Chapter 21 深入理解JSON

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前言

在当今数据驱动的世界中，JSON（JavaScript Object Notation）作为一种轻量级的数据交换格式，得到了广泛的应用。本章详细讲解了JSON数据格式的基本概念、JSON格式的数据转化以及推荐一些实用的在线工具来帮助用户格式化JSON数据。

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本篇文章参考：黑马程序员

一、JSON数据格式

1. 什么是JSON？

JSON是一种轻量级的数据交互格式，采用完全独立于编程语言的文本格式来存储和表示数据，本质上是一个带有特定格式的字符串。JSON负责不同编程语言中的数据传递和交互，类似国际通用语言中的英语。
各种编程语言存储数据的容器不尽相同，在Python中有字典dict这样的数据类型，而其它语言可能没有对应的字典。为了让不同的语言都能够相互通用的互相传递数据，JSON就是一种非常良好的中转数据格式。如下图，以Python和C语言互传数据为例：

2. JSON数据的格式

①基本结构
JSON是一个键值对（key/value）的集合。

• 键：必须是字符串类型
• 值：可以是字符串、数字、布尔值、数组、对象（即嵌套的键值对集合）以及null

②格式规范

• 必须以开头的{或[开始，并以对应的 } 或 ] 结尾
• 所有的键名必须是双引号括起来的字符串
• 数组和对象中的元素或成员之间用逗号 , 分隔，最后一个元素或成员后面可以有或没有逗号，但建议不加，以保持一致性。

# 写法一：
[{"name":"小明","age":11},{"name":"小红","age":15},{"name":"小玉","age":17}]
# 写法二:
{"name":"小菲","address":"北京"}

二、JSON格式数据转化

①序列化
使用json.dumps()函数可以将Python对象序列化为JSON格式的字符串。

# 导入JSON模块
import json# 准备符合json格式要求的python数据
data=[{"name":"小明","age":11},{"name":"小红","age":15},{"name":"小玉","age":17}]
# 通过 json.dumps(data) 方法把python数据转化为了json数据
json_str=json.dumps(data)
print(type(json_str))
print(json_str)

输出结果：
<class ‘str’>
[{“name”: “\u5c0f\u660e”, “age”: 11}, {“name”: “\u5c0f\u7ea2”, “age”: 15}, {“name”: “\u5c0f\u7389”, “age”: 17}]

如果有中文可以带上ensure_ascii=False参数来确保中文的正常转换。

# 导入JSON模块
import json# 准备符合json格式要求的python数据
data=[{"name":"小明","age":11},{"name":"小红","age":15},{"name":"小玉","age":17}]
# 通过 json.dumps(data) 方法把python数据转化为了json数据
json_str=json.dumps(data,ensure_ascii=False)
print(type(json_str))
print(json_str)# 准备符合json格式要求的python数据
data2={"name":"小菲","address":"北京"}
json_str2=json.dumps(data2,ensure_ascii=False)
print(type(json_str2))
print(json_str2)

输出结果：
<class ‘str’>
[{“name”: “小明”, “age”: 11}, {“name”: “小红”, “age”: 15}, {“name”: “小玉”, “age”: 17}]
<class ‘str’>
{“name”: “小菲”, “address”: “北京”}

②反序列化
使用json.loads()函数可以将JSON格式的字符串反序列化为Python对象。

# 导入JSON模块
import json
# 通过 json.loads(data)方法把json数据转化为了 python数据
s1='[{"name":"小明","age":11},{"name":"小红","age":15},{"name":"小玉","age":17}]'
l1=json.loads(s1)
print(type(l1))
print(l1)s2='{"name":"小菲","address":"北京"}'
l2=json.loads(s2)
print(type(l2))
print(l2)

输出结果：
[{‘name’: ‘小明’, ‘age’: 11}, {‘name’: ‘小红’, ‘age’: 15}, {‘name’: ‘小玉’, ‘age’: 17}]
<class ‘dict’>
{‘name’: ‘小菲’, ‘address’: ‘北京’}

问题：在编写代码的过程中我们会发现如下图那样编写会报错。

出现错误的原因是双重引号的使用问题。在Python中使用双引号"来定义字符串时，如果字符串中又包含了双引号"，则会导致Python解析字符串时出现混淆，无法正确解析字符串的边界和内容，从而引发语法错误。

解决方案：

• 转义内部双引号：
  在字符串中的双引号"前面加上反斜杠\进行转义

s1 = "[{\"name\":\"小明\",\"age\":11},{\"name\":\"小红\",\"age\":15},{\"name\":\"小玉\",\"age\":17}]"

• 使用单引号包裹外部字符串：

s1 = '[{"name":"小明","age":11},{"name":"小红","age":15},{"name":"小玉","age":17}]'

【例题】
以下为一个不符合规范的JSON文件，请通过代码取出其日期数据。

# 导包
import json# 处理数据
f_us=open("D:/美国.txt","r",encoding="UTF-8")
# 读取美国的全部内容
us_data=f_us.read()
# 去掉不合JSON规范的开头
us_data=us_data.replace("jsonp_1629344292311_69436(","")
# 去掉不合JSON规范的结尾
us_data=us_data[:-2]
# JSON转python字典
us_dict=json.loads(us_data)
# 获取trend key
trend_data=us_dict["data"][0]["trend"]
# 获取日期数据
date=trend_data["updateDate"]
print(date)

输出结果：
[‘2.22’, ‘2.23’, ‘2.24’, ‘2.25’, ‘2.26’]

三、格式化JSON数据的在线工具

虽然JSON格式清晰易懂，但当数据量大或嵌套层次深时，手动阅读和编辑JSON数据可能会变得非常困难。在这种情况下，格式化工具显得尤为重要。
JSON格式化就是将原本难以阅读的JSON字符串转换为更具可读性的结构，便于我们理解数据的层次和关系，通常通过添加适当的缩进和换行来完成。

例如：
准备一段复杂的JSON数据：

"""
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"""

①JSONLint
JSONLint网站：https://jsonlint.com/

格式化后的数据：

②JSON Formatter & Validator
JSON Formatter & Validator网站：https://jsonformatter.curiousconcept.com/#

格式化后的数据：

③JSON Editor Online
JSON Editor Online网站：https://jsoneditoronline.org/#left=local.hejeki

格式化后的数据：

④ab173
ab173网站：http://www.ab173.com
该网站提供了快速查看和格式化 JSON 数据的在线工具。用户可以将 JSON 数据粘贴到网站上，以便查看其结构、格式化和调试，帮助用户浏览复杂的 JSON 数据，以理解其层级和内容。

粘贴标准的 JSON 数据并点击格式化。

格式化后的JSON数据：

点击左上角的视图，在视图界面中我们可以折叠和展开格式化后的 JSON 数据，便于查看更深层的数据结构。