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# MessagePack for Python

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## 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.

* 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 use `use_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.
  * `encoding` option is removed.  You can use `raw=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 pass `strict_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](https://pip.pypa.io/) 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.

```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:

```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).

```py
   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`.

```py
    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.

```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.


## 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.

```pycon
    >>> 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.

```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.


### Security

To unpacking data received from unreliable source, msgpack 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`.


### 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
```