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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:

>>> 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:

>>> 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:

>>> 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:

>>> 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:

>>> 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:

>>> 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:

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:

# 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:

>>> 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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