{
    "info": {
        "author": "Radomir Stevanovic",
        "author_email": "radomir.stevanovic@gmail.com",
        "bugtrack_url": null,
        "classifiers": [
            "Development Status :: 5 - Production/Stable",
            "Intended Audience :: Developers",
            "License :: OSI Approved :: MIT License",
            "Operating System :: OS Independent",
            "Programming Language :: Python",
            "Programming Language :: Python :: 2",
            "Programming Language :: Python :: 2.6",
            "Programming Language :: Python :: 2.7",
            "Programming Language :: Python :: 3",
            "Programming Language :: Python :: 3.3",
            "Programming Language :: Python :: 3.4",
            "Programming Language :: Python :: 3.5",
            "Programming Language :: Python :: 3.6",
            "Topic :: Software Development :: Libraries :: Python Modules"
        ],
        "description": "JSON+\n=====\n\n.. image:: https://img.shields.io/pypi/v/jsonplus.svg\n    :target: https://pypi.python.org/pypi/jsonplus\n\n.. image:: https://img.shields.io/pypi/l/jsonplus.svg\n    :target: https://pypi.python.org/pypi/jsonplus\n\n.. image:: https://img.shields.io/pypi/wheel/jsonplus.svg\n    :target: https://pypi.python.org/pypi/jsonplus\n\n.. image:: https://img.shields.io/pypi/pyversions/jsonplus.svg\n    :target: https://pypi.python.org/pypi/jsonplus\n\n.. image:: https://api.travis-ci.org/randomir/jsonplus.svg?branch=master\n    :target: https://travis-ci.org/randomir/jsonplus\n\n\nSerialization of Python types to JSON that \"just works\".\n\nForget errors like::\n\n    TypeError: datetime.datetime(...) is not JSON serializable\n\nIn addition to (de-)serialization of basic types (provided by simplejson_), jsonplus_\nprovides support for **exact** (de-)serialization of other commonly used types, like:\n``tuple``/``namedtuple``, ``set``/``frozenset``, ``complex``/``decimal.Decimal``/``fractions.Fraction``,\nand ``datetime``/``date``/``time``/``timedelta``.\n\nIf the exact representation of types is not your cup of tea, and all you wish\nfor is the ``json.dumps`` to work on your data structure with non-basic types,\naccepting the loss of \"type-precision\" along the way, than you can use the\n**compatibility** mode (thread-local ``jsonplus.prefer_compat()``, or\nper-call override ``jsonplus.dumps(..., exact=False)``).\n\n.. _simplejson: https://simplejson.readthedocs.io/en/latest/#encoders-and-decoders\n.. _jsonplus: https://pypi.python.org/pypi/jsonplus/\n\n\nInstallation\n------------\n\n``jsonplus`` is available as a Python package. To install it, simply type::\n\n    $ pip install jsonplus\n\n\nUsage\n-----\n\nYou can treat ``jsonplus`` as a friendly *drop-in* replacement for ``json``/``simplejson``.\n\n.. code-block:: python\n\n    >>> import jsonplus as json\n\n    >>> x = json.loads('{\"a\":1,\"b\":2}')\n    >>> y = json.dumps(x, indent=4)\n    >>> z = json.pretty(x)\n\n\nExamples\n--------\n\nLet's start with that beloved ``datetime``.\n\n.. code-block:: python\n\n    >>> import jsonplus as json\n\n    >>> from datetime import datetime\n    >>> json.dumps({\n    ...     \"x\": [4,3],\n    ...     \"t\": datetime.now()\n    ... })\n    '{\"x\":[4,3],\"t\":{\"__class__\":\"datetime\",\"__value__\":\"2013-09-06T23:38:55.819791\"}}'\n    \n    >>> json.loads(_)\n    {u'x': [4, 3], u't': datetime.datetime(2013, 9, 6, 23, 38, 55, 819791)}\n\nSimilarly for other ``datetime.*`` types, like ``timedelta``, ``date``, and ``time``:\n\n.. code-block:: python\n\n    >>> from datetime import timedelta, date, time\n    >>> print(json.pretty({\"dt\": timedelta(0, 1234567, 123), \"d\": date.today(), \"t\": datetime.now().time()}))\n    {\n        \"d\": {\n            \"__class__\": \"date\",\n            \"__value__\": \"2013-09-22\"\n        },\n        \"dt\": {\n            \"__class__\": \"timedelta\",\n            \"__value__\": {\n                \"days\": 14,\n                \"microseconds\": 123,\n                \"seconds\": 24967\n            }\n        },\n        \"t\": {\n            \"__class__\": \"time\",\n            \"__value__\": \"23:33:16.335360\"\n        }\n    }\n\nAlso, ``set`` and ``complex``:\n\n.. code-block:: python\n\n    >>> json.dumps([set(range(3)), 1+2j])\n    '[{\"__class__\":\"set\",\"__value__\":[0,1,2]},{\"__class__\":\"complex\",\"__value__\":{\"real\":1.0,\"imag\":2.0}}]'\n    \n    >>> json.loads(_)\n    [set([0, 1, 2]), (1+2j)]\n\n``tuple`` and ``namedtuple`` are also preserved:\n\n.. code-block:: python\n\n    >>> from collections import namedtuple\n    >>> Point = namedtuple('Point', ['x', 'y'])\n\n    >>> data = json.pretty({\"vect\": (1, 2, 3), \"dot\": Point(3, 4)})\n    >>> print(data)\n    {\n        \"dot\": {\n            \"__class__\": \"namedtuple\",\n            \"__value__\": {\n                \"fields\": [\n                    \"x\",\n                    \"y\"\n                ],\n                \"name\": \"Point\",\n                \"values\": [\n                    3,\n                    4\n                ]\n            }\n        },\n        \"vect\": {\n            \"__class__\": \"tuple\",\n            \"__value__\": [\n                1,\n                2,\n                3\n            ]\n        }\n    }\n\n    >>> json.loads(data)\n    {'vect': (1, 2, 3), 'dot': Point(x=3, y=4)}\n\n\nCompatibility mode\n------------------\n\nAll types supported in the exact mode are also supported in the compatibility\nmode. JSON representation differs, however.\n\nIn the exact mode, *type* and *value* are encoded with ``JSON Object``'s\n``__class__`` and ``__value__`` keys, while in the compatibility mode, \n**values are \"rounded off\" to the closest JSON type**.\n\nFor example, ``tuple`` and ``set`` are represented with ``JSON Array``, and\n``namedtuple`` is coded as a plain ``JSON Object``. ``Decimal`` is\nrepresented as ``JSON Number`` with arbitrary precision (which is lost if\ndecoded as ``float``).\n\nTo switch between the **exact** and **compatibility** modes, use the \n(thread-local) functions ``prefer_exact()`` and ``prefer_compat()``, or call\n``dumps(..., exact=False)``:\n\n.. code-block:: python\n\n    >>> import jsonplus as json\n\n    >>> json.prefer_compat()\n    # or:\n    >>> json.prefer(json.COMPAT)\n    # per-instance override:\n    >>> json.dumps(obj, exact=False)\n\n    # to go back to (default) exact coding:\n    >>> json.prefer_exact()\n\nThe above ``tuple``/``namedtuple``/``datetime`` examples run in the compatibility \ncoding mode result with:\n\n.. code-block:: python\n\n    >>> json.prefer_compat()\n\n    >>> print(json.pretty({\"vect\": (1, 2, 3), \"dot\": Point(3, 4)}))\n    {\n        \"point\": {\n            \"x\": 3,\n            \"y\": 4\n        },\n        \"vector\": [\n            1,\n            2,\n            3\n        ]\n    }\n\n    >>> json.dumps({\"now\": datetime.now()})\n    '{\"now\":\"2017-01-26T00:37:40.293963\"}'\n\nSo, to be able to properly decode values in the compatibility mode, some \nadditional context will have to be provided to the decoder.\n\n\nAdding user types\n-----------------\n\nSupport for user/custom types can easily be added with `@jsonplus.encoder` and\n`@jsonplus.decoder` decorators.\n\nFor example, to enable serialization of your type named ``mytype`` in exact mode\n(to add compat-mode serialization, append ``exact=False`` in decorator):\n\n.. code-block:: python\n\n    @jsonplus.encoder('mytype')\n    def mytype_exact_encoder(myobj):\n        return myobj.to_json()\n\n.. code-block:: python\n\n    @jsonplus.decoder('mytype')\n    def mytype_decoder(value):\n        return mytype(value, reconstruct=True, ...)\n\nIf detection of object class is more complex than a simple classname comparison,\nif you need to use a predicate function, simply add ``predicate=...`` to the ``encoder``\ndecorator. For example:\n\n.. code-block:: python\n\n    @jsonplus.encoder('BaseClass', lambda obj: isinstance(obj, BaseClass))\n    def all_derived_classes_encoder(derived):\n        return derived.base_encoder()\n",
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