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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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