import logging
import time
import random
import re
import requests
from urllib import parse
import pdb
from selenium import webdriver
from selenium.webdriver.common.action_chains import ActionChains
from PIL import Image
from io import BytesIO
import numpy as np
class Bilibili(object):
"""docstring for Bilibili"""
js="""
console.log(document.cookie);
var keys=document.cookie.match(/[^ =;]+(?=\=)/g);
console.log(keys);
if (keys) {
for (var i = keys.length; i--;)
document.cookie=keys[i]+'=0;expires=' + new Date( 0).toUTCString();
console.log(document.cookie);
} """
def __init__(self):
"""构造函数"""
super(Bilibili,self).__init__()
self.browser=webdriver.Chrome()
self.browser.set_page_load_timeout(20)
self.browser.implicitly_wait(10)
def __del__(self):
"""析构函数"""
if self.browser is not None:
self.browser.quit()
def logging(self,username,password):
self.browser.get("https://passport.bilibili.com/login")
dom_input_id = self.browser.find_element_by_id("login-username")
dom_input_keyword = self.browser.find_element_by_id("login-passwd")
dom_btn_log = self.browser.find_element_by_xpath('//*[@class="btn-box"]/a[1]')
#pdb.set_trace()
dom_input_id.send_keys(username)
dom_input_keyword.send_keys(password)
flag_success = False
while not flag_success:
image_full_bg = self.get_image("gt_cut_fullbg_slice")
# 下载完整的验证图
image_bg = self.get_image("gt_cut_bg_slice")
# 下载有缺口的验证图
diff_x = self.get_diff_x(image_full_bg, image_bg)
#pdb.set_trace()
track = self.get_track(diff_x)
result = self.simulate_drag(track)
print(result)
if u'验证通过' in result:
flag_success = True
elif u'出现错误:' in result:
self.browser.execute_script('location.reload()')
continue
elif u'再' in result:
time.sleep(4)
continue
elif u'吃' in result:
time.sleep(5)
else:
break
if flag_success:
time.sleep(random.uniform(1.5, 2))
self.browser.execute_script(self.js)
def get_image(self,class_name):
"""
下载并还原极验的验证图
Args:
class_name: 验证图所在的html标签的class name
Returns:
返回验证图
Errors:
IndexError: list index out of range. ajax超时未加载完成,导致image_slices为空
"""
image_slices = self.browser.find_elements_by_class_name(class_name)
#pdb.set_trace()
if len(image_slices) == 0:
print('No such a class')
div_style=image_slices[0].get_attribute('style')
print(div_style)
#pdb.set_trace()
image_url = re.findall("background-image: url\(\"(.*)\"\); background-position: (.*)px (.*)px;",div_style)[0][0]
# image_url = re.findall("background-image: url\("(.*)"\); background-position: (.*)px (.*)px;",div_style)[0][0]
image_url = image_url.replace("webp","jpg")
image_filename = parse.urlsplit(image_url).path.split('/')[-1]
location_list = list()
for image_slice in image_slices:
location = dict()
location['x'] = int(re.findall("background-image: url\(\"(.*)\"\); background-position: (.*)px (.*)px;",
image_slice.get_attribute('style'))[0][1])
#
location['y'] = int(re.findall("background-image: url\(\"(.*)\"\); background-position: (.*)px (.*)px;",
image_slice.get_attribute('style'))[0][2])
location_list.append(location)
headers = {"User-Agent": "Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/56.0.2924.87 Safari/537.36"}
response = requests.get(image_url,headers=headers)
image = Image.open(BytesIO(response.content))
image = self.recover_image(image,location_list)
return image
def recover_image(self,image,location_list):
"""
还原验证图像
Args:
image: 打乱的验证图像(PIL.Image数据类型)
location_list: 验证图像每个碎片的位置
Returns:
还原过后的图像
"""
new_im = Image.new('RGB',(260,116))
im_list_upper = []
im_list_down = []
for location in location_list:
if location['y'] == -58:
im_list_upper.append(image.crop((abs(location['x']), 58, abs(location['x']) + 10, 116)))
if location['y'] == 0:
im_list_down.append(image.crop((abs(location['x']), 0, abs(location['x']) + 10, 58)))
x_offset = 0
for im in im_list_upper:
new_im.paste(im, (x_offset, 0))
x_offset += im.size[0]
x_offset = 0
for im in im_list_down:
new_im.paste(im, (x_offset, 58))
x_offset += im.size[0]
return new_im
def get_diff_x(self,image1,image2):
"""
计算验证图的缺口位置(x轴)
两张原始图的大小都是相同的260*116,那就通过两个for循环依次对比每个像素点的RGB值,
如果RGB三元素中有一个相差超过50则就认为找到了缺口的位置
Args:
image1: 图像1
image2: 图像2
Returns:
x_offset
"""
for x in range(0, 260):
for y in range(0, 116):
if not self.__is_similar(image1, image2, x, y):
print(1111111111111111111,x)
return x
def __is_similar(self, image1, image2, x_offset, y_offset):
"""
判断image1, image2的[x, y]这一像素是否相似,如果该像素的RGB值相差都在50以内,则认为相似。
Args:
image1: 图像1
image2: 图像2
x_offset: x坐标
y_offset: y坐标
Returns:
boolean
"""
pixel1 = image1.getpixel((x_offset, y_offset))
pixel2 = image2.getpixel((x_offset, y_offset))
for i in range(0, 3):
if abs(pixel1[i] - pixel2[i]) >= 50:
return False
return True
def get_track(self, x_offset):
track = list()
length = x_offset - 6
x = random.randint(1,5)
while length - x >4:
track.append([x,0,0.1])
length=length - x
x= random.randint(1,15)
for i in range(length):
if x_offset>47:
track.append([1,0,random.randint(10,12)/100.0])
else:
track.append([1, 0, random.randint(13, 14)/100.0])
print(22222222,track)
print((np.array(track)[:,0]).sum())
return track
def simulate_drag(self, track):
dom_div_slider = self.browser.find_element_by_xpath('//*[@id="gc-box"]/div/div[3]/div[2]')
ActionChains(self.browser).click_and_hold(on_element=dom_div_slider).perform()
# for x,y,z in track:
# ActionChains(self.browser).move_to_element_with_offset(
# to_element=dom_div_slider,
# xoffset=x+22,
# yoffset=y+22).perform()
# time.sleep(z)
for x,y,z in track:
ActionChains(self.browser).move_by_offset(
xoffset=x,
yoffset=y).perform()
time.sleep(z)
# ActionChains(self.browser).move_by_offset(
# xoffset=(np.array(track)[:,0]).sum(),
# yoffset=0).perform()
time.sleep(0.9)
ActionChains(self.browser).release(on_element=dom_div_slider).perform()
time.sleep(1)
dom_div_gt_info = self.browser.find_element_by_class_name('gt_info_type')
return dom_div_gt_info.text
if __name__ == '__main__':
bilibili=Bilibili()
bilibili.logging('username','password')