basabuuka_prototyp/venv/lib/python3.5/site-packages/msgpack-0.5.6.dist-info/METADATA

Metadata-Version: 2.0
Name: msgpack
Version: 0.5.6
Summary: MessagePack (de)serializer.
Home-page: http://msgpack.org/
Author: INADA Naoki
Author-email: songofacandy@gmail.com
License: Apache 2.0
Description-Content-Type: UNKNOWN
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: Implementation :: CPython
Classifier: Programming Language :: Python :: Implementation :: PyPy
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: Apache Software License

======================
MessagePack for Python
======================

.. image:: https://travis-ci.org/msgpack/msgpack-python.svg?branch=master
   :target: https://travis-ci.org/msgpack/msgpack-python
   :alt: Build Status

.. image:: https://readthedocs.org/projects/msgpack-python/badge/?version=latest
   :target: https://msgpack-python.readthedocs.io/en/latest/?badge=latest
   :alt: Documentation Status


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.


Deprecating encoding option
^^^^^^^^^^^^^^^^^^^^^^^^^^^^

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'``.

Planned backward incompatible changes
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

When msgpack 1.0, I planning these breaking changes:

* packer and unpacker: Remove ``encoding`` and ``unicode_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`` and ``raw`` options explicitly.
* If your application handle large (>1MB) data, specify ``max_xxx_len`` options too.


Install
-------

::

   $ pip install msgpack

PyPy
^^^^

msgpack provides a pure Python implementation.  PyPy can use this.

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.

For Python 2.7, `Microsoft Visual C++ Compiler for Python 2.7 <https://www.microsoft.com/en-us/download/details.aspx?id=44266>`_
is recommended solution.

For Python 3.5, `Microsoft Visual Studio 2015 <https://www.visualstudio.com/en-us/products/vs-2015-product-editions.aspx>`_
Community Edition or Express Edition can be used to build extension module.


How to use
----------

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.

.. code-block:: pycon

   >>> 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:

.. code-block:: pycon

   >>> 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).

.. code-block:: python

   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)


Packing/unpacking of custom data type
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

It is also possible to pack/unpack custom data types. Here is an example for
``datetime.datetime``.

.. code-block:: python

    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.

.. code-block:: pycon

    >>> 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:

.. code-block:: python

    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 (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:

.. code-block:: pycon

    >>> 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):

.. code-block:: pycon

    >>> 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']


ext type
^^^^^^^^

To use the **ext** type, pass ``msgpack.ExtType`` object to packer.

.. code-block:: pycon

    >>> 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.


Note about performance
----------------------

GC
^^

CPython's GC starts when growing allocated object.
This means unpacking may cause useless GC.
You can use ``gc.disable()`` when unpacking large message.

use_list option
^^^^^^^^^^^^^^^

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``.


Development
-----------

Test
^^^^

MessagePack uses `pytest` for testing.
Run test with following command:

    $ make test


..
    vim: filetype=rst