python - 通过 python 代码附加 JSON 文件

Question

我正在尝试创建一个函数，将数据追加到 json 文件中，然后使用已经存在的相同缩进。我创建了如下所示的 json 文件。

{
    "TableA":
        [
            {"ID": "10001", "Name": "Chandan","Age": "29"},
            {"ID": "10002", "Name": "Rajesh", "Age": "24"},
            {"ID": "10003", "Name": "Raju", "Age": "25"}
        ]
}

Python 代码:

import json

# Write Data on Json file
a_dict = {"ID": "10005", "Name": "Manoj","Age": "31"}
try:
    with open('TableA.json', 'a') as f:
        json_obj = json.dump(a_dict, json.load(f),ensure_ascii=False)
        f.write(json_obj)
        f.close()
except IOError as io:
    print "ERROR: ", io


# Read data from Json File
with open('TableA.json') as data_file:    
    data = json.load(data_file)

for i in data["TableA"]:
    print "ID: \t", i["ID"]
    print "Name: \t", i["Name"]
    print "Age: \t", i["Age"]

Answer 1

我做了一些更改以获得正确的输出。如果有人帮助我优化代码，请为此提供帮助。

import json

# Write Data
a_dict = {}
try:
    with open('TableA.json') as data_file:    
        data = json.load(data_file)
        temp_list = []
        for dicObj in data["TableA"]:
            temp_list.append(dicObj)
        temp_list.append({"ID": "10006", "Name": "Ritesh","Age": "21"})
        data["TableA"] = temp_list
        a_dict["TableA"] = data["TableA"]
        with open('TableA.json','w') as f:
            f.write(json.dumps(a_dict, indent=4, sort_keys=True, encoding="utf-8"))
except IOError as io:
    print "ERROR: ", io

# Read data from Json File
with open('TableA.json') as data_file:    
    data = json.load(data_file)

for i in data["TableA"]:
    print "ID: \t", i["ID"]
    print "Name: \t", i["Name"]
    print "Age: \t", i["Age"]

输出:

 {
    "TableA": [
        {
            "Age": "29", 
            "ID": "10001", 
            "Name": "Chandan"
        }, 
        {
            "Age": "24", 
            "ID": "10002", 
            "Name": "Rajesh"
        }, 
        {
            "Age": "25", 
            "ID": "10003", 
            "Name": "Raju"
        }, 
        {
            "Age": "31", 
            "ID": "10005", 
            "Name": "Manoj"
        }, 
        {
            "Age": "21", 
            "ID": "10004", 
            "Name": "Ritesh"
        }, 
        {
            "Age": "21", 
            "ID": "10006", 
            "Name": "Ritesh"
        }
    ]
}