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Remove dtypes.int_/float_ to eliminate confusion
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@jmao-denver
jmao-denver committed Jun 6, 2024
1 parent 081793d commit 6c75403
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Showing 7 changed files with 23 additions and 32 deletions.
4 changes: 2 additions & 2 deletions py/server/deephaven/csv.py
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Original file line number Diff line number Diff line change
Expand Up @@ -75,9 +75,9 @@ def read(
dht.byte: _JParsers.BYTE,
dht.char: _JParsers.CHAR,
dht.short: _JParsers.SHORT,
dht.int_: _JParsers.INT,
dht.int64: _JParsers.INT,
dht.long: _JParsers.LONG,
dht.float_: _JParsers.FLOAT_FAST,
dht.float64: _JParsers.FLOAT_FAST,
dht.double: _JParsers.DOUBLE,
dht.string: _JParsers.STRING,
dht.Instant: _JParsers.DATETIME,
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8 changes: 0 additions & 8 deletions py/server/deephaven/dtypes.py
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Original file line number Diff line number Diff line change
Expand Up @@ -85,8 +85,6 @@ def __call__(self, *args, **kwargs):
"""Signed 64bit integer type"""
int64 = long
"""Signed 64bit integer type"""
int_ = long
"""Signed 64bit integer type"""
float32 = DType(j_name="float", qst_type=_JQstType.floatType(), is_primitive=True, np_type=np.float32)
"""Single-precision floating-point number type"""
single = float32
Expand All @@ -95,8 +93,6 @@ def __call__(self, *args, **kwargs):
"""Double-precision floating-point number type"""
double = float64
"""Double-precision floating-point number type"""
float_ = float64
"""Double-precision floating-point number type"""
string = DType(j_name="java.lang.String", qst_type=_JQstType.stringType(), np_type=np.str_)
"""String type"""
Character = DType(j_name="java.lang.Character")
Expand Down Expand Up @@ -143,8 +139,6 @@ def __call__(self, *args, **kwargs):
"""64bit integer array type"""
int64_array = long_array
"""64bit integer array type"""
int_array = long_array
"""64bit integer array type"""
single_array = DType(j_name='[F')
"""Single-precision floating-point array type"""
float32_array = single_array
Expand All @@ -153,8 +147,6 @@ def __call__(self, *args, **kwargs):
"""Double-precision floating-point array type"""
float64_array = double_array
"""Double-precision floating-point array type"""
float_array = double_array
"""Double-precision floating-point array type"""
string_array = DType(j_name='[Ljava.lang.String;')
"""Java String array type"""
boolean_array = DType(j_name='[Ljava.lang.Boolean;')
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3 changes: 1 addition & 2 deletions py/server/deephaven/filters.py
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Original file line number Diff line number Diff line change
Expand Up @@ -6,10 +6,9 @@
from __future__ import annotations

from enum import Enum
from typing import List, Union
from typing import List, Union, Sequence

import jpy
import functools

from deephaven import DHError
from deephaven._wrapper import JObjectWrapper
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8 changes: 4 additions & 4 deletions py/server/tests/test_csv.py
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Original file line number Diff line number Diff line change
Expand Up @@ -16,15 +16,15 @@ def test_read_simple(self):

def test_read_header(self):
col_names = ["Strings", "Longs", "Floats"]
col_types = [dtypes.string, dtypes.long, dtypes.float_]
col_types = [dtypes.string, dtypes.long, dtypes.float64]
table_header = {k: v for k, v in zip(col_names, col_types)}
t = read_csv('tests/data/test_csv.csv', header=table_header)
t_col_names = [col.name for col in t.columns]
self.assertEqual(col_names, t_col_names)

def test_read_error_col_type(self):
col_names = ["Strings", "Longs", "Floats"]
col_types = [dtypes.string, dtypes.float_, dtypes.long]
col_types = [dtypes.string, dtypes.float64, dtypes.long]
table_header = {k: v for k, v in zip(col_names, col_types)}
with self.assertRaises(DHError) as cm:
t = read_csv('tests/data/test_csv.csv', header=table_header)
Expand All @@ -33,7 +33,7 @@ def test_read_error_col_type(self):

def test_read_error_quote(self):
col_names = ["Strings", "Longs", "Floats"]
col_types = [dtypes.string, dtypes.long, dtypes.float_]
col_types = [dtypes.string, dtypes.long, dtypes.float64]
table_header = {k: v for k, v in zip(col_names, col_types)}
with self.assertRaises(DHError) as cm:
t = read_csv('tests/data/test_csv.csv', header=table_header, quote=",")
Expand All @@ -48,7 +48,7 @@ def test_write(self):
self.assertEqual(t_cols, [col.name for col in t.columns])

col_names = ["Strings", "Longs", "Floats"]
col_types = [dtypes.string, dtypes.long, dtypes.float_]
col_types = [dtypes.string, dtypes.long, dtypes.float64]
table_header = {k: v for k, v in zip(col_names, col_types)}
t = read_csv('tests/data/test_csv.csv', header=table_header)
write_csv(t, "./test_write.csv", cols=col_names)
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18 changes: 9 additions & 9 deletions py/server/tests/test_dtypes.py
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Original file line number Diff line number Diff line change
Expand Up @@ -30,20 +30,20 @@ class DTypesTestCase(BaseTestCase):
def test_type_alias(self):
self.assertEqual(dtypes.byte, dtypes.int8)
self.assertEqual(dtypes.short, dtypes.int16)
self.assertEqual(dtypes.int_, dtypes.int64)
self.assertEqual(dtypes.int64, dtypes.int64)
self.assertEqual(dtypes.long, dtypes.int64)
self.assertEqual(dtypes.float_, dtypes.double)
self.assertEqual(dtypes.float_, dtypes.float64)
self.assertEqual(dtypes.float64, dtypes.double)
self.assertEqual(dtypes.float64, dtypes.float64)
self.assertEqual(dtypes.double, dtypes.float64)

def test_j_type(self):
self.assertEqual(dtypes.bool_.j_type, jpy.get_type("java.lang.Boolean"))
self.assertEqual(dtypes.byte.j_type, jpy.get_type("byte"))
self.assertEqual(dtypes.short.j_type, jpy.get_type("short"))
self.assertEqual(dtypes.char.j_type, jpy.get_type("char"))
self.assertEqual(dtypes.int_.j_type, jpy.get_type("long"))
self.assertEqual(dtypes.int64.j_type, jpy.get_type("long"))
self.assertEqual(dtypes.long.j_type, jpy.get_type("long"))
self.assertEqual(dtypes.float_.j_type, jpy.get_type("double"))
self.assertEqual(dtypes.float64.j_type, jpy.get_type("double"))
self.assertEqual(dtypes.double.j_type, jpy.get_type("double"))
self.assertEqual(dtypes.string.j_type, jpy.get_type("java.lang.String"))
self.assertEqual(dtypes.BigDecimal.j_type, jpy.get_type("java.math.BigDecimal"))
Expand All @@ -65,9 +65,9 @@ def test_np_type(self):
self.assertEqual(dtypes.byte.np_type, np.int8)
self.assertEqual(dtypes.short.np_type, np.int16)
self.assertEqual(dtypes.char.np_type, np.dtype('uint16'))
self.assertEqual(dtypes.int_.np_type, np.int64)
self.assertEqual(dtypes.int64.np_type, np.int64)
self.assertEqual(dtypes.long.np_type, np.int64)
self.assertEqual(dtypes.float_.np_type, np.float64)
self.assertEqual(dtypes.float64.np_type, np.float64)
self.assertEqual(dtypes.double.np_type, np.float64)
self.assertEqual(dtypes.string.np_type, np.str_)
self.assertEqual(dtypes.BigDecimal.np_type, np.object_)
Expand Down Expand Up @@ -95,7 +95,7 @@ def test_callable(self):
self.assertEqual(j_string.toString(), "abc")

def test_array(self):
j_array = dtypes.array(dtypes.int_, range(5))
j_array = dtypes.array(dtypes.int64, range(5))
np_array = np.frombuffer(j_array, np.int64)
expected = np.array([0, 1, 2, 3, 4], dtype=np.int64)
self.assertTrue(np.array_equal(np_array, expected))
Expand Down Expand Up @@ -136,7 +136,7 @@ def test_integer_array(self):

def test_floating_array(self):

nulls = {dtypes.float_: NULL_FLOAT, dtypes.double: NULL_DOUBLE}
nulls = {dtypes.float64: NULL_FLOAT, dtypes.double: NULL_DOUBLE}

np_array = np.array([float('nan'), 1.7976931348623157e+300, NULL_DOUBLE, 1.1, float('inf')], dtype=np.float64)
for dt, nv in nulls.items():
Expand Down
10 changes: 5 additions & 5 deletions py/server/tests/test_kafka_consumer.py
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Original file line number Diff line number Diff line change
Expand Up @@ -56,7 +56,7 @@ def test_json_spec(self):
col_defs=[('Symbol', dtypes.string),
('Side', dtypes.string),
('Price', dtypes.double),
('Qty', dtypes.int_),
('Qty', dtypes.int64),
('Tstamp', dtypes.Instant)],
mapping={
'jsymbol': 'Symbol',
Expand All @@ -70,7 +70,7 @@ def test_json_spec(self):
'Symbol': dtypes.string,
'Side': dtypes.string,
'Price': dtypes.double,
'Qty': dtypes.int_,
'Qty': dtypes.int64,
'Tstamp': dtypes.Instant
},
mapping={
Expand Down Expand Up @@ -102,7 +102,7 @@ def test_json_spec(self):
self.assertEqual("Price", cols[5].name)
self.assertEqual(dtypes.double, cols[5].data_type)
self.assertEqual("Qty", cols[6].name)
self.assertEqual(dtypes.int_, cols[6].data_type)
self.assertEqual(dtypes.int64, cols[6].data_type)
self.assertEqual("Tstamp", cols[7].name)
self.assertEqual(dtypes.Instant, cols[7].data_type)

Expand Down Expand Up @@ -344,7 +344,7 @@ def test_json_spec_partitioned_table(self):
[('Symbol', dtypes.string),
('Side', dtypes.string),
('Price', dtypes.double),
('Qty', dtypes.int_),
('Qty', dtypes.int64),
('Tstamp', dtypes.Instant)],
mapping={
'jsymbol': 'Symbol',
Expand All @@ -368,7 +368,7 @@ def test_json_spec_partitioned_table(self):
self.assertEqual("Price", cols[5].name)
self.assertEqual(dtypes.double, cols[5].data_type)
self.assertEqual("Qty", cols[6].name)
self.assertEqual(dtypes.int_, cols[6].data_type)
self.assertEqual(dtypes.int64, cols[6].data_type)
self.assertEqual("Tstamp", cols[7].name)
self.assertEqual(dtypes.Instant, cols[7].data_type)

Expand Down
4 changes: 2 additions & 2 deletions py/server/tests/test_udf_scalar_args.py
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Original file line number Diff line number Diff line change
Expand Up @@ -548,7 +548,7 @@ def f2(x: float) -> Optional[int]:
...

t = empty_table(1).update("X = f2(f1(ii))")
self.assertEqual(t.columns[0].data_type, dtypes.int_)
self.assertEqual(t.columns[0].data_type, dtypes.int64)

with self.subTest("jpy.JType"):
def f1(x: jpy.JType) -> bool:
Expand Down Expand Up @@ -594,7 +594,7 @@ def use_c(c: Sequence) -> int:

t = empty_table(3).update(["C = make_c()", "V = use_c(C)"])
self.assertIsNotNone(t)
self.assertEqual(t.columns[1].data_type, dtypes.int_)
self.assertEqual(t.columns[1].data_type, dtypes.int64)

def misuse_c(c: int) -> int:
return c
Expand Down

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