在當前互聯網產品叠代頻繁的背景下，回歸測試的時間越來越少，很難在每個叠代都對所有功能做完整回歸。但接口自動化測試因其實現簡單、維護成本低，容?提高覆蓋率等特點，越來越受重視。
為?麽要自己寫框架呢?
使用Postman調試通過過直接可以獲取接口測試的基本代碼，結合使用requets + unittest很容?實現接口自動化測試的封裝，而且requests的api已經非常人性化，非常簡單，但通過封裝以後（特別是針對公司內特定接口），可以進壹步提高腳本編寫效率。
壹個現有的簡單接口?子
下面使用requests + unittest測試壹個查詢接口
接口信息如下
請求信息:
Method：POST
URL：api/match/image/getjson
Request：
{
"category": "image",
"offset": "0",
"limit": "30",
"sourceId": "0",
"metaTitle": "",
"metaId": "0",
"classify": "unclassify",
"startTime": "",
"endTime": "",
"createStart": "",
"createEnd": "",
"sourceType": "",
"isTracking": "true",
"metaGroup": "",
"companyId": "0",
"lastDays": "1",
"author": ""
}
Response示例：
{
"timestamp" : xxx,
"errorMsg" : "",
"data" : {
"config" : xxx
}
Postman測試方法見截圖：
測試思路
1.獲取Postman原始腳本
2.使用requests庫模擬發送HTTP請求**
3.對原始腳本進行基礎改造**
4.使用python標準庫?unittest寫測試case**
原始腳本實現
未優化
該代碼只是簡單的壹次調用，而且返回的結果太多，很多返回信息暫時沒用，示例代碼如下
import requests
url = "/api/match/image/getjson"
querystring = {"category":"image","offset":"0","limit":"30","sourceId":"0","metaTitle":"","metaId":"0","classify":"unclassify","startTime":"","endTime":"","createStart":"","createEnd":"","sourceType":"","isTracking":"true","metaGroup":"","companyId":"0","lastDays":"1","author":""}
headers = { 'cache-control': "no-cache", 'postman-token': "e97a99b0-424b-b2a5-7602-22cd50223c15"
}
response = requests.request("POST", url, headers=headers, params=querystring)
print(response.text)
優化 第壹版
調整代碼結構，輸出結果Json出來，獲取需要驗證的response.status_code，以及獲取結果校驗需要用到的results['total']
#!/usr/bin/env python#coding: utf-8'''
unittest merchant backgroud interface
@author: zhang_jin
@version: 1.0
@see:/api/match/image/getjson"
querystring = { "category": "image", "offset": "0", "limit": "30", "sourceId": "0", "metaTitle": "", "metaId": "0", "classify": "unclassify", "startTime": "", "endTime": "", "createStart": "", "createEnd": "", "sourceType": "", "isTracking": "true", "metaGroup": "", "companyId": "0", "lastDays": "1", "author": ""
}
headers = { 'cache-control': "no-cache", 'postman-token': "e97a99b0-424b-b2a5-7602-22cd50223c15"
}#Post接口調用
response = requests.request("POST", url, headers=headers, params=querystring)#對返回結果進行轉義成json串
results = json.loads(response.text)#獲取/api/match/image/getjson"
querystring = { "category": "image", "offset": "0", "limit": "30", "sourceId": "0", "metaTitle": "", "metaId": "0", "classify": "unclassify", "startTime": "", "endTime": "", "createStart": "", "createEnd": "", "sourceType": "", "isTracking": "true", "metaGroup": "", "companyId": "0", "lastDays": "1", "author": ""
}
headers = { 'cache-control': "no-cache", 'postman-token': "e97a99b0-424b-b2a5-7602-22cd50223c15"
}try: #Post接口調用
response = requests.request("POST", url, headers=headers, params=querystring) #對http返回值進行判斷，對於200做基本校驗 if response.status_code == 200:
results = json.loads(response.text) if results['total'] == 191: print "Success" else: print "Fail" print results['total'] else: #對於http返回非200的code，輸出相應的code raise Exception("http error info:%s" %response.status_code)except:
traceback.print_exc()