Python JSON Handling Examples for API Automation

Example 1: Convert JSON string to Python dict

import json
json_str = '{"name": "张三", "age": 25, "city": "北京"}'
data_dict = json.loads(json_str)
print(data_dict)  # Output: {'name': '张三', 'age': 25, 'city': '北京'}

Example 2: Convert Python dict to JSON string

data_dict = {"username": "testuser", "password": "123456"}
json_output = json.dumps(data_dict, ensure_ascii=False)
print(json_output)  # Output: {"username": "testuser", "password": "123456"}

Example 3: Read JSON file content

import json
with open('testdata.json', 'r', encoding='utf-8') as f:
    data = json.load(f)
print(data)  # Output the JSON content from the file

Example 4: Write data to a JSON file

import json
result_data = {"status": "success", "code": 200, "data": {"id": 100}}
with open('result.json', 'w', encoding='utf-8') as f:
    json.dump(result_data, f, ensure_ascii=False, indent=4)
# result.json is created with formatted content

Example 5: Extract a nested field from JSON

json_data = {
    "code": 200,
    "data": {
        "user": {
            "id": 1,
            "name": "李四"
        }
    }
}
user_name = json_data["data"]["user"]["name"]
print(user_name)  # Output: 李四

Example 6: Add a new field to JSON data

data = {"username": "admin", "token": "abc123"}
data["timestamp"] = "2025-04-30T09:14:00"  # Add new field
print(data)  # Output includes the timestamp

Example 7: Delete an unnecessary field from JSON

data = {"username": "testuser", "password": "123456", "age": 25}
del data["password"]  # Remove sensitive field
print(data)  # Output: {'username': 'testuser', 'age': 25}

Example 8: Check if JSON contains a specific key

data = {"id": 100, "name": "用户A"}
if "name" in data:
    print("包含 name 字段")  # Output: 包含 name 字段

Example 9: Iterate over all key‑value pairs in JSON

data = {"status": "ok", "count": 5, "items": [1, 2, 3]}
for key, value in data.items():
    print(f"{key}: {value}")
# Outputs each pair

Example 10: Merge two JSON objects

dict1 = {"a": 1, "b": 2}
dict2 = {"c": 3, "d": 4}
merged = {**dict1, **dict2}
print(merged)  # Output: {'a': 1, 'b': 2, 'c': 3, 'd': 4}

Example 11: Get a default value from nested JSON

data = {"user": {"name": "王五", "profile": {}}}
email = data.get("user", {}).get("email", "未填写")
print(email)  # Output: 未填写

Example 12: Filter a list of JSON objects by condition

users = [
    {"name": "Alice", "age": 25},
    {"name": "Bob", "age": 17},
    {"name": "Charlie", "age": 30}
]
adults = [u for u in users if u['age'] >= 18]
print(adults)  # Output: [{'name': 'Alice', 'age': 25}, {'name': 'Charlie', 'age': 30}]

Example 13: Compare two JSON objects for equality

import json
res1 = {"code": 200, "data": {"name": "test"}}
res2 = {"code": 200, "data": {"name": "test"}}
if json.dumps(res1, sort_keys=True) == json.dumps(res2, sort_keys=True):
    print("两个JSON相同")  # Output: 两个JSON相同

Example 14: Output JSON sorted by keys

data = {"b": 2, "a": 1, "c": 3}
sorted_json = json.dumps(data, sort_keys=True)
print(sorted_json)  # Output: {"a": 1, "b": 2, "c": 3}

Example 15: Parse API response JSON and verify status code

import requests, json
response = requests.get("https://api.example.com/status")
json_response = response.json()
if json_response.get("code") == 200:
    print("接口调用成功")
else:
    print("失败:", json_response.get("message"))

Example 16: Extract token from login response and use it for subsequent requests

import requests
login_url = "https://api.example.com/login"
payload = {"username": "test", "password": "123456"}
response = requests.post(login_url, json=payload)
token = response.json().get("token")
headers = {"Authorization": f"Bearer {token}"}
user_info = requests.get("https://api.example.com/user", headers=headers)
print(user_info.json())

Example 17: Use jsonpath to extract fields from complex JSON structures (third‑party library)

from jsonpath import jsonpath
data = {
    "store": {
        "book": [
            {"title": "Book A", "price": 20},
            {"title": "Book B", "price": 30}
        ]
    }
}
titles = jsonpath(data, "$.store.book[*].title")
print(titles)  # Output: ['Book A', 'Book B']
# Install with: pip install jsonpath

Example 18: Convert Java‑style field names to Python‑style (key renaming)

def rename_keys(data):
    return {k.replace("userName", "username"): v for k, v in data.items()}
json_data = {"userName": "Tom", "age": 25}
renamed = rename_keys(json_data)
print(renamed)  # Output: {'username': 'Tom', 'age': 25}

Example 19: Print JSON data as a formatted table

from tabulate import tabulate
data = [
    {"name": "Alice", "age": 25},
    {"name": "Bob", "age": 17}
]
table = tabulate(data, headers="keys", tablefmt="grid")
print(table)
# Install with: pip install tabulate

Example 20: Mock an API response and wrap it in a function for unit testing

import json
def mock_api_response():
    return json.dumps({
        "code": 200,
        "message": "Success",
        "data": {"id": 1, "name": "Mock Data"}
    })
response = mock_api_response()
print(response)  # Output the mocked JSON string

These Python JSON handling examples cover the most common operations needed in interface automation testing, including parsing/constructing, modifying/adding/removing fields, data extraction/assertion, logging/debugging, and mocking/encapsulating API responses. Mastering these techniques is essential for anyone involved in API automation.