def testSaveAllLoadAllWithDict(self): ''' Creates 2..n files from an input columns dict depending upon the number of arkouda_server locales, retrieves all datasets and correspoding pdarrays, and confirms they match inputs :return: None :raise: AssertionError if the input and returned datasets and pdarrays don't match ''' self._create_file(columns=self.dict_columns, path_prefix='{}/iotest_dict'.format( IOTest.io_test_dir)) retrieved_columns = ak.load_all('{}/iotest_dict'.format( IOTest.io_test_dir)) self.assertEqual(3, len(retrieved_columns)) self.assertEqual(self.dict_columns['int_tens_pdarray'].all(), retrieved_columns['int_tens_pdarray'].all()) self.assertEqual(self.dict_columns['int_hundreds_pdarray'].all(), retrieved_columns['int_hundreds_pdarray'].all()) self.assertEqual(self.dict_columns['float_pdarray'].all(), retrieved_columns['float_pdarray'].all()) self.assertEqual( 3, len( ak.get_datasets('{}/iotest_dict_LOCALE0'.format( IOTest.io_test_dir))))
def testSaveAllLoadAllWithList(self): ''' Creates 2..n files from an input columns and names list depending upon the number of arkouda_server locales, retrieves all datasets and correspoding pdarrays, and confirms they match inputs :return: None :raise: AssertionError if the input and returned datasets and pdarrays don't match ''' self._create_file(columns=self.list_columns, prefix_path='{}/iotest_list'.format(IOTest.io_test_dir), names=self.names) retrieved_columns = ak.load_all(path_prefix='{}/iotest_list'.format(IOTest.io_test_dir)) itp = self.list_columns[0].to_ndarray() itp.sort() ritp = retrieved_columns['int_tens_pdarray'].to_ndarray() ritp.sort() ihp = self.list_columns[1].to_ndarray() ihp.sort() rihp = retrieved_columns['int_hundreds_pdarray'].to_ndarray() rihp.sort() fp = self.list_columns[2].to_ndarray() fp.sort() rfp = retrieved_columns['float_pdarray'].to_ndarray() rfp.sort() self.assertEqual(4, len(retrieved_columns)) self.assertTrue((itp == ritp).all()) self.assertTrue((ihp == rihp).all()) self.assertTrue((fp == rfp).all()) self.assertEqual(len(self.list_columns[3]), len(retrieved_columns['bool_pdarray'])) self.assertEqual(4, len(ak.get_datasets('{}/iotest_list_LOCALE0'.format(IOTest.io_test_dir))))
def testGetDataSets(self): ''' Creates 1..n files depending upon the number of arkouda_server locales containing three datasets and confirms the expected number of datasets along with the dataset names :return: None :raise: AssertionError if the input and returned dataset names don't match ''' self._create_file(columns=self.dict_columns, prefix_path='{}/iotest_dict_columns'.format( IOTest.io_test_dir)) datasets = ak.get_datasets('{}/iotest_dict_columns_LOCALE0000'.format( IOTest.io_test_dir)) self.assertEqual(4, len(datasets)) for dataset in datasets: self.assertIn(dataset, self.names) # Test load_all with invalid filename with self.assertRaises(RuntimeError) as cm: ak.get_datasets('{}/iotest_dict_columns_LOCALE000'.format( IOTest.io_test_dir)) self.assertIn('does not exist in a location accessible to Arkouda', cm.exception.args[0])
def testGetDataSets(self): ''' Creates 1..n files depending upon the number of arkouda_server locales containing three datasets and confirms the expected number of datasets along with the dataset names :return: None :raise: AssertionError if the input and returned dataset names don't match ''' self._create_file(columns=self.dict_columns, prefix_path='{}/iotest_dict_columns'.format(IOTest.io_test_dir)) datasets = ak.get_datasets('{}/iotest_dict_columns_LOCALE0'.format(IOTest.io_test_dir)) self.assertEqual(4, len(datasets)) for dataset in datasets: self.assertIn(dataset, self.names)
def testSaveAllLoadAllWithList(self): ''' Creates 2..n files from an input columns and names list depending upon the number of arkouda_server locales, retrieves all datasets and correspoding pdarrays, and confirms they match inputs :return: None :raise: AssertionError if the input and returned datasets and pdarrays don't match ''' self._create_file(columns=self.list_columns, path_prefix='/tmp/iotest_list', names=self.names) retrieved_columns = ak.load_all(path_prefix='/tmp/iotest_list') self.assertEqual(3, len(retrieved_columns)) self.assertEqual(self.list_columns[0].all(), retrieved_columns['int_tens_pdarray'].all()) self.assertEqual(self.list_columns[1].all(), retrieved_columns['int_hundreds_pdarray'].all()) self.assertEqual(self.list_columns[2].all(), retrieved_columns['float_pdarray'].all()) self.assertEqual(3, len(ak.get_datasets('/tmp/iotest_list_LOCALE0')))