission %d not scored "
"because user is hidden." % submission_id)
return
dataset = Dataset.get_from_id(dataset_id, session)
if dataset is None:
logger.error("[new_evaluation] Couldn't find dataset %d "
"in the database." % dataset_id)
raise ValueError
submission_result = submission.get_result(dataset)
# We'll accept only submissions that either didn't compile
# at all or that did evaluate successfully.
if submission_result is None or not submission_result.compiled():
logger.warning("[new_evaluation] Submission %d(%d) is "
"not compiled." % (submission_id, dataset_id))
return
elif submission_result.compilation_outcome == "ok" and \
not submission_result.evaluated():
logger.warning("[new_evaluation] Submission %d(%d) is "
"compiled but is not evaluated." %
(submission_id, dataset_id))
return
# Assign score to the submission.
score_type = get_score_type(dataset=dataset)
score, details, public_score, public_details, ranking_details = \
score_type.compute_score(submission_result)
# Mark submission as scored.
self.submission_results_scored.add((submission_id, dataset_id))
# Filling submission's score info in the db.
submission_result.score = score
submission_result.public_score = public_score
# And details.
submission_result.score_details = details
submission_result.public_score_details = public_details
submission_result.ranking_score_details = ranking_details
# If dataset is the active one, update RWS.
if dataset is submission.task.active_dataset:
self.rankings_send_score(submission)
def action_finished(self, data, plus, error=None):
"""Callback from a worker, to signal that is finished some
action (compilation or evaluation).
data (dict): a dictionary that describes a Job instance.
plus (tuple): the tuple (type_,
object_id,
dataset_id,
testcase_codename,
side_data=(priority, timestamp),
shard_of_worker)
"""
# Unpack the plus tuple. It's built in the RPC call to Worker's
# execute_job method inside WorkerPool.acquire_worker.
type_, object_id, dataset_id, testcase_codename, _, \
shard = plus
# Restore operation from its fields.
operation = ESOperation(
type_, object_id, dataset_id, testcase_codename)
# We notify the pool that the worker is available again for
# further work (no matter how the current request turned out,
# even if the worker encountered an error). If the pool
# informs us that the data produced by the worker has to be
# ignored (by returning True) we interrupt the execution of
# this method and do nothing because in that case we know the
# operation has returned to the queue and perhaps already been
# reassigned to another worker.
if self.get_executor().pool.release_worker(shard):
logger.info("Ignored result from worker %s as requested.", shard)
return
job_success = True
if error is not None:
logger.error("Received error from Worker: `%s'.", error)
job_success = False
else:
try:
job = Job.import_from_dict_with_type(data)
except:
logger.error("[action_finished] Couldn't build Job for "
"data %s.", data, exc_info=True)
job_success = False
else:
if not job.success:
logger.error("Worker %s signaled action "
"not successful.", shard)
job_success = False
logger.info("Operation `%s' for submission %s completed. Success: %s.",
operation, object_id, job_success)
# We get the submission from DB and update it.
with SessionGen() as session:
dataset = Dataset.get_from_id(dataset_id, session)
if dataset is None:
logger.error("[action_finished] Could not find "
"dataset %d in the database.",
dataset_id)
return
# TODO Try to move this 4-cases if-clause into a method of
# ESOperation: I'd really like ES itself not to care about
# which type of operation it's handling.
if type_ == ESOperation.COMPILATION:
submission = Submission.get_from_id(object_id, session)
if submission is None:
logger.error("[action_finished] Could not find "
"submission %d in the database.",
object_id)
return
submission_result = submission.get_result(dataset)
if submission_result is None:
logger.info("[action_finished] Couldn't find "
"submission %d(%d) in the database. "
"Creating it.", object_id, dataset_id)
submission_result = \
submission.get_result_or_create(dataset)
if job_success:
job.to_submission(submission_result)
else:
submission_result.compilation_tries += 1
session.commit()
self.compilation_ended(submission_result)
elif type_ == ESOperation.EVALUATION:
submission = Submission.get_from_id(object_id, session)
if submission is None:
logger.error("[action_finished] Could not find "
"submission %d in the database.",
object_id)
return
submission_result = submission.get_result(dataset)
if submission_result is None:
logger.error("[action_finished] Couldn't find "
"submission %d(%d) in the database.",
object_id, dataset_id)
return
if job_success:
job.to_submission(submission_result)
else:
submission_result.evaluation_tries += 1
# Submission evaluation will be ended only when
# evaluation for each testcase is available.
evaluation_complete = (len(submission_result.evaluations) ==
len(dataset.testcases))
if evaluation_complete:
submission_result.set_evaluation_outcome()
session.commit()
if evaluation_complete:
self.evaluation_ended(submission_result)
elif type_ == ESOperation.USER_TEST_COMPILATION:
user_test = UserTest.get_from_id(object_id, session)
if user_test is None:
logger.error("[action_finished] Could not find "
"user test %d in the database.",
object_id)
return
user_test_result = user_test.get_result(dataset)
if user_test_result is None:
logger.error("[action_finished] Couldn't find "
"user test %d(%d) in the database. "
"Creating it.", object_id, dataset_id)
user_test_result = \
user_test.get_result_or_create(dataset)
if job_success:
job.to_user_test(user_test_result)
else:
user_test_result.compilation_tries += 1
session.commit()
self.user_test_compilation_ended(user_test_result)
elif type_ == ESOperation.USER_TEST_EVALUATION:
user_test = UserTest.get_from_id(object_id, session)
if user_test is None:
logger.error("[action_finished] Could not find "
"user test %d in the database.",
object_id)
return
user_test_result = user_test.get_result(dataset)
if user_test_result is None:
logger.error("[action_finished] Couldn't find "
"user test %d(%d) in the database.",
object_id, dataset_id)
return
if job_success:
job.to_user_test(user_test_result)
else:
user_test_result.evaluation_tries += 1
session.commit()
self.user_test_evaluation_ended(user_test_result)
else:
logger.error("Invalid operation type %r.", type_)
return
def execute(self, entry):
"""Assign a score to a submission result.
This is the core of ScoringService: here we retrieve the result
from the database, check if it is in the correct status,
instantiate its ScoreType, compute its score, store it back in
the database and tell ProxyService to update RWS if needed.
entry (QueueEntry): entry containing the operation to perform.
"""
operation = entry.item
with SessionGen() as session:
# Obtain submission.
submission = Submission.get_from_id(operation.submission_id,
session)
if submission is None:
raise ValueError("Submission %d not found in the database." %
operation.submission_id)
# Obtain dataset.
dataset = Dataset.get_from_id(operation.dataset_id, session)
if dataset is None:
raise ValueError("Dataset %d not found in the database." %
operation.dataset_id)
# Obtain submission result.
submission_result = submission.get_result(dataset)
# It means it was not even compiled (for some reason).
if submission_result is None:
raise ValueError("Submission result %d(%d) was not found." %
(operation.submission_id,
operation.dataset_id))
# Check if it's ready to be scored.
if not submission_result.needs_scoring():
if submission_result.scored():
logger.info("Submission result %d(%d) is already scored.",
operation.submission_id, operation.dataset_id)
return
else:
raise ValueError("The state of the submission result "
"%d(%d) doesn't allow scoring." %
(operation.submission_id,
operation.dataset_id))
# For Codebreaker, your score depends on your previous submissions
# to this task. So, let's get the previous submisisons for this task
previous_submissions = session.query(Submission)\
.filter(Submission.user_id == submission.user_id,
Submission.task_id == submission.task_id)\
.order_by(asc(Submission.timestamp))\
.all()
# Counterintuitively, because we're nice people, we don't care how
# these submissions were scored. We only care about their
# evaluations, which will tell us how to score them.
# For a codebreaker, this will be in one-to-one correspondence with
# previous submissions, since each "task" should only have the one
# "testcase".
previous_evaluations = [
session.query(Evaluation)
.filter(Evaluation.submission_id == sub.id).first()
for sub in previous_submissions]
assert(len(previous_evaluations) == len(previous_submissions))
# Now that we have the evaluations, we can pass these as parameters
# to our score type
params = [evaluation.outcome for evaluation in previous_evaluations]
# Instantiate the score type.
# We don't want to use the dataset since we have to pass in custom
# params. Instead we'll just hardcode the name of the class in,
# which is unfortunate.
# TODO (bgbn): work out a way to make this more generic.
score_type = get_score_type(name="AIOCCodebreakerScoreType",
parameters=json.dumps(params),
public_testcases=dict((k, tc.public)
for k, tc in
dataset.testcases.iteritems()))
# Compute score and fill it in the database.
submission_result.score, \
submission_result.score_details, \
submission_result.public_score, \
submission_result.public_score_details, \
submission_result.ranking_score_details = \
score_type.compute_score(submission_result)
# Store it.
session.commit()
# If dataset is the active one, update RWS.
if dataset is submission.task.active_dataset:
self.proxy_service.submission_scored(
submission_id=submission.id)
def get(self, submission_id):
"""Retrieve a single submission.
Query the database for the submission with the given ID, and
the dataset given as query parameter (or the active one).
submission_id (int): the ID of a submission.
"""
# If it's not an integer we will ignore it. But if it's an
# integer of a dataset that doesn't exist we'll raise a 404.
dataset_id = local.request.args.get("dataset_id", type=int)
with SessionGen() as local.session:
# Load the submission, and check for existence.
submission = Submission.get_from_id(submission_id, local.session)
if submission is None:
raise NotFound()
# Load the dataset.
if dataset_id is not None:
dataset = Dataset.get_from_id(dataset_id, local.session)
if dataset is None:
raise NotFound()
else:
q = local.session.query(Dataset)
q = q.join(Task, Dataset.id == Task.active_dataset_id)
q = q.filter(Task.id == submission.task_id)
dataset = q.one()
# Get the result (will fire a query).
submission_result = submission.get_result(dataset)
# Get the ScoreType (will fire a query for testcases).
score_type = get_score_type(dataset=dataset)
# Produce the data structure.
s = submission
sr = submission_result
result = {
'_ref': "%s" % s.id,
'dataset': '%s' % dataset.id,
'user': "******" % s.user_id,
'task': "%s" % s.task_id,
'timestamp': make_timestamp(s.timestamp),
'language': s.language,
# No files, no token: AWS doesn't need them.
}
if sr is not None:
result.update({
'compilation_outcome':
{"ok": True,
"fail": False}.get(sr.compilation_outcome),
'compilation_text':
format_status_text(sr.compilation_text),
'compilation_tries': sr.compilation_tries,
'compilation_stdout': sr.compilation_stdout,
'compilation_stderr': sr.compilation_stderr,
'compilation_time': sr.compilation_time,
'compilation_wall_clock_time':
sr.compilation_wall_clock_time,
'compilation_memory': sr.compilation_memory,
'compilation_shard': sr.compilation_shard,
'compilation_sandbox': sr.compilation_sandbox,
'evaluation_outcome':
{"ok": True}.get(sr.evaluation_outcome),
'evaluation_tries': sr.evaluation_tries,
'evaluations': dict((ev.codename, {
'codename': ev.codename,
'outcome': ev.outcome,
'text': format_status_text(ev.text),
'execution_time': ev.execution_time,
'execution_wall_clock_time':
ev.execution_wall_clock_time,
'execution_memory': ev.execution_memory,
'evaluation_shard': ev.evaluation_shard,
'evaluation_sandbox': ev.evaluation_sandbox,
}) for ev in sr.evaluations),
'score': sr.score,
'max_score': score_type.max_score,
'score_details':
score_type.get_html_details(sr.score_details)
if sr.score is not None else None,
})
else:
# Just copy all fields with None.
result.update({
'compilation_outcome': None,
'compilation_text': None,
'compilation_tries': 0,
'compilation_stdout': None,
'compilation_stderr': None,
'compilation_time': None,
'compilation_wall_clock_time': None,
'compilation_memory': None,
'compilation_shard': None,
'compilation_sandbox': None,
'evaluation_outcome': None,
'evaluation_tries': 0,
'evaluations': {},
'score': None,
'max_score': score_type.max_score,
'score_details': None,
})
# Encode and send.
local.response.mimetype = "application/json"
local.response.data = json.dumps(result)
def write_results(self, items):
"""Receive worker results from the cache and writes them to the DB.
Grouping results together by object (i.e., submission result
or user test result) and type (compilation or evaluation)
allows this method to talk less to the DB, for example by
retrieving datasets and submission results only once instead
of once for every result.
items ([(operation, Result)]): the results received by ES but
not yet written to the db.
"""
logger.info("Starting commit process...")
# Reorganize the results by submission/usertest result and
# operation type (i.e., group together the testcase
# evaluations for the same submission and dataset).
by_object_and_type = defaultdict(list)
for operation, result in items:
t = (operation.type_, operation.object_id, operation.dataset_id)
by_object_and_type[t].append((operation, result))
with SessionGen() as session:
for key, operation_results in by_object_and_type.items():
type_, object_id, dataset_id = key
dataset = Dataset.get_from_id(dataset_id, session)
if dataset is None:
logger.error("Could not find dataset %d in the database.",
dataset_id)
continue
# Get submission or user test results.
if type_ in [ESOperation.COMPILATION, ESOperation.EVALUATION]:
object_ = Submission.get_from_id(object_id, session)
if object_ is None:
logger.error("Could not find submission %d "
"in the database.", object_id)
continue
object_result = object_.get_result_or_create(dataset)
else:
object_ = UserTest.get_from_id(object_id, session)
if object_ is None:
logger.error("Could not find user test %d "
"in the database.", object_id)
continue
object_result = object_.get_result_or_create(dataset)
self.write_results_one_object_and_type(
session, object_result, operation_results)
logger.info("Committing evaluations...")
session.commit()
num_testcases_per_dataset = dict()
for type_, object_id, dataset_id in by_object_and_type.keys():
if type_ == ESOperation.EVALUATION:
if dataset_id not in num_testcases_per_dataset:
num_testcases_per_dataset[dataset_id] = session\
.query(func.count(Testcase.id))\
.filter(Testcase.dataset_id == dataset_id).scalar()
num_evaluations = session\
.query(func.count(Evaluation.id)) \
.filter(Evaluation.dataset_id == dataset_id) \
.filter(Evaluation.submission_id == object_id).scalar()
if num_evaluations == num_testcases_per_dataset[dataset_id]:
submission_result = SubmissionResult.get_from_id(
(object_id, dataset_id), session)
submission_result.set_evaluation_outcome()
logger.info("Committing evaluation outcomes...")
session.commit()
logger.info("Ending operations for %s objects...",
len(by_object_and_type))
for type_, object_id, dataset_id in by_object_and_type.keys():
if type_ == ESOperation.COMPILATION:
submission_result = SubmissionResult.get_from_id(
(object_id, dataset_id), session)
self.compilation_ended(submission_result)
elif type_ == ESOperation.EVALUATION:
submission_result = SubmissionResult.get_from_id(
(object_id, dataset_id), session)
if submission_result.evaluated():
self.evaluation_ended(submission_result)
elif type_ == ESOperation.USER_TEST_COMPILATION:
user_test_result = UserTestResult.get_from_id(
(object_id, dataset_id), session)
self.user_test_compilation_ended(user_test_result)
elif type_ == ESOperation.USER_TEST_EVALUATION:
user_test_result = UserTestResult.get_from_id(
(object_id, dataset_id), session)
self.user_test_evaluation_ended(user_test_result)
logger.info("Done")
def write_results(self, items):
"""Receive worker results from the cache and writes them to the DB.
Grouping results together by object (i.e., submission result
or user test result) and type (compilation or evaluation)
allows this method to talk less to the DB, for example by
retrieving datasets and submission results only once instead
of once for every result.
items ([(operation, Result)]): the results received by ES but
not yet written to the db.
"""
logger.info("Starting commit process...")
# Reorganize the results by submission/usertest result and
# operation type (i.e., group together the testcase
# evaluations for the same submission and dataset).
by_object_and_type = defaultdict(list)
for operation, result in items:
t = (operation.type_, operation.object_id, operation.dataset_id,
operation.archive_sandbox)
by_object_and_type[t].append((operation, result))
with SessionGen() as session:
for key, operation_results in iteritems(by_object_and_type):
type_, object_id, dataset_id, archive_sandbox = key
dataset = Dataset.get_from_id(dataset_id, session)
if dataset is None:
logger.error("Could not find dataset %d in the database.",
dataset_id)
continue
# Get submission or user test results.
if type_ in [ESOperation.COMPILATION, ESOperation.EVALUATION]:
object_ = Submission.get_from_id(object_id, session)
if object_ is None:
logger.error(
"Could not find submission %d "
"in the database.", object_id)
continue
object_result = object_.get_result_or_create(dataset)
else:
object_ = UserTest.get_from_id(object_id, session)
if object_ is None:
logger.error(
"Could not find user test %d "
"in the database.", object_id)
continue
object_result = object_.get_result_or_create(dataset)
self.write_results_one_object_and_type(session, object_result,
operation_results)
logger.info("Committing evaluations...")
session.commit()
num_testcases_per_dataset = dict()
for type_, object_id, dataset_id, archive_sandbox in by_object_and_type:
if type_ == ESOperation.EVALUATION:
if dataset_id not in num_testcases_per_dataset:
num_testcases_per_dataset[dataset_id] = session\
.query(func.count(Testcase.id))\
.filter(Testcase.dataset_id == dataset_id).scalar()
num_evaluations = session\
.query(func.count(Evaluation.id)) \
.filter(Evaluation.dataset_id == dataset_id) \
.filter(Evaluation.submission_id == object_id).scalar()
if num_evaluations == num_testcases_per_dataset[
dataset_id]:
submission_result = SubmissionResult.get_from_id(
(object_id, dataset_id), session)
submission_result.set_evaluation_outcome()
logger.info("Committing evaluation outcomes...")
session.commit()
logger.info("Ending operations for %s objects...",
len(by_object_and_type))
for type_, object_id, dataset_id, archive_sandbox in iterkeys(
by_object_and_type):
if type_ == ESOperation.COMPILATION:
submission_result = SubmissionResult.get_from_id(
(object_id, dataset_id), session)
self.compilation_ended(submission_result, archive_sandbox)
elif type_ == ESOperation.EVALUATION:
submission_result = SubmissionResult.get_from_id(
(object_id, dataset_id), session)
if submission_result.evaluated():
self.evaluation_ended(submission_result,
archive_sandbox)
elif type_ == ESOperation.USER_TEST_COMPILATION:
user_test_result = UserTestResult.get_from_id(
(object_id, dataset_id), session)
self.user_test_compilation_ended(user_test_result)
elif type_ == ESOperation.USER_TEST_EVALUATION:
user_test_result = UserTestResult.get_from_id(
(object_id, dataset_id), session)
self.user_test_evaluation_ended(user_test_result)
logger.info("Done")
