| Author: | INADA Naoki |
|---|---|
| Version: | 0.2.0 |
| Date: | 2012-06-27 |
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.
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 tuple.
To unpack it to list, Use use_list option.
>>> msgpack.unpackb(b'\x93\x01\x02\x03', use_list=True) [1, 2, 3]
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())
You can use pip or easy_install to install msgpack:
$ easy_install msgpack-python or $ pip install msgpack-python
msgpack provides some binary distribution for Windows. You can install msgpack without compiler with them.
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.)
MessagePack uses nosetest for testing. Run test with following command:
$ nosetests test