import time
 from selenium import webdriver
 from slideVerfication import SlideVerificationCode
 ​
 # 1、創(chuàng)建一個(gè)driver對(duì)象，訪(fǎng)問(wèn)qq登錄頁(yè)面
 browser = webdriver.Chrome()
 browser.get("https://qzone.qq.com/")
 ​
 # 2、輸入賬號(hào)密碼
 # 2.0 點(diǎn)擊切換到登錄的iframe
 browser.switch_to.frame('login_frame')
 # 2.1 點(diǎn)擊賬號(hào)密碼登錄
 browser.find_element_by_id('switcher_plogin').click()
 # 2.2定位賬號(hào)輸入框，輸入賬號(hào)
 browser.find_element_by_id("u").send_keys("123292678")
 # 2.3定位密碼輸入輸入密碼
 browser.find_element_by_id("p").send_keys("PYTHON01")
 # 3、點(diǎn)擊登錄
 browser.find_element_by_id('login_button').click()
 time.sleep(3)
 ​
 # 4、模擬滑動(dòng)驗(yàn)證
 # 4.1切換到滑動(dòng)驗(yàn)證碼的iframe中
 tcaptcha = browser.find_element_by_id("tcaptcha_iframe")
 browser.switch_to.frame(tcaptcha)
 # 4.2 獲取滑動(dòng)相關(guān)的元素
 # 選擇拖動(dòng)滑塊的節(jié)點(diǎn)
 slide_element = browser.find_element_by_id('tcaptcha_drag_thumb')
 # 獲取滑塊圖片的節(jié)點(diǎn)
 slideBlock_ele = browser.find_element_by_id('slideBlock')
 # 獲取缺口背景圖片節(jié)點(diǎn)
 slideBg = browser.find_element_by_id('slideBg')
 # 4.3計(jì)算滑動(dòng)距離
 sc = SlideVerificationCode(save_image=True)
 distance = sc.get_element_slide_distance(slideBlock_ele,slideBg)
 # 滑動(dòng)距離誤差校正，滑動(dòng)距離*圖片在網(wǎng)頁(yè)上顯示的縮放比-滑塊相對(duì)的初始位置
 distance = distance*(280/680) - 22
 print("校正后的滑動(dòng)距離",distance)
 # 4.4、進(jìn)行滑動(dòng)
 sc.slide_verification(browser,slide_element,distance=100)

def get_element_slide_distance(self, slider_ele, background_ele, correct=0):
     """
     根據(jù)傳入滑塊，和背景的節(jié)點(diǎn)，計(jì)算滑塊的距離
 ​
     該方法只能計(jì)算 滑塊和背景圖都是一張完整圖片的場(chǎng)景，
     如果背景圖是通過(guò)多張小圖拼接起來(lái)的背景圖，
     該方法不適用，請(qǐng)使用get_image_slide_distance這個(gè)方法
     :param slider_ele: 滑塊圖片的節(jié)點(diǎn)
     :type slider_ele: WebElement
     :param background_ele: 背景圖的節(jié)點(diǎn)
     :type background_ele:WebElement
     :param correct:滑塊缺口截圖的修正值，默認(rèn)為0,調(diào)試截圖是否正確的情況下才會(huì)用
     :type: int
     :return: 背景圖缺口位置的X軸坐標(biāo)位置（缺口圖片左邊界位置）
     """
     # 獲取驗(yàn)證碼的圖片
     slider_url = slider_ele.get_attribute("src")
     background_url = background_ele.get_attribute("src")
     # 下載驗(yàn)證碼背景圖,滑動(dòng)圖片
     slider = "slider.jpg"
     background = "background.jpg"
     self.onload_save_img(slider_url, slider)
     self.onload_save_img(background_url, background)
     # 讀取進(jìn)行色度圖片，轉(zhuǎn)換為numpy中的數(shù)組類(lèi)型數(shù)據(jù)，
     slider_pic = cv2.imread(slider, 0)
     background_pic = cv2.imread(background, 0)
     # 獲取缺口圖數(shù)組的形狀 -->缺口圖的寬和高
     width, height = slider_pic.shape[::-1]
     # 將處理之后的圖片另存
     slider01 = "slider01.jpg"
     background_01 = "background01.jpg"
     cv2.imwrite(background_01, background_pic)
     cv2.imwrite(slider01, slider_pic)
     # 讀取另存的滑塊圖
     slider_pic = cv2.imread(slider01)
     # 進(jìn)行色彩轉(zhuǎn)換
     slider_pic = cv2.cvtColor(slider_pic, cv2.COLOR_BGR2GRAY)
     # 獲取色差的絕對(duì)值
     slider_pic = abs(255 - slider_pic)
     # 保存圖片
     cv2.imwrite(slider01, slider_pic)
     # 讀取滑塊
     slider_pic = cv2.imread(slider01)
     # 讀取背景圖
     background_pic = cv2.imread(background_01)
     # 比較兩張圖的重疊區(qū)域
     result = cv2.matchTemplate(slider_pic, background_pic, cv2.TM_CCOEFF_NORMED)
     # 獲取圖片的缺口位置
     top, left = np.unravel_index(result.argmax(), result.shape)
     # 背景圖中的圖片缺口坐標(biāo)位置
     print("當(dāng)前滑塊的缺口位置：", (left, top, left + width, top + height))
     return left
   def slide_verification(self, driver, slide_element, distance):
     """
     滑動(dòng)滑塊進(jìn)行驗(yàn)證
     
     :param driver: driver對(duì)象
     :type driver:webdriver.Chrome
     :param slide_element: 滑塊的元組
     :type slider_ele: WebElement
     :param distance: 滑動(dòng)的距離
     :type: int
     :return:
     """
     # 獲取滑動(dòng)前頁(yè)面的url地址
     start_url = driver.current_url
     print("需要滑動(dòng)的距離為：", distance)
     # 根據(jù)滑動(dòng)距離生成滑動(dòng)軌跡
     locus = self.get_slide_locus(distance)
     print("生成的滑動(dòng)軌跡為:{}，軌跡的距離之和為{}".format(locus, distance))
     # 按下鼠標(biāo)左鍵
     ActionChains(driver).click_and_hold(slide_element).perform()
     time.sleep(0.5)
     # 遍歷軌跡進(jìn)行滑動(dòng)
     for loc in locus:
       time.sleep(0.01)
       ActionChains(driver).move_by_offset(loc, random.randint(-5, 5)).perform()
       ActionChains(driver).context_click(slide_element)
     # 釋放鼠標(biāo)
     ActionChains(driver).release(on_element=slide_element).perform()