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')))
