MessagePack (de)serializer.
Project description
MessagePack for Python
What's this
MessagePack <https://msgpack.org/>
_ 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 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.
- The extension module does not support Python 2 anymore.
The pure Python implementation (
-
Packer
use_bin_type=True
by default. bytes are encoded in bin type in msgpack. If you are still sing Python 2, you must use unicode for all string types. You can useuse_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.encdoding
option is rmeoved. You can useraw=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 passstrict_map_key=False
if you have data which contain map keys which type is not bytes or str.
Install
$ 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.
Windows
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)
'\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.
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))
buf.seek(0)
unpacker = msgpack.Unpacker(buf, raw=False)
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, 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
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 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())
Notes
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.
Security
To unpacking data received from unreliable source, msgpack provides two security options.
max_buffer_size
(default: 10010241024) 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.
Development
Test
MessagePack uses pytest
for testing.
Run test with following command:
$ make test
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