Python JSON案例如何解析JSON数据

wen python案例 2026-06-30 243

本文目录导读：

JSON 基础解析
嵌套JSON解析
高级解析技巧
错误处理
实际应用案例

我来详细介绍Python中解析JSON数据的各种方法和案例。

JSON 基础解析

1 从字符串解析JSON

import json
# JSON字符串
json_str = '{"name": "张三", "age": 25, "city": "北京"}'
# 解析JSON字符串为Python字典
data = json.loads(json_str)
print(data)
print(type(data))  # <class 'dict'>
print(data['name'])  # 张三

2 从文件读取JSON

import json
# 方式1：使用json.load()
with open('data.json', 'r', encoding='utf-8') as f:
    data = json.load(f)
    print(data)
# 方式2：先读取字符串再解析
with open('data.json', 'r', encoding='utf-8') as f:
    content = f.read()
    data = json.loads(content)
    print(data)

3 JSON数组解析

import json
# JSON数组
json_array = '[{"name": "张三", "age": 25}, {"name": "李四", "age": 30}]'
# 解析为Python列表
users = json.loads(json_array)
print(type(users))  # <class 'list'>
for user in users:
    print(f"姓名: {user['name']}, 年龄: {user['age']}")

嵌套JSON解析

1 处理复杂嵌套结构

import json
# 嵌套的JSON结构
complex_json = '''
{
    "company": "ABC科技",
    "employees": [
        {
            "id": 1,
            "name": "张三",
            "department": "开发部",
            "skills": ["Python", "Java", "SQL"],
            "contact": {
                "email": "zhangsan@email.com",
                "phone": "13800138001"
            }
        },
        {
            "id": 2,
            "name": "李四",
            "department": "运维部",
            "skills": ["Docker", "Kubernetes", "Linux"],
            "contact": {
                "email": "lisi@email.com",
                "phone": "13800138002"
            }
        }
    ],
    "departments": ["开发部", "运维部", "测试部"]
}
'''
data = json.loads(complex_json)
# 解析嵌套数据
company = data['company']
print(f"公司名称: {company}")
for emp in data['employees']:
    print(f"\n员工信息:")
    print(f"  姓名: {emp['name']}")
    print(f"  部门: {emp['department']}")
    print(f"  技能: {', '.join(emp['skills'])}")
    print(f"  邮箱: {emp['contact']['email']}")

高级解析技巧

1 使用自定义解码器

import json
from datetime import datetime
class CustomDecoder(json.JSONDecoder):
    def decode(self, s):
        # 自定义解码逻辑
        result = super().decode(s)
        return self.convert_dates(result)
    def convert_dates(self, obj):
        if isinstance(obj, dict):
            for key, value in obj.items():
                if key == 'date' and isinstance(value, str):
                    obj[key] = datetime.strptime(value, '%Y-%m-%d')
                else:
                    obj[key] = self.convert_dates(value)
        return obj
# 测试
json_str = '{"event": "会议", "date": "2024-01-15"}'
data = json.loads(json_str, cls=CustomDecoder)
print(data)  # {'event': '会议', 'date': datetime.datetime(2024, 1, 15, 0, 0)}

2 使用object_hook进行转换

import json
from collections import namedtuple
def json_to_object(data):
    """将JSON字典转换为命名元组"""
    return namedtuple('Object', data.keys())(*data.values())
# 使用object_hook参数
json_str = '{"name": "张三", "age": 25, "city": "北京"}'
data = json.loads(json_str, object_hook=json_to_object)
print(data.name)  # 张三
print(data.age)   # 25

错误处理

1 处理解析异常

import json
def safe_json_parse(json_string):
    """安全解析JSON字符串"""
    try:
        data = json.loads(json_string)
        return data, None
    except json.JSONDecodeError as e:
        return None, f"JSON解析错误: {e}"
    except Exception as e:
        return None, f"未知错误: {e}"
# 测试
test_jsons = [
    '{"name": "张三"}',  # 有效JSON
    '{"name": "张三"',   # 无效JSON
    '{"age": "25"}',      # 有效JSON
]
for test in test_jsons:
    data, error = safe_json_parse(test)
    if error:
        print(f"错误: {error}")
    else:
        print(f"成功解析: {data}")

2 验证JSON格式

import json
def validate_json(json_string):
    """验证JSON格式是否有效"""
    try:
        json.loads(json_string)
        return True
    except json.JSONDecodeError:
        return False
# 使用示例
json_data = '{"name": "测试"}'
print(f"JSON格式有效: {validate_json(json_data)}")
bad_json = '{name: "测试"}'
print(f"JSON格式有效: {validate_json(bad_json)}")

实际应用案例

1 API响应解析

import json
import requests  # 需要安装：pip install requests
def parse_api_response():
    """解析API响应数据"""
    # 模拟API响应
    api_response = '''
    {
        "status": "success",
        "code": 200,
        "data": {
            "total": 2,
            "items": [
                {"id": 1, "title": "文章1", "views": 100},
                {"id": 2, "title": "文章2", "views": 200}
            ]
        },
        "message": "请求成功"
    }
    '''
    response = json.loads(api_response)
    # 检查状态
    if response['status'] == 'success' and response['code'] == 200:
        articles = response['data']['items']
        total = response['data']['total']
        print(f"共 {total} 篇文章:")
        for article in articles:
            print(f"  ID: {article['id']}, 标题: {article['title']}, 浏览: {article['views']}")
    else:
        print(f"请求失败: {response['message']}")
parse_api_response()

2 配置文件解析

import json
import os
def load_config(config_file='config.json'):
    """加载配置文件"""
    default_config = {
        "database": {
            "host": "localhost",
            "port": 3306,
            "username": "root",
            "password": ""
        },
        "app": {
            "debug": True,
            "port": 8000
        }
    }
    try:
        if os.path.exists(config_file):
            with open(config_file, 'r', encoding='utf-8') as f:
                config = json.load(f)
                # 合并默认配置
                for key in default_config:
                    if key not in config:
                        config[key] = default_config[key]
                return config
        else:
            print(f"配置文件 {config_file} 不存在，使用默认配置")
            return default_config
    except json.JSONDecodeError as e:
        print(f"配置文件格式错误: {e}")
        return default_config
# 使用示例
config = load_config()
print(config['database']['host'])  # localhost

这些案例涵盖了Python中JSON解析的各种实际应用场景，根据你的具体需求,可以选择合适的解析方式。

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