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This package is no longer maintained. For a typed MessagePack serializer, see tmsgpack (part of semifun).
This package msgpack_sorted is a fork of the msgpack python package. It adds only one option sort_keys (default: False) and its implementation: Sort dictionary keys with the python sorted function when serializing data.
The serialized data format is identical to the msgpack standard, msgpack_sorted and msgpack can correctly parse each others output.
This forked package is not intended to replace the official msgpack package -- but to coexist with it. For that purpose its name is change to msgpack_sorted. you can install it with pip install msgpack-sorted and import it with import msgpack_sorted as msgpack.
Plase refer to the official documentation of msgpack for all features (except the option sort_keys explained above).
Most of the documentation below is retained from the msgpack package.
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.
Package name on PyPI was changed from msgpack-python to msgpack from 0.5.
When upgrading from msgpack-0.4 or earlier, do pip uninstall msgpack-python before pip install -U msgpack.
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.
Python 2
Packer
Unpacker
$ pip install msgpack-sorted
The extension module in msgpack_sorted (msgpack_sorted._cmsgpack) does not support Python 2 and PyPy.
But msgpack_sorted provides a pure Python implementation (msgpack_sorted.fallback) for PyPy and Python 2.
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.
NOTE: For msgpack_sorted, raw=False and use_bin_type=True are defaults --- just as in msgpack >= 1.0.
Use packb for packing and unpackb for unpacking. msgpack_sorted 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_sorted as 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 also unpack to tuple:
>>> msgpack.unpackb(b'\x93\x01\x02\x03', use_list=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_sorted as msgpack
from io import BytesIO
buf = BytesIO()
for i in range(100):
buf.write(msgpack.packb(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_sorted as msgpack
useful_dict = {
"id": 1,
"created": datetime.datetime.now(),
}
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)
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.
It is also possible to pack/unpack custom data types using the ext type.
>>> import msgpack_sorted as 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
TrueAs 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.
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_sorted as msgpack
>>> msgpack.unpackb(msgpack.packb([b'spam', 'eggs'], use_bin_type=False), raw=True)
[b'spam', b'eggs']
>>> msgpack.unpackb(msgpack.packb([b'spam', 'eggs']))
[b'spam', 'eggs']To use the ext type, pass msgpack.ExtType object to packer.
>>> import msgpack_sorted as 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_sorted 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.
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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