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深入解析Python编程中JSON模块的使用

Jun 06, 2016 am 11:14 AM
json python

JSON编码支持的基本数据类型为 None , bool , int , float 和 str , 以及包含这些类型数据的lists,tuples和dictionaries。 对于dictionaries,keys需要是字符串类型(字典中任何非字符串类型的key在编码时会先转换为字符串)。 为了遵循JSON规范,你应该只编码Python的lists和dictionaries。 而且,在web应用程序中,顶层对象被编码为一个字典是一个标准做法。

JSON编码的格式对于Python语法而已几乎是完全一样的,除了一些小的差异之外。 比如,True会被映射为true,False被映射为false,而None会被映射为null。 下面是一个例子,演示了编码后的字符串效果:

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>>> json.dumps(False)

'false'

>>> d = {'a': True,

...   'b': 'Hello',

...   'c': None}

>>> json.dumps(d)

'{"b": "Hello", "c": null, "a": true}'

>>>

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如果你试着去检查JSON解码后的数据,你通常很难通过简单的打印来确定它的结构, 特别是当数据的嵌套结构层次很深或者包含大量的字段时。 为了解决这个问题,可以考虑使用pprint模块的 pprint() 函数来代替普通的 print() 函数。 它会按照key的字母顺序并以一种更加美观的方式输出。 下面是一个演示如何漂亮的打印输出Twitter上搜索结果的例子:

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>>> from urllib.request import urlopen

>>> import json

>>> u = urlopen('http://search.twitter.com/search.json?q=python&rpp=5')

>>> resp = json.loads(u.read().decode('utf-8'))

>>> from pprint import pprint

>>> pprint(resp)

{'completed_in': 0.074,

'max_id': 264043230692245504,

'max_id_str': '264043230692245504',

'next_page': '?page=2&max_id=264043230692245504&q=python&rpp=5',

'page': 1,

'query': 'python',

'refresh_url': '?since_id=264043230692245504&q=python',

'results': [{'created_at': 'Thu, 01 Nov 2012 16:36:26 +0000',

      'from_user': ...

      },

      {'created_at': 'Thu, 01 Nov 2012 16:36:14 +0000',

      'from_user': ...

      },

      {'created_at': 'Thu, 01 Nov 2012 16:36:13 +0000',

      'from_user': ...

      },

      {'created_at': 'Thu, 01 Nov 2012 16:36:07 +0000',

      'from_user': ...

      }

      {'created_at': 'Thu, 01 Nov 2012 16:36:04 +0000',

      'from_user': ...

      }],

'results_per_page': 5,

'since_id': 0,

'since_id_str': '0'}

>>>

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一般来讲,JSON解码会根据提供的数据创建dicts或lists。 如果你想要创建其他类型的对象,可以给 json.loads() 传递object_pairs_hook或object_hook参数。 例如,下面是演示如何解码JSON数据并在一个OrderedDict中保留其顺序的例子:

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>>> s = '{"name": "ACME", "shares": 50, "price": 490.1}'

>>> from collections import OrderedDict

>>> data = json.loads(s, object_pairs_hook=OrderedDict)

>>> data

OrderedDict([('name', 'ACME'), ('shares', 50), ('price', 490.1)])

>>>

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下面是如何将一个JSON字典转换为一个Python对象例子:

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>>> class JSONObject:

...   def __init__(self, d):

...     self.__dict__ = d

...

>>>

>>> data = json.loads(s, object_hook=JSONObject)

>>> data.name

'ACME'

>>> data.shares

50

>>> data.price

490.1

>>>

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最后一个例子中,JSON解码后的字典作为一个单个参数传递给 __init__() 。 然后,你就可以随心所欲的使用它了,比如作为一个实例字典来直接使用它。

在编码JSON的时候,还有一些选项很有用。 如果你想获得漂亮的格式化字符串后输出,可以使用 json.dumps() 的indent参数。 它会使得输出和pprint()函数效果类似。比如:

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>>> print(json.dumps(data))

{"price": 542.23, "name": "ACME", "shares": 100}

>>> print(json.dumps(data, indent=4))

{

  "price": 542.23,

  "name": "ACME",

  "shares": 100

}

>>>

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对象实例通常并不是JSON可序列化的。例如:

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>>> class Point:

...   def __init__(self, x, y):

...     self.x = x

...     self.y = y

...

>>> p = Point(2, 3)

>>> json.dumps(p)

Traceback (most recent call last):

  File "<stdin>", line 1, in <module>

  File "/usr/local/lib/python3.3/json/__init__.py", line 226, in dumps

    return _default_encoder.encode(obj)

  File "/usr/local/lib/python3.3/json/encoder.py", line 187, in encode

    chunks = self.iterencode(o, _one_shot=True)

  File "/usr/local/lib/python3.3/json/encoder.py", line 245, in iterencode

    return _iterencode(o, 0)

  File "/usr/local/lib/python3.3/json/encoder.py", line 169, in default

    raise TypeError(repr(o) + " is not JSON serializable")

TypeError: <__main__.Point object at 0x1006f2650> is not JSON serializable

>>>

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如果你想序列化对象实例,你可以提供一个函数,它的输入是一个实例,返回一个可序列化的字典。例如:

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def serialize_instance(obj):

  d = { '__classname__' : type(obj).__name__ }

  d.update(vars(obj))

  return d

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如果你想反过来获取这个实例,可以这样做:

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# Dictionary mapping names to known classes

classes = {

  'Point' : Point

}

 

def unserialize_object(d):

  clsname = d.pop('__classname__', None)

  if clsname:

    cls = classes[clsname]

    obj = cls.__new__(cls) # Make instance without calling __init__

    for key, value in d.items():

      setattr(obj, key, value)

      return obj

  else:

    return d

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下面是如何使用这些函数的例子:

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>>> p = Point(2,3)

>>> s = json.dumps(p, default=serialize_instance)

>>> s

'{"__classname__": "Point", "y": 3, "x": 2}'

>>> a = json.loads(s, object_hook=unserialize_object)

>>> a

<__main__.Point object at 0x1017577d0>

>>> a.x

2

>>> a.y

3

>>>

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json 模块还有很多其他选项来控制更低级别的数字、特殊值如NaN等的解析。 可以参考官方文档获取更多细节。

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