msgpack-python 0.4.7

MessagePack (de)serializer.

Author:

INADA Naoki

Version:

0.4.6

Date:

2015-03-13

What’s this

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.

Install

$ pip install msgpack-python

PyPy

msgpack-python provides pure python implementation. PyPy can use this.

Windows

When you can’t use 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.

How to use

One-shot pack & unpack

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 option below.

Read the docstring for other options.

Streaming unpacking

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

Packing/unpacking of custom data type

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.

Extended types

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
True

Advanced unpacking control

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())

Notes

string and binary type

In old days, msgpack doesn’t distinguish string and binary types like Python 1. The type for represent string and binary types is named raw.

msgpack can distinguish string and binary type for now. But it is not like Python 2. Python 2 added unicode string. But msgpack renamed raw to str and added bin type. It is because keep compatibility with data created by old libs. raw was used for text more than binary.

Currently, while msgpack-python supports new bin type, default setting doesn’t use it and decodes raw as bytes instead of unicode (str in Python 3).

You can change this by using use_bin_type=True option in Packer and encoding=”utf-8” option in Unpacker.

>>> import msgpack
>>> packed = msgpack.packb([b'spam', u'egg'], use_bin_type=True)
>>> msgpack.unpackb(packed, encoding='utf-8')
['spam', u'egg']

ext type

To use 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.

Note for msgpack-python 0.2.x users

The msgpack-python 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.

Note about performance

GC

CPython’s GC starts when growing allocated object. This means unpacking may cause useless GC. You can use gc.disable() when unpacking large message.

use_list option

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.

Development

Test

MessagePack uses pytest for testing. Run test with following command:

$ py.test