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。
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</code>进行转义
代码语言:python
代码运行次数:0
复制
Cloud Studio 代码运行
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:
代码语言:python
代码运行次数:0
复制
Cloud Studio 代码运行
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。
代码语言:python
代码运行次数:0
复制
Cloud Studio 代码运行
# 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:
代码语言:python
代码运行次数:0
复制
Cloud Studio 代码运行
"""
/*
- 提示:该行代码过长,系统自动注释不进行高亮。一键复制会移除系统注释
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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。