PyCS/pycs/pipeline/PipelineManager.py

from os import path

from eventlet import tpool

from pycs.pipeline.Fit import Fit
from pycs.pipeline.Job import Job


class PipelineManager:
    def __init__(self, project):
        code_path = path.join(project['model']['path'], project['model']['code']['module'])
        module_name = code_path.replace('/', '.').replace('\\', '.')
        class_name = project['model']['code']['class']

        mod = __import__(module_name, fromlist=[class_name])
        cl = getattr(mod, class_name)

        self.project = project
        self.pipeline = cl(project['model']['path'], project['model'])

    def close(self):
        print('PipelineManager', 'close')
        self.pipeline.close()

    def run(self, media_file):
        # create job list
        # TODO update job progress
        job = Job(self.project, media_file)
        result = tpool.execute(lambda p, j: p.execute(j), self.pipeline, job)

        # remove existing pipeline predictions from media_fle
        media_file.remove_pipeline_results()

        # add new predictions
        for prediction in result:
            media_file.add_result(prediction, origin='pipeline')

    def fit(self):
        print('PipelineManager', 'fit')
        data = []

        for identifier in self.project['data']:
            fit = Fit(self.project, self.project['data'][identifier])
            data.append(fit)

        for key in self.project.unmanaged_files:
            obj = self.project.unmanaged_files[key].get_data()
            fit = Fit(self.project, obj)
            data.append(fit)

        self.pipeline.fit(data)