PyCS/pycs/frontend/endpoints/pipelines/FitModel.py

from flask import abort
from flask import make_response
from flask import request
from flask.views import View

from pycs.database.Project import Project
from pycs.interfaces.MediaStorage import MediaStorage
from pycs.jobs.JobGroupBusyException import JobGroupBusyException
from pycs.jobs.JobRunner import JobRunner
from pycs.util.PipelineCache import PipelineCache


class FitModel(View):
    """
    use annotated data to fit a model
    """
    # pylint: disable=arguments-differ
    methods = ['POST']

    def __init__(self, jobs: JobRunner, pipelines: PipelineCache):
        # pylint: disable=invalid-name
        self.jobs = jobs
        self.pipelines = pipelines

    def dispatch_request(self, user: str, project_id):
        # pylint: disable=unused-argument
        project = Project.get_or_404(project_id)

        # extract request data
        data = request.get_json(force=True)

        if not data.get('fit', False):
            abort(400, "fit flag is missing")


        # create job
        try:
            self.jobs.run(project,
                          'Model Interaction',
                          f'{project.name} (fit model with new data)',
                          f'{project.name}/model-interaction',
                          FitModel.load_and_fit,
                          self.pipelines,
                          project.id)

        except JobGroupBusyException:
            return abort(400, "Model fitting already running")

        return make_response()

    @staticmethod
    def load_and_fit(pipelines: PipelineCache, project_id: int):
        """
        load the pipeline and call the fit function

        :param pipelines: pipeline cache
        :param project_id: project id
        """
        pipeline = None

        # create new database instance
        project = Project.query.get(project_id)
        model = project.model
        storage = MediaStorage(project_id)

        # load pipeline
        try:
            pipeline = pipelines.load_from_root_folder(project_id, model.root_folder)
            yield from pipeline.fit(storage)
        except TypeError:
            pass
        finally:
            if pipeline is not None:
                pipelines.free_instance(model.root_folder)