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204 lines
4.4 KiB
Markdown
204 lines
4.4 KiB
Markdown
# json 模块：处理 JSON 数据
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[JSON (JavaScript Object Notation)](http://json.org) 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。
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## JSON 基础
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`JSON` 的基础结构有两种：键值对 (`name/value pairs`) 和数组 (`array`)。
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`JSON` 具有以下形式：
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* `object` - 对象，用花括号表示，形式为（数据是无序的）：
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* `{ pair_1, pair_2, ..., pair_n }`
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* `pair` - 键值对，形式为：
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* `string : value`
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* `array` - 数组，用中括号表示，形式为（数据是有序的）：
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* `[value_1, value_2, ..., value_n ]`
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* `value` - 值，可以是
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* `string` 字符串
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* `number` 数字
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* `object` 对象
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* `array` 数组
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* `true / false / null` 特殊值
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* `string` 字符串
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例子：
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```py
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{
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"name": "echo",
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"age": 24,
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"coding skills": ["python", "matlab", "java", "c", "c++", "ruby", "scala"],
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"ages for school": {
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"primary school": 6,
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"middle school": 9,
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"high school": 15,
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"university": 18
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},
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"hobby": ["sports", "reading"],
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"married": false
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}
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```
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## JSON 与 Python 的转换
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假设我们已经将上面这个 `JSON` 对象写入了一个字符串：
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In [1]:
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```py
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import json
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from pprint import pprint
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info_string = """
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{
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"name": "echo",
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"age": 24,
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"coding skills": ["python", "matlab", "java", "c", "c++", "ruby", "scala"],
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"ages for school": {
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"primary school": 6,
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"middle school": 9,
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"high school": 15,
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"university": 18
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},
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"hobby": ["sports", "reading"],
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"married": false
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}
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"""
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```
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我们可以用 `json.loads()` (load string) 方法从字符串中读取 `JSON` 数据：
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In [2]:
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```py
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info = json.loads(info_string)
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pprint(info)
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```
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```py
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{u'age': 24,
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u'ages for school': {u'high school': 15,
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u'middle school': 9,
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u'primary school': 6,
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u'university': 18},
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u'coding skills': [u'python',
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u'matlab',
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u'java',
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u'c',
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u'c++',
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u'ruby',
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u'scala'],
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u'hobby': [u'sports', u'reading'],
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u'married': False,
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u'name': u'echo'}
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```
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此时，我们将原来的 `JSON` 数据变成了一个 `Python` 对象，在我们的例子中这个对象是个字典（也可能是别的类型，比如列表）：
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In [3]:
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```py
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type(info)
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```
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Out[3]:
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```py
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dict
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```
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可以使用 `json.dumps()` 将一个 `Python` 对象变成 `JSON` 对象：
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In [4]:
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```py
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info_json = json.dumps(info)
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print info_json
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```
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```py
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{"name": "echo", "age": 24, "married": false, "ages for school": {"middle school": 9, "university": 18, "high school": 15, "primary school": 6}, "coding skills": ["python", "matlab", "java", "c", "c++", "ruby", "scala"], "hobby": ["sports", "reading"]}
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```
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从中我们可以看到，生成的 `JSON` 字符串中，数组的元素顺序是不变的（始终是 `["python", "matlab", "java", "c", "c++", "ruby", "scala"]`），而对象的元素顺序是不确定的。
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## 生成和读取 JSON 文件
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与 `pickle` 类似，我们可以直接从文件中读取 `JSON` 数据，也可以将对象保存为 `JSON` 格式。
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* `json.dump(obj, file)` 将对象保存为 JSON 格式的文件
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* `json.load(file)` 从 JSON 文件中读取数据
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In [5]:
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```py
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with open("info.json", "w") as f:
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json.dump(info, f)
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```
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可以查看 `info.json` 的内容：
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In [6]:
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```py
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with open("info.json") as f:
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print f.read()
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```
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```py
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{"name": "echo", "age": 24, "married": false, "ages for school": {"middle school": 9, "university": 18, "high school": 15, "primary school": 6}, "coding skills": ["python", "matlab", "java", "c", "c++", "ruby", "scala"], "hobby": ["sports", "reading"]}
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```
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从文件中读取数据：
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In [7]:
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```py
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with open("info.json") as f:
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info_from_file = json.load(f)
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pprint(info_from_file)
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```
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```py
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{u'age': 24,
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u'ages for school': {u'high school': 15,
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u'middle school': 9,
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u'primary school': 6,
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u'university': 18},
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u'coding skills': [u'python',
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u'matlab',
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u'java',
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u'c',
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u'c++',
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u'ruby',
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u'scala'],
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u'hobby': [u'sports', u'reading'],
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u'married': False,
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u'name': u'echo'}
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```
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删除生成的文件：
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In [8]:
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```py
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import os
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os.remove("info.json")
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``` |