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.
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 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.
encoding and unicode_errors options are deprecated.
In case of packer, use UTF-8 always. Storing other than UTF-8 is not recommended.
For backward compatibility, you can use use_bin_type=False
and pack bytes
object into msgpack raw type.
In case of unpacker, there is new raw
option. It is True
by default
for backward compatibility, but it is changed to False
in near future.
You can use raw=False
instead of encoding='utf-8'
.
When msgpack 1.0, I planning these breaking changes:
- packer and unpacker: Remove
encoding
andunicode_errors
option. - packer: Change default of
use_bin_type
option from False to True. - unpacker: Change default of
raw
option from True to False. - unpacker: Reduce all
max_xxx_len
options for typical usage. - unpacker: Remove
write_bytes
option from all methods.
To avoid these breaking changes breaks your application, please:
- Don't use deprecated options.
- Pass
use_bin_type
andraw
options explicitly. - If your application handle large (>1MB) data, specify
max_xxx_len
options too.
$ pip install msgpack
msgpack 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], use_bin_type=True)
'\x93\x01\x02\x03'
>>> 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.
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), use_bin_type=True))
buf.seek(0)
unpacker = msgpack.Unpacker(buf, raw=False)
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, 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.
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
True
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.
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 raw=False
.
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),
raw=False)
['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),
raw=False)
[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.
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:
$ make test