def test_existing_arbitrary_collection_mdataframe(self):
data = {
'foo': 'bar',
'bax': {
'fox': 'fax',
}
}
store = OmegaStore()
store.register_backend(PandasRawDictBackend.KIND, PandasRawDictBackend)
foo_coll = store.mongodb['foo']
foo_coll.insert(data)
store.make_metadata('myfoo', collection='foo',
kind='pandas.rawdict').save()
self.assertIn('myfoo', store.list())
# test we get back _id column if raw=True
mdf = store.getl('myfoo', raw=True)
self.assertIsInstance(mdf, MDataFrame)
data_df = mdf.value
data_raw = store.collection('myfoo').find_one()
assert_frame_equal(json_normalize(data_raw), data_df)
# test we get just the data column
mdf = store.getl('myfoo', raw=False)
self.assertIsInstance(mdf, MDataFrame)
data_df = mdf.value
data_raw = store.collection('myfoo').find_one()
cols = ['foo', 'bax.fox']
assert_frame_equal(json_normalize(data)[cols], data_df[cols])
def test_existing_arbitrary_collection_flat(self):
data = {'foo': 'bar', 'bax': 'fox'}
store = OmegaStore()
store.register_backend(PandasRawDictBackend.KIND, PandasRawDictBackend)
foo_coll = store.mongodb['foo']
foo_coll.insert(data)
store.make_metadata('myfoo', collection='foo',
kind='pandas.rawdict').save()
self.assertIn('myfoo', store.list())
# test we get back _id column if raw=True
data_ = store.get('myfoo', raw=True)
assert_frame_equal(json_normalize(data), data_)
# test we get just the data column
data_ = store.get('myfoo', raw=False)
cols = ['foo', 'bax']
assert_frame_equal(json_normalize(data)[cols], data_[cols])