MessagePack is an efficient binary serialization format. It lets you exchange data among multiple languages like JSON. But it's faster and smaller. This package provides CPython bindings for reading and writing MessagePack data.
$ pip install msgpack-python
msgpack-python provides a pure Python implementation. PyPy can use this.
When you can't use a binary distribution, you need to install Visual Studio or Windows SDK on Windows. Without extension, using pure Python implementation on CPython runs slowly.
For Python 2.7, Microsoft Visual C++ Compiler for Python 2.7 is recommended solution.
For Python 3.5, Microsoft Visual Studio 2015 Community Edition or Express Edition can be used to build extension module.
Use packb for packing and unpackb for unpacking.
msgpack provides dumps and loads as an alias for compatibility with
json and pickle.
pack and dump packs to a file-like object.
unpack and load unpacks from a file-like object.
>>> import msgpack
>>> msgpack.packb([1, 2, 3])
'\x93\x01\x02\x03'
>>> msgpack.unpackb(_)
[1, 2, 3]unpack unpacks msgpack's array to Python's list, but can also unpack to tuple:
>>> msgpack.unpackb(b'\x93\x01\x02\x03', use_list=False)
(1, 2, 3)You should always specify the use_list keyword argument for backward compatibility.
See performance issues relating to use_list option below.
Read the docstring for other options.
Unpacker is a "streaming unpacker". It unpacks multiple objects from one
stream (or from bytes provided through its feed method).
import msgpack
from io import BytesIO
buf = BytesIO()
for i in range(100):
buf.write(msgpack.packb(range(i)))
buf.seek(0)
unpacker = msgpack.Unpacker(buf)
for unpacked in unpacker:
print unpackedIt is also possible to pack/unpack custom data types. Here is an example for
datetime.datetime.
import datetime
import msgpack
useful_dict = {
"id": 1,
"created": datetime.datetime.now(),
}
def decode_datetime(obj):
if b'__datetime__' in obj:
obj = datetime.datetime.strptime(obj["as_str"], "%Y%m%dT%H:%M:%S.%f")
return obj
def encode_datetime(obj):
if isinstance(obj, datetime.datetime):
return {'__datetime__': True, 'as_str': obj.strftime("%Y%m%dT%H:%M:%S.%f")}
return obj
packed_dict = msgpack.packb(useful_dict, default=encode_datetime)
this_dict_again = msgpack.unpackb(packed_dict, object_hook=decode_datetime)Unpacker's object_hook callback receives a dict; the
object_pairs_hook callback may instead be used to receive a list of
key-value pairs.
It is also possible to pack/unpack custom data types using the ext type.
>>> import msgpack
>>> import array
>>> def default(obj):
... if isinstance(obj, array.array) and obj.typecode == 'd':
... return msgpack.ExtType(42, obj.tostring())
... raise TypeError("Unknown type: %r" % (obj,))
...
>>> def ext_hook(code, data):
... if code == 42:
... a = array.array('d')
... a.fromstring(data)
... return a
... return ExtType(code, data)
...
>>> data = array.array('d', [1.2, 3.4])
>>> packed = msgpack.packb(data, default=default)
>>> unpacked = msgpack.unpackb(packed, ext_hook=ext_hook)
>>> data == unpacked
TrueAs an alternative to iteration, Unpacker objects provide unpack,
skip, read_array_header and read_map_header methods. The former two
read an entire message from the stream, respectively de-serialising and returning
the result, or ignoring it. The latter two methods return the number of elements
in the upcoming container, so that each element in an array, or key-value pair
in a map, can be unpacked or skipped individually.
Each of these methods may optionally write the packed data it reads to a callback function:
from io import BytesIO
def distribute(unpacker, get_worker):
nelems = unpacker.read_map_header()
for i in range(nelems):
# Select a worker for the given key
key = unpacker.unpack()
worker = get_worker(key)
# Send the value as a packed message to worker
bytestream = BytesIO()
unpacker.skip(bytestream.write)
worker.send(bytestream.getvalue())Early versions of msgpack didn't distinguish string and binary types (like Python 1). The type for representing both string and binary types was named raw.
For backward compatibility reasons, msgpack-python will still default all strings to byte strings, unless you specify the use_bin_type=True option in the packer. If you do so, it will use a non-standard type called bin to serialize byte arrays, and raw becomes to mean str. If you want to distinguish bin and raw in the unpacker, specify encoding='utf-8'.
Note that Python 2 defaults to byte-arrays over Unicode strings:
>>> import msgpack
>>> msgpack.unpackb(msgpack.packb([b'spam', u'eggs']))
['spam', 'eggs']
>>> msgpack.unpackb(msgpack.packb([b'spam', u'eggs'], use_bin_type=True),
encoding='utf-8')
['spam', u'eggs']This is the same code in Python 3 (same behaviour, but Python 3 has a different default):
>>> import msgpack
>>> msgpack.unpackb(msgpack.packb([b'spam', u'eggs']))
[b'spam', b'eggs']
>>> msgpack.unpackb(msgpack.packb([b'spam', u'eggs'], use_bin_type=True),
encoding='utf-8')
[b'spam', 'eggs']To use the ext type, pass msgpack.ExtType object to packer.
>>> import msgpack
>>> packed = msgpack.packb(msgpack.ExtType(42, b'xyzzy'))
>>> msgpack.unpackb(packed)
ExtType(code=42, data='xyzzy')You can use it with default and ext_hook. See below.
The msgpack-python release 0.3 has some incompatible changes.
The default value of use_list keyword argument is True from 0.3.
You should pass the argument explicitly for backward compatibility.
Unpacker.unpack() and some unpack methods now raises OutOfData instead of StopIteration. StopIteration is used for iterator protocol only.
CPython's GC starts when growing allocated object.
This means unpacking may cause useless GC.
You can use gc.disable() when unpacking large message.
List is the default sequence type of Python.
But tuple is lighter than list.
You can use use_list=False while unpacking when performance is important.
Python's dict can't use list as key and MessagePack allows array for key of mapping.
use_list=False allows unpacking such message.
Another way to unpacking such object is using object_pairs_hook.
MessagePack uses pytest for testing. Run test with following command:
$ py.test