def test_build_row_desc(self):
pd = pytest.importorskip("pandas")
import numpy as np
from mapd.ttypes import TTypeInfo, TColumnType
data = pd.DataFrame({
"boolean_": [True, False],
"smallint_": np.array([0, 1], dtype=np.int8),
"int_": np.array([0, 1], dtype=np.int32),
"bigint_": np.array([0, 1], dtype=np.int64),
"float_": np.array([0, 1], dtype=np.float32),
"double_": np.array([0, 1], dtype=np.float64),
"varchar_": ["a", "b"],
"text_": ['a', 'b'],
"time_": [datetime.time(0, 11, 59), datetime.time(13)],
"timestamp_": [pd.Timestamp("2016"), pd.Timestamp("2017")],
"date_": [datetime.date(2016, 1, 1), datetime.date(2017, 1, 1)],
}, columns=['boolean_', 'smallint_', 'int_', 'bigint_', 'float_',
'double_', 'varchar_', 'text_', 'time_', 'timestamp_',
'date_'])
result = _pandas_loaders.build_row_desc(data)
expected = [
TColumnType(col_name='boolean_',
col_type=TTypeInfo(type=10),
is_reserved_keyword=None),
TColumnType(col_name='smallint_',
col_type=TTypeInfo(type=0),
is_reserved_keyword=None),
TColumnType(col_name='int_',
col_type=TTypeInfo(type=1),
is_reserved_keyword=None),
TColumnType(col_name='bigint_',
col_type=TTypeInfo(type=2)),
TColumnType(col_name='float_',
col_type=TTypeInfo(type=3)),
TColumnType(col_name='double_',
col_type=TTypeInfo(type=5)),
TColumnType(col_name='varchar_',
col_type=TTypeInfo(type=6)),
TColumnType(col_name='text_',
col_type=TTypeInfo(type=6)),
TColumnType(col_name='time_',
col_type=TTypeInfo(type=7)),
TColumnType(col_name='timestamp_',
col_type=TTypeInfo(type=8)),
TColumnType(col_name='date_',
col_type=TTypeInfo(type=9))
]
assert result == expected
data.index.name = 'idx'
result = _pandas_loaders.build_row_desc(data, preserve_index=True)
expected.insert(0, TColumnType(col_name='idx',
col_type=TTypeInfo(type=2)))
assert result == expected
def test_create_non_pandas_raises(self):
with pytest.raises(TypeError) as m:
_pandas_loaders.build_row_desc([(1, 'a'), (2, 'b')])
assert m.match('is not supported for type ')
def test_build_row_desc(self):
data = pd.DataFrame(
{
'boolean_': [True, False],
'smallint_':
np.array([0, 1], dtype=np.int16),
'int_':
np.array([0, 1], dtype=np.int32),
'bigint_':
np.array([0, 1], dtype=np.int64),
'float_':
np.array([0, 1], dtype=np.float32),
'double_':
np.array([0, 1], dtype=np.float64),
'varchar_': ['a', 'b'],
'text_': ['a', 'b'],
'time_': [datetime.time(0, 11, 59),
datetime.time(13)],
'timestamp1_': [pd.Timestamp('2016'),
pd.Timestamp('2017')],
'timestamp2_': [
np.datetime64('2016-01-01 01:01:01.001001001'),
np.datetime64('2017-01-01 01:01:01.001001001'),
],
'date_': [
datetime.date(2016, 1, 1),
datetime.date(2017, 1, 1),
],
},
columns=[
'boolean_',
'smallint_',
'int_',
'bigint_',
'float_',
'double_',
'varchar_',
'text_',
'time_',
'timestamp1_',
'timestamp2_',
'date_',
],
)
result = _pandas_loaders.build_row_desc(data)
expected = [
TColumnType(
col_name='boolean_',
col_type=TTypeInfo(type=10),
is_reserved_keyword=None,
),
TColumnType(
col_name='smallint_',
col_type=TTypeInfo(type=0),
is_reserved_keyword=None,
),
TColumnType(
col_name='int_',
col_type=TTypeInfo(type=1),
is_reserved_keyword=None,
),
TColumnType(col_name='bigint_', col_type=TTypeInfo(type=2)),
TColumnType(col_name='float_', col_type=TTypeInfo(type=3)),
TColumnType(col_name='double_', col_type=TTypeInfo(type=5)),
TColumnType(col_name='varchar_',
col_type=TTypeInfo(type=6, encoding=4)),
TColumnType(col_name='text_',
col_type=TTypeInfo(type=6, encoding=4)),
TColumnType(col_name='time_', col_type=TTypeInfo(type=7)),
TColumnType(col_name='timestamp1_', col_type=TTypeInfo(type=8)),
TColumnType(col_name='timestamp2_',
col_type=TTypeInfo(type=8, precision=9)),
TColumnType(col_name='date_', col_type=TTypeInfo(type=9)),
]
assert result == expected
data.index.name = 'idx'
result = _pandas_loaders.build_row_desc(data, preserve_index=True)
expected.insert(
0, TColumnType(col_name='idx', col_type=TTypeInfo(type=2)))
assert result == expected
