ormsgpack is a fast msgpack serialization library for Python derived from orjson, with native support for various Python types.
ormsgpack supports CPython 3.9, 3.10, 3.11, 3.12 and 3.13. Releases follow semantic versioning and serializing a new object type without an opt-in flag is considered a breaking change.
ormsgpack is licensed under both the Apache 2.0 and MIT licenses. The repository and issue tracker is github.com/aviramha/ormsgpack, and patches may be submitted there. There is a CHANGELOG available in the repository.
To install a wheel from PyPI:
pip install --upgrade "pip>=20.3" # manylinux_x_y, universal2 wheel support
pip install --upgrade ormsgpackTo build a wheel, see packaging.
This is an example of serializing, with options specified, and deserializing:
>>> import ormsgpack, datetime, numpy
>>> data = {
... "type": "job",
... "created_at": datetime.datetime(1970, 1, 1),
... "status": "🆗",
... "payload": numpy.array([[1, 2], [3, 4]]),
... }
>>> ormsgpack.packb(data, option=ormsgpack.OPT_NAIVE_UTC | ormsgpack.OPT_SERIALIZE_NUMPY)
b'\x84\xa4type\xa3job\xaacreated_at\xb91970-01-01T00:00:00+00:00\xa6status\xa4\xf0\x9f\x86\x97\xa7payload\x92\x92\x01\x02\x92\x03\x04'
>>> ormsgpack.unpackb(_)
{'type': 'job', 'created_at': '1970-01-01T00:00:00+00:00', 'status': '🆗', 'payload': [[1, 2], [3, 4]]}def packb(
__obj: Any,
default: Optional[Callable[[Any], Any]] = ...,
option: Optional[int] = ...,
) -> bytes: ...packb() serializes Python objects to msgpack.
It natively serializes various Python types and supports
arbitrary types through the default argument.
The output is a bytes object.
The global interpreter lock (GIL) is held for the duration of the call.
It raises MsgpackEncodeError on an unsupported type. This exception
describes the invalid object with the error message Type is not msgpack serializable: ....
It raises MsgpackEncodeError if a str contains invalid UTF-8.
It raises MsgpackEncodeError if a dict has a key of a type other than str or bytes,
unless OPT_NON_STR_KEYS is specified.
It raises MsgpackEncodeError if the output of default recurses to handling by
default more than 254 levels deep.
It raises MsgpackEncodeError on circular references.
It raises MsgpackEncodeError if a tzinfo on a datetime object is
unsupported.
MsgpackEncodeError is a subclass of TypeError.
To serialize a subclass or arbitrary types, specify default as a
callable that returns a supported type. default may be a function,
lambda, or callable class instance. To specify that a type was not
handled by default, raise an exception such as TypeError.
>>> import ormsgpack, decimal
>>> def default(obj):
... if isinstance(obj, decimal.Decimal):
... return str(obj)
... raise TypeError
...
>>> ormsgpack.packb(decimal.Decimal("0.0842389659712649442845"))
TypeError: Type is not msgpack serializable: decimal.Decimal
>>> ormsgpack.packb(decimal.Decimal("0.0842389659712649442845"), default=default)
b'\xb80.0842389659712649442845'
>>> ormsgpack.packb({1, 2}, default=default)
TypeError: Type is not msgpack serializable: setThe default callable may return an object that itself
must be handled by default up to 254 times before an exception
is raised.
It is important that default raise an exception if a type cannot be handled.
Python otherwise implicitly returns None, which appears to the caller
like a legitimate value and is serialized:
>>> import ormsgpack, decimal
>>> def default(obj):
... if isinstance(obj, decimal.Decimal):
... return str(obj)
...
>>> ormsgpack.packb({"set":{1, 2}}, default=default)
b'\x81\xa3set\xc0'
>>> ormsgpack.unpackb(_)
{'set': None}To serialize a type as a MessagePack extension type, return an
ormsgpack.Ext object. The instantiation arguments are an integer in
the range [0, 127] and a bytes object, defining the type and
value, respectively.
>>> import ormsgpack, decimal
>>> def default(obj):
... if isinstance(obj, decimal.Decimal):
... return ormsgpack.Ext(0, str(obj).encode())
... raise TypeError
...
>>> ormsgpack.packb(decimal.Decimal("0.0842389659712649442845"), default=default)
b'\xc7\x18\x000.0842389659712649442845'default can also be used to serialize some supported types to a custom
format by enabling the corresponding passthrough options.
To modify how data is serialized, specify option. Each option is an integer
constant in ormsgpack. To specify multiple options, mask them together, e.g.,
option=ormsgpack.OPT_NON_STR_KEYS | ormsgpack.OPT_NAIVE_UTC.
Serialize naive datetime.datetime objects and numpy.datetime64
objects as UTC. This has no effect on aware datetime.datetime
objects.
>>> import ormsgpack, datetime
>>> ormsgpack.packb(
... datetime.datetime(1970, 1, 1, 0, 0, 0),
... )
b'\xb31970-01-01T00:00:00'
>>> ormsgpack.unpackb(_)
'1970-01-01T00:00:00'
>>> ormsgpack.packb(
... datetime.datetime(1970, 1, 1, 0, 0, 0),
... option=ormsgpack.OPT_NAIVE_UTC,
... )
b'\xb91970-01-01T00:00:00+00:00'
>>> ormsgpack.unpackb(_)
'1970-01-01T00:00:00+00:00'Serialize dict keys of type other than str. This allows dict keys
to be one of str, int, float, bool, None, datetime.datetime,
datetime.date, datetime.time, enum.Enum, and uuid.UUID.
dict keys of unsupported types are not handled using default and
result in MsgpackEncodeError being raised.
>>> import ormsgpack, datetime, uuid
>>> ormsgpack.packb(
... {uuid.UUID("7202d115-7ff3-4c81-a7c1-2a1f067b1ece"): [1, 2, 3]},
... option=ormsgpack.OPT_NON_STR_KEYS,
... )
b'\x81\xd9$7202d115-7ff3-4c81-a7c1-2a1f067b1ece\x93\x01\x02\x03'
>>> ormsgpack.unpackb(_)
{'7202d115-7ff3-4c81-a7c1-2a1f067b1ece': [1, 2, 3]}
>>> ormsgpack.packb(
... {datetime.datetime(1970, 1, 1, 0, 0, 0): [1, 2, 3]},
... option=ormsgpack.OPT_NON_STR_KEYS | ormsgpack.OPT_NAIVE_UTC,
... )
b'\x81\xb91970-01-01T00:00:00+00:00\x93\x01\x02\x03'
>>> ormsgpack.unpackb(_)
{'1970-01-01T00:00:00+00:00': [1, 2, 3]}These types are generally serialized how they would be as
values, e.g., datetime.datetime is still an RFC 3339 string and respects
options affecting it.
This option has the risk of creating duplicate keys. This is because non-str
objects may serialize to the same str as an existing key, e.g.,
{"1970-01-01T00:00:00+00:00": true, datetime.datetime(1970, 1, 1, 0, 0, 0): false}.
The last key to be inserted to the dict will be serialized last and a msgpack deserializer will presumably take the last
occurrence of a key (in the above, false). The first value will be lost.
This option is not compatible with ormsgpack.OPT_SORT_KEYS.
Do not serialize the microsecond component of datetime.datetime,
datetime.time and numpy.datetime64 instances.
>>> import ormsgpack, datetime
>>> ormsgpack.packb(
... datetime.datetime(1970, 1, 1, 0, 0, 0, 1),
... )
b'\xba1970-01-01T00:00:00.000001'
>>> ormsgpack.unpackb(_)
'1970-01-01T00:00:00.000001'
>>> ormsgpack.packb(
... datetime.datetime(1970, 1, 1, 0, 0, 0, 1),
... option=ormsgpack.OPT_OMIT_MICROSECONDS,
... )
b'\xb31970-01-01T00:00:00'
>>> ormsgpack.unpackb(_)
'1970-01-01T00:00:00'Enable passthrough of int instances smaller than -9223372036854775807 or
larger than 18446744073709551615 to default.
>>> import ormsgpack
>>> ormsgpack.packb(
... 2**65,
... )
TypeError: Integer exceeds 64-bit range
>>> ormsgpack.packb(
... 2**65,
... option=ormsgpack.OPT_PASSTHROUGH_BIG_INT,
... default=lambda _: {"type": "bigint", "value": str(_) }
... )
b'\x82\xa4type\xa6bigint\xa5value\xb436893488147419103232'
>>> ormsgpack.unpackb(_)
{'type': 'bigint', 'value': '36893488147419103232'}Enable passthrough of dataclasses to default.
>>> import ormsgpack, dataclasses
>>> @dataclasses.dataclass
... class User:
... id: str
... name: str
... password: str
...
>>> def default(obj):
... if isinstance(obj, User):
... return {"id": obj.id, "name": obj.name}
... raise TypeError
...
>>> ormsgpack.packb(User("3b1", "asd", "zxc"))
b'\x83\xa2id\xa33b1\xa4name\xa3asd\xa8password\xa3zxc'
>>> ormsgpack.packb(User("3b1", "asd", "zxc"), option=ormsgpack.OPT_PASSTHROUGH_DATACLASS)
TypeError: Type is not msgpack serializable: User
>>> ormsgpack.packb(
... User("3b1", "asd", "zxc"),
... option=ormsgpack.OPT_PASSTHROUGH_DATACLASS,
... default=default,
... )
b'\x82\xa2id\xa33b1\xa4name\xa3asd'Enable passthrough of datetime.datetime, datetime.date, and
datetime.time instances to default.
>>> import ormsgpack, datetime
>>> def default(obj):
... if isinstance(obj, datetime.datetime):
... return obj.strftime("%a, %d %b %Y %H:%M:%S GMT")
... raise TypeError
...
>>> ormsgpack.packb({"created_at": datetime.datetime(1970, 1, 1)})
b'\x81\xaacreated_at\xb31970-01-01T00:00:00'
>>> ormsgpack.packb({"created_at": datetime.datetime(1970, 1, 1)}, option=ormsgpack.OPT_PASSTHROUGH_DATETIME)
TypeError: Type is not msgpack serializable: datetime.datetime
>>> ormsgpack.packb(
... {"created_at": datetime.datetime(1970, 1, 1)},
... option=ormsgpack.OPT_PASSTHROUGH_DATETIME,
... default=default,
... )
b'\x81\xaacreated_at\xbdThu, 01 Jan 1970 00:00:00 GMT'Enable passthrough of enum members to default.
Enable passthrough of subclasses of str, int, dict and list to
default.
>>> import ormsgpack
>>> class Secret(str):
... pass
...
>>> def default(obj):
... if isinstance(obj, Secret):
... return "******"
... raise TypeError
...
>>> ormsgpack.packb(Secret("zxc"))
b'\xa3zxc'
>>> ormsgpack.packb(Secret("zxc"), option=ormsgpack.OPT_PASSTHROUGH_SUBCLASS)
TypeError: Type is not msgpack serializable: Secret
>>> ormsgpack.packb(Secret("zxc"), option=ormsgpack.OPT_PASSTHROUGH_SUBCLASS, default=default)
b'\xa6******'Enable passthrough of tuple instances to default.
>>> import ormsgpack
>>> ormsgpack.packb(
... (9193, "test", 42),
... )
b'\x93\xcd#\xe9\xa4test*'
>>> ormsgpack.unpackb(_)
[9193, 'test', 42]
>>> ormsgpack.packb(
... (9193, "test", 42),
... option=ormsgpack.OPT_PASSTHROUGH_TUPLE,
... default=lambda _: {"type": "tuple", "value": list(_)}
... )
b'\x82\xa4type\xa5tuple\xa5value\x93\xcd#\xe9\xa4test*'
>>> ormsgpack.unpackb(_)
{'type': 'tuple', 'value': [9193, 'test', 42]}Enable passthrough of uuid.UUID instances to default.
Serialize instances of numpy types.
Serialize pydantic.BaseModel instances.
Serialize dict keys and pydantic model fields in sorted order. The default
is to serialize in an unspecified order.
This can be used to ensure the order is deterministic for hashing or tests. It has a substantial performance penalty and is not recommended in general.
>>> import ormsgpack
>>> ormsgpack.packb({"b": 1, "c": 2, "a": 3})
b'\x83\xa1b\x01\xa1c\x02\xa1a\x03'
>>> ormsgpack.packb({"b": 1, "c": 2, "a": 3}, option=ormsgpack.OPT_SORT_KEYS)
b'\x83\xa1a\x03\xa1b\x01\xa1c\x02'The sorting is not collation/locale-aware:
>>> import ormsgpack
>>> ormsgpack.packb({"a": 1, "ä": 2, "A": 3}, option=ormsgpack.OPT_SORT_KEYS)
b'\x83\xa1A\x03\xa1a\x01\xa2\xc3\xa4\x02'dataclass also serialize as maps but this has no effect on them.
Serialize a UTC timezone on datetime.datetime and numpy.datetime64 instances
as Z instead of +00:00.
>>> import ormsgpack, datetime
>>> ormsgpack.packb(
... datetime.datetime(1970, 1, 1, 0, 0, 0, tzinfo=datetime.timezone.utc),
... )
b'\xb91970-01-01T00:00:00+00:00'
>>> ormsgpack.packb(
... datetime.datetime(1970, 1, 1, 0, 0, 0, tzinfo=datetime.timezone.utc),
... option=ormsgpack.OPT_UTC_Z
... )
b'\xb41970-01-01T00:00:00Z'def unpackb(
__obj: Union[bytes, bytearray, memoryview],
/,
ext_hook: Optional[Callable[[int, bytes], Any]] = ...,
option: Optional[int] = ...,
) -> Any: ...unpackb() deserializes msgpack to Python objects. It deserializes to dict,
list, int, float, str, bool, bytes and None objects.
bytes, bytearray, memoryview input are accepted.
ormsgpack maintains a cache of map keys for the duration of the process. This causes a net reduction in memory usage by avoiding duplicate strings. The keys must be at most 64 bytes to be cached and 512 entries are stored.
The global interpreter lock (GIL) is held for the duration of the call.
It raises MsgpackDecodeError if given an invalid type or invalid
msgpack.
MsgpackDecodeError is a subclass of ValueError.
To deserialize extension types, specify the optional ext_hook
argument. The value should be a callable and is invoked with the
extension type and value as arguments.
>>> import ormsgpack, decimal
>>> def ext_hook(tag, data):
... if tag == 0:
... return decimal.Decimal(data.decode())
... raise TypeError
...
>>> ormsgpack.packb(
... ormsgpack.Ext(0, str(decimal.Decimal("0.0842389659712649442845")).encode())
... )
b'\xc7\x18\x000.0842389659712649442845'
>>> ormsgpack.unpackb(_, ext_hook=ext_hook)
Decimal('0.0842389659712649442845'Deserialize map keys of type other than string. Be aware that this option is considered unsafe and disabled by default in msgpack due to possibility of HashDoS.
The None object is serialized as nil.
bool instances are serialized as booleans.
Instances of int and of subclasses of int are serialized as
integers. The minimum and maximum representable values are
-9223372036854775807 and 18446744073709551615, respectively.
float instances are serialized as IEEE 754 double precision floating point numbers.
Instances of str and of subclasses of str are serialized as strings.
bytes, bytearray and memoryview instances are serialized as binary objects.
Instances of list and of subclasses of list are serialized as arrays.
tuple instances are serialized as arrays.
Instances of dict and of subclasses of dict are serialized as maps.
Dataclasses are serialized as maps. The fields are serialized in the
order they are defined in the class. All variants of dataclasses are
supported, including dataclasses with __slots__, frozen dataclasses
and dataclasses with descriptor-typed fields.
>>> import dataclasses, ormsgpack, typing
>>> @dataclasses.dataclass
... class Member:
... id: int
... active: bool = dataclasses.field(default=False)
...
>>> @dataclasses.dataclass
... class Object:
... id: int
... name: str
... members: typing.List[Member]
...
>>> ormsgpack.packb(Object(1, "a", [Member(1, True), Member(2)]))
b'\x83\xa2id\x01\xa4name\xa1a\xa7members\x92\x82\xa2id\x01\xa6active\xc3\x82\xa2id\x02\xa6active\xc2'datetime.date instances are serialized as RFC 3339 strings.
>>> import ormsgpack, datetime
>>> ormsgpack.packb(datetime.date(1900, 1, 2))
b'\xaa1900-01-02'
>>> ormsgpack.unpackb(_)
'1900-01-02'Naive datetime.time instances are serialized as RFC 3339 strings.
Aware datetime.time instances are not supported.
>>> import ormsgpack, datetime
>>> ormsgpack.packb(datetime.time(12, 0, 15, 290))
b'\xaf12:00:15.000290'
>>> ormsgpack.unpackb(_)
'12:00:15.000290'Naive datetime.datetime instances and aware datetime.datetime
instances are serialized as RFC 3339 strings.
>>> import ormsgpack, datetime, zoneinfo
>>> ormsgpack.packb(
... datetime.datetime(2018, 12, 1, 2, 3, 4, 9, tzinfo=zoneinfo.ZoneInfo('Australia/Adelaide'))
... )
b'\xd9 2018-12-01T02:03:04.000009+10:30'
>>> ormsgpack.unpackb(_)
'2018-12-01T02:03:04.000009+10:30'
>>> ormsgpack.packb(
... datetime.datetime.fromtimestamp(4123518902).replace(tzinfo=datetime.timezone.utc)
... )
b'\xb92100-09-02T00:55:02+00:00'
>>> ormsgpack.unpackb(_)
'2100-09-02T00:55:02+00:00'
>>> ormsgpack.packb(
... datetime.datetime.fromtimestamp(4123518902)
... )
b'\xb32100-09-02T00:55:02'
>>> ormsgpack.unpackb(_)
'2100-09-02T00:55:02'Errors with tzinfo result in MsgpackEncodeError being raised.
The serialization can be customized using the OPT_NAIVE_UTC, OPT_OMIT_MICROSECONDS, and OPT_UTC_Z options.
Enum members are serialized as their values. Options apply to their
values. All subclasses of enum.EnumType are supported.
>>> import enum, datetime, ormsgpack
>>> class DatetimeEnum(enum.Enum):
... EPOCH = datetime.datetime(1970, 1, 1, 0, 0, 0)
...
>>> ormsgpack.packb(DatetimeEnum.EPOCH)
b'\xb31970-01-01T00:00:00'
>>> ormsgpack.unpackb(_)
'1970-01-01T00:00:00'
>>> ormsgpack.packb(DatetimeEnum.EPOCH, option=ormsgpack.OPT_NAIVE_UTC)
b'\xb91970-01-01T00:00:00+00:00'
>>> ormsgpack.unpackb(_)
'1970-01-01T00:00:00+00:00'Enum members whose value is not a supported type can be serialized using
default:
>>> import enum, ormsgpack
>>> class Custom:
... def __init__(self, val):
... self.val = val
...
>>> def default(obj):
... if isinstance(obj, Custom):
... return obj.val
... raise TypeError
...
>>> class CustomEnum(enum.Enum):
... ONE = Custom(1)
...
>>> ormsgpack.packb(CustomEnum.ONE, default=default)
b'\x01'
>>> ormsgpack.unpackb(_)
1uuid.UUID instances are serialized as RFC 4122 strings.
>>> import ormsgpack, uuid
>>> ormsgpack.packb(uuid.UUID('f81d4fae-7dec-11d0-a765-00a0c91e6bf6'))
b'\xd9$f81d4fae-7dec-11d0-a765-00a0c91e6bf6'
>>> ormsgpack.unpackb(_)
'f81d4fae-7dec-11d0-a765-00a0c91e6bf6'
>>> ormsgpack.packb(uuid.uuid5(uuid.NAMESPACE_DNS, "python.org"))
b'\xd9$886313e1-3b8a-5372-9b90-0c9aee199e5d'
>>> ormsgpack.unpackb(_)
'886313e1-3b8a-5372-9b90-0c9aee199e5dnumpy.bool, numpy.float16, numpy.float32, numpy.float64,
numpy.int8, numpy.int16, numpy.int32, numpy.int64, numpy.intp,
numpy.uint8, numpy.uint16, numpy.uint32, numpy.uint64, numpy.uintp
instances are serialized as the corresponding builtin types.
numpy.datetime64 instances are serialized as RFC 3339 strings.
The serialization can be customized using the
OPT_NAIVE_UTC,
OPT_OMIT_MICROSECONDS, and
OPT_UTC_Z options.
numpy.ndarray instances are serialized as arrays. The array must be
a C-contiguous array (C_CONTIGUOUS) and of a supported data type.
Unsupported arrays can be serialized using default, by
converting the array to a list with the numpy.ndarray.tolist method.
The serialization of numpy types is disabled by default and can be enabled by using the OPT_SERIALIZE_NUMPY option.
>>> import ormsgpack, numpy
>>> ormsgpack.packb(
... numpy.array([[1, 2, 3], [4, 5, 6]]),
... option=ormsgpack.OPT_SERIALIZE_NUMPY,
... )
b'\x92\x93\x01\x02\x03\x93\x04\x05\x06'
>>> ormsgpack.unpackb(_)
[[1, 2, 3], [4, 5, 6]]pydantic.BaseModel instances are serialized as maps, with
duck-typing.
This is equivalent to serializing
model.model_dump(serialize_as_any=True) with Pydantic V2 or
model.dict()with Pydantic V1.
The serialization of pydantic models is disabled by default and can be enabled by using the OPT_SERIALIZE_PYDANTIC option.
----------------------------------------------------------------------------- benchmark 'canada packb': 2 tests ------------------------------------------------------------------------------
Name (time in ms) Min Max Mean StdDev Median IQR Outliers OPS Rounds Iterations
----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
test_ormsgpack_packb[canada] 3.5302 (1.0) 3.8939 (1.0) 3.7319 (1.0) 0.0563 (1.0) 3.7395 (1.0) 0.0484 (1.0) 56;22 267.9571 (1.0) 241 1
test_msgpack_packb[canada] 8.8642 (2.51) 14.0432 (3.61) 9.3660 (2.51) 0.5649 (10.03) 9.2983 (2.49) 0.0982 (2.03) 3;11 106.7691 (0.40) 106 1
----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
------------------------------------------------------------------------------- benchmark 'canada unpackb': 2 tests --------------------------------------------------------------------------------
Name (time in ms) Min Max Mean StdDev Median IQR Outliers OPS Rounds Iterations
----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
test_msgpack_unpackb[canada] 10.1176 (1.0) 62.0466 (1.18) 33.4806 (1.0) 18.8279 (1.0) 46.6582 (1.0) 38.5921 (1.02) 30;0 29.8680 (1.0) 67 1
test_ormsgpack_unpackb[canada] 11.3992 (1.13) 52.6587 (1.0) 34.1842 (1.02) 18.9461 (1.01) 47.6456 (1.02) 37.8024 (1.0) 8;0 29.2533 (0.98) 20 1
----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
----------------------------------------------------------------------------- benchmark 'citm_catalog packb': 2 tests -----------------------------------------------------------------------------
Name (time in ms) Min Max Mean StdDev Median IQR Outliers OPS Rounds Iterations
---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
test_ormsgpack_packb[citm_catalog] 1.8024 (1.0) 2.1259 (1.0) 1.9487 (1.0) 0.0346 (1.0) 1.9525 (1.0) 0.0219 (1.0) 79;60 513.1650 (1.0) 454 1
test_msgpack_packb[citm_catalog] 3.4195 (1.90) 3.8128 (1.79) 3.6928 (1.90) 0.0535 (1.55) 3.7009 (1.90) 0.0250 (1.14) 47;49 270.7958 (0.53) 257 1
---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
------------------------------------------------------------------------------ benchmark 'citm_catalog unpackb': 2 tests ------------------------------------------------------------------------------
Name (time in ms) Min Max Mean StdDev Median IQR Outliers OPS Rounds Iterations
-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
test_ormsgpack_unpackb[citm_catalog] 5.6986 (1.0) 46.1843 (1.0) 14.2491 (1.0) 15.9791 (1.0) 6.1051 (1.0) 0.3074 (1.0) 5;5 70.1798 (1.0) 23 1
test_msgpack_unpackb[citm_catalog] 7.2600 (1.27) 56.6642 (1.23) 16.4095 (1.15) 16.3257 (1.02) 7.7364 (1.27) 0.4944 (1.61) 28;29 60.9404 (0.87) 125 1
-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
----------------------------------------------------------------------------------- benchmark 'github packb': 2 tests -----------------------------------------------------------------------------------
Name (time in us) Min Max Mean StdDev Median IQR Outliers OPS (Kops/s) Rounds Iterations
---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
test_ormsgpack_packb[github] 73.0000 (1.0) 215.9000 (1.0) 80.4826 (1.0) 4.8889 (1.0) 80.3000 (1.0) 1.1000 (1.83) 866;1118 12.4250 (1.0) 6196 1
test_msgpack_packb[github] 103.8000 (1.42) 220.8000 (1.02) 112.8049 (1.40) 4.9686 (1.02) 113.0000 (1.41) 0.6000 (1.0) 1306;1560 8.8649 (0.71) 7028 1
---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
----------------------------------------------------------------------------------- benchmark 'github unpackb': 2 tests -----------------------------------------------------------------------------------
Name (time in us) Min Max Mean StdDev Median IQR Outliers OPS (Kops/s) Rounds Iterations
-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
test_ormsgpack_unpackb[github] 201.3000 (1.0) 318.5000 (1.0) 219.0861 (1.0) 6.7340 (1.0) 219.1000 (1.0) 1.2000 (1.0) 483;721 4.5644 (1.0) 3488 1
test_msgpack_unpackb[github] 289.8000 (1.44) 436.0000 (1.37) 314.9631 (1.44) 9.4130 (1.40) 315.1000 (1.44) 2.3000 (1.92) 341;557 3.1750 (0.70) 2477 1
-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
--------------------------------------------------------------------------------------- benchmark 'twitter packb': 2 tests ---------------------------------------------------------------------------------------
Name (time in us) Min Max Mean StdDev Median IQR Outliers OPS Rounds Iterations
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
test_ormsgpack_packb[twitter] 820.7000 (1.0) 2,945.2000 (2.03) 889.3791 (1.0) 78.4139 (2.43) 884.2000 (1.0) 12.5250 (1.0) 4;76 1,124.3799 (1.0) 809 1
test_msgpack_packb[twitter] 1,209.3000 (1.47) 1,451.2000 (1.0) 1,301.3615 (1.46) 32.2147 (1.0) 1,306.7000 (1.48) 14.1000 (1.13) 118;138 768.4260 (0.68) 592 1
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
------------------------------------------------------------------------------ benchmark 'twitter unpackb': 2 tests -----------------------------------------------------------------------------
Name (time in ms) Min Max Mean StdDev Median IQR Outliers OPS Rounds Iterations
-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
test_ormsgpack_unpackb[twitter] 2.7097 (1.0) 41.1530 (1.0) 3.2721 (1.0) 3.5860 (1.03) 2.8868 (1.0) 0.0614 (1.32) 4;38 305.6098 (1.0) 314 1
test_msgpack_unpackb[twitter] 3.8079 (1.41) 42.0617 (1.02) 4.4459 (1.36) 3.4893 (1.0) 4.1097 (1.42) 0.0465 (1.0) 2;54 224.9267 (0.74) 228 1
-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
--------------------------------------------------------------------------------- benchmark 'dataclass': 2 tests --------------------------------------------------------------------------------
Name (time in ms) Min Max Mean StdDev Median IQR Outliers OPS Rounds Iterations
-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
test_dataclass_ormsgpack 3.4248 (1.0) 7.7949 (1.0) 3.6266 (1.0) 0.3293 (1.0) 3.5815 (1.0) 0.0310 (1.0) 4;34 275.7434 (1.0) 240 1
test_dataclass_msgpack 140.2774 (40.96) 143.6087 (18.42) 141.3847 (38.99) 1.0038 (3.05) 141.1823 (39.42) 0.7304 (23.60) 2;1 7.0729 (0.03) 8 1
-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
---------------------------------------------------------------------------------- benchmark 'numpy float64': 2 tests ---------------------------------------------------------------------------------
Name (time in ms) Min Max Mean StdDev Median IQR Outliers OPS Rounds Iterations
-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
test_numpy_ormsgpack[float64] 77.9625 (1.0) 85.2507 (1.0) 79.0326 (1.0) 1.9043 (1.0) 78.5505 (1.0) 0.7408 (1.0) 1;1 12.6530 (1.0) 13 1
test_numpy_msgpack[float64] 511.5176 (6.56) 606.9395 (7.12) 559.0017 (7.07) 44.0661 (23.14) 572.5499 (7.29) 81.2972 (109.75) 3;0 1.7889 (0.14) 5 1
-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
------------------------------------------------------------------------------------- benchmark 'numpy int32': 2 tests -------------------------------------------------------------------------------------
Name (time in ms) Min Max Mean StdDev Median IQR Outliers OPS Rounds Iterations
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
test_numpy_ormsgpack[int32] 197.8751 (1.0) 210.3111 (1.0) 201.1033 (1.0) 5.1886 (1.0) 198.8518 (1.0) 3.8297 (1.0) 1;1 4.9726 (1.0) 5 1
test_numpy_msgpack[int32] 1,363.8515 (6.89) 1,505.4747 (7.16) 1,428.2127 (7.10) 53.4176 (10.30) 1,425.3516 (7.17) 72.8064 (19.01) 2;0 0.7002 (0.14) 5 1
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
-------------------------------------------------------------------------------- benchmark 'numpy int8': 2 tests ---------------------------------------------------------------------------------
Name (time in ms) Min Max Mean StdDev Median IQR Outliers OPS Rounds Iterations
--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
test_numpy_ormsgpack[int8] 107.8013 (1.0) 113.7336 (1.0) 109.0364 (1.0) 1.7805 (1.0) 108.3574 (1.0) 0.4066 (1.0) 1;2 9.1712 (1.0) 10 1
test_numpy_msgpack[int8] 685.4149 (6.36) 703.2958 (6.18) 693.2396 (6.36) 7.9572 (4.47) 691.5435 (6.38) 14.4142 (35.45) 1;0 1.4425 (0.16) 5 1
--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
------------------------------------------------------------------------------------- benchmark 'numpy npbool': 2 tests --------------------------------------------------------------------------------------
Name (time in ms) Min Max Mean StdDev Median IQR Outliers OPS Rounds Iterations
--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
test_numpy_ormsgpack[npbool] 87.9005 (1.0) 89.5460 (1.0) 88.7928 (1.0) 0.5098 (1.0) 88.8508 (1.0) 0.6609 (1.0) 4;0 11.2622 (1.0) 12 1
test_numpy_msgpack[npbool] 1,095.0599 (12.46) 1,176.3442 (13.14) 1,120.5916 (12.62) 32.9993 (64.73) 1,110.4216 (12.50) 38.4189 (58.13) 1;0 0.8924 (0.08) 5 1
--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
--------------------------------------------------------------------------------- benchmark 'numpy uint8': 2 tests ---------------------------------------------------------------------------------
Name (time in ms) Min Max Mean StdDev Median IQR Outliers OPS Rounds Iterations
----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
test_numpy_ormsgpack[uint8] 133.1743 (1.0) 134.7246 (1.0) 134.2793 (1.0) 0.4946 (1.0) 134.3120 (1.0) 0.4492 (1.0) 1;1 7.4472 (1.0) 8 1
test_numpy_msgpack[uint8] 727.1393 (5.46) 824.8247 (6.12) 775.7032 (5.78) 34.9887 (70.73) 775.9595 (5.78) 36.2824 (80.78) 2;0 1.2892 (0.17) 5 1
----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
-------------------------------------------------------------------------------- benchmark 'pydantic': 2 tests ---------------------------------------------------------------------------------
Name (time in ms) Min Max Mean StdDev Median IQR Outliers OPS Rounds Iterations
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
test_pydantic_ormsgpack 4.3918 (1.0) 12.6521 (1.0) 4.8550 (1.0) 1.1455 (3.98) 4.6101 (1.0) 0.0662 (1.0) 11;24 205.9727 (1.0) 204 1
test_pydantic_msgpack 124.5500 (28.36) 125.5427 (9.92) 125.0582 (25.76) 0.2877 (1.0) 125.0855 (27.13) 0.2543 (3.84) 2;0 7.9963 (0.04) 8 1
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
The above was measured using Python 3.7.9 on Azure Linux VM (x86_64) with ormsgpack 0.2.1 and msgpack 1.0.2.
The latency results can be reproduced using ./scripts/benchmark.sh and graphs using
pytest --benchmark-histogram benchmarks/bench_*.
Probably pip needs to be upgraded to version 20.3 or later to support
the latest manylinux_x_y or universal2 wheel formats.
No. This requires a schema specifying what types are expected and how to handle errors etc. This is addressed by data validation libraries a level above this.
To package ormsgpack requires Rust 1.81
or newer and the maturin build
tool. The default feature unstable-simd enables the usage of SIMD
operations and requires nightly Rust. The recommended build command
is:
maturin build --release --stripormsgpack is tested on Linux/amd64, Linux/aarch64, Linux/armv7, macOS/amd64 and Windows/amd64.
There are no runtime dependencies other than libc.
orjson was written by ijl <ijl@mailbox.org>, copyright 2018 - 2021, licensed under both the Apache 2 and MIT licenses.
ormsgpack was forked from orjson by Aviram Hassan and is now maintained by Emanuele Giaquinta (@exg), licensed same as orjson.