diff --git a/README.md b/README.md
index 003c12335774cec4816bdefc6d38b7c4ec126665_UkVBRE1FLm1k..d0519d5809b751939f67cf4688dc6349ab17cead_UkVBRE1FLm1k 100644
--- a/README.md
+++ b/README.md
@@ -784,8 +784,8 @@
### numpy
orjson natively serializes `numpy.ndarray` and individual `numpy.float64`,
-`numpy.float32`, `numpy.int64`, `numpy.int32`, `numpy.uint64`, and
-`numpy.uint32` instances. Arrays may have a
+`numpy.float32`, `numpy.int64`, `numpy.int32`, `numpy.int8`, `numpy.uint64`,
+`numpy.uint32`, and `numpy.uint8` instances. Arrays may have a
`dtype` of `numpy.bool`, `numpy.float32`, `numpy.float64`, `numpy.int32`,
`numpy.int64`, `numpy.uint32`, `numpy.uint64`, `numpy.uintp`, or `numpy.intp`.
orjson is faster than all compared libraries at serializing
diff --git a/pynumpy b/pynumpy
index 003c12335774cec4816bdefc6d38b7c4ec126665_cHludW1weQ==..d0519d5809b751939f67cf4688dc6349ab17cead_cHludW1weQ== 100755
--- a/pynumpy
+++ b/pynumpy
@@ -30,4 +30,8 @@
assert array.dtype == numpy.float64
elif kind == "bool":
array = numpy.random.choice((True, False), size=(100000, 200))
+elif kind == "int8":
+ array = numpy.random.randint(((2 ** 7) - 1), size=(100000, 100), dtype=numpy.int8)
+elif kind == "uint8":
+ array = numpy.random.randint(((2 ** 8) - 1), size=(100000, 100), dtype=numpy.uint8)
else:
@@ -33,5 +37,5 @@
else:
- print("usage: pynumpy (bool|int32|float64)")
+ print("usage: pynumpy (bool|int32|float64|int8|uint8)")
sys.exit(1)
proc = psutil.Process()
diff --git a/src/serialize/numpy.rs b/src/serialize/numpy.rs
index 003c12335774cec4816bdefc6d38b7c4ec126665_c3JjL3NlcmlhbGl6ZS9udW1weS5ycw==..d0519d5809b751939f67cf4688dc6349ab17cead_c3JjL3NlcmlhbGl6ZS9udW1weS5ycw== 100644
--- a/src/serialize/numpy.rs
+++ b/src/serialize/numpy.rs
@@ -19,5 +19,6 @@
|| ob_type == scalar_types.float32
|| ob_type == scalar_types.int64
|| ob_type == scalar_types.int32
+ || ob_type == scalar_types.int8
|| ob_type == scalar_types.uint64
|| ob_type == scalar_types.uint32
@@ -22,5 +23,6 @@
|| ob_type == scalar_types.uint64
|| ob_type == scalar_types.uint32
+ || ob_type == scalar_types.uint8
}
}
@@ -61,5 +63,6 @@
BOOL,
F32,
F64,
+ I8,
I32,
I64,
@@ -64,5 +67,6 @@
I32,
I64,
+ U8,
U32,
U64,
}
@@ -73,44 +77,6 @@
UnsupportedDataType,
}
-#[repr(transparent)]
-pub struct NumpyScalar {
- pub ptr: *mut pyo3::ffi::PyObject,
-}
-
-impl NumpyScalar {
- pub fn new(ptr: *mut PyObject) -> Self {
- NumpyScalar { ptr }
- }
-}
-
-impl<'p> Serialize for NumpyScalar {
- fn serialize<S>(&self, serializer: S) -> Result<S::Ok, S::Error>
- where
- S: Serializer,
- {
- unsafe {
- let ob_type = ob_type!(self.ptr);
- let scalar_types = NUMPY_TYPES.deref_mut().as_ref().unwrap();
- if ob_type == scalar_types.float64 {
- (*(self.ptr as *mut NumpyFloat64)).serialize(serializer)
- } else if ob_type == scalar_types.float32 {
- (*(self.ptr as *mut NumpyFloat32)).serialize(serializer)
- } else if ob_type == scalar_types.int64 {
- (*(self.ptr as *mut NumpyInt64)).serialize(serializer)
- } else if ob_type == scalar_types.int32 {
- (*(self.ptr as *mut NumpyInt32)).serialize(serializer)
- } else if ob_type == scalar_types.uint64 {
- (*(self.ptr as *mut NumpyUint64)).serialize(serializer)
- } else if ob_type == scalar_types.uint32 {
- (*(self.ptr as *mut NumpyUint32)).serialize(serializer)
- } else {
- unreachable!()
- }
- }
- }
-}
-
// >>> arr = numpy.array([[[1, 2], [3, 4]], [[5, 6], [7, 8]]], numpy.int32)
// >>> arr.ndim
// 3
@@ -127,6 +93,7 @@
}
impl<'a> NumpyArray {
+ #[inline(never)]
pub fn new(ptr: *mut PyObject) -> Result<Self, PyArrayError> {
let capsule = ffi!(PyObject_GetAttr(ptr, ARRAY_STRUCT_STR));
let array = unsafe { (*(capsule as *mut PyCapsule)).pointer as *mut PyArrayInterface };
@@ -176,5 +143,6 @@
(098, 1) => Some(ItemType::BOOL),
(102, 4) => Some(ItemType::F32),
(102, 8) => Some(ItemType::F64),
+ (105, 1) => Some(ItemType::I8),
(105, 4) => Some(ItemType::I32),
(105, 8) => Some(ItemType::I64),
@@ -179,5 +147,6 @@
(105, 4) => Some(ItemType::I32),
(105, 8) => Some(ItemType::I64),
+ (117, 1) => Some(ItemType::U8),
(117, 4) => Some(ItemType::U32),
(117, 8) => Some(ItemType::U64),
_ => None,
@@ -237,6 +206,7 @@
}
impl<'p> Serialize for NumpyArray {
+ #[inline(never)]
fn serialize<S>(&self, serializer: S) -> Result<S::Ok, S::Error>
where
S: Serializer,
@@ -248,7 +218,6 @@
for child in &self.children {
seq.serialize_element(child).unwrap();
}
-
} else {
let data_ptr = self.data();
let num_items = self.num_items();
@@ -277,6 +246,6 @@
seq.serialize_element(&DataTypeI32 { obj: each }).unwrap();
}
}
- ItemType::U64 => {
- let slice: &[u64] = slice!(data_ptr as *const u64, num_items);
+ ItemType::I8 => {
+ let slice: &[i8] = slice!(data_ptr as *const i8, num_items);
for &each in slice.iter() {
@@ -282,5 +251,11 @@
for &each in slice.iter() {
- seq.serialize_element(&DataTypeU64 { obj: each }).unwrap();
+ seq.serialize_element(&DataTypeI8 { obj: each }).unwrap();
+ }
+ }
+ ItemType::U8 => {
+ let slice: &[u8] = slice!(data_ptr as *const u8, num_items);
+ for &each in slice.iter() {
+ seq.serialize_element(&DataTypeU8 { obj: each }).unwrap();
}
}
ItemType::U32 => {
@@ -289,6 +264,12 @@
seq.serialize_element(&DataTypeU32 { obj: each }).unwrap();
}
}
+ ItemType::U64 => {
+ let slice: &[u64] = slice!(data_ptr as *const u64, num_items);
+ for &each in slice.iter() {
+ seq.serialize_element(&DataTypeU64 { obj: each }).unwrap();
+ }
+ }
ItemType::BOOL => {
let slice: &[u8] = slice!(data_ptr as *const u8, num_items);
for &each in slice.iter() {
@@ -331,6 +312,20 @@
}
#[repr(transparent)]
+pub struct DataTypeI8 {
+ pub obj: i8,
+}
+
+impl<'p> Serialize for DataTypeI8 {
+ fn serialize<S>(&self, serializer: S) -> Result<S::Ok, S::Error>
+ where
+ S: Serializer,
+ {
+ serializer.serialize_i8(self.obj)
+ }
+}
+
+#[repr(transparent)]
pub struct DataTypeI32 {
pub obj: i32,
}
@@ -359,6 +354,20 @@
}
#[repr(transparent)]
+pub struct DataTypeU8 {
+ pub obj: u8,
+}
+
+impl<'p> Serialize for DataTypeU8 {
+ fn serialize<S>(&self, serializer: S) -> Result<S::Ok, S::Error>
+ where
+ S: Serializer,
+ {
+ serializer.serialize_u8(self.obj)
+ }
+}
+
+#[repr(transparent)]
pub struct DataTypeU32 {
pub obj: u32,
}
@@ -400,6 +409,64 @@
}
}
+#[repr(transparent)]
+pub struct NumpyScalar {
+ pub ptr: *mut pyo3::ffi::PyObject,
+}
+
+impl NumpyScalar {
+ pub fn new(ptr: *mut PyObject) -> Self {
+ NumpyScalar { ptr }
+ }
+}
+
+impl<'p> Serialize for NumpyScalar {
+ fn serialize<S>(&self, serializer: S) -> Result<S::Ok, S::Error>
+ where
+ S: Serializer,
+ {
+ unsafe {
+ let ob_type = ob_type!(self.ptr);
+ let scalar_types = NUMPY_TYPES.deref_mut().as_ref().unwrap();
+ if ob_type == scalar_types.float64 {
+ (*(self.ptr as *mut NumpyFloat64)).serialize(serializer)
+ } else if ob_type == scalar_types.float32 {
+ (*(self.ptr as *mut NumpyFloat32)).serialize(serializer)
+ } else if ob_type == scalar_types.int64 {
+ (*(self.ptr as *mut NumpyInt64)).serialize(serializer)
+ } else if ob_type == scalar_types.int32 {
+ (*(self.ptr as *mut NumpyInt32)).serialize(serializer)
+ } else if ob_type == scalar_types.int8 {
+ (*(self.ptr as *mut NumpyInt8)).serialize(serializer)
+ } else if ob_type == scalar_types.uint64 {
+ (*(self.ptr as *mut NumpyUint64)).serialize(serializer)
+ } else if ob_type == scalar_types.uint32 {
+ (*(self.ptr as *mut NumpyUint32)).serialize(serializer)
+ } else if ob_type == scalar_types.uint8 {
+ (*(self.ptr as *mut NumpyUint8)).serialize(serializer)
+ } else {
+ unreachable!()
+ }
+ }
+ }
+}
+
+#[repr(C)]
+pub struct NumpyInt8 {
+ pub ob_refcnt: Py_ssize_t,
+ pub ob_type: *mut PyTypeObject,
+ pub value: i8,
+}
+
+impl<'p> Serialize for NumpyInt8 {
+ fn serialize<S>(&self, serializer: S) -> Result<S::Ok, S::Error>
+ where
+ S: Serializer,
+ {
+ serializer.serialize_i8(self.value)
+ }
+}
+
#[repr(C)]
pub struct NumpyInt32 {
pub ob_refcnt: Py_ssize_t,
@@ -433,6 +500,22 @@
}
#[repr(C)]
+pub struct NumpyUint8 {
+ pub ob_refcnt: Py_ssize_t,
+ pub ob_type: *mut PyTypeObject,
+ pub value: u8,
+}
+
+impl<'p> Serialize for NumpyUint8 {
+ fn serialize<S>(&self, serializer: S) -> Result<S::Ok, S::Error>
+ where
+ S: Serializer,
+ {
+ serializer.serialize_u8(self.value)
+ }
+}
+
+#[repr(C)]
pub struct NumpyUint32 {
pub ob_refcnt: Py_ssize_t,
pub ob_type: *mut PyTypeObject,
diff --git a/src/typeref.rs b/src/typeref.rs
index 003c12335774cec4816bdefc6d38b7c4ec126665_c3JjL3R5cGVyZWYucnM=..d0519d5809b751939f67cf4688dc6349ab17cead_c3JjL3R5cGVyZWYucnM= 100644
--- a/src/typeref.rs
+++ b/src/typeref.rs
@@ -7,7 +7,8 @@
use std::sync::Once;
pub struct NumpyTypes {
+ pub array: *mut PyTypeObject,
pub float64: *mut PyTypeObject,
pub float32: *mut PyTypeObject,
pub int64: *mut PyTypeObject,
pub int32: *mut PyTypeObject,
@@ -10,6 +11,7 @@
pub float64: *mut PyTypeObject,
pub float32: *mut PyTypeObject,
pub int64: *mut PyTypeObject,
pub int32: *mut PyTypeObject,
+ pub int8: *mut PyTypeObject,
pub uint64: *mut PyTypeObject,
pub uint32: *mut PyTypeObject,
@@ -14,6 +16,6 @@
pub uint64: *mut PyTypeObject,
pub uint32: *mut PyTypeObject,
- pub array: *mut PyTypeObject,
+ pub uint8: *mut PyTypeObject,
}
pub static mut HASH_SEED: u64 = 0;
@@ -146,7 +148,8 @@
array: look_up_numpy_type(numpy, "ndarray\0")?.as_ptr(),
float32: look_up_numpy_type(numpy, "float32\0")?.as_ptr(),
float64: look_up_numpy_type(numpy, "float64\0")?.as_ptr(),
+ int8: look_up_numpy_type(numpy, "int8\0")?.as_ptr(),
int32: look_up_numpy_type(numpy, "int32\0")?.as_ptr(),
int64: look_up_numpy_type(numpy, "int64\0")?.as_ptr(),
uint32: look_up_numpy_type(numpy, "uint32\0")?.as_ptr(),
uint64: look_up_numpy_type(numpy, "uint64\0")?.as_ptr(),
@@ -149,7 +152,8 @@
int32: look_up_numpy_type(numpy, "int32\0")?.as_ptr(),
int64: look_up_numpy_type(numpy, "int64\0")?.as_ptr(),
uint32: look_up_numpy_type(numpy, "uint32\0")?.as_ptr(),
uint64: look_up_numpy_type(numpy, "uint64\0")?.as_ptr(),
+ uint8: look_up_numpy_type(numpy, "uint8\0")?.as_ptr(),
});
Py_XDECREF(numpy);
types
diff --git a/test/test_numpy.py b/test/test_numpy.py
index 003c12335774cec4816bdefc6d38b7c4ec126665_dGVzdC90ZXN0X251bXB5LnB5..d0519d5809b751939f67cf4688dc6349ab17cead_dGVzdC90ZXN0X251bXB5LnB5 100644
--- a/test/test_numpy.py
+++ b/test/test_numpy.py
@@ -54,6 +54,24 @@
b"[0,18446744073709551615]",
)
+ def test_numpy_array_d1_i8(self):
+ self.assertEqual(
+ orjson.dumps(
+ numpy.array([-128, 127], numpy.int8),
+ option=orjson.OPT_SERIALIZE_NUMPY,
+ ),
+ b"[-128,127]",
+ )
+
+ def test_numpy_array_d1_u8(self):
+ self.assertEqual(
+ orjson.dumps(
+ numpy.array([0, 255], numpy.uint8),
+ option=orjson.OPT_SERIALIZE_NUMPY,
+ ),
+ b"[0,255]",
+ )
+
def test_numpy_array_d1_i32(self):
self.assertEqual(
orjson.dumps(
@@ -117,6 +135,24 @@
b"[[1.0,2.0,3.0],[4.0,5.0,6.0]]",
)
+ def test_numpy_array_d3_i8(self):
+ self.assertEqual(
+ orjson.dumps(
+ numpy.array([[[1, 2], [3, 4]], [[5, 6], [7, 8]]], numpy.int8),
+ option=orjson.OPT_SERIALIZE_NUMPY,
+ ),
+ b"[[[1,2],[3,4]],[[5,6],[7,8]]]",
+ )
+
+ def test_numpy_array_d3_u8(self):
+ self.assertEqual(
+ orjson.dumps(
+ numpy.array([[[1, 2], [3, 4]], [[5, 6], [7, 8]]], numpy.uint8),
+ option=orjson.OPT_SERIALIZE_NUMPY,
+ ),
+ b"[[[1,2],[3,4]],[[5,6],[7,8]]]",
+ )
+
def test_numpy_array_d3_i32(self):
self.assertEqual(
orjson.dumps(
@@ -159,7 +195,7 @@
)
def test_numpy_array_unsupported_dtype(self):
- array = numpy.array([[1, 2], [3, 4]], numpy.int8)
+ array = numpy.array([[1, 2], [3, 4]], numpy.float16)
with self.assertRaises(orjson.JSONEncodeError):
orjson.dumps(array, option=orjson.OPT_SERIALIZE_NUMPY)
self.assertEqual(
@@ -314,8 +350,20 @@
array.tolist(),
)
- def test_numpy_primitives(self):
- # int32
+ def test_numpy_scalar_int8(self):
+ self.assertEqual(
+ orjson.dumps(numpy.int8(0), option=orjson.OPT_SERIALIZE_NUMPY), b"0"
+ )
+ self.assertEqual(
+ orjson.dumps(numpy.int8(127), option=orjson.OPT_SERIALIZE_NUMPY),
+ b"127",
+ )
+ self.assertEqual(
+ orjson.dumps(numpy.int8(--128), option=orjson.OPT_SERIALIZE_NUMPY),
+ b"-128",
+ )
+
+ def test_numpy_scalar_int32(self):
self.assertEqual(
orjson.dumps(numpy.int32(1), option=orjson.OPT_SERIALIZE_NUMPY), b"1"
)
@@ -327,7 +375,8 @@
orjson.dumps(numpy.int32(-2147483648), option=orjson.OPT_SERIALIZE_NUMPY),
b"-2147483648",
)
- # int 64
+
+ def test_numpy_scalar_int64(self):
self.assertEqual(
orjson.dumps(
numpy.int64(-9223372036854775808), option=orjson.OPT_SERIALIZE_NUMPY
@@ -340,7 +389,17 @@
),
b"9223372036854775807",
)
- # uint32
+
+ def test_numpy_scalar_uint8(self):
+ self.assertEqual(
+ orjson.dumps(numpy.uint8(0), option=orjson.OPT_SERIALIZE_NUMPY), b"0"
+ )
+ self.assertEqual(
+ orjson.dumps(numpy.uint8(255), option=orjson.OPT_SERIALIZE_NUMPY),
+ b"255",
+ )
+
+ def test_numpy_scalar_uint32(self):
self.assertEqual(
orjson.dumps(numpy.uint32(0), option=orjson.OPT_SERIALIZE_NUMPY), b"0"
)
@@ -348,7 +407,8 @@
orjson.dumps(numpy.uint32(4294967295), option=orjson.OPT_SERIALIZE_NUMPY),
b"4294967295",
)
- # uint64
+
+ def test_numpy_scalar_uint64(self):
self.assertEqual(
orjson.dumps(numpy.uint64(0), option=orjson.OPT_SERIALIZE_NUMPY), b"0"
)
@@ -359,8 +419,8 @@
b"18446744073709551615",
)
- # float32
+ def test_numpy_scalar_float32(self):
self.assertEqual(
orjson.dumps(numpy.float32(1.0), option=orjson.OPT_SERIALIZE_NUMPY), b"1.0"
)
@@ -363,8 +423,8 @@
self.assertEqual(
orjson.dumps(numpy.float32(1.0), option=orjson.OPT_SERIALIZE_NUMPY), b"1.0"
)
- # float64
+ def test_numpy_scalar_float64(self):
self.assertEqual(
orjson.dumps(numpy.float64(123.123), option=orjson.OPT_SERIALIZE_NUMPY),
b"123.123",