- author
INADA Naoki
- version
0.3.0
- date
2012-12-07
MessagePack is a fast, compact binary serialization format, suitable for similar data to JSON. This package provides CPython bindings for reading and writing MessagePack data.
You can use pip
or easy_install
to install msgpack:
$ easy_install msgpack-python
or
$ pip install msgpack-python
msgpack-python provides pure python implementation. PyPy can use this.
When you can't use binary distribution, you need to install Visual Studio or Windows SDK on Windows. (NOTE: Visual C++ Express 2010 doesn't support amd64. Windows SDK is recommanded way to build amd64 msgpack without any fee.)
Without extension, using pure python implementation on CPython runs slowly.
The msgpack 0.3 have 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.
Use packb
for packing and unpackb
for unpacking. msgpack provides dumps
and loads
as alias for compatibility with json
and pickle
.
pack
and dump
packs to file-like object. unpack
and load
unpacks from 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 unpack to tuple:
>>> msgpack.unpackb(b'\x93\x01\x02\x03', use_list=False)
(1, 2, 3)
You should always pass the use_list
keyword argument. See performance issues relating to use_list 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 unpacked
It 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.
As 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 deserialising 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())
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