自动化接口测试JSON Schema断言应用

什么是 JSON Schema？

• JSON Schema is a vocabulary that allows you to annotate and validate JSON documents.
• http://json-schema.org/
• 示例，简而言之，json schema就是json数据格式的一个描述，可以用来作实例验证。

// JSON Example
{
  "message": "操作成功",
  "responseCode": "0",
  "hasError": false,
  "data": {
    "id": 100123456
  }
}
// 与之对应的JSON Schema
{
    "$schema": "http://json-schema.org/schema#",
    "type": "object",
    "properties": {
        "message": {
            "type": "string"
        },
        "responseCode": {
            "type": "string"
        },
        "hasError": {
            "type": "boolean"
        },
        "data": {
            "type": "object",
            "properties": {
                "id": {
                    "type": "integer"
                }
            },
            "required": ["id"]
        }
    },
    "required": ["data", "hasError", "message", "responseCode"]
}

接口自动化测试利用 JSON Schema 断言 Response？

接口自动化测试一些常用断言方法：

• status_code：response.status_code == 200
• headers.xxx：Content-Type == application/json
• content.xxx：content.responseCode == "0"、content.message == "操作成功"

今天来个不一样的，Json schema Validate：

#!/usr/bin/env python
# -*- encoding: utf-8 -*-

from jsonschema import validate

#! 正常的返回值
resp_pass = {
    "message": "操作成功",
    "responseCode": "0",
    "hasError": False,
    "data": {
        "id": 100120384
    }
}
#! 错误的返回值，没有返回Data ID
resp_fail = {
    "message": "操作成功",
    "responseCode": "0",
    "hasError": False,
    "data": {}
}
#! 预期Schema
resp_schema = {
    "$schema": "http://json-schema.org/schema#",
    "type": "object",
    "properties": {
        "message": {
            "type": "string"
        },
        "responseCode": {
            "type": "string"
        },
        "hasError": {
            "type": "boolean"
        },
        "data": {
            "type": "object",
            "properties": {
                "id": {
                    "type": "integer"
                }
            },
            "required": ["id"]
        }
    },
    "required": ["data", "hasError", "message", "responseCode"]
}
#! 验证成功
try:
    validate(resp_pass, resp_schema)
except Exception as e:
    print('An exception occurred: ', e)

#! 验证失败
try:
    validate(resp_fail, resp_schema)
except Exception as e:
    print('An exception occurred: ', e)

以上执行结果为：

# 看得懂哈，不解释了 :)
An exception occurred:  'id' is a required property

Failed validating 'required' in schema['properties']['data']:
    {'properties': {'id': {'type': 'integer'}},
     'required': ['id'],
     'type': 'object'}

On instance['data']:
    {}
json schema validate fail

问：这么好用，怎么写预期的 json schema呢？

https://www.liquid-technologies.com/online-json-to-schema-converter

可以”硬写“也可以在线转换，输入预期的返回值json，转换成对应的 json schema

online-json-to-schema-converter

进阶：初次自动生成 JSON Schema用于后续断言？

以上，我们在写接口Case的时候还需要打开额外的网站去转换 json to json schema，有没有更简单的方式？

#!/usr/bin/env python
# -*- encoding: utf-8 -*-

from genson import SchemaBuilder

#! 正确的返回值
resp_pass = {
    "message": "操作成功",
    "responseCode": "0",
    "hasError": False,
    "data": {
        "id": 100120384
    }
}

#! 通过正确的返回值生成预期Json schema
builder = SchemaBuilder()
builder.add_object(resp_pass)
resp_schema = builder.to_json()

print(resp_schema)
 """ 输出结果
{
    "$schema": "http://json-schema.org/schema#",
    "type": "object",
    "properties": {
        "message": {
            "type": "string"
        },
        "responseCode": {
            "type": "string"
        },
        "hasError": {
            "type": "boolean"
        },
        "data": {
            "type": "object",
            "properties": {
                "id": {
                    "type": "integer"
                }
            },
            "required": ["id"]
        }
    },
    "required": ["data", "hasError", "message", "responseCode"]
}
 """

我们可以把预期的Json Schema 存在本地（比如CSV或者数据库中），validate时先查询有没有expect schema，有就取出来与response做validation，没有就自动用当前的response生成并保存expect schema（so调试时要确保用正确的返回值生成），后续都拿这个expect schema来validate。把这个过程写成一个方法一直复用，是不是又省时又省力？