Comprehensive Guide to JSON Operations in Python

Basic Operations

Convert a Python dictionary to a JSON string, parse a JSON string back to a Python object, write a Python object to a JSON file, and read a JSON file into a Python object.

import json
# Python dictionary
data = {
    'name': '张三',
    'age': 30,
    'city': '北京'
}
json_string = json.dumps(data, ensure_ascii=False)
print("Python对象转换为JSON字符串:")
print(json_string)

# JSON string
json_string = '{"name": "李四", "age": 35, "city": "上海"}'
# Parse JSON string
import json
data = json.loads(json_string)
print("JSON字符串解析为Python对象:")
print(data)

# Write to file
with open('data.json', 'w', encoding='utf-8') as f:
    json.dump(data, f, ensure_ascii=False)
print("已将Python对象写入JSON文件")

# Read from file
with open('data.json', 'r', encoding='utf-8') as f:
    data = json.load(f)
print("已从JSON文件读取Python对象:")
print(data)

Data Manipulation

Modify, merge, add, or delete entries in JSON files.

# Modify JSON file data
with open('data.json', 'r', encoding='utf-8') as f:
    data = json.load(f)
data['age'] = 45
with open('data.json', 'w', encoding='utf-8') as f:
    json.dump(data, f, ensure_ascii=False)
print("已修改JSON文件中的数据并保存")

# Merge two JSON files
with open('file1.json', 'r', encoding='utf-8') as f:
    data1 = json.load(f)
with open('file2.json', 'r', encoding='utf-8') as f:
    data2 = json.load(f)
combined_data = {**data1, **data2}
with open('combined.json', 'w', encoding='utf-8') as f:
    json.dump(combined_data, f, ensure_ascii=False)
print("已合并两个JSON文件并保存")

# Add new key-value pair
with open('data.json', 'r', encoding='utf-8') as f:
    data = json.load(f)
data['职业'] = '工程师'
with open('data.json', 'w', encoding='utf-8') as f:
    json.dump(data, f, ensure_ascii=False)
print("已添加新键值对并保存")

# Delete a key-value pair
with open('data.json', 'r', encoding='utf-8') as f:
    data = json.load(f)
del data['city']
with open('data.json', 'w', encoding='utf-8') as f:
    json.dump(data, f, ensure_ascii=False)
print("已删除键值对并保存")

Advanced Operations

Pretty‑print JSON, handle nested structures, and serialize complex objects with a custom default function.

# Pretty‑print JSON
data = {'name': '赵六', 'age': 28, 'city': '深圳'}
json_string = json.dumps(data, indent=4, ensure_ascii=False)
print("格式化输出JSON字符串:")
print(json_string)

# Nested JSON conversion
nested_data = {'name': '钱七', 'details': {'age': 32, 'city': '杭州'}}
json_string = json.dumps(nested_data, ensure_ascii=False)
print("嵌套JSON结构转换为JSON字符串:")
print(json_string)

# Parse nested JSON
json_string = '{"name": "孙八", "details": {"age": 36, "city": "南京"}}'
data = json.loads(json_string)
print("访问嵌套的数据:")
print(data['details']['city'])

# Custom default for complex objects
from datetime import datetime
complex_data = {'name': '周九', 'registered': datetime.now()}
def default(o):
    if isinstance(o, datetime):
        return o.isoformat()
json_string = json.dumps(complex_data, default=default, ensure_ascii=False)
print("处理复杂对象并转换为JSON字符串:")
print(json_string)

File and Directory Operations

Batch‑process JSON files in a directory and create backup copies.

import os, json
json_files = [f for f in os.listdir() if f.endswith('.json')]
for file in json_files:
    with open(file, 'r', encoding='utf-8') as f:
        data = json.load(f)
        print(f"已处理文件 {file}")

import shutil
shutil.copy('data.json', 'data_backup.json')
print("已创建备份文件")

Performance Optimization

Use the ultra‑fast ujson library for serialization and deserialization.

import ujson
data = {'name': '吴十', 'age': 42, 'city': '成都'}
json_string = ujson.dumps(data, ensure_ascii=False)
data_back = ujson.loads(json_string)
print("使用ujson库提高性能:")
print(data_back)

Special Uses

Fetch JSON data from a REST API and post JSON data to an API endpoint.

import requests
# GET request
response = requests.get('https://api.example.com/data')
if response.status_code == 200:
    data = response.json()
    print("从API获取JSON数据成功:")
    print(data)
else:
    print("请求失败")

# POST request
payload = {'name': '郑十一', 'age': 38, 'city': '武汉'}
resp = requests.post('https://api.example.com/data', json=payload)
if resp.status_code == 200:
    print("已将JSON数据写入API")
else:
    print("请求失败")

Data Analysis and Aggregation

Combine data from multiple JSON files into a single aggregated file.

import os, json
json_files = [f for f in os.listdir() if f.endswith('.json')]
aggregated_data = {}
for file in json_files:
    with open(file, 'r', encoding='utf-8') as f:
        data = json.load(f)
        aggregated_data.update(data)
with open('aggregated_data.json', 'w', encoding='utf-8') as f:
    json.dump(aggregated_data, f, ensure_ascii=False)
print("已聚合多个JSON文件的数据并保存")

Error Handling

Catch and report JSON decoding errors gracefully.

import json
json_string = '{"name": "王十二", "age": "not a number", "city": "重庆"}'
try:
    data = json.loads(json_string)
except json.JSONDecodeError as e:
    print(f"JSON解析错误: {e}")
else:
    print("JSON解析成功:")
    print(data)

Special Format Handling

Read JSON files that contain comments using the jsoncomment library.

import jsoncomment
with open('data_with_comments.json', 'r', encoding='utf-8') as f:
    data = jsoncomment.JsonComment().loads(f.read())
print("已读取带注释的JSON文件:")
print(data)

These scripts cover a wide range of JSON processing tasks, from fundamental conversions to advanced handling, suitable for many real‑world Python applications.