How to use mock_dataframe method in pandera

Best Python code snippet using pandera_python

plot_workflow_result_tests.py

Source:plot_workflow_result_tests.py

1from unittest import mock2import pandas as pd3from datetime import datetime as dt4from tethysext.atcore.models.resource_workflow_results import PlotWorkflowResult5from tethysext.atcore.tests.utilities.sqlalchemy_helpers import SqlAlchemyTestCase6from tethysext.atcore.tests.utilities.sqlalchemy_helpers import setup_module_for_sqlalchemy_tests, \7    tear_down_module_for_sqlalchemy_tests8import plotly.graph_objs as go9from bokeh.plotting import figure10def setUpModule():11    setup_module_for_sqlalchemy_tests()12def tearDownModule():13    tear_down_module_for_sqlalchemy_tests()14class PlotWorkflowResultTests(SqlAlchemyTestCase):15    def setUp(self):16        super().setUp()17        self.instance = PlotWorkflowResult(name='test')18    def bind_instance_to_session(self):19        self.session.add(self.instance)20        self.session.commit()21    def test_default_options(self):22        baseline = {23            'renderer': 'plotly',24            'axes': [],25            'plot_type': 'lines',26            'axis_labels': ['x', 'y'],27            'line_shape': 'linear',28            'x_axis_type': 'datetime',29            'no_dataset_message': 'No dataset found.'30        }31        self.assertDictEqual(baseline, self.instance.default_options)32    def test_datasets(self):33        self.assertDictEqual({}, self.instance.data)34        ret = self.instance.datasets35        self.assertListEqual([], ret)36    def test_reset(self):37        self.instance.data['datasets'] = 'Bad data to reset'38        self.instance.reset()39        ret = self.instance.data['datasets']40        self.assertEqual([], ret)41    def test__add_dataset(self):42        test_data = 'Test data'43        self.instance._add_dataset(test_data)44        self.assertListEqual([test_data], self.instance.datasets)45    def test__add_plot(self):46        test_data = 'Test plot'47        self.instance._add_plot(test_data)48        self.assertEqual(test_data, self.instance.plot)49    def test_datasets_bound(self):50        self.bind_instance_to_session()51        self.test_datasets()52    def test_reset_datasets_bound(self):53        self.bind_instance_to_session()54        self.test_reset()55    def test__add_dataset_bound(self):56        self.bind_instance_to_session()57        self.test__add_dataset()58    def test_add_series_no_title(self):59        self.assertRaises(ValueError, self.instance.add_series, '', ['test'])60    def test_add_series_no_data(self):61        self.assertRaises(ValueError, self.instance.add_series, 'title', '')62    def test_add_series_empty_data_frame(self):63        mock_dataframe = mock.MagicMock(spec=pd.DataFrame, empty=True)64        self.assertRaises(ValueError, self.instance.add_series, 'title', mock_dataframe)65    @mock.patch('tethysext.atcore.models.resource_workflow_results.plot_workflow_result.PlotWorkflowResult._add_dataset')  # noqa: E50166    def test_add_series(self, mock_add_dataset):67        mock_dataframe = mock.MagicMock(spec=pd.DataFrame, empty=False)68        self.instance.add_series('series title', mock_dataframe)69        baseline = {70            'title': 'series title',71            'dataset': mock_dataframe,72        }73        mock_add_dataset.assert_called_with(baseline)74    @mock.patch('tethysext.atcore.models.resource_workflow_results.plot_workflow_result.PlotWorkflowResult._add_dataset')  # noqa: E50175    def test_plot_from_dataframe(self, mock_add_dataset):76        mock_dataframe = mock.MagicMock(spec=pd.DataFrame, empty=False)77        self.instance.plot_from_dataframe(mock_dataframe)78        baseline = {79            'dataset': mock_dataframe,80            'series_axes': [],81            'series_labels': []82        }83        mock_add_dataset.assert_called_with(baseline)84    def test_plot_from_dataframe_not_dataframe(self):85        self.assertRaises(ValueError, self.instance.plot_from_dataframe, ['test'])86    def test_plot_from_dataframe_empty_dataframe(self):87        mock_dataframe = mock.MagicMock(spec=pd.DataFrame, empty=True)88        self.assertRaises(ValueError, self.instance.plot_from_dataframe, mock_dataframe)89    @mock.patch('tethysext.atcore.models.resource_workflow_results.plot_workflow_result.PlotWorkflowResult._add_plot')  # noqa: E50190    def test_add_plot(self, mock_add_dataset):91        mock_plot = mock.MagicMock(spec=go.Figure, empty=False)92        self.instance.add_plot(mock_plot)93        baseline = {94            'plot_object': mock_plot,95        }96        mock_add_dataset.assert_called_with(baseline)97    def test_add_plot_not_plolty(self):98        self.assertRaises(ValueError, self.instance.add_plot, 'foo')99    @mock.patch('tethysext.atcore.models.resource_workflow_results.plot_workflow_result.PlotWorkflowResult.options')100    def test_get_plot_object_dict(self, mock_options):101        mock_plotly_plot = mock.MagicMock(spec=go.Figure, empty=False)102        mock_options.get = mock.MagicMock(side_effect=['plotly', 'lines', ['x', 'y'], 'linear', 'linear'])103        self.instance.add_plot(mock_plotly_plot)104        ret_plot = self.instance.get_plot_object()105        self.assertEqual(ret_plot, mock_plotly_plot)106    @mock.patch('tethysext.atcore.models.resource_workflow_results.plot_workflow_result.PlotWorkflowResult.options')107    @mock.patch('tethysext.atcore.models.resource_workflow_results.plot_workflow_result.figure')108    def test_get_plot_object_bokeh_line(self, mock_bokeh_figure, mock_options):109        mock_bokeh_plot = mock.MagicMock(110            spec=figure, xaxis=mock.MagicMock(axis_label='x'), yaxis=mock.MagicMock(axis_label='y'),111            line=mock.MagicMock(return_value='test line type')112        )113        mock_bokeh_figure.return_value = mock_bokeh_plot114        mock_dataframe = pd.DataFrame({115            'x': [dt(2020, 1, 2), dt(2020, 1, 3), dt(2020, 1, 4), dt(2020, 1, 5), dt(2020, 1, 6), dt(2020, 1, 7)],116            'y': [2, 3, 4, 5, 6, 7]117        })118        mock_datasets = [{119            'title': 'Test Title',120            'series_axes': [('x', 'y')],121            'series_labels': ['test_label'],122            'dataset': mock_dataframe123        }]124        mock_options.get = mock.MagicMock(side_effect=['bokeh', 'lines', ['x', 'y'], 'linear', 'linear'])125        self.instance.plot = mock_bokeh_plot126        self.instance.datasets = mock_datasets127        ret_plot = self.instance.get_plot_object()128        self.assertEqual(ret_plot, mock_bokeh_plot)129    @mock.patch('tethysext.atcore.models.resource_workflow_results.plot_workflow_result.PlotWorkflowResult.options')130    @mock.patch('tethysext.atcore.models.resource_workflow_results.plot_workflow_result.figure')131    def test_get_plot_object_bokeh_scatter(self, mock_bokeh_figure, mock_options):132        mock_bokeh_plot = mock.MagicMock(133            spec=figure, xaxis=mock.MagicMock(axis_label='x'), yaxis=mock.MagicMock(axis_label='y'),134            scatter=mock.MagicMock(return_value='test scatter type')135        )136        mock_bokeh_figure.return_value = mock_bokeh_plot137        mock_dataframe = pd.DataFrame(138            {'x': [dt(2020, 1, 2), dt(2020, 1, 3), dt(2020, 1, 4)], 'y': [2, 3, 4]},139            columns=['x', 'y']140        )141        mock_datasets = [{142            'title': 'Test Title',143            'series_axes': [],144            'series_labels': [],145            'dataset': mock_dataframe146        }]147        mock_options.get = mock.MagicMock(side_effect=['bokeh', 'scatter', ['x', 'y'], 'linear', 'linear'])148        self.instance.plot = mock_bokeh_plot149        self.instance.datasets = mock_datasets150        ret_plot = self.instance.get_plot_object()151        self.assertEqual(ret_plot, mock_bokeh_plot)152    @mock.patch('tethysext.atcore.models.resource_workflow_results.plot_workflow_result.PlotWorkflowResult.options')153    @mock.patch('tethysext.atcore.models.resource_workflow_results.plot_workflow_result.go.Figure')154    @mock.patch('tethysext.atcore.models.resource_workflow_results.plot_workflow_result.go.Scatter')155    def test_get_plot_object_plotly_line(self, mock_scatter_plot, mock_plotly_figure, mock_options):156        mock_plotly_plot = mock.MagicMock(157            spec=go.Figure, xaxis=mock.MagicMock(axis_label='x'), yaxis=mock.MagicMock(axis_label='y'),158            add_trace=mock.MagicMock(return_value=mock_scatter_plot)159        )160        mock_plotly_figure.return_value = mock_plotly_plot161        mock_dataframe = pd.DataFrame({162            'x': [dt(2020, 1, 2), dt(2020, 1, 3), dt(2020, 1, 4), dt(2020, 1, 5), dt(2020, 1, 6), dt(2020, 1, 7)],163            'y': [2, 3, 4, 5, 6, 7]164        })165        mock_datasets = [{166            'title': 'Test Title',167            'series_axes': [('x', 'y')],168            'series_labels': ['test_label'],169            'dataset': mock_dataframe170        }]171        mock_options.get = mock.MagicMock(side_effect=['plotly', 'lines', ['x', 'y'], 'linear', 'linear'])172        self.instance.plot = mock_plotly_plot173        self.instance.datasets = mock_datasets174        ret_plot = self.instance.get_plot_object()175        self.assertEqual(ret_plot, mock_plotly_plot)176    @mock.patch('tethysext.atcore.models.resource_workflow_results.plot_workflow_result.PlotWorkflowResult.options')177    @mock.patch('tethysext.atcore.models.resource_workflow_results.plot_workflow_result.go.Figure')178    @mock.patch('tethysext.atcore.models.resource_workflow_results.plot_workflow_result.go.Scatter')179    def test_get_plot_object_plotly_list_dataset(self, mock_scatter_plot, mock_plotly_figure,180                                                 mock_options):181        mock_plotly_plot = mock.MagicMock(182            spec=go.Figure, xaxis=mock.MagicMock(axis_label='x'), yaxis=mock.MagicMock(axis_label='y'),183            add_trace=mock.MagicMock(return_value=mock_scatter_plot)184        )185        mock_plotly_figure.return_value = mock_plotly_plot186        mock_dataset = [187            [dt(2020, 1, 2), dt(2020, 1, 3), dt(2020, 1, 4), dt(2020, 1, 5), dt(2020, 1, 6), dt(2020, 1, 7)],188            [2, 3, 4, 5, 6, 7]189        ]190        mock_datasets = [{191            'title': 'Test Title',192            'series_axes': [('x', 'y')],193            'series_labels': ['test_label'],194            'dataset': mock_dataset195        }]196        mock_options.get = mock.MagicMock(side_effect=['plotly', 'scatter', ['x', 'y'], 'linear', 'linear'])197        self.instance.plot = mock_plotly_plot198        self.instance.datasets = mock_datasets199        ret_plot = self.instance.get_plot_object()...

test_stock_data.py

Source:test_stock_data.py

1import os2import unittest3import datetime as dt4import requests_mock5from unittest.mock import Mock, patch, call6import logging7import pandas as pd8import pandas_datareader.data as web9import requests10import scan_data as scan_data11from alpaca import Alpaca12from stock_data import Stock13logging.disable(logging.CRITICAL)14class TestStockData(unittest.TestCase):15    def setUp(self):16        self.mock_stock = Stock('FAKE')17        self.mock_dict = {18            'date': ['2019-11-12', '2019-11-13'],19            'open': [261.55, 261.13],20            'high': [262.79, 264.78],21            'low': [260.92, 261.07],22            'close': [261.96, 264.47],23            'adjusted close': [260.6421, 263.1395],24            'volume': [21847226, 25817593],25            'dividend amount': [0., 0.],26            'split coefficient': [1., 1.],27            }28        self.mock_dataframe = pd.DataFrame.from_dict(data=self.mock_dict)29        self.mock_dataframe.set_index('date')30    ### ------------------- DATA GETTERS TESTS ------------------- ###31    @patch('stock_data.web.DataReader')32    def test_get_trend_data(self, mock_datareader):33        mock_datareader.return_value = self.mock_dataframe34        mock_result_dataframe = self.mock_dataframe.copy()35        mock_result_dataframe['sma50'] = [float('nan'), float('nan')]36        actual_result = self.mock_stock.get_trend_data()37        pd.testing.assert_frame_equal(actual_result, mock_result_dataframe)38    39    @patch.object(Stock, 'get_stochastic')40    @patch('stock_data.TimeSeries')41    def test_get_tactical_data(self, mock_timeseries, mock_get_stochastic):42        mock_timeseries.return_value.get_intraday.return_value = (self.mock_dataframe, '')43        mock_result_dataframe = self.mock_dataframe.copy()44        mock_result_dataframe.rename(lambda s: '   ' + s, axis=1, inplace=True)45        mock_result_dataframe['fast k'] = [float('nan'), float('nan')]46        mock_result_dataframe['k'] = [float('nan'), float('nan')]47        mock_result_dataframe['d'] = [float('nan'), float('nan')]48        mock_get_stochastic.return_value = mock_result_dataframe49        actual_result = self.mock_stock.get_tactical_data()50        mock_get_stochastic.assert_called_once_with(self.mock_dataframe)51        pd.testing.assert_frame_equal(actual_result, mock_result_dataframe)52    53    @patch('stock_data.json.loads')54    #@patch('stock_data.pd.DataFrame.from_dict')55    @requests_mock.Mocker()56    def test_get_execution_data(self, mock_json_loads, mock_request):57        58        mock_bars = {59            "FAKE": [60                {61                "t": 1544129220,62                "o": 172.26,63                "h": 172.3,64                "l": 172.16,65                "c": 172.18,66                "v": 3892,67                }68            ]69            }70        url = 'https://data.alpaca.markets/v1/bars/1Min?symbols=FAKE&limit=10'71        mock_request.get(url, text='request ok')72        mock_json_loads.return_value = mock_bars73        actual_result = self.mock_stock.get_execution_data()74        self.assertIsInstance(actual_result, pd.DataFrame)75        76    ### ------------------- POTENTIAL GETTERS TESTS ------------------- ###77    78    def test_get_trend_potential(self):79        pass80 81    82    def test_get_tactical_potential(self):83        pass84 85    def test_get_execution_potential(self):86        pass87    ### ------------------- STATIC METHODS TESTS ------------------- ###88    def test_is_in_range_true_default_range(self):89        x = 9590        y = 10591        actual_result = self.mock_stock.is_in_range(x, y)92        self.assertEqual(actual_result, True)93    94    95    def test_is_in_range_false_default_range(self):96        x = 8997        y = 11198        actual_result = self.mock_stock.is_in_range(x, y)99        self.assertEqual(actual_result, False)100 101    def test_is_in_range_true_custom_range(self):102        x = 89103        y = 111104        range_percent = 20105        actual_result = self.mock_stock.is_in_range(x, y, range_percent)106        self.assertEqual(actual_result, True)107 108    def test_is_trending_up_true_default_step(self):109        array = [1, 2, 3]110        actual_result = self.mock_stock.is_trending_up(array)111        self.assertEqual(actual_result, True)112        113    def test_is_trending_up_false_default_step(self):114        array = [3, 1, 2]115        actual_result = self.mock_stock.is_trending_up(array)116        self.assertEqual(actual_result, False)117 118    def test_is_trending_up_true_custom_step(self):119        array = [1, 2, 3, 4, 5, 6, 7, 6, 9, 10]120        step = 2121        actual_result = self.mock_stock.is_trending_up(array, step)122        self.assertEqual(actual_result, True)123 124    def test_is_trending_up_false_custom_step(self):125        array = [1, 2, 3, 8, 5, 6, 7, 8, 9, 10]126        step = 2127        actual_result = self.mock_stock.is_trending_up(array, step)128        self.assertEqual(actual_result, False)...

dataset_workflow_result_tests.py

Source:dataset_workflow_result_tests.py

1from unittest import mock2import pandas as pd3from tethysext.atcore.models.resource_workflow_results import DatasetWorkflowResult4from tethysext.atcore.tests.utilities.sqlalchemy_helpers import SqlAlchemyTestCase5from tethysext.atcore.tests.utilities.sqlalchemy_helpers import setup_module_for_sqlalchemy_tests, \6    tear_down_module_for_sqlalchemy_tests7def setUpModule():8    setup_module_for_sqlalchemy_tests()9def tearDownModule():10    tear_down_module_for_sqlalchemy_tests()11class DatasetWorkflowResultTests(SqlAlchemyTestCase):12    def setUp(self):13        super().setUp()14        self.instance = DatasetWorkflowResult(name='test')15    def bind_instance_to_session(self):16        self.session.add(self.instance)17        self.session.commit()18    def test_default_options(self):19        baseline = {20            'data_table_kwargs': {21                'searching': False,22                'paging': False,23                'info': False24            },25            'no_dataset_message': 'No dataset found.'26        }27        self.assertDictEqual(baseline, self.instance.default_options)28    def test_datasets(self):29        self.assertDictEqual({}, self.instance.data)30        ret = self.instance.datasets31        self.assertListEqual([], ret)32    def test_reset(self):33        self.instance.data['datasets'] = 'Bad data to reset'34        self.instance.reset()35        ret = self.instance.data['datasets']36        self.assertEqual([], ret)37    def test__add_dataset(self):38        test_data = 'Test data'39        self.instance._add_dataset(test_data)40        self.assertListEqual([test_data], self.instance.datasets)41    def test_datasets_bound(self):42        self.bind_instance_to_session()43        self.test_datasets()44    def test_reset_datasets_bound(self):45        self.bind_instance_to_session()46        self.test_reset()47    def test__add_dataset_bound(self):48        self.bind_instance_to_session()49        self.test__add_dataset()50    @mock.patch('tethysext.atcore.models.resource_workflow_results.dataset_workflow_result.DatasetWorkflowResult._add_dataset')  # noqa: E50151    def test_add_pandas_dataframe(self, mock_add_dataset):52        mock_dataframe = mock.MagicMock(spec=pd.DataFrame, empty=False)53        self.instance.add_pandas_dataframe('foo', mock_dataframe)54        baseline = {55            'title': 'foo',56            'dataset': mock_dataframe,57            'show_export_button': False58        }59        mock_add_dataset.assert_called_with(baseline)60    def test_add_pandas_dataframe_no_title(self):61        mock_dataframe = mock.MagicMock(spec=pd.DataFrame, empty=False)62        self.assertRaises(ValueError, self.instance.add_pandas_dataframe, '', mock_dataframe)63        self.assertRaises(ValueError, self.instance.add_pandas_dataframe, None, mock_dataframe)64    def test_add_pandas_dataframe_not_dataframe(self):65        self.assertRaises(ValueError, self.instance.add_pandas_dataframe, 'foo', ['test'])66    def test_add_pandas_dataframe_empty_dataframe(self):67        mock_dataframe = mock.MagicMock(spec=pd.DataFrame, empty=True)...

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