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2[0])
res2 = abs(rgb1[1] - rgb2[1])
res3 = abs(rgb1[2] - rgb2[2])
if not (res1 < threhold and res2 < threhold and res3 < threhold):
print(i)
if i not in v:
v.append(i)
stop = 0
for i in range(0, len(v)):
val = i + v[0]
if v[i] != val:
stop = v[i]
break
width = stop - v[0]
print(stop, v[0], width)
return width
def get_tracks(distance):
import random
exceed_distance = random.randint(0, 5)
distance += exceed_distance # 先滑过一点，最后再反着滑动回来
v = 0
t = 0.2
forward_tracks = []
current = 0
mid = distance * 3 / 5
while current < distance:
if current < mid:
a = random.randint(1, 3)
else:
a = random.randint(1, 3)
a = -a
s = v * t + 0.5 * a * (t ** 2)
v = v + a * t
current += s
forward_tracks.append(round(s))
# 反着滑动到准确位置
v = 0
t = 0.2
back_tracks = []
current = 0
mid = distance * 4 / 5
while abs(current) < exceed_distance:
if current < mid:
a = random.randint(1, 3)
else:
a = random.randint(-3, -5)
a = -a
s = -v * t - 0.5 * a * (t ** 2)
v = v + a * t
current += s
back_tracks.append(round(s))
return {'forward_tracks': forward_tracks, 'back_tracks': list(reversed(back_tracks))}
def crack(driver): # 破解滑动认证
# 1、点击按钮，得到没有缺口的图片
button = driver.find_element_by_xpath('//*[@id="embed-captcha"]/div/div[2]/div[1]/div[3]')
button.click()
# 2、获取没有缺口的图片
image1 = get_image(driver)
# 3、点击滑动按钮，得到有缺口的图片
button = driver.find_element_by_class_name('geetest_slider_button')
button.click()
# 4、获取有缺口的图片
image2 = get_image(driver)
# 5、对比两种图片的像素点，找出位移
distance = get_distance(image1, image2)
print(distance)
#
# 6、模拟人的行为习惯，根据总位移得到行为轨迹
tracks = get_tracks(int(distance / 2))
# 7、按照行动轨迹先正向滑动，后反滑动
button = driver.find_element_by_class_name('geetest_slider_button')
ActionChains(driver).click_and_hold(button).perform()
# 正常人类总是自信满满地开始正向滑动，自信地表现是疯狂加速
for track in tracks['forward_tracks']:
ActionChains(driver).move_by_offset(xoffset=track, yoffset=0).perform()
# 结果傻逼了，正常的人类停顿了一下，回过神来发现，卧槽，滑过了,然后开始反向滑动
time.sleep(0.5)
for back_track in tracks['back_tracks']:
ActionChains(driver).move_by_offset(xoffset=back_track, yoffset=0).perform()
#
# # 小范围震荡一下，进一步迷惑极验后台，这一步可以极大地提高成功率
ActionChains(driver).move_by_offset(xoffset=3, yoffset=0).perform()
ActionChains(driver).move_by_offset(xoffset=-3, yoffset=0).perform()
# # 成功后，骚包人类总喜欢默默地欣赏一下自己拼图的成果，然后恋恋不舍地松开那只脏手
time.sleep(0.5)
ActionChains(driver).release().perform()
def login_luffy(username, password):
driver = webdriver.Chrome('/Users/wupeiqi/drivers/chromedriver')
driver.set_window_size(960, 800)
try:
# 1、输入账号密码回车
driver.implicitly_wait(3)
driver.get('https://www.luffycity.com/login')
input_username = driver.find_element_by_xpath('//*[@id="router-view"]/div/div/div[2]/div[2]/input[1]')
input_pwd = driver.find_element_by_xpath('//*[@id="router-view"]/div/div/div[2]/div[2]/input[2]')
input_username.send_keys(username)
input_pwd.send_keys(password)
# 2、破解滑动认证
crack(driver)
time.sleep(10) # 睡时间长一点，确定登录成功
finally:
pass
# driver.close()
if __name__ == '__main__':
login_luffy(username='wupeiqi', password='123123123')
四：总结
通过selenium模拟人类单机浏览器的行为，破解滑动验证码，让我有get到了爬虫的一个本领，首先需要掌握selenium点击行为的一般模式，最后可以好好的参考peiqi老师的代码，作为模板用到以后的工作中，很有帮助，谢谢！下一步想再学学其他验证码的破解方式，多多益善！
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