1，cookie登入

利用cookie的特性：cookie會保持較長的時間，來避免使用者頻繁登入

2OCR庫裡的tesseract（光學文字識別）可以解決大多數的傳統驗證碼

軟體tesserract-ocr先安裝，然後安裝pytesserract類庫

注意：1Windows需要下載軟體安裝包，再配置環境變數              2linux  直接在命令視窗輸入：sudo apt-get tesseract-ocr

模擬瀏覽器，selenium和PIL庫的截圖功能，來識別驗證碼（save_screenshot截圖）

3打碼平臺

打碼兔和QQ超人打碼，有提供Python的接入方式，人工打碼平臺需要收費。

以QQ超人打碼平臺，先要註冊開發者賬號，在識別程式中需要填寫個人賬號進行認證計費，登入之後接入，開始計費（一個碼六分錢）

4selenium 來模擬拉動來破解滑動驗證碼

import random
import time

from selenium.webdriver import ActionChains
from selenium.webdriver.support import expected_conditions as EC
from selenium.webdriver.support.ui import WebDriverWait
from selenium.webdriver.common.by import By
from urllib.request import urlretrieve
from selenium import webdriver
from bs4 import BeautifulSoup
import PIL.Image as image
import re
import random

class Crack():
    def __init__(self, username, passwd):
        self.url = 'https://passport.bilibili.com/login'
        self.browser = webdriver.Chrome()
        self.wait = WebDriverWait(self.browser, 100)
        self.BORDER = 6
        self.passwd = passwd
        self.username = username

    def open(self):
        """
        開啟瀏覽器,並輸入查詢內容
        """
        self.browser.get(self.url)
        keyword = self.wait.until(EC.presence_of_element_located((By.ID, 'login-username')))
        keyword.send_keys(self.username)
        keyword = self.wait.until(EC.presence_of_element_located((By.ID, 'login-passwd')))
        keyword.send_keys(self.passwd)
        # bowton.click()

    def get_images(self, bg_filename='bg.jpg', fullbg_filename='fullbg.jpg'):
        """
        獲取驗證碼圖片
        :return: 圖片的location資訊
        """
        bg = []
        fullgb = []
        while bg == [] and fullgb == []:
            bf = BeautifulSoup(self.browser.page_source, 'lxml')
            bg = bf.find_all('div', class_='gt_cut_bg_slice')
            fullgb = bf.find_all('div', class_='gt_cut_fullbg_slice')
        bg_url = re.findall('url\(\"(.*)\"\);', bg[0].get('style'))[0].replace('webp', 'jpg')
        fullgb_url = re.findall('url\(\"(.*)\"\);', fullgb[0].get('style'))[0].replace('webp', 'jpg')
        bg_location_list = []
        fullbg_location_list = []
        for each_bg in bg:
            location = {}
            location['x'] = int(re.findall('background-position: (.*)px (.*)px;', each_bg.get('style'))[0][0])
            location['y'] = int(re.findall('background-position: (.*)px (.*)px;', each_bg.get('style'))[0][1])
            bg_location_list.append(location)
        for each_fullgb in fullgb:
            location = {}
            location['x'] = int(re.findall('background-position: (.*)px (.*)px;', each_fullgb.get('style'))[0][0])
            location['y'] = int(re.findall('background-position: (.*)px (.*)px;', each_fullgb.get('style'))[0][1])
            fullbg_location_list.append(location)
        # 把資源下載到臨時目錄
        urlretrieve(url=bg_url, filename=bg_filename)
        print('缺口圖片下載完成')
        urlretrieve(url=fullgb_url, filename=fullbg_filename)
        print('背景圖片下載完成')
        return bg_location_list, fullbg_location_list

    def get_merge_image(self, filename, location_list):
        """
        根據位置對圖片進行合併還原
        :filename:圖片
        :location_list:圖片位置
        """
        im = image.open(filename)
        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(im.crop((abs(location['x']), 58, abs(location['x']) + 10, 166)))
            if location['y'] == 0:
                im_list_down.append(im.crop((abs(location['x']), 0, abs(location['x']) + 10, 58)))

        new_im = image.new('RGB', (260, 116))

        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]

        new_im.save(filename)

        return new_im


    def is_pixel_equal(self, img1, img2, x, y):
        """
        判斷兩個畫素是否相同
        :param image1: 圖片1
        :param image2: 圖片2
        :param x: 位置x
        :param y: 位置y
        :return: 畫素是否相同
        """
        # 取兩個圖片的畫素點
        pix1 = img1.load()[x, y]
        pix2 = img2.load()[x, y]
        threshold = 60
        if (abs(pix1[0] - pix2[0] < threshold) and abs(pix1[1] - pix2[1] < threshold) and abs(
                        pix1[2] - pix2[2] < threshold)):
            return True
        else:
            return False

    def get_gap(self, img1, img2):
        """
        獲取缺口偏移量
        :param img1: 不帶缺口圖片
        :param img2: 帶缺口圖片
        :return:
        """
        left = 43
        for i in range(left, img1.size[0]):
            for j in range(img1.size[1]):
                if not self.is_pixel_equal(img1, img2, i, j):
                    left = i
                    return left
        return left



    def get_track(self, distance):
        """
        根據偏移量獲取移動軌跡
        :param distance: 偏移量
        :return: 移動軌跡
        """
        # 移動軌跡
        track = []
        # 當前位移
        current = 0
        # 減速閾值
        mid = distance * 3 / 5
        # 計算間隔
        t = 0.2
        # 初速度
        v = 0

        while current < distance:
            if current < mid:
                # 加速度為正2
                a = 2
            else:
                # 加速度為負3
                a = -3            # 初速度v0
            v0 = v
            # 當前速度v = v0 + at
            v = v0 + a * t
            # 移動距離x = v0t + 1/2 * a * t^2
            move = v0 * t + 1 / 2 * a * t * t
            # 當前位移
            current += move
            # 加入軌跡
            track.append(round(move))

            # track.append(round(move))
        time.sleep(random.random()*6)
        # print('111')
        return track

    def get_slider(self):
        """
        獲取滑塊
        :return: 滑塊物件
        """
        while True:
            try:
                slider = self.browser.find_element_by_xpath("//div[@class='gt_slider_knob gt_show']")
                break
            except:
                time.sleep(0.5)
        return slider

    def move_to_gap(self, slider, track):
        """
        拖動滑塊到缺口處
        :param slider: 滑塊
        :param track: 軌跡
        :return:
        """
        ActionChains(self.browser).click_and_hold(slider).perform()
        while track:
            x = random.choice(track)
            ActionChains(self.browser).move_by_offset(xoffset=x, yoffset=0).perform()
            track.remove(x)
        time.sleep(0.8)
        ActionChains(self.browser).release().perform()
        time.sleep(2)
        self.browser.quit()

    def crack(self):
        # 開啟瀏覽器
        self.open()

        # 儲存的圖片名字
        bg_filename = './images/bg.jpg'
        fullbg_filename = './images/fullbg.jpg'

        # 獲取圖片
        bg_location_list, fullbg_location_list = self.get_images(bg_filename, fullbg_filename)

        # 根據位置對圖片進行合併還原
        bg_img = self.get_merge_image(bg_filename, bg_location_list)
        fullbg_img = self.get_merge_image(fullbg_filename, fullbg_location_list)

        # 獲取缺口位置
        gap = self.get_gap(fullbg_img, bg_img)
        print('缺口位置', gap)

        track = self.get_track(gap - self.BORDER)
        print('滑動滑塊')
        print(track)

        # 點按撥出缺口
        slider = self.get_slider()
        # 拖動滑塊到缺口處
        self.move_to_gap(slider, track)


if __name__ == '__main__':
    crack = Crack('username', 'passwd')
    crack.crack()
    print('驗證成功')