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MessagePack for Python

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What's this

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.

Very important notes for existing users

PyPI package name

TL;DR: When upgrading from msgpack-0.4 or earlier, don't do pip install -U msgpack-python. Do pip uninstall msgpack-python; pip install -U msgpack instead.

Package name on PyPI was changed to msgpack from 0.5. I upload transitional package (msgpack-python 0.5 which depending on msgpack) for smooth transition from msgpack-python to msgpack.

Sadly, this doesn't work for upgrade install. After pip install -U msgpack-python, msgpack is removed, and import msgpack fail.

Compatibility with the old format

You can use use_bin_type=False option to pack bytes object into raw type in the old msgpack spec, instead of bin type in new msgpack spec.

You can unpack old msgpack format using raw=True option. It unpacks str (raw) type in msgpack into Python bytes.

See note below for detail.

Major breaking changes in msgpack 1.0

  • Python 2

    • The extension module does not support Python 2 anymore. The pure Python implementation (msgpack.fallback) is used for Python 2.
  • Packer

    • use_bin_type=True by default. bytes are encoded in bin type in msgpack. If you are still using Python 2, you must use unicode for all string types. You can use use_bin_type=False to encode into old msgpack format.
    • encoding option is removed. UTF-8 is used always.
  • Unpacker

    • raw=False by default. It assumes str types are valid UTF-8 string and decode them to Python str (unicode) object.
    • encoding option is removed. You can use raw=True to support old format.
    • Default value of max_buffer_size is changed from 0 to 100 MiB.
    • Default value of strict_map_key is changed to True to avoid hashdos. You need to pass strict_map_key=False if you have data which contain map keys which type is not bytes or str.


$ pip install msgpack

Pure Python implementation

The extension module in msgpack (msgpack._cmsgpack) does not support Python 2 and PyPy.

But msgpack provides a pure Python implementation (msgpack.fallback) for PyPy and Python 2.

Since the pip uses the pure Python implementation, Python 2 support will not be dropped in the foreseeable future.


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.

How to use

NOTE: In examples below, I use raw=False and use_bin_type=True for users using msgpack < 1.0. These options are default from msgpack 1.0 so you can omit them.

One-shot pack & unpack

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], use_bin_type=True)
   >>> msgpack.unpackb(_, raw=False)
   [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, raw=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.

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(i, use_bin_type=True))

   unpacker = msgpack.Unpacker(buf, raw=False)
   for unpacked in unpacker:

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,

    def decode_datetime(obj):
        if '__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, use_bin_type=True)
    this_dict_again = msgpack.unpackb(packed_dict, object_hook=decode_datetime, raw=False)

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, use_bin_type=True)
    >>> unpacked = msgpack.unpackb(packed, ext_hook=ext_hook, raw=False)
    >>> data == unpacked

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 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.


string and binary type

Early versions of msgpack didn't distinguish string and binary types. The type for representing both string and binary types was named raw.

You can pack into and unpack from this old spec using use_bin_type=False and raw=True options.

    >>> import msgpack
    >>> msgpack.unpackb(msgpack.packb([b'spam', u'eggs'], use_bin_type=False), raw=True)
    [b'spam', b'eggs']
    >>> msgpack.unpackb(msgpack.packb([b'spam', u'eggs'], use_bin_type=True), raw=False)
    [b'spam', 'eggs']

ext type

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.


To unpacking data received from unreliable source, msgpack provides two security options.

max_buffer_size (default: 100*1024*1024) limits the internal buffer size. It is used to limit the preallocated list size too.

strict_map_key (default: True) limits the type of map keys to bytes and str. While msgpack spec doesn't limit the types of the map keys, there is a risk of the hashdos. If you need to support other types for map keys, use strict_map_key=False.

Performance tips

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.

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