Python处理列表套字典结构JSON数据的三种方式对比

[
  {"id": 1, "name": "Alice", "age": 25, "active": true},
  {"id": 2, "name": "Bob", "age": 30, "active": false},
  {"id": 3, "name": "Charlie", "age": 28, "active": true}
]

import json

# 1. 读取 JSON 文件（列表套字典结构，解析后是 Python 列表）
with open("users.json", "r", encoding="utf-8") as f:
    data_list = json.load(f)  # data_list 是一个包含字典的列表

# 2. 遍历列表，查找目标字典并修改值
for item in data_list:
    # 假设通过 "id" 定位目标字典（可根据实际条件调整）
    if item.get("id") == 2:  # 找到 id=2 的字典
        item["age"] = 31  # 修改 age 的值
        item["active"] = True  # 修改 active 的值
        break  # 找到后退出循环，提高效率

# 3. 将修改后的列表写回 JSON 文件
with open("users.json", "w", encoding="utf-8") as f:
    json.dump(data_list, f, indent=2, ensure_ascii=False)

import json

# 1. 读取数据并构建索引字典（以id为键）
with open("users.json", "r", encoding="utf-8") as f:
    data_list = json.load(f)

# 构建映射：{id: 对应的字典}
id_to_item = {item["id"]: item for item in data_list}

# 2. 直接通过id查找并修改（无需遍历）
target_id = 2
if target_id in id_to_item:
    id_to_item[target_id]["age"] = 31
    id_to_item[target_id]["active"] = True

# 3. 写回文件（原列表已被修改，因为字典是引用类型）
with open("users.json", "w", encoding="utf-8") as f:
    json.dump(data_list, f, indent=2, ensure_ascii=False)

import json

with open("users.json", "r", encoding="utf-8") as f:
    data_list = json.load(f)

# 用生成器表达式查找第一个符合条件的字典（找到即停止）
target = next((item for item in data_list if item["id"] == 2), None)
if target:
    target["age"] = 31
    target["active"] = True

with open("users.json", "w", encoding="utf-8") as f:
    json.dump(data_list, f, indent=2, ensure_ascii=False)

import json
import pandas as pd

# 1. 读取JSON并转为DataFrame
with open("users.json", "r", encoding="utf-8") as f:
    data_list = json.load(f)
df = pd.DataFrame(data_list)

# 2. 定位并修改（通过条件筛选）
df.loc[df["id"] == 2, ["age", "active"]] = [31, True]

# 3. 转回列表并写回文件
updated_list = df.to_dict("records")  # 转为列表套字典
with open("users.json", "w", encoding="utf-8") as f:
    json.dump(updated_list, f, indent=2, ensure_ascii=False)