def add_output_attributes(candset, l_output_attrs=None, r_output_attrs=None, l_output_prefix='ltable_',
r_output_prefix='rtable_', validate=True, copy_props=True,
delete_from_catalog=True, verbose=False):
if not isinstance(candset, pd.DataFrame):
logger.error('Input object is not of type pandas data frame')
raise AssertionError('Input object is not of type pandas data frame')
# # get metadata
key, fk_ltable, fk_rtable, ltable, rtable, l_key, r_key = cm.get_metadata_for_candset(candset, logger, verbose)
if validate:
cm._validate_metadata_for_candset(candset, key, fk_ltable, fk_rtable, ltable, rtable, l_key, r_key,
logger, verbose)
index_values = candset.index
df = _add_output_attributes(candset, fk_ltable, fk_rtable, ltable, rtable, l_key, r_key,
l_output_attrs, r_output_attrs, l_output_prefix, r_output_prefix,
validate=False)
df.set_index(index_values, inplace=True)
if copy_props:
cm.init_properties(df)
cm.copy_properties(candset, df)
if delete_from_catalog:
cm.del_all_properties(candset)
return df
def add_output_attributes(candset, l_output_attrs=None, r_output_attrs=None, l_output_prefix='ltable_',
r_output_prefix='rtable_', validate=True, copy_props=True,
delete_from_catalog=True, verbose=False):
if not isinstance(candset, pd.DataFrame):
logger.error('Input object is not of type pandas data frame')
raise AssertionError('Input object is not of type pandas data frame')
# # get metadata
key, fk_ltable, fk_rtable, ltable, rtable, l_key, r_key = cm.get_metadata_for_candset(candset, logger, verbose)
if validate:
cm._validate_metadata_for_candset(candset, key, fk_ltable, fk_rtable, ltable, rtable, l_key, r_key,
logger, verbose)
index_values = candset.index
df = _add_output_attributes(candset, fk_ltable, fk_rtable, ltable, rtable, l_key, r_key,
l_output_attrs, r_output_attrs, l_output_prefix, r_output_prefix,
validate=False)
df.set_index(index_values, inplace=True)
if copy_props:
cm.init_properties(df)
cm.copy_properties(candset, df)
if delete_from_catalog:
cm.del_all_properties(candset)
return df
def test_del_all_properties_df_notin_catalog(self):
A = pd.read_csv(path_a)
cm.del_all_properties(A)
def test_del_all_properties_invalid_df(self):
cm.del_all_properties(None)
def test_del_all_properties_valid_2(self):
A = read_csv_metadata(path_a)
B = read_csv_metadata(path_b)
C = read_csv_metadata(path_c, ltable=A, rtable=B)
cm.del_all_properties(C)
self.assertEqual(cm.is_dfinfo_present(C), False)
def test_del_all_properties_valid_1(self):
A = read_csv_metadata(path_a)
cm.del_all_properties(A)
self.assertEqual(cm.is_dfinfo_present(A), False)
