def build_row_desc(data, preserve_index=False):
if not isinstance(data, (pd.DataFrame, gpd.GeoDataFrame)):
# Once https://issues.apache.org/jira/browse/ARROW-1576 is complete
# we can support pa.Table here too
raise TypeError("Create table is not supported for type {}. "
"Use a pandas DataFrame, or perform the create "
"separately".format(type(data)))
if preserve_index:
data = data.reset_index()
dtypes = []
is_array = {}
for col in data.columns:
_dtype = get_mapd_dtype(data[col])
is_array[col] = True if _dtype.startswith('ARRAY') else None
dtypes.append((col, _dtype.replace('ARRAY/', '')))
# row_desc :: List<TColumnType>
row_desc = [
TColumnType(
name,
TTypeInfo(getattr(TDatumType, mapd_type), is_array=is_array[name]),
) for name, mapd_type in dtypes
]
# force text encoding dict for all string columns
# default is TEXT ENCODING DICT(32) when only tct.col_type.encoding = 4 set
# https://github.com/omnisci/pymapd/issues/140#issuecomment-477353420
for tct in row_desc:
if tct.col_type.type == 6:
tct.col_type.encoding = 4
elif tct.col_type.type in GEO_TYPE_ID:
tct.col_type.precision = 23
return row_desc
def build_row_desc(data, preserve_index=False):
if not isinstance(data, pd.DataFrame):
# Once https://issues.apache.org/jira/browse/ARROW-1576 is complete
# we can support pa.Table here too
raise TypeError("Create table is not supported for type {}. "
"Use a pandas DataFrame, or perform the create "
"separately".format(type(data)))
if preserve_index:
data = data.reset_index()
dtypes = [(col, get_mapd_dtype(data[col])) for col in data.columns]
# row_desc :: List<TColumnType>
row_desc = [
TColumnType(name, TTypeInfo(getattr(TDatumType, mapd_type)))
for name, mapd_type in dtypes
]
# force text encoding dict for all string columns
# default is TEXT ENCODING DICT(32) when only tct.col_type.encoding = 4 set
# https://github.com/omnisci/pymapd/issues/140#issuecomment-477353420
for tct in row_desc:
if tct.col_type.type == 6:
tct.col_type.encoding = 4
return row_desc
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
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)],
"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, 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='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_nulls_handled(self):
rs = TQueryResult(
TRowSet(
row_desc=[
TColumnType(col_name='a',
col_type=TTypeInfo(type=0, nullable=True)),
TColumnType(col_name='b',
col_type=TTypeInfo(type=1, nullable=True)),
TColumnType(col_name='c',
col_type=TTypeInfo(type=2, nullable=True)),
TColumnType(col_name='d',
col_type=TTypeInfo(type=3, nullable=True)),
TColumnType(col_name='e',
col_type=TTypeInfo(type=4, nullable=True)),
TColumnType(col_name='f',
col_type=TTypeInfo(type=5, nullable=True)),
TColumnType(col_name='g',
col_type=TTypeInfo(type=6, nullable=True)),
TColumnType(col_name='h',
col_type=TTypeInfo(type=7, nullable=True)),
TColumnType(col_name='i',
col_type=TTypeInfo(type=8, nullable=True)),
TColumnType(col_name='j',
col_type=TTypeInfo(type=9, nullable=True)),
TColumnType(
col_name='k',
col_type=TTypeInfo(type=10, nullable=True),
),
],
rows=[],
columns=[
TColumn(data=TColumnData(int_col=[-2147483648]),
nulls=[True]),
TColumn(data=TColumnData(int_col=[-2147483648]),
nulls=[True]),
TColumn(data=TColumnData(int_col=[-2147483648]),
nulls=[True]),
TColumn(data=TColumnData(real_col=[-2147483648]),
nulls=[True]), # noqa
TColumn(data=TColumnData(real_col=[-2147483648]),
nulls=[True]), # noqa
TColumn(data=TColumnData(real_col=[-2147483648]),
nulls=[True]), # noqa
TColumn(data=TColumnData(str_col=[-2147483648]),
nulls=[True]),
TColumn(data=TColumnData(int_col=[-2147483648]),
nulls=[True]),
TColumn(data=TColumnData(int_col=[-2147483648]),
nulls=[True]),
TColumn(data=TColumnData(int_col=[-2147483648]),
nulls=[True]),
TColumn(data=TColumnData(int_col=[-2147483648]),
nulls=[True]),
],
is_columnar=True,
))
result = list(make_row_results_set(rs))
assert result == [(None, ) * 11]
def test_sql_validate(self, con):
from omnisci.common.ttypes import TTypeInfo
c = con.cursor()
c.execute('drop table if exists stocks;')
create = ('create table stocks (date_ text, trans text, symbol text, '
'qty int, price float, vol float);')
c.execute(create)
q = "select * from stocks"
results = con._client.sql_validate(con._session, q)
col_names = sorted([r.col_name for r in results])
col_types = [r.col_type for r in results]
expected_col_names = [
'date_',
'price',
'qty',
'symbol',
'trans',
'vol',
]
expected_types = [
TTypeInfo(
type=6,
encoding=4,
nullable=True,
is_array=False,
precision=0,
scale=0,
comp_param=32,
size=-1,
),
TTypeInfo(
type=6,
encoding=4,
nullable=True,
is_array=False,
precision=0,
scale=0,
comp_param=32,
size=-1,
),
TTypeInfo(
type=6,
encoding=4,
nullable=True,
is_array=False,
precision=0,
scale=0,
comp_param=32,
size=-1,
),
TTypeInfo(
type=1,
encoding=0,
nullable=True,
is_array=False,
precision=0,
scale=0,
comp_param=0,
size=-1,
),
TTypeInfo(
type=3,
encoding=0,
nullable=True,
is_array=False,
precision=0,
scale=0,
comp_param=0,
size=-1,
),
TTypeInfo(
type=3,
encoding=0,
nullable=True,
is_array=False,
precision=0,
scale=0,
comp_param=0,
size=-1,
),
]
assert col_types == expected_types
assert col_names == expected_col_names
def test_extract_row_details(self):
data = [
TColumnType(
col_name='date_',
col_type=TTypeInfo(
type=6,
encoding=4,
nullable=True,
is_array=False,
precision=0,
scale=0,
comp_param=32,
),
is_reserved_keyword=False,
src_name='',
),
TColumnType(
col_name='trans',
col_type=TTypeInfo(
type=6,
encoding=4,
nullable=True,
is_array=False,
precision=0,
scale=0,
comp_param=32,
),
is_reserved_keyword=False,
src_name='',
),
TColumnType(
col_name='symbol',
col_type=TTypeInfo(
type=6,
encoding=4,
nullable=True,
is_array=False,
precision=0,
scale=0,
comp_param=32,
),
is_reserved_keyword=False,
src_name='',
),
TColumnType(
col_name='qty',
col_type=TTypeInfo(
type=1,
encoding=0,
nullable=True,
is_array=False,
precision=0,
scale=0,
comp_param=0,
),
is_reserved_keyword=False,
src_name='',
),
TColumnType(
col_name='price',
col_type=TTypeInfo(
type=3,
encoding=0,
nullable=True,
is_array=False,
precision=0,
scale=0,
comp_param=0,
),
is_reserved_keyword=False,
src_name='',
),
TColumnType(
col_name='vol',
col_type=TTypeInfo(
type=3,
encoding=0,
nullable=True,
is_array=False,
precision=0,
scale=0,
comp_param=0,
),
is_reserved_keyword=False,
src_name='',
),
]
result = _extract_column_details(data)
expected = [
ColumnDetails(
name='date_',
type='STR',
nullable=True,
precision=0,
scale=0,
comp_param=32,
encoding='DICT',
is_array=False,
),
ColumnDetails(
name='trans',
type='STR',
nullable=True,
precision=0,
scale=0,
comp_param=32,
encoding='DICT',
is_array=False,
),
ColumnDetails(
name='symbol',
type='STR',
nullable=True,
precision=0,
scale=0,
comp_param=32,
encoding='DICT',
is_array=False,
),
ColumnDetails(
name='qty',
type='INT',
nullable=True,
precision=0,
scale=0,
comp_param=0,
encoding='NONE',
is_array=False,
),
ColumnDetails(
name='price',
type='FLOAT',
nullable=True,
precision=0,
scale=0,
comp_param=0,
encoding='NONE',
is_array=False,
),
ColumnDetails(
name='vol',
type='FLOAT',
nullable=True,
precision=0,
scale=0,
comp_param=0,
encoding='NONE',
is_array=False,
),
]
assert result == expected