How to use a2ml - 10 common examples

def test_init(self):
        fulldir=os.getcwd()+"/tests/test_google"
        os.chdir(fulldir)
        # load config(s) from test app
        ctx = Context()

        a2ml = A2ML(ctx)
        assert len(a2ml.runner.providers)==3
        assert isinstance(a2ml.runner.providers[0], GoogleA2ML)

def test_calculate_scores(self):
        model_path = 'tests/fixtures/test_predict_by_model/iris'
        options = fsclient.read_json_file(os.path.join(model_path, "options.json"))

        y_test, _ = ModelHelper.preprocess_target(model_path, 
            records=[["setosa"], ["versicolor"], ["virginica"], ["setosa"], ["versicolor"], ["virginica"]], 
            features=["species"]
        )
        y_pred, _ = ModelHelper.preprocess_target(model_path, 
            records=[["setosa"], ["versicolor"], ["versicolor"], ["setosa"], ["versicolor"], ["virginica"]], 
            features=["species"]
        )

        scores = ModelHelper.calculate_scores(options, y_test=y_test, y_pred=y_pred)
        self.assertEqual(len(scores), len(options['scoreNames']))
        self.assertTrue(scores['accuracy']>0.8)

def test_distribution_chart_stats_for_categorical_target():
    model_path = 'tests/fixtures/test_distribution_chart_stats/adult'
    date_from = datetime.date(2020, 2, 16)
    date_to = datetime.date(2020, 2, 20)

    res = ModelReview(load_metric_task_params(model_path)).distribution_chart_stats(date_from, date_to)
    assert type(res) is dict
    assert type(res[str(date_to)]) is dict

    assert res[str(date_to)] == {
      'income': {'dist': {' <=50K': 1}, 'imp': 0},
      'age': {'avg': 0.0, 'std_dev': 0, 'imp': 0.716105},
      'workclass': {'dist': {0: 1}, 'imp': 0.120064},
      'fnlwgt': {'avg': 0.0, 'std_dev': 0, 'imp': 1.0},
      'education': {'dist': {0: 1}, 'imp': 0.299958},
      'education-num': {'avg': 0.0, 'std_dev': 0, 'imp': 0},
      'marital-status': {'dist': {0: 1}, 'imp': 0.143296},
      'occupation': {'dist': {0: 1}, 'imp': 0.209677},
      'relationship': {'dist': {0: 1}, 'imp': 0.086982},
      'race': {'dist': {0: 1}, 'imp': 0.041806},
      'sex': {'dist': {0: 1}, 'imp': 0.039482},
      'capital-gain': {'avg': 0.0, 'std_dev': 0, 'imp': 0.313237},

def test_set_support_review_model_flag():
    # setup
    model_path = 'tests/fixtures/test_set_support_review_model_flag'
    shutil.copyfile(model_path + '/options_original.json', model_path + '/options.json')

    # test
    ModelReview({'model_path': model_path}).set_support_review_model_flag(True)

    res = {}

    with open(model_path + '/options.json', 'r') as f:
      res = json.load(f)

    assert res['support_review_model'] == True

    # teardown
    os.remove(model_path + '/options.json')

def test_count_actuals_by_prediction_id():
    model_path = 'tests/fixtures/test_count_actuals_by_prediction_id/adult'
    res = ModelReview({'model_path': model_path}).count_actuals_by_prediction_id()

    assert type(res) is dict
    assert len(res) > 0

    assert res == {
      'ffa89d52-5300-412d-b7a4-d21b3c9b7d16': 2,
      '5d9f640d-529a-42bd-be85-172107249a01': 1,
      '066f3c25-80ee-4c75-af15-38cda8a4ad57': 1
    }

def test_distribution_chart_stats():
    model_path = 'tests/fixtures/test_distribution_chart_stats/bikesharing'
    date_from = datetime.date(2020, 2, 16)
    date_to = datetime.date(2020, 2, 19)

    res = ModelReview(load_metric_task_params(model_path)).distribution_chart_stats(date_from, date_to)
    assert type(res) is dict
    assert type(res[str(date_to)]) is dict

    assert res[str(date_to)] == {
      'cnt': { 'avg': 483.18357849636016, 'std_dev': 0.0, 'imp': 0 },
      'dteday': { 'avg': 0.0,  'std_dev': 0.0, 'imp': 0 },
      'season': { 'dist': { 0: 2 }, 'imp': 0},
      'yr': { 'dist': { 0: 2 }, 'imp': 0 },
      'mnth': { 'avg': 0.0, 'std_dev': 0.0, 'imp': 0 },
      'holiday': { 'dist': { 0: 2 }, 'imp': 0},
      'weekday': { 'dist': { 0: 2 }, 'imp': 0},
      'workingday': { 'dist': { 0: 2 }, 'imp': 0},
      'weathersit': { 'dist': { 0: 2 }, 'imp': 0},
      'temp': { 'avg': 0.0, 'std_dev': 0.0, 'imp': 0 },
      'atemp': { 'avg': 0.0, 'std_dev': 0.0, 'imp': 0 },
      'hum': { 'avg': 0.0, 'std_dev': 0.0, 'imp': 0 },

def test_get_feature_importances_general_metrics_cache():
    model_path = 'tests/fixtures/test_distribution_chart_stats/adult'

    params = load_metric_task_params(model_path)

    res = ModelReview(params)._get_feature_importances()
    assert res == {'workclass': 0.12006373015194421, 'sex': 0.039481754114499897,
      'occupation': 0.20967661413259162, 'education': 0.2999579889231273,
      'relationship': 0.08698243068672135, 'marital-status': 0.14329620992107325,
      'race': 0.04180630794271793, 'native-country': 0.02072552576600564,
      'capital-loss': 0.2571256791934569, 'capital-gain': 0.31323744185565716,
      'hours-per-week': 0.4246393312722869, 'age': 0.7161049235052714, 'fnlwgt': 1.0}

def test_score_model_performance_daily_no_matching_actuals_and_predictions():
    model_path = 'tests/fixtures/test_score_model_performance_daily/iris_no_matches'
    date_from = datetime.date(2020, 2, 16)
    date_to = datetime.date(2020, 2, 18)

    res = ModelReview({'model_path': model_path}).score_model_performance_daily(date_from, str(date_to))
    assert type(res) is dict
    assert res[str(date_from)] == 0

def test_import_data(self):
        print("Current directory: {}".format(os.getcwd()))
        self.ctx = Context()
        print("Project name: {}".format(self.ctx.config.get('name')))
        a2ml = AzureA2ML(self.ctx.copy('azure'))
        a2ml.import_data()

def test_list_projects_server(self):
        from a2ml.api.a2ml_project import A2MLProject

        ctx = Context(
            path=os.path.join(
                os.environ.get('A2ML_PROJECT_PATH', ''),
                'cli-integration-test'
            ),
            debug=True
        )
        provider = "azure"
        ctx.config.set('providers', [provider])
        ctx.config.set('use_server', True)

        A2MLProject(ctx, provider).list()