Add learning api unit test
Add unit test for leanring api Change-Id: I4250cb723712f825c652c96e1e579a50389136fb
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shunliz
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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 learnings
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from meteos import context
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from meteos import test
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fake_learning = {"learning": {
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"id": "e71dbd349248a4187be134e1118cff29fcd6121e",
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"args": "MTEsMTAsMjAxNiwyLDAsNjcsODA=",
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"description": "This is a sample job",
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"name": "example-learning-job",
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"method": "predict",
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"status": "creating",
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"stdout": "1.0",
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"stderr": "none",
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"created_at": "2016-11-30T07:16:17.000000",
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"user_id": "6bd3561e9db3175f07299818ddb46a8ac7c72a12",
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"project_id": "7a1e6f042f00ac94ec30bb8c6bf5d05b34623832",
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"model_type": "LinearRegression",
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"model_id": "27032fe5-cb88-42bc-a753-f6a1359d629e"}}
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result = {"learning": {
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"id": "e71dbd349248a4187be134e1118cff29fcd6121e",
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"args": "MTEsMTAsMjAxNiwyLDAsNjcsODA=",
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"display_description": "This is a sample job",
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"display_name": "example-learning-job",
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"learning_id": "b45fb6a9-6f93-4e4b-93ec-0b128927b62d",
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"method": "predict",
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"status": "creating",
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"stdout": "1.0",
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"stderr": "none",
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"created_at": "2016-11-30T07:16:17.000000",
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"user_id": "6bd3561e9db3175f07299818ddb46a8ac7c72a12",
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"project_id": "7a1e6f042f00ac94ec30bb8c6bf5d05b34623832",
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"type": "LinearRegression",
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"model_id": "27032fe5-cb88-42bc-a753-f6a1359d629e"}}
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fakelearning_list = [{
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"id": "bd14f7f23e01968aba70f0025b85dc15f110abc1",
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"args": "MTEsMTAsMjAxNiwyLDAsNjcsODA=",
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"description": "This is second sample job",
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"name": "second example-learning-job",
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"learning_id": "c733d48580da2d8ac99a382fab0785becc24cdbb",
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"method": "predict",
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"status": "creating",
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"stdout": "1.0",
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"stderr": "none",
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"created_at": "2016-11-30T07:16:17.000000",
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"user_id": "6bd3561e9db3175f07299818ddb46a8ac7c72a12",
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"project_id": "7a1e6f042f00ac94ec30bb8c6bf5d05b34623832",
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"model_type": "LinearRegression",
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"model_id": "98b28d675d3e2059e4c0d457dc42166aef286d27"},
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fake_learning['learning']]
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base = 'http://www.meteos.com'
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project_id = '7a1e6f042f00ac94ec30bb8c6bf5d05b34623832'
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user_id1 = 'bd14f7f23e01968aba70f0025b85dc15f110abc1'
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user_id2 = 'e71dbd349248a4187be134e1118cff29fcd6121e'
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href11 = base + '/v1.1/123/' + project_id + '/learnings/' + user_id1
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href12 = base + '/123/' + project_id + '/learnings/' + user_id1
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href21 = base + '/v1.1/123/' + project_id + '/learnings/' + user_id2
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href22 = base + '/123/' + project_id + '/learnings/' + user_id2
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expect_result = {
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'learnings': [
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{
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"id": "bd14f7f23e01968aba70f0025b85dc15f110abc1",
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"args": "MTEsMTAsMjAxNiwyLDAsNjcsODA=",
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"description": "This is second sample job",
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"name": "second example-learning-job",
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"method": "predict",
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"status": "creating",
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"stdout": "1.0",
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"stderr": "none",
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"created_at": "2016-11-30T07:16:17.000000",
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"user_id": "6bd3561e9db3175f07299818ddb46a8ac7c72a12",
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"project_id": "7a1e6f042f00ac94ec30bb8c6bf5d05b34623832",
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"model_id": "98b28d675d3e2059e4c0d457dc42166aef286d27",
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"type": "LinearRegression",
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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": "e71dbd349248a4187be134e1118cff29fcd6121e",
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"args": "MTEsMTAsMjAxNiwyLDAsNjcsODA=",
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"description": "This is a sample job",
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"name": "example-learning-job",
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"method": "predict",
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"status": "creating",
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"stdout": "1.0",
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"stderr": "none",
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"created_at": "2016-11-30T07:16:17.000000",
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"user_id": "6bd3561e9db3175f07299818ddb46a8ac7c72a12",
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"project_id": "7a1e6f042f00ac94ec30bb8c6bf5d05b34623832",
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"model_id": "27032fe5-cb88-42bc-a753-f6a1359d629e",
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"type": "LinearRegression",
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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 FakeExperiment(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.status = 'available'
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self.cluster_id = 'e1644ac1d86d4836ca26e89258b5aa6e93b9f770'
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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 = '1234567890'
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class FakeModel(object):
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def __init__(self):
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self.status = 'available'
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self.experiment_id = '124567890'
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self.model_type = "LinearRegression"
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self.dataset_format = "csv"
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self.experiment_id = '124567890'
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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_learning(self, context, id):
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return result['learning']
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def delete_learning(self, context, id):
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pass
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def get_all_learnings(self, context, search_opts=None,
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sort_key='created_at', sort_dir='desc'):
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learnings = copy.deepcopy(fakelearning_list)
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name = learnings[0]['name']
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del learnings[0]['name']
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learnings[0]['display_name'] = name
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description = learnings[0]['description']
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del learnings[0]['description']
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learnings[0]['display_description'] = description
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name = learnings[1]['name']
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del learnings[1]['name']
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learnings[1]['display_name'] = name
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description = learnings[1]['description']
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del learnings[1]['description']
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learnings[1]['display_description'] = description
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return learnings
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def get_experiment(self, context, experiment_id):
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return FakeExperiment()
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def get_template(self, context, template_id):
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return FakeTemplate()
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def get_model(self, context, model_id):
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return FakeModel()
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def create_learning(self, context, name, description, status, model_id,
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method, model_type, dataset_format, args, template_id,
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job_template_id, experiment_id, cluster_id):
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return {
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"id": "b45fb6a9-6f93-4e4b-93ec-0b128927b62d",
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"created_at": "2016-11-30T07:16:17.000000",
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"status": "creating",
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"display_name": "example-learning-job",
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"display_description": "This is a sample job",
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"user_id": "e6f8dbb55fc8fccb18f4ccb5ed5723a2efc3b025",
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"project_id": "bd14f7f23e01968aba70f0025b85dc15f110abc1",
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"stdout": "2",
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"stderr": "none",
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"method": "predict",
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"model_id": "27032fe5-cb88-42bc-a753-f6a1359d629e",
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"args": "MTEsMTAsMjAxNiwyLDAsNjcsODA="
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}
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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 = ('7a1e6f042f00ac94ec30bb8c6bf5d'
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'05b34623832')
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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 LearningTestCase(test.TestCase):
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"""Test Case for learning."""
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Controller = learnings.LearningController
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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(LearningTestCase, self).setUp()
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self.controller = self.Controller()
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def test_show_learning(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_learning)
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del expected['learning']['model_type']
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self.assertDictMatch(result, expected)
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def test_delete_learning(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_learning(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['learnings'][0]['user_id']
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del expect['learnings'][0]['project_id']
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del expect['learnings'][1]['user_id']
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del expect['learnings'][1]['project_id']
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del expect['learnings'][0]['method']
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del expect['learnings'][1]['method']
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del expect['learnings'][0]['stderr']
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del expect['learnings'][1]['stderr']
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self.assertDictMatch(expect, result)
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def test_detail_learning(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['learnings'][0]['links']
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del expect['learnings'][1]['links']
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del expect['learnings'][0]['type']
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del expect['learnings'][1]['type']
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self.assertDictMatch(expect, result)
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def test_create_learning(self):
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self.req = FakeRequest()
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fake_body = {
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"learning": {
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"args": "MTEsMTAsMjAxNiwyLDAsNjcsODA=",
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"display_description": "This is a sample job",
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"display_name": "example-learning-job",
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"learning_id": "b45fb6a9-6f93-4e4b-93ec-0b128927b62d",
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"method": "predict",
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"model_id": "27032fe5-cb88-42bc-a753-f6a1359d629e"
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}
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}
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expect = {
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"learning": {
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'status': 'creating',
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'model_id': '27032fe5-cb88-42bc-a753-f6a1359d629e',
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'description': 'This is a sample job',
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'stdout': '2',
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'args': 'MTEsMTAsMjAxNiwyLDAsNjcsODA=',
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'id': 'b45fb6a9-6f93-4e4b-93ec-0b128927b62d',
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'user_id': 'e6f8dbb55fc8fccb18f4ccb5ed5723a2efc3b025',
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'name': 'example-learning-job',
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'created_at': '2016-11-30T07:16:17.000000',
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'stderr': 'none',
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'project_id': 'bd14f7f23e01968aba70f0025b85dc15f110abc1',
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'method': 'predict'
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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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