For web applications, in consideration of security, verification codes will be set when logging in. There are many types of verification codes, such as identifying numbers and letters in pictures, clicking on specified text in pictures, and arithmetic calculation results Yes, a little more complicated is the sliding verification. Verification codes like this increase the security of our system, but for our testers, it is undoubtedly a difficult problem in the process of automated testing.
1. Web-based verification code solution
Generally, during our testing, when login encounters the above-mentioned verification code, there are the following solutions:
- The first way is to let the development remove the verification code
- Second, set a universal verification code
- The third way is to bypass login through cookies
- Fourth, automatic identification technology identification verification code
2. Verification code solution
# coding:utf-8
import os
import subprocess
from PIL import Image
def get_captcha(driver, captcha_id, full_screen_img_path, captcha_img_path, captcha_final_path, txt_path, ocr_path):
# 浏览器界面截图
driver.save_screenshot(full_screen_img_path)
# 找到验证码图片，得到它的坐标
element = driver.find_element_by_id(captcha_id)
left = element.location['x']
top = element.location['y']
right = element.location['x'] + element.size['width']
bottom = element.location['y'] + element.size['height']
left, top, right, bottom = int(left), int(top), int(right), int(bottom)
img = Image.open(full_screen_img_path)
img = img.crop((left, top, right, bottom))
# 得到验证码图片
img.save(captcha_img_path)
# 打开验证码图片
img = Image.open(captcha_img_path)
# 颜色直方图，255种颜色，255为白色
# 新建一张图片(大小和原图大小相同，背景颜色为255白色)
img_new = Image.new('P', img.size, 255)
for x in range(img.size[1]):
for y in range(img.size[0]):
# 遍历图片的xy坐标像素点颜色
pix = img.getpixel((y, x))
# print(pix)
# 自己调色，r=0，g=0，b>0为蓝色
if pix[0] < 20 and pix[1] < 20 and pix[2] > 50:
# 把遍历的结果放到新图片上，0为透明度，不透明
img_new.putpixel((y, x), 0)
img_new.save(captcha_final_path, format='png')
# 通过tesseract工具解析验证码图片，生成文本
os.system(ocr_path)
# 读取txt文件里面的验证码
with open(txt_path, 'r') as f:
if f.read():
t = f.read().strip()
# 去掉中间空格
if ' ' in t:
t = t.replace(' ', '')
if t.isdigit() and len(t) == 4:
return t
else:
return 'fail'
def check_resp(result, msg):
if msg in result:
return 'pass'
else:
return 'failed'
# 接口 - 识别验证码
def get_captcha(captcha_img_path, captcha_final_path, txt_path, ocr_path):
# 打开验证码图片
img = Image.open(captcha_img_path)
# 新建一张图片(大小和原图大小相同，背景颜色为255白色)
img_new = Image.new('P', img.size, 55)
for x in range(img.size[1]):
for y in range(img.size[0]):
# 遍历图片的xy坐标像素点颜色
pix = img.getpixel((y, x))
# print(pix)
# 自己调色，r=0，g=0，b>0为蓝色
if pix[0] < 20 and pix[1] < 20 and pix[2] > 50:
# 把遍历的结果放到新图片上，0为透明度，不透明
img_new.putpixel((y, x), 0)
img_new.save(captcha_final_path, format='png')
# 通过tesseract工具解析验证码图片，生成文本，【Tesseract-OCR必须和jpg的根目录必须相同，如C盘、D盘！！！】
os.system(ocr_path)
# 读取txt文件里面的验证码
with open(txt_path, 'r') as f:
if r.read():
t = f.read().strip()
# 去掉中间空格
if ' ' in t:
t = t.replace(' ', '')
# 如果是数字且长度为4，就返回数字，如果不是就返回 fail
if t.isdigit() and len(t) == 4:
return t
else:
return fail
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