{
    "info": {
        "author": "Timothy Edmund Crosley",
        "author_email": "timothy.crosley@gmail.com",
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        "classifiers": [
            "Intended Audience :: Developers",
            "License :: OSI Approved :: MIT License",
            "Programming Language :: Python :: 3",
            "Topic :: Software Development :: Libraries :: Python Modules"
        ],
        "description": "[![preconvert - Supercharge Your Serializers](https://raw.github.com/timothycrosley/preconvert/master/art/logo_large.png)](https://timothycrosley.github.io/preconvert/)\n===================\n\n[![PyPI version](https://badge.fury.io/py/preconvert.svg)](http://badge.fury.io/py/preconvert)\n[![Build Status](https://travis-ci.org/timothycrosley/preconvert.svg?branch=master)](https://travis-ci.org/timothycrosley/preconvert)\n[![codecov](https://codecov.io/gh/timothycrosley/preconvert/branch/master/graph/badge.svg)](https://codecov.io/gh/timothycrosley/preconvert)\n[![Gitter](https://badges.gitter.im/preconvert/community.svg)](https://gitter.im/preconvert/community?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge)\n[![License](https://img.shields.io/github/license/mashape/apistatus.svg)](https://pypi.python.org/pypi/hug/)\n[![Downloads](https://pepy.tech/badge/preconvert)](https://pepy.tech/project/preconvert)\n\n_________________\n\n[Read Latest Documentation](https://timothycrosley.github.io/preconvert/) - [Browse GitHub Code Repository](https://github.com/timothycrosley/preconvert/)\n_________________\n\nPreconvert is a library that extends existing serializiers (json, simplejson, bson, msgpack, ..) to be capable of converting *all* the types you use.\nIt accomplishes this by efficiently preconverting just the types the serializers aren't aware of (things like dataclasses and namedtuples) into basic built-in types that all\nserializers can understand. It then provides a mechanism for you to build custom preconverters, and preconvert_plugins that automatically take effect when installed via pip.\n\n## Quickstart\n\n1. Install preconvert using pip:\n\n        pip3 install preconvert\n\n2. Replace existing json (or other serialization library) with preconvert equivalent:\n\n        from preconvert.output import simplejson as json\n\n        ...\n\n        json.dumps(MY_COMPLEX_OBJECT_WITH_DATA_CLASSSES)\n\n4. Define preconverters for any custom types, even if they aren't under your control:\n\n        import numpy\n        from preconvert import json\n\n\n        class Employee:\n\n            def __init__(self, first_name, last_name):\n                self.first_name = first_name\n                self.last_name = last_name\n\n            def __preconvert__(self):\n                return {'name': {'first': self.first_name, 'last': self.last_name}}\n\n\n        @preconvert.converter(numpy.integer)\n        def numpy_integer_to_python_int(numpy_int):\n            return int(numpy_int)\n\n\n        json.dumps({\n            'employee': Employee('Timothy', 'Crosley'),\n            'height_inches': numpy.int_(73)\n        })\n\n3. Enjoy a more comprehensive and configurable serializer!\n\n## Why?\n\nHave you ever tried to `json.dumps` a data structure, only to be surprised when your DataClass throws an exception, or your namedtuple outputs as a list?\nPreconvert was created to solve this problem across common serialization formats.\n\n\nBefore preconvert:\n\n```python\nimport sys\nimport json\nfrom dataclasses import dataclass\n\n\n@dataclass\nclass InventoryItem:\n    \"\"\"Class for keeping track of an item in inventory.\"\"\"\n    name: str\n    unit_price: float\n    quantity_on_hand: int = 0\n\n    def total_cost(self) -> float:\n        return self.unit_price * self.quantity_on_hand\n\n\nmy_store_inventory = [InventoryItem(\"beer\", unit_price=0.0, quantity_on_hand=sys.maxsize),  InventoryItem(\"bacon\", unit_price=2.5, quantity_on_hand=3)]\njson.dumps(my_store_inventory)\n\noutput >>>\n\n    177\n    178\n--> 179         raise TypeError(f'Object of type {o.__class__.__name__} '\n    180                         f'is not JSON serializable')\n    181\n\nTypeError: Object of type InventoryItem is not JSON serializable\n\nD:\n```\n\nAfter preconvert:\n\n```python\nimport sys\nimport json\nfrom preconvert.output import json\n\n\n@dataclass\nclass InventoryItem:\n    \"\"\"Class for keeping track of an item in inventory.\"\"\"\n    name: str\n    unit_price: float\n    quantity_on_hand: int = 0\n\n    def total_cost(self) -> float:\n        return self.unit_price * self.quantity_on_hand\n\n\nmy_store_inventory = [\n    InventoryItem(\"beer\", unit_price=0.0, quantity_on_hand=sys.maxsize),\n    InventoryItem(\"bacon\", unit_price=2.5, quantity_on_hand=3)\n]\njson.dumps(my_store_inventory)\n\n>>> [\n        {\n            \"name\": \"beer\",\n            \"unit_price\": 0.0,\n            \"quantity_on_hand\": 9223372036854775807\n        },\n        {\n            \"name\": \"bacon\",\n            \"unit_price\": 2.5,\n            \"quantity_on_hand\": 3\n        }\n    ]\n\n:D\n```\n\n## Design goals:\n\n- Easy utilization from existing projects\n- Enable conversion from complex to simple types independant of desired output format\n- Provide built in conversion for common types that are not universally supported (dataclasses, namedtuple, etc...)\n- Provide a way to build custom preconverts or override built-in preconverts\n- Ability to build preconverts that are dependent on the destination format\n- Minimal overhead when utilized with common serialization formats\n\n## How do I use this?\n\nIf your project uses one of our built-in supported serializers (json, msgpak, bson)\nyou can simply replace your existing serializer import with a preconvert one:\n\n`from preconvert.outputs import json`\n\nOR\n\n`from preconvert.outputs import simplejson as json`\n\nOR\n\n`from preconvert.outputs import msgpack`\n\nOR\n\n`from preconvert.outputs import bson`\n\nIf not you can inject preconvert before usage of any other serializers, often by setting a `default` or `on_onknown` parameter:\n\n```\nimport preconvert\nimport my_serializer\n\nmy_serializer.dumps(default=preconvert.default_serializable)\n```\n\n## How do I extend this?\n\nWant to add preconversion to your own custom types? For OOP projects, one easy way to do this is to add a `__preconvert__` method to your object:\n\n```python\nclass MyCustomClass(object):\n    def __init__(self, first_name, children=()):\n        self.first_name = first_name\n        self.children = children\n\n    def __jsonifiable__(self)\n        return {'first': self.first_name, 'children': children}\n```\n\nFor other entities, such as objects you do not control, you can register a new preconvert using the `preconvert.converter` decorator:\n\n```python\nimport preconvert\n\n\n@preconvert.converter(SomeFrameworkObject)\ndef convert_framework_object(instance):\n    return {'name': instance.name}\n```\n\nYou can also, optionally, specify preconversions per an intended serialization format:\n\n```python\nimport preconvert\n\n\n@preconvert.json(SomeFrameworkObject)\ndef convert_framework_object(instance):\n    return {'json': {'name': instance.name}}\n\n\n@preconvert.msgpack(SomeFrameworkObject)\ndef convert_framework_object(instance):\n    return ['name', instance.name]\n```\n\nFinally, you can resister any modules that contain converters to package 'preconvert.converters' entrypoints, and they will take effect automatically as long as the package that contains them is installed.\nSee the [preconvert_numpy](https://github.com/timothycrosley/preconvert_numpy/blob/master/pyproject.toml#L28) for an example of how this works.\n\n",
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