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- from glob import glob
- from json import load, dump
- from os import path, mkdir
- from shutil import rmtree, copytree
- from time import time
- from uuid import uuid1
- from pycs import ApplicationStatus
- from pycs.observable import ObservableDict
- from pycs.projects.Project import Project
- class ProjectManager(ObservableDict):
- def __init__(self, app_status: ApplicationStatus):
- # TODO create projects folder if it does not exist
- self.app_status = app_status
- # initialize observable dict with no keys and
- # app_status object as parent
- super().__init__({}, app_status)
- app_status['projects'] = self
- # find projects
- for folder in glob('projects/*'):
- # load project.json
- with open(path.join(folder, 'project.json'), 'r') as file:
- project = Project(load(file), self)
- self[project['id']] = project
- def write_project(self, uuid):
- copy = self[uuid].copy()
- del copy['jobs']
- del copy['model']
- with open(path.join('projects', uuid, 'project.json'), 'w') as file:
- dump(copy, file, indent=4)
- def create_project(self, name, description, model):
- # create dict representation
- uuid = str(uuid1())
- # create project directory
- folder = path.join('projects', uuid)
- mkdir(folder)
- # copy model to project directory
- copytree(self.parent['models'][model]['path'], path.join(folder, 'model'))
- # create project object
- self[uuid] = Project({
- 'id': uuid,
- 'name': name,
- 'description': description,
- 'created': int(time()),
- 'data': {},
- 'labels': {},
- 'jobs': {}
- }, self)
- # create project.json
- self.write_project(uuid)
- def update_project(self, uuid, update):
- # abort if uuid is no valid key
- if uuid not in self.keys():
- return
- # set values and write to disk
- self[uuid].update_properties(update)
- self.write_project(uuid)
- def delete_project(self, uuid):
- # abort if uuid is no valid key
- if uuid not in self.keys():
- return
- # delete project folder
- folder = path.join('projects', uuid)
- rmtree(folder)
- # delete project data
- del self[uuid]
- def predict(self, uuid, identifiers=None):
- # abort if uuid is no valid key
- if uuid not in self.keys():
- return
- project = self[uuid]
- # get identifiers
- if identifiers is None:
- identifiers = list(project['data'].keys())
- # run prediction
- project.predict(identifiers)
- def fit(self, uuid):
- # abort if uuid is no valid key
- if uuid not in self.keys():
- return
- project = self[uuid]
- # run fit
- project.fit()
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