一文带你搞懂Python如何解读JSON文件

{
    "sites": [
    { "name":"maybe" , "url":"www.maybe.com" }, 
    { "name":"google" , "url":"www.google.com" }
    ]
}

{
    "number_1" : 20,
    "number_2" : -21.5,
    "number_3" : 1.0E+1
}  

{
    "author": {
        "name": "C",
        "description": "C语言"
    }
}

{
    "course" : [
        "JSON",
        "CSS",
        {
            "ok" : "well",
            "how" : "fine"
        },
        [
            3.1,
            fasle
        ],
        null
    ]
}

{
    "employee": {
        "name": "John Doe",
        "age": 35,
        "department": {
            "name": "Engineering",
            "location": "Building A"
        }
    }
}

import json

# 读取 JSON 数据
with open('data/data.json', 'r') as f:
    json_data = f.read()

# 解析 JSON 数据
data = json.loads(json_data)
print(type(data))  # dict

for key, value in data.items():  # 遍历第一层
    print(f"Key: {key}, Value: {value}")
    # 如果值是字典，继续遍历第二层
    if isinstance(value, dict):
        for sub_key, sub_value in value.items():  # 遍历第二层
            print(f"  Sub-key: {sub_key}, Sub-value: {sub_value}")
            # 如果第二层的值还是字典，进一步处理
            if isinstance(sub_value, dict):
                for deep_key, deep_value in sub_value.items():
                    print(f"    Deep-key: {deep_key}, Deep-value: {deep_value}")

import pandas as pd

path = 'data/data.json'

# 1. 打开并读取 JSON 文件
df = pd.read_json(path)
print(type(df))  # DataFrame

# 2. 按行解析 JSON 数据
x = df.to_dict(orient='records')
print(type(x))  # list ，其中每个元素是一个字典

# 3. 按列解析 JSON 数据
y = df.to_dict(orient='list')
print(type(y))  # dict 类型，其中每个键的值是列表

# 4. 扁平化嵌套的 JSON 数据
x_normalized = pd.json_normalize(x)
print(x_normalized)

# 5. 将 DataFrame 转换为 JSON 格式
json_data = df.to_json()
print(json_data)

# 6. 将 DataFrame 写入 JSON 文件
df.to_json('output.json')