python request接口测试笔记(1)
python request接口测试笔记(1)
涉及到的功能说明：
- 需要登录拿到token，才能进行下一个接口的请求
- 读取csv文件中的信息，作为接口的参数
- 将接口响应结果，写入csv文件，以便分析统计
# -*- coding:utf-8 -*-
'''
author:***cy
time:2019-08-28
主要功能说明：
1、获取登录接口的token
2、接入食物识别的接口，批量测试食物识别模型，得出模型的正确率
'''
import requests
import json
import csv
class FoodDetect():
def __init__(self):
print("----------------start----------------")
'''获取token'''
def login_token(self):
# 初始化登录接口
login_url = 'https://api.ty.com/oauth2/token?grant_type=password&sms_verify=true'
login_header = {"Authorization": "Basic T23DZZMfrrdFrTfdfR4esdFGrfrdfOjdmTFJyEmFmYzgxRDgwSfdfR="}
login_data = {
"username": "15012345678",
"password": "123456",
"appName": "ty",
"grant_type": "password",
"sms_verify": "true"
}
# 登录请求接口
r_login = requests.post(url=login_url, data=login_data, headers=login_header)
# 获取登录的响应报文
print(r_login.text)
# login_response = json.loads(r_login.text)
# 保存登录的token信息
# access_token = login_response['access_token']
token = r_login.json()['access_token']
print(token)
'''请求接口获取token值'''
return token
def detect_food(self):
# 初始化
food_flag_init = 0
food_error_init = 0
food_fail_init = 0
# 读取csv文件
with open('E:\\test\\ty\\food_detect_init.csv', 'r') as csvFile:
reader = csv.reader(csvFile)
print(type(reader))
next(reader)
for row in reader:
# 食物识别问答接口的请求参数msg
food_msg = {"msg": row[0]}
print(food_msg)
# 获取登录接口中的token
food_headers = {"Authorization": "Bearer " + self.login_token()}
# 食物识别接口url
food_url = 'https://api.ty.com/nlp/api/v1.0/food_detect'
# 食物识别模型接口请求
r_food = requests.post(url=food_url, data=food_msg, headers=food_headers)
# 获取响应报文
print(r_food.text)
# 转换响应结果为dict格式
food_response = json.loads(r_food.text)
# 判断响应结果是否为空,不为空，则获取cal_name和name的名称
if food_response:
print(food_response[0])
food_response_all = food_response[0]
food_response_all_one = food_response_all['properties']
# 获取cal_name的值
food_response_cal = food_response_all_one['cal_name']
food_response_name = food_response_all_one['name']
print("food的calname：" + food_response_cal)
#food_response_name
if food_response_cal == row[0]:
# 如果calname和输入的食物名称一致，则测试通过，写入food_py_success文件
"""
模型匹配的方法：先匹配name，然后和库里面的cal_name对比，这里需要修改一下判断条件
"""
food_flag_init = food_flag_init + 1
print("food匹配成功%d" %food_flag_init)
else:
fail_data = ['food_name','name','cal_name']
food_fail_init = food_fail_init + 1
print("food匹配错误%d" %food_fail_init)
with open('E:\\test\\ty\\food_detect_fail.csv','a+',encoding='utf-8-sig') as ff:
fail_data[0] = row[0]
fail_data[1] = food_response_name
fail_data[2] = food_response_cal
ff.write(','.join(fail_data))
ff.write('\n')
ff.close()
else:
food_error_init = food_error_init + 1
print("food匹配失败%d" % food_error_init)
# 将失败的食物name存在csv文件
error_data = ['name']
with open('E:\\test\\ty\\food_detect_error.csv','a+',encoding = 'utf-8-sig')as ef:
error_data[0] = row[0]
ef.write(','.join(error_data))
ef.write('\n')
ef.close()
# 写入csv文件
data_row = ['food_real_name', 'food_response_name','food_response_cal']
with open('E:\\test\\ty\\food_detect_py.csv','a+',encoding='utf-8-sig') as f:
# csv_write = csv.writer(f)
data_row[0] = row[0]
data_row[1] = food_response_name
data_row[2] = food_response_cal
# data_row = list(data_row)
# print(data_row)
f.write(','.join(data_row))
f.write("\n")
# f.write("\\n")
print("down")
f.close()
# 打印食物匹配结果
print("food匹配成功%d" % food_flag_init)
print("food匹配错误%d" % food_fail_init)
print("food匹配失败%d" % food_error_init)
csvFile.close()
if __name__ == '__main__':
fd = FoodDetect()
fd.detect_food()
食物检测接口的响应结果格式如下：
[
{
"properties":{
"cal_name":"苹果汁",
"type":"food",
"index":4,
"food_id":4342,
"kcal_unit_weight":53.56,
"name":"苹果汁",
"start_index":0,
"time_stamp":1567226386
},
"sub_properties":{
"grams":543,
"is_default":true,
"quantifier_id":54,
"quantity":1,
"unit":"瓶"
},
"type":"Entity"
}
]
所以这里想要获取响应结果中的cal_name，需要先获取properties，代码如下：
food_response_all = food_response[0]
food_response_all_one = food_response_all['properties']
# 获取cal_name的值
food_response_cal = food_response_all_one['cal_name']
整体下来，批量测试接口模型的工作就是这样，其中将接口返回结果写入csv时，需要注意要换行写入，而且使用写入的格式是'a'或'a+'追加模式。
