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Basic json usage with python

2016-07-30

Python: Json实例

JSON(JavaScript Object Notation) 是一种轻量级的数据交换格式。易于人阅读和编写。同时也易于机器解析和生成。

数据格式可以简单地理解为键值对的集合(A collection of name/value pairs)。不同的语言中,它被理解为对象(object),纪录(record),结构(struct),字典(dictionary),哈希表(hash table),有键列表(keyed list),或者关联数组 (associative array)。
值的有序列表(An ordered list of values)。在大部分语言中,它被理解为数组(array)。

import json

Pyhton的Json模块提供了把内存中的对象序列化的方法。

json.dumps

dump的功能就是把Python对象encode为json对象,一个编码过程。注意json模块提供了json.dumpsjson.dump方法,区别是dump直接到文件,而dumps到一个字符串,这里的s可以理解为string

data = [ { 'a':'A', 'b':(2, 4), 'c':3.0 } ]
print 'DATA:', repr(data)

data_string = json.dumps(data)
print 'JSON:', data_string
DATA: [{'a': 'A', 'c': 3.0, 'b': (2, 4)}]
JSON: [{"a": "A", "c": 3.0, "b": [2, 4]}]

查看其类型,发现是string对象。

print type(data)
print type(data_string)
<type 'list'>
<type 'str'>

json.dump

不仅可以把Python对象编码为string,还可以写入文件。因为我们不能把Python对象直接写入文件,这样会报错TypeError: expected a string or other character buffer object ,我们需要将其序列化之后才可以。

data = [ { 'a':'A', 'b':(2, 4), 'c':3.0 } ]
with open('output.json','w') as fp:
    json.dump(data,fp)
cat output.json
[{"a": "A", "c": 3.0, "b": [2, 4]}]

json.loads

Python内置对象dumpjson对象我们知道如何操作了,那如何从json对象decode解码为Python可以识别的对象呢?是的用json.loads方法,当然这个是基于string的,如果是文件,我们可以用json.load方法。

decoded_json = json.loads(data_string)
# 和之前一样,还是list
print type(decoded_json)
<type 'list'>
# 像访问 data = [ { 'a':'A', 'b':(2, 4), 'c':3.0 } ]一样
print decoded_json[0]['a']
A

json.load

可以直接load文件。

with open('output.json') as fp:
    print type(fp)
    loaded_json = json.load(fp)
<type 'file'>
# 和之前一样,还是list
print type(decoded_json)
<type 'list'>
# 像访问 data = [ { 'a':'A', 'b':(2, 4), 'c':3.0 } ]一样
print decoded_json[0]['a']
A

数据类型对应

jsonPython对象转换过程中,数据类型不完全一致,有对应。

Python Json
dict object
list,tuple array
str, unicode string
int,long,float number
True true
False false
None null

json.dumps常用参数

一些参数,可以让我们更好地控制输出。常见的比如sort_keysindentseparatorsskipkeys等。

sort_keys名字就很清楚了,输出时字典的是按键值排序的,而不是随机的。

data = [ { 'a':'A', 'b':(2, 4), 'c':3.0 } ]
print 'DATA:', repr(data)

unsorted = json.dumps(data)
print 'JSON:', json.dumps(data)
print 'SORT:', json.dumps(data, sort_keys=True)
DATA: [{'a': 'A', 'c': 3.0, 'b': (2, 4)}]
JSON: [{"a": "A", "c": 3.0, "b": [2, 4]}]
SORT: [{"a": "A", "b": [2, 4], "c": 3.0}]

indent就是更个缩进,让我们更好地看清结构。

data = [ { 'a':'A', 'b':(2, 4), 'c':3.0 } ]
print 'DATA:', repr(data)

print 'NORMAL:', json.dumps(data, sort_keys=True)
print 'INDENT:', json.dumps(data, sort_keys=True, indent=2)
DATA: [{'a': 'A', 'c': 3.0, 'b': (2, 4)}]
NORMAL: [{"a": "A", "b": [2, 4], "c": 3.0}]
INDENT: [
  {
    "a": "A", 
    "b": [
      2, 
      4
    ], 
    "c": 3.0
  }
]

separators是提供分隔符,可以出去白空格,输出更紧凑,数据更小。默认的分隔符是(', ', ': '),有白空格的。不同的dumps参数,对应文件大小一目了然。

data = [ { 'a':'A', 'b':(2, 4), 'c':3.0 } ]
print 'DATA:', repr(data)
print 'repr(data)             :', len(repr(data))
print 'dumps(data)            :', len(json.dumps(data))
print 'dumps(data, indent=2)  :', len(json.dumps(data, indent=2))
print 'dumps(data, separators):', len(json.dumps(data, separators=(',',':')))
DATA: [{'a': 'A', 'c': 3.0, 'b': (2, 4)}]
repr(data)             : 35
dumps(data)            : 35
dumps(data, indent=2)  : 76
dumps(data, separators): 29

json需要字典的的键是字符串,否则会抛出ValueError

data = [ { 'a':'A', 'b':(2, 4), 'c':3.0, ('d',):'D tuple' } ]

print 'First attempt'
try:
    print json.dumps(data)
except (TypeError, ValueError) as err:
    print 'ERROR:', err

print
print 'Second attempt'
print json.dumps(data, skipkeys=True)
First attempt
ERROR: keys must be a string

Second attempt
[{"a": "A", "c": 3.0, "b": [2, 4]}]

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