Merge "Add model api unit test"
This commit is contained in:
Jenkins
Gerrit Code Review
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905fb575c7
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# Copyright (c) 2017 OpenStack Foundation
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# All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License"); you may
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# not use this file except in compliance with the License. You may obtain
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# a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
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# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
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# License for the specific language governing permissions and limitations
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# under the License.
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import copy
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import mock
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import webob
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from meteos.api.openstack import api_version_request as api_version
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from meteos.api.openstack import wsgi as os_wsgi
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from meteos.api.v1 import models
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from meteos import context
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from meteos import test
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fake_model = {"model": {
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"created_at": "2016-11-30T07:03:33.000000",
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"description": 'null',
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"id": "c8707239-ae83-40c8-9d1b-273981ba209d",
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"name": 'null',
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"params": "eydudW1JdGVyYXRpb25zJzogMSwgJ2Rlc2lyZWRfb3V0cHV0JzowfQ==",
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"project_id": "7a1e6f042f00ac94ec30bb8c6bf5d05b34623832",
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"status": "available",
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"source_dataset_url": "swift://meteos/linear_data.txt",
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"stderr": "",
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"experiment_id": "2ddd9a75b6fc888e0842589255",
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"stdout": "",
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"type": "LinearRegression",
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"user_id": "511c049d52524ba9b14b0ff33867d3b8"}}
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result = {"model": {
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"id": "8caaabed10aaae1d1366f50a28a8b501c77c2c5c",
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"created_at": "2016-11-30T07:03:33.000000",
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"description": 'null',
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"id": "c8707239-ae83-40c8-9d1b-273981ba209d",
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"name": 'null',
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"params": "eydudW1JdGVyYXRpb25zJzogMSwgJ2Rlc2lyZWRfb3V0cHV0JzowfQ==",
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"project_id": "7a1e6f042f00ac94ec30bb8c6bf5d05b34623832",
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"experiment_id": "2ddd9a75b6fc888e0842589255",
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"status": "available",
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"stderr": "",
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"stdout": "",
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"type": "LinearRegression",
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"user_id": "511c049d52524ba9b14b0ff33867d3b8"}}
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fakemodel_list = [fake_model['model'], {
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"id": "8227e5ff9fa099b529b906cecfe5e2a1c8c86214",
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"description": 'null',
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"name": "null",
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"created_at": "2016-11-30T07:03:33.000000",
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"experiment_id": "aaaa-bbbb-cccc-eeee-dddd",
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"params": "aaaabbbbbccccdddddb25zJzogMSwgJ2Rlc23V0cHV0JzowfQ==",
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"type": "LinearRegression",
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"user_id": "892f96b98daf797fdbfcdd559f69d43e322590f1",
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"project_id": "7a1e6f042f00ac94ec30bb8c6bf5d05b34623832",
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"source_dataset_url": "swift://meteos/linear_data2.txt",
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"status": "available",
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"stdout": "",
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"swift_password": "nova",
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"stderr": "",
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"swift_tenant": "demo",
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"swift_username": "demo"}]
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base = 'http://www.meteos.com'
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project_id = '7a1e6f042f00ac94ec30bb8c6bf5d05b34623832'
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model_id1 = 'c8707239-ae83-40c8-9d1b-273981ba209d'
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model_id2 = '8227e5ff9fa099b529b906cecfe5e2a1c8c86214'
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href11 = base + '/v1.1/123/' + project_id + '/models/' + model_id1
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href12 = base + '/123/' + project_id + '/models/' + model_id1
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href21 = base + '/v1.1/123/' + project_id + '/models/' + model_id2
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href22 = base + '/123/' + project_id + '/models/' + model_id2
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expect_result = {
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'models': [
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{
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"id": "c8707239-ae83-40c8-9d1b-273981ba209d",
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"experiment_id": "2ddd9a75b6fc888e0842589255",
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"params": "eydudW1JdGVyYXRpb25zJzogMSwgJ2Rlc2lyZWRfb3V0cHV0JzowfQ==",
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"type": "LinearRegression",
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"created_at": "2016-11-30T07:03:33.000000",
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"source_dataset_url": "swift://meteos/linear_data.txt",
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"user_id": "511c049d52524ba9b14b0ff33867d3b8",
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"project_id": "7a1e6f042f00ac94ec30bb8c6bf5d05b34623832",
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"status": "available",
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"description": 'null',
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"name": "null",
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"stdout": "",
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"stderr": "",
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'links': [
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{
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'href': href11,
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'rel': 'self'
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},
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{
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'href': href12,
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'rel': 'bookmark'
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}
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]
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},
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{
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"id": "8227e5ff9fa099b529b906cecfe5e2a1c8c86214",
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"experiment_id": "aaaa-bbbb-cccc-eeee-dddd",
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"params": "aaaabbbbbccccdddddb25zJzogMSwgJ2Rlc23V0cHV0JzowfQ==",
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"type": "LinearRegression",
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"source_dataset_url": "swift://meteos/linear_data2.txt",
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"status": "available",
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"created_at": "2016-11-30T07:03:33.000000",
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"user_id": "892f96b98daf797fdbfcdd559f69d43e322590f1",
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"project_id": "7a1e6f042f00ac94ec30bb8c6bf5d05b34623832",
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"name": "null",
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"description": 'null',
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"stdout": "",
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"stderr": "",
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'links': [
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{
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'href': href21,
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'rel': 'self'
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},
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{
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'href': href22,
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'rel': 'bookmark'
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}
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]
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}
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]
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}
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class FakeTemplate(object):
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def __init__(self):
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self.id = "124567890"
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self.template_id = "1234567890"
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self.job_template_id = "11111111111"
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class FakeExperiment(object):
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def __init__(self):
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self.id = "124567890"
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self.status = 'available'
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self.template_id = "1234567890"
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self.cluster_id = "11111111111"
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class FakeModel(object):
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def __init__(self, **entries):
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self.add_entries(**entries)
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def add_entries(self, **entries):
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for key, value in entries.items():
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if type(value) is dict:
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self.__dict__[key] = FakeModel(**value)
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else:
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self.__dict__[key] = value
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def __getitem__(self, key):
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return getattr(self, key)
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def get(self, key):
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return getattr(self, key)
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class FakeEngine(object):
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def API(self):
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return self
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def get_model(self, context, id):
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model = copy.deepcopy(result['model'])
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desc = model.get("description")
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del model['description']
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model['display_description'] = desc
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name = model.get("name")
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del model['name']
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model['display_name'] = name
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params = model.get("params")
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del model['params']
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model['model_params'] = params
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ttype = model.get("type")
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del model['type']
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model['model_type'] = ttype
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fake_model = FakeModel(**model)
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fake_model.dataset_format = 'fake_format'
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fake_model.job_template_id = '111111'
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fake_model.cluster_id = '22222'
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if id == 'Ia1a0a6bdf0707ccf96a02dec36f94f0c68b165fc':
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fake_model.status = 'active'
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return fake_model
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def delete_model(self, context, id):
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pass
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def get_all_models(self, context, search_opts=None,
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sort_key='created_at', sort_dir='desc'):
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fs = copy.deepcopy(fakemodel_list)
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for flist in fs:
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desc = flist.get("description")
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del flist['description']
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flist['display_description'] = desc
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name = flist.get("name")
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del flist['name']
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flist['display_name'] = name
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params = flist.get("params")
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del flist['params']
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flist['model_params'] = params
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ttype = flist.get("type")
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del flist['type']
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flist['model_type'] = ttype
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return fs
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def get_template(self, context, template_id):
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return FakeTemplate()
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def get_experiment(self, context, model_id):
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return FakeExperiment()
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def create_model(self, context, display_name, description,
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source_dataset_url, dataset_format, model_type,
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model_params, template_id, job_template_id,
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experiment_id, cluster_id, swift_tenant,
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swift_username, swift_password):
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return {
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"id": "f78676d89eebe539bdc4a498f7572624cc65afb3",
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"status": 'active',
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"display_name": "null",
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"display_description": 'null',
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"user_id": "892f96b98daf797fdbfcdd559f69d43e322590f1",
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"project_id": "7a1e6f042f00ac94ec30bb8c6bf5d05b34623832",
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"experiment_id": "b45fb6a9-6f93-4e4b-93ec-0b128927b62d",
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"model_params": "eydudW1JdGVyYXRpb25zJzogMSwgJ2Rlc2lyZWRfb3V0cHV0JzowfQ==",
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"model_type": "LinearRegression",
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"source_dataset_url": "swift://meteos/linear_data.txt",
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"created_at": "2016-11-30T07:03:33.000000",
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"stdout": "null",
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"stderr": "null"
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}
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def load_model(self, context, id, dataset_format, model_type,
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job_template_id, experiment_id, cluster_id):
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pass
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def unload_model(self, context, id, dataset_format, model_type,
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job_template_id, experiment_id, cluster_id):
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pass
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def recreate_model(self, context, id, source_dataset_url, dataset_format,
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model_type, model_params, template_id,
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job_template_id, experiment_id, cluster_id,
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swift_tenant, swift_username, swift_password):
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pass
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class FakeRequest(object):
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environ = {"meteos.context": context.get_admin_context()}
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environ['meteos.context'].project_id = ('7a1e6f042f00ac94ec30bb8c6b'
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'f5d05b34623832')
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GET = {}
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def __init__(self, version=os_wsgi.DEFAULT_API_VERSION):
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super(FakeRequest, self).__init__()
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self.api_version_request = api_version.APIVersionRequest(version)
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self.application_url = 'http://www.meteos.com/v1.1/123'
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self.params = {}
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class ModelTestCase(test.TestCase):
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"""Test Case for model."""
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Controller = models.ModelController
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def _setup_stubs(self):
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self.stub_out('meteos.engine.API',
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FakeEngine().API)
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def setUp(self):
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self._setup_stubs()
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super(ModelTestCase, self).setUp()
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self.controller = self.Controller()
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def test_show_model(self):
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id = 'e71dbd349248a4187be134e1118cff29fcd6121e'
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self.req = FakeRequest()
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result = self.controller.show(self.req, id)
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expected = copy.deepcopy(fake_model)
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del expected['model']['source_dataset_url']
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self.assertDictMatch(result, expected)
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def test_delete_model(self):
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id = 'e71dbd349248a4187be134e1118cff29fcd6121e'
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self.req = FakeRequest()
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response = self.controller.delete(self.req, id)
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self.assertEqual('202 Accepted', response._status)
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def test_index_model(self):
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self.req = FakeRequest()
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result = self.controller.index(self.req)
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expect = copy.deepcopy(expect_result)
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del expect['models'][0]['user_id']
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del expect['models'][0]['project_id']
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del expect['models'][1]['user_id']
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del expect['models'][1]['project_id']
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del expect['models'][0]['stderr']
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del expect['models'][1]['stderr']
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self.assertDictMatch(expect, result)
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def test_detail_model(self):
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self.req = FakeRequest()
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result = self.controller.detail(self.req)
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expect = copy.deepcopy(expect_result)
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del expect['models'][0]['links']
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del expect['models'][1]['links']
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del expect['models'][0]['source_dataset_url']
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del expect['models'][1]['source_dataset_url']
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self.assertDictMatch(expect, result)
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def test_create_model(self):
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self.req = FakeRequest()
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fake_body = {
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"model": {
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"experiment_id": "b45fb6a9-6f93-4e4b-93ec-0b128927b62d",
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"model_params": "eydudW1JdGVyYXRpb25zJzogMSwgJ2Rlc2lyZWRfb3V0cHV0JzowfQ==",
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"model_type": "LinearRegression",
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"source_dataset_url": "swift://meteos/linear_data.txt",
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"swift_password": "nova",
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"swift_tenant": "demo",
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"swift_username": "demo"
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}
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}
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expect = {
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"model": {
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"status": 'active',
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"description": 'null',
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"stdout": 'null',
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"id": "f78676d89eebe539bdc4a498f7572624cc65afb3",
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"user_id": "892f96b98daf797fdbfcdd559f69d43e322590f1",
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"project_id": "7a1e6f042f00ac94ec30bb8c6bf5d05b34623832",
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"name": "null",
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"stderr": 'null',
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"created_at": "2016-11-30T07:03:33.000000",
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"experiment_id": "b45fb6a9-6f93-4e4b-93ec-0b128927b62d",
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"params": "eydudW1JdGVyYXRpb25zJzogMSwgJ2Rlc2lyZWRfb3V0cHV0JzowfQ==",
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"type": "LinearRegression",
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}
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}
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result = self.controller.create(self.req, fake_body)
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self.assertDictMatch(expect, result)
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def test_model_load(self):
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mid = "f78676d89eebe539bdc4a498f7572624cc65afb3"
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self.req = FakeRequest()
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body = {}
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result = self.controller.load(self.req, mid, body)
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expect = {'model': {'id': mid}}
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self.assertDictMatch(expect, result)
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def test_model_unload(self):
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mid = "Ia1a0a6bdf0707ccf96a02dec36f94f0c68b165fc"
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self.req = FakeRequest()
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body = {}
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result = self.controller.unload(self.req, mid, body)
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expect = {'model': {'id': mid}}
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self.assertDictMatch(expect, result)
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def test_model_recreate(self):
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mid = "Ia1a0a6bdf0707ccf96a02dec36f94f0c68b165fc"
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self.req = FakeRequest()
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body = {}
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result = self.controller.unload(self.req, mid, body)
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expect = {'model': {'id': mid}}
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self.assertDictMatch(expect, result)
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