Metadata-Version: 2.0
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Name: msgpack
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Version: 0.5.6
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Summary: MessagePack (de)serializer.
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Home-page: http://msgpack.org/
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Author: INADA Naoki
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Author-email: songofacandy@gmail.com
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License: Apache 2.0
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Description-Content-Type: UNKNOWN
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Platform: UNKNOWN
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Classifier: Programming Language :: Python :: 2
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Classifier: Programming Language :: Python :: 2.7
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Classifier: Programming Language :: Python :: 3
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Classifier: Programming Language :: Python :: 3.5
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Classifier: Programming Language :: Python :: 3.6
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Classifier: Programming Language :: Python :: 3.7
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Classifier: Programming Language :: Python :: Implementation :: CPython
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Classifier: Programming Language :: Python :: Implementation :: PyPy
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Classifier: Intended Audience :: Developers
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Classifier: License :: OSI Approved :: Apache Software License
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======================
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MessagePack for Python
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======================
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.. image:: https://travis-ci.org/msgpack/msgpack-python.svg?branch=master
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:target: https://travis-ci.org/msgpack/msgpack-python
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:alt: Build Status
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.. image:: https://readthedocs.org/projects/msgpack-python/badge/?version=latest
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:target: https://msgpack-python.readthedocs.io/en/latest/?badge=latest
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:alt: Documentation Status
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What's this
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-----------
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`MessagePack <https://msgpack.org/>`_ is an efficient binary serialization format.
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It lets you exchange data among multiple languages like JSON.
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But it's faster and smaller.
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This package provides CPython bindings for reading and writing MessagePack data.
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Very important notes for existing users
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---------------------------------------
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PyPI package name
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^^^^^^^^^^^^^^^^^
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TL;DR: When upgrading from msgpack-0.4 or earlier, don't do `pip install -U msgpack-python`.
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Do `pip uninstall msgpack-python; pip install msgpack` instead.
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Package name on PyPI was changed to msgpack from 0.5.
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I upload transitional package (msgpack-python 0.5 which depending on msgpack)
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for smooth transition from msgpack-python to msgpack.
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Sadly, this doesn't work for upgrade install. After `pip install -U msgpack-python`,
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msgpack is removed and `import msgpack` fail.
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Deprecating encoding option
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^^^^^^^^^^^^^^^^^^^^^^^^^^^^
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encoding and unicode_errors options are deprecated.
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In case of packer, use UTF-8 always. Storing other than UTF-8 is not recommended.
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For backward compatibility, you can use ``use_bin_type=False`` and pack ``bytes``
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object into msgpack raw type.
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In case of unpacker, there is new ``raw`` option. It is ``True`` by default
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for backward compatibility, but it is changed to ``False`` in near future.
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You can use ``raw=False`` instead of ``encoding='utf-8'``.
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Planned backward incompatible changes
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^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
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When msgpack 1.0, I planning these breaking changes:
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* packer and unpacker: Remove ``encoding`` and ``unicode_errors`` option.
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* packer: Change default of ``use_bin_type`` option from False to True.
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* unpacker: Change default of ``raw`` option from True to False.
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* unpacker: Reduce all ``max_xxx_len`` options for typical usage.
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* unpacker: Remove ``write_bytes`` option from all methods.
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To avoid these breaking changes breaks your application, please:
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* Don't use deprecated options.
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* Pass ``use_bin_type`` and ``raw`` options explicitly.
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* If your application handle large (>1MB) data, specify ``max_xxx_len`` options too.
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Install
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-------
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::
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$ pip install msgpack
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PyPy
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^^^^
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msgpack provides a pure Python implementation. PyPy can use this.
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Windows
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^^^^^^^
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When you can't use a binary distribution, you need to install Visual Studio
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or Windows SDK on Windows.
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Without extension, using pure Python implementation on CPython runs slowly.
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For Python 2.7, `Microsoft Visual C++ Compiler for Python 2.7 <https://www.microsoft.com/en-us/download/details.aspx?id=44266>`_
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is recommended solution.
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For Python 3.5, `Microsoft Visual Studio 2015 <https://www.visualstudio.com/en-us/products/vs-2015-product-editions.aspx>`_
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Community Edition or Express Edition can be used to build extension module.
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How to use
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----------
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One-shot pack & unpack
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^^^^^^^^^^^^^^^^^^^^^^
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Use ``packb`` for packing and ``unpackb`` for unpacking.
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msgpack provides ``dumps`` and ``loads`` as an alias for compatibility with
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``json`` and ``pickle``.
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``pack`` and ``dump`` packs to a file-like object.
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``unpack`` and ``load`` unpacks from a file-like object.
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.. code-block:: pycon
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>>> import msgpack
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>>> msgpack.packb([1, 2, 3], use_bin_type=True)
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'\x93\x01\x02\x03'
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>>> msgpack.unpackb(_, raw=False)
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[1, 2, 3]
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``unpack`` unpacks msgpack's array to Python's list, but can also unpack to tuple:
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.. code-block:: pycon
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>>> msgpack.unpackb(b'\x93\x01\x02\x03', use_list=False, raw=False)
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(1, 2, 3)
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You should always specify the ``use_list`` keyword argument for backward compatibility.
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See performance issues relating to `use_list option`_ below.
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Read the docstring for other options.
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Streaming unpacking
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^^^^^^^^^^^^^^^^^^^
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``Unpacker`` is a "streaming unpacker". It unpacks multiple objects from one
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stream (or from bytes provided through its ``feed`` method).
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.. code-block:: python
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import msgpack
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from io import BytesIO
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buf = BytesIO()
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for i in range(100):
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buf.write(msgpack.packb(range(i), use_bin_type=True))
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buf.seek(0)
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unpacker = msgpack.Unpacker(buf, raw=False)
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for unpacked in unpacker:
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print(unpacked)
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Packing/unpacking of custom data type
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^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
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It is also possible to pack/unpack custom data types. Here is an example for
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``datetime.datetime``.
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.. code-block:: python
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import datetime
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import msgpack
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useful_dict = {
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"id": 1,
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"created": datetime.datetime.now(),
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}
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def decode_datetime(obj):
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if b'__datetime__' in obj:
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obj = datetime.datetime.strptime(obj["as_str"], "%Y%m%dT%H:%M:%S.%f")
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return obj
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def encode_datetime(obj):
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if isinstance(obj, datetime.datetime):
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return {'__datetime__': True, 'as_str': obj.strftime("%Y%m%dT%H:%M:%S.%f")}
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return obj
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packed_dict = msgpack.packb(useful_dict, default=encode_datetime, use_bin_type=True)
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this_dict_again = msgpack.unpackb(packed_dict, object_hook=decode_datetime, raw=False)
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``Unpacker``'s ``object_hook`` callback receives a dict; the
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``object_pairs_hook`` callback may instead be used to receive a list of
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key-value pairs.
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Extended types
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^^^^^^^^^^^^^^
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It is also possible to pack/unpack custom data types using the **ext** type.
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.. code-block:: pycon
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>>> import msgpack
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>>> import array
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>>> def default(obj):
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... if isinstance(obj, array.array) and obj.typecode == 'd':
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... return msgpack.ExtType(42, obj.tostring())
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... raise TypeError("Unknown type: %r" % (obj,))
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...
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>>> def ext_hook(code, data):
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... if code == 42:
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... a = array.array('d')
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... a.fromstring(data)
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... return a
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... return ExtType(code, data)
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...
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>>> data = array.array('d', [1.2, 3.4])
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>>> packed = msgpack.packb(data, default=default, use_bin_type=True)
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>>> unpacked = msgpack.unpackb(packed, ext_hook=ext_hook, raw=False)
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>>> data == unpacked
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True
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Advanced unpacking control
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^^^^^^^^^^^^^^^^^^^^^^^^^^
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As an alternative to iteration, ``Unpacker`` objects provide ``unpack``,
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``skip``, ``read_array_header`` and ``read_map_header`` methods. The former two
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read an entire message from the stream, respectively de-serialising and returning
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the result, or ignoring it. The latter two methods return the number of elements
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in the upcoming container, so that each element in an array, or key-value pair
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in a map, can be unpacked or skipped individually.
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Each of these methods may optionally write the packed data it reads to a
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callback function:
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.. code-block:: python
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from io import BytesIO
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def distribute(unpacker, get_worker):
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nelems = unpacker.read_map_header()
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for i in range(nelems):
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# Select a worker for the given key
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key = unpacker.unpack()
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worker = get_worker(key)
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# Send the value as a packed message to worker
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bytestream = BytesIO()
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unpacker.skip(bytestream.write)
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worker.send(bytestream.getvalue())
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Notes
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-----
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string and binary type
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^^^^^^^^^^^^^^^^^^^^^^
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Early versions of msgpack didn't distinguish string and binary types (like Python 1).
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The type for representing both string and binary types was named **raw**.
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For backward compatibility reasons, msgpack-python will still default all
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strings to byte strings, unless you specify the ``use_bin_type=True`` option in
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the packer. If you do so, it will use a non-standard type called **bin** to
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serialize byte arrays, and **raw** becomes to mean **str**. If you want to
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distinguish **bin** and **raw** in the unpacker, specify ``raw=False``.
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Note that Python 2 defaults to byte-arrays over Unicode strings:
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.. code-block:: pycon
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>>> import msgpack
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>>> msgpack.unpackb(msgpack.packb([b'spam', u'eggs']))
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['spam', 'eggs']
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>>> msgpack.unpackb(msgpack.packb([b'spam', u'eggs'], use_bin_type=True),
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raw=False)
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['spam', u'eggs']
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This is the same code in Python 3 (same behaviour, but Python 3 has a
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different default):
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.. code-block:: pycon
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>>> import msgpack
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>>> msgpack.unpackb(msgpack.packb([b'spam', u'eggs']))
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[b'spam', b'eggs']
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>>> msgpack.unpackb(msgpack.packb([b'spam', u'eggs'], use_bin_type=True),
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raw=False)
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[b'spam', 'eggs']
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ext type
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^^^^^^^^
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To use the **ext** type, pass ``msgpack.ExtType`` object to packer.
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.. code-block:: pycon
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>>> import msgpack
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>>> packed = msgpack.packb(msgpack.ExtType(42, b'xyzzy'))
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>>> msgpack.unpackb(packed)
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ExtType(code=42, data='xyzzy')
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You can use it with ``default`` and ``ext_hook``. See below.
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Note about performance
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----------------------
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GC
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^^
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CPython's GC starts when growing allocated object.
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This means unpacking may cause useless GC.
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You can use ``gc.disable()`` when unpacking large message.
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use_list option
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^^^^^^^^^^^^^^^
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List is the default sequence type of Python.
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But tuple is lighter than list.
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You can use ``use_list=False`` while unpacking when performance is important.
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Python's dict can't use list as key and MessagePack allows array for key of mapping.
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``use_list=False`` allows unpacking such message.
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Another way to unpacking such object is using ``object_pairs_hook``.
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Development
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-----------
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Test
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^^^^
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MessagePack uses `pytest` for testing.
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Run test with following command:
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$ make test
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..
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vim: filetype=rst
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