submission_processor.py 4.78 KB
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import random
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from pathlib import Path

from storage import UploadedEntity

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import portal.tools.worker_client
from portal import logger, tools
from portal.database import Project, Submission, SubmissionState, Worker
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log = logger.get_logger(__name__)
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class SubmissionProcessor:
    def __init__(self, submission: Submission, params: dict = None):
        self._submission = submission
        self._params = params
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        from portal.service.rest import RestService
        self._rest = RestService()
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    @property
    def submission(self) -> Submission:
        return self._submission

    @property
    def params(self) -> dict:
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        return self.submission.parameters
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    @property
    def project(self) -> Project:
        return self.submission.project

    @property
    def celery(self):
        from portal.async_celery import celery_app
        return celery_app

    @property
    def storage(self):
        from portal import storage
        return storage

    def reset_task_id(self, state=None):
        if state is not None:
            self.submission.state = state

        self.submission.async_task_id = None
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        self._rest.submissions.write_entity(self.submission)
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    def submission_enqueue_ended(self):
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        log.info(f"[ASYNC] Submission enqueue ended {self.submission.log_name}: {self.submission}")
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        self.reset_task_id(state=SubmissionState.QUEUED)

    def get_delay_for_submission(self):
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        log.debug(f"[ASYNC] Submission delay {self.submission.log_name}: {self.submission}")
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        time_wait = self.project.config.submissions_cancellation_period
        return time_wait

    def dispatch_submission_processing(self):
        delay = self.get_delay_for_submission()
        args = (self.submission.id, self.params)
        from .tasks import start_processing_submission
        start_processing_submission.apply_async(args=args, countdown=delay)

    def submission_store_ended(self, version: str):
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        log.info(f"[ASYNC] Submission preparation ended {self.submission.log_name}: "
                 f"{self.submission}")
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        self.submission.source_hash = version
        self.reset_task_id(state=SubmissionState.READY)

    def download_submission(self):
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        file_params = self.params['file_params']
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        log.info(f"[ASYNC] Uploading submission: {self.submission.log_name} with {file_params}")
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        updated_entity: UploadedEntity = self.storage. \
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            submissions.create(entity_id=self.submission.id, **file_params)
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        self.submission_store_ended(version=updated_entity.version)

    def clone(self, target):
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        log.info(f"[ASYNC] Cloning submission: {self.submission.log_name} to {target.log_name}")
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        self.storage.submissions.clone(self.submission.id, target.id)
        self.submission_store_ended(version=self.submission.source_hash)

    def send_to_worker(self):
        # TODO: implement processing
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        log.info(f"[ASYNC] Sending submission to worker: {self.submission.log_name}")
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        worker = self.schedule_submission_to_worker()
        self.execute_submission(worker)
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    def upload_result(self, path, file_params):
        log.info(f"[ASYNC] Uploading result for the submission "
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                 f"{self.submission.log_name} with {file_params}")
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        self.storage.results.create(entity_id=self.submission.id, **file_params)
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        Path(path).unlink()
        self.reset_task_id(SubmissionState.FINISHED)

    def process_submission(self):
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        log.info(f"[ASYNC] Processing submission {self.submission.log_name}")
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        self.download_submission()
        self.dispatch_submission_processing()
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    def revoke_task(self):
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        log.info(f'[ASYNC] Submission processing cancelled {self.submission.log_name}')
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        task_id = self.submission.async_task_id
        if task_id:
            self.celery.control.revoke(task_id=task_id, terminate=True)
            self.reset_task_id(state=SubmissionState.CANCELLED)
        # TODO: Storage clean up
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    # TODO implement - @mdujava
    # STUB: Select initialized worker
    def schedule_submission_to_worker(self) -> Worker:
        """Based on the features (worker tags) and preferences in project config
        schedule submission for the execution on initialized worker

        Returns(Worker): Worker instance on which the submission will be executed
        """
        workers = Worker.query.filter(Worker.is_initialized).all()
        if not workers:
            self._worker_not_available()
        worker = random.choice(workers)  # randomly select a worker
        return worker

    def execute_submission(self, worker: Worker):
        worker_client = tools.worker_client.WorkerClient(worker=worker)
        worker_client.execute_submission(self.submission)

    def _worker_not_available(self):
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        log.warning(f"[PROC] Worker is no available for submission: {self.submission.log_name}")
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        pass