高效轻量的Python MessagePack库:u-msgpack-python

高效轻量的Python MessagePack库:u-msgpack-python

u-msgpack-pythonA portable, lightweight MessagePack serializer and deserializer written in pure Python, compatible with Python 2, Python 3, CPython, PyPy / msgpack.org[Python] 项目地址:https://gitcode.com/gh_mirrors/um/u-msgpack-python

u-msgpack-python 是一个纯Python实现的高效MessagePack序列化和反序列化的库,它兼容Python 2和3,并且与CPython和PyPy平台无缝协作。这个库完全符合最新的MessagePack规范,包括对二进制、UTF-8字符串、应用定义的扩展类型以及时间戳的支持。

项目简介

u-msgpack-python以其简单易用而著称,提供了一个易于安装和集成的包。无论你是想要在本地项目中直接引入单个文件模块,还是通过pip或easy_install进行全局安装,它都能满足你的需求。

技术分析

  • 轻量级:u-msgpack-python以Python编写,无需依赖其他库,可以轻松整合到任何Python项目中。
  • 跨版本兼容:支持Python 2和3,意味着它可以广泛应用于各种环境。
  • 高性能:u-msgpack-python优化了数据序列化和反序列化的效率,尤其适合大数据传输和存储。
  • 完整支持新特性:库提供了对最新MessagePack规范的所有数据类型的编码和解码,包括扩展类型和时间戳。

应用场景

  • 网络通信:在网络应用中,u-msgpack-python可用于创建紧凑、高效的协议消息。
  • 数据存储:在数据库、缓存系统或者日志记录中,它能帮助你节省存储空间。
  • API接口:构建RESTful API时,可以作为JSON之外的一个高效替代方案。
  • 数据分析:处理大量结构化数据时,MessagePack的压缩效果可以减少内存占用。

项目特点

  1. 易用性:内置示例代码直观易懂,帮助快速上手。
  2. 流式处理:支持对文件对象的序列化和反序列化,方便处理大文件。
  3. 自定义类型处理:通过ext_serializable装饰器或自定义的Ext处理器,可以便捷地扩展对自定义数据类型的序列化和反序列化。
  4. 多平台支持:不仅在标准Python解释器下工作良好,也适用于PyPy这样的JIT编译器。

要开始使用u-msgpack-python,只需按照readme中的步骤进行安装,然后尽情享受其带来的高效序列化体验吧!

# 示例代码:
import umsgpack
packed = umsgpack.packb({u"compact": True, u"schema": 0})
print(packed)  # 输出:b'\x82\xa7compact\xc3\xa6schema\x00'
unpacked = umsgpack.unpackb(packed)
print(unpacked)  # 输出:{u'compact': True, u'schema': 0}

更多高级特性和详细文档,可访问官方文档获取更多信息。

现在就加入u-msgpack-python的行列,提升你的Python项目性能吧!

u-msgpack-pythonA portable, lightweight MessagePack serializer and deserializer written in pure Python, compatible with Python 2, Python 3, CPython, PyPy / msgpack.org[Python] 项目地址:https://gitcode.com/gh_mirrors/um/u-msgpack-python

创作声明:本文部分内容由AI辅助生成(AIGC),仅供参考

======================= MessagePack for Python ======================= :author: INADA Naoki :version: 0.4.1 :date: 2014-02-17 .. image:: https://secure.travis-ci.org/msgpack/msgpack-python.png :target: https://travis-ci.org/#!/msgpack/msgpack-python What's this ------------ `MessagePack <http://msgpack.org/>`_ is a fast, compact binary serialization format, suitable for similar data to JSON. This package provides CPython bindings for reading and writing MessagePack data. Install --------- You can use ``pip`` or ``easy_install`` to install msgpack:: $ easy_install msgpack-python or $ pip install msgpack-python PyPy ^^^^^ msgpack-python provides pure python implementation. PyPy can use this. Windows ^^^^^^^ When you can't use binary distribution, you need to install Visual Studio or Windows SDK on Windows. (NOTE: Visual C++ Express 2010 doesn't support amd64. Windows SDK is recommanded way to build amd64 msgpack without any fee.) Without extension, using pure python implementation on CPython runs slowly. Notes ----- Note for msgpack 2.0 support ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ msgpack 2.0 adds two types: *bin* and *ext*. *raw* was bytes or string type like Python 2's ``str``. To distinguish string and bytes, msgpack 2.0 adds *bin*. It is non-string binary like Python 3's ``bytes``. To use *bin* type for packing ``bytes``, pass ``use_bin_type=True`` to packer argument. >>> import msgpack >>> packed = msgpack.packb([b'spam', u'egg'], use_bin_type=True) >>> msgpack.unpackb(packed, encoding='utf-8') ['spam', u'egg'] You shoud use it carefully. When you use ``use_bin_type=True``, packed binary can be unpacked by unpackers supporting msgpack-2.0. To use *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. Note for msgpack 0.2.x users ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ The msgpack 0.3 have some incompatible changes. The default value of ``use_list`` keyword argument is ``True`` from 0.3. You should pass the argument explicitly for backward compatibility. `Unpacker.unpack()` and some unpack methods now raises `OutOfData` instead of `StopIteration`. `StopIteration` is used for iterator protocol only. How to use ----------- One-shot pack & unpack ^^^^^^^^^^^^^^^^^^^^^^ Use ``packb`` for packing and ``unpackb`` for unpacking. msgpack provides ``dumps`` and ``loads`` as alias for compatibility with ``json`` and ``pickle``. ``pack`` and ``dump`` packs to file-like object. ``unpack`` and ``load`` unpacks from file-like object. :: >>> import 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 unpack to tuple:: >>> msgpack.unpackb(b'\x93\x01\x02\x03', use_list=False) (1, 2, 3) You should always pass the ``use_list`` keyword argument. See performance issues relating to use_list_ 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(range(i))) buf.seek(0) unpacker = msgpack.Unpacker(buf) 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) 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. Extended types ^^^^^^^^^^^^^^^ It is also possible to pack/unpack custom data types using the msgpack 2.0 feature. >>> 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) >>> unpacked = msgpack.unpackb(packed, ext_hook=ext_hook) >>> 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 deserialising 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()) 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``. Test ---- MessagePack uses `pytest` for testing. Run test with following command: $ py.test .. vim: filetype=rst
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