如何使用Selenium和Python通过“ onclick”查找并单击按钮？

Question

页面上有2个按钮，这两个按钮之间的区别是"onclick"。

<button class="btn btn-primary" style="width: 96px;" type="button" id="YesBtn" onclick="check_security('security_div0')">OK</button>

<button class="btn btn-primary" style="width: 96px;" type="button" id="YesBtn" onclick="check_security('wlan1security_div0')">OK</button>

我当时正在考虑使用xpath：

driver.find_element_by_xpath("//form[@id='update-container-id']/div/div/div/div[2]/div/div[2]/table[1]/tbody/tr[1]/td[8]/div[3]/div/div/div/div[3]/button").click()

但是它响应以下错误：

selenium.common.exceptions.ElementNotInteractableException: Message: Element <button id="YesBtn" class="btn btn-primary" type="button"> could not be scrolled into view

有人可以帮助我正确单击第二个按钮吗？非常感谢。

Answer 1

尝试使用x路径import random import numpy as np import math def sampling(a, b, Ip, In, alpha, elements): #print("sampling") result = [] print("a:", a) print("b:", b) print("alpha:", alpha) print("elements:", elements) print("Ip:", Ip) print("In:", In) summary = 0 N = len(alpha) for i in range(N): A = 0 B = 0 value = 0 ''' if i == elements: continue ''' for j in range(elements): print("A:") print("1:", a[i][j] + Ip[j], ",2:", b[i][j] + In[j], ",3:", a[i][j] + b[i][j] + Ip[j] + In[j]) A += math.lgamma(a[i][j] + Ip[j]) + math.lgamma(b[i][j] + In[j]) - math.lgamma(a[i][j] + b[i][j] + Ip[j] + In[j]) print("B:") print("1:", a[i][j] + b[i][j], ",2:", a[i][j], ",3:", b[i][j]) B += math.lgamma(a[i][j] + b[i][j]) - math.lgamma(a[i][j]) - math.lgamma(b[i][j]) print("A:", A) print("B:", B) print("value:", value) value += math.log(alpha[i]) + A + B print("i:", i, "value:", value) summary += math.exp(value) result.append(math.exp(value)) print("percentage:", np.array(result) / summary) #print("summary:", summary) choose = random.uniform(0.0, summary) #print("choose:", choose) num = N - 1 for i in range(N): choose -= result[i] if choose <= 0: num = i break ''' if num >= elements: num += 1 ''' return num def delta(x, y): if x == y: return 1 return 0 data = [] print("please input (k, l):") num = map(int, raw_input().split()) k_l = k = num[0] l_l = l = num[1] param_p = np.array([[0 for i in range(k)] for j in range(l)]) param_n = np.array([[0 for i in range(k)] for j in range(l)]) param_k = np.array([0] * k) param_l = np.array([0] * l) count = 1000 print("please input (N1, N2):") number = map(int, raw_input().split()) N1 = number[0] N2 = number[1] random.randint(50, 100) z1 = [] z2 = [] z1_sum = np.array([[[0 for i in range(k)] for j in range(l)] for n in range(N1)]) z2_sum = np.array([[[0 for i in range(k)] for j in range(l)] for n in range(N2)]) z1_zero = np.array([[[0 for i in range(k)] for j in range(l)] for n in range(N1)]) z2_zero = np.array([[[0 for i in range(k)] for j in range(l)] for n in range(N2)]) value = 0 valuesL = [] for i in range(N2): valuesL.append(value) if i % l == l - 1: value = 0 else: value += 1 valuesL = np.sort(np.array(valuesL)) for i in range(N2): z2.append([valuesL[i], i],) tempAlpha = 0.5 tempA = 0.5 tempB = 0.5 alpha1 = np.array([tempAlpha for i in range(k)]) alpha2 = np.array([tempAlpha for i in range(l)]) a = np.array([[tempA for i in range(k)] for j in range(l)]) b = np.array([[tempB for i in range(k)] for j in range(l)]) value = 0 valuesK = [] for i in range(N1): valuesK.append(value) if i % k == k - 1: value = 0 else: value += 1 valuesK = np.sort(np.array(valuesK)) for i in range(N1): z1.append([valuesK[i], i],) z1 = np.array(z1) z2 = np.array(z2) print(z1) print(z2) print("please input relation-data:") for i in range(N2): line = map(int, raw_input().split()) data.append(line) #print(data) for i in range(N2): l = z2[i][0] for j in range(N1): k = z1[j][0] z1_sum[j][l][k] += data[i][j] z2_sum[i][l][k] += data[i][j] z1_zero[j][l][k] += 1 - data[i][j] z2_zero[i][l][k] += 1 - data[i][j] param_p[l][k] += data[i][j] param_n[l][k] += 1 - data[i][j] param_k[k] += data[i][j] param_l[l] += data[i][j] #print("param_p:", param_p) #print("param_n:", param_n) #print("param_k:", param_k) #print("param_l:", param_l) #print("z1-sum:") #print(z1_sum) #print("z2-sum:") #print(z2_sum) #sampling(a, b, I, alpha, length, elements) k = 0 l = 0 pastK = np.array([0 for i in range(N1)]) pastL = np.array([0 for i in range(N2)]) for n in range(count): pastK[:] = z1[:, 0] for i in range(N1): #sampling z1 objects t_k = z1[i][0] k = z1[i][0] = sampling((a[:, :] + param_p[:, :] - z1_sum[i, :, :]).T, (b[:, :] + param_n[:, :] - z1_zero[i, :, :]).T, np.sum(z1_sum[i, :, :], axis=1), np.sum(z1_zero[i, :, :], axis=1), alpha1[:] + param_k[:] - np.sum(z1_sum[i, :, :], axis=0), l_l) #print("t_k:", t_k, "k:", k) for i in range(N1): t_k = pastK[i] k = z1[i][0] print("t_k:", t_k, "k:", k) if t_k != k: #change param_p param_n param_k #print("old-z1:", z1) print("param_p(past):", param_p) print("param_n(past):", param_n) print("param_k(past):", param_k) z1_sum_temp = z1_sum[i, :, t_k] #reduce order z1_zero_temp = z1_zero[i, :, t_k] summary = np.sum(z1_sum_temp) param_p[:, t_k] -= z1_sum_temp #minus old value param_n[:, t_k] -= z1_zero_temp param_k[t_k] -= summary param_p[:, k] += z1_sum_temp #plus new value param_n[:, k] += z1_zero_temp param_k[k] += summary print("param_p(now):", param_p) print("param_n(now):", param_n) print("param_k(now):", param_k) #print("past-z2-sum:", z2_sum) for j in range(N2): l_j = z2[j][0] z2_sum[j][l_j][t_k] -= data[j][i] z2_sum[j][l_j][k] += data[j][i] z2_zero[j][l_j][t_k] -= 1 - data[j][i] z2_zero[j][l_j][k] += 1 - data[j][i] #print("now-z2-sum:", z2_sum) #print("past-z1-sum:", z1_sum) #change z1_sum z1_sum[i, :, k] = z1_sum[i, :, t_k] z1_sum[i, :, t_k] = 0 z1_zero[i, :, k] = z1_zero[i, :, t_k] z1_zero[i, :, t_k] = 0 #print("now-z1-sum:", z1_sum) #print("new-z1:", z1) pastL[:] = z2[:, 0] for i in range(N2): #sampling z2 objects t_l = z2[i][0] l = z2[i][0] = sampling(a[:, :] + param_p[:, :] - z2_sum[i, :, :], b[:, :] + param_n[:, :] - z2_zero[i, :, :], np.sum(z2_sum[i, :, :], axis=0), np.sum(z2_zero[i, :, :], axis=0), alpha2[:] + param_l[:] - np.sum(z2_sum[i, :, :], axis=1), k_l) print("t_l:", t_l, "l:", l) for i in range(N2): t_l = pastL[i] l = z2[i][0] print("t_l:", t_l, "l:", l) if t_l != l: #change param_p param_n param_l #print("old-z2:", z2) z2_sum_temp = z2_sum[i, t_l, :] #reduce order z2_zero_temp = z2_zero[i, t_l, :] summary = np.sum(z2_sum_temp) param_p[t_l, :] -= z2_sum_temp #minus old value param_n[t_l, :] -= z2_zero_temp param_l[t_l] -= summary param_p[l, :] += z2_sum_temp #plus new value param_n[l, :] += z2_zero_temp param_l[l] += summary #print("param_p(past):", param_p) #print("param_n(past):", param_n) #print("param_l(past):", param_l) print("param_p(now):", param_p) print("param_n(now):", param_n) print("param_l(now):", param_l) #print("past-z1-sum(past):", z1_sum) #print("past-z1-zero(past):", z1_zero) #change z1_sum for j in range(N1): k_j = z1[j][0] z1_sum[j][t_l][k_j] -= data[i][j] z1_sum[j][l][k_j] += data[i][j] z1_zero[j][t_l][k_j] -= 1 - data[i][j] z1_zero[j][l][k_j] += 1 - data[i][j] #print("now-z1-sum(now):", z1_sum) #print("past-z1-zero(now):", z1_zero) #print("past-z2-sum(past):", z2_sum) #print("past-z2-zero(past):", z2_zero) #change z2_sum z2_sum[i, l, :] = z2_sum[i, t_l, :] z2_sum[i, t_l, :] = 0 z2_zero[i, l, :] = z2_zero[i, t_l, :] z2_zero[i, t_l, :] = 0 #print("now-z2-sum(now):", z2_sum) #print("now-z2-zero(now):", z2_sum) #print("new-z2:", z2) #z = input() print("Hello") z1 = z1[z1[:, 0].argsort(), :] z2 = z2[z2[:, 0].argsort(), :] lists = np.array(data) lists = lists[:, z1[:, 1]] lists = lists[z2[:, 1], :] print(z1) print(z2) print(lists)

//button[@onclick="check_security('wlan1security_div0')"]

使用Action类，

driver.find_element_by_xpath("//button[@onclick=\"check_security('wlan1security_div0')\"]").click()

使用Java脚本执行程序，

button = driver.find_element_by_xpath("//button[@onclick=\"check_security('wlan1security_div0')\"]")
ActionChains(driver).move_to_element(button).click(button).perform()

Answer 2

根据您提供的 HTML ，要使用onclick()事件单击按钮，可以使用以下解决方案：

• 第一个元素（css_selector）：

  driver.find_element_by_css_selector("button.btn.btn-primary#YesBtn[onclick*='security_div0']").click()
  

• 第一个元素（xpath）：

  driver.find_element_by_xpath("//button[@class='btn btn-primary' and @id='YesBtn'][@onclick=\"check_security('security_div0')\"]").click()
  

• 第二个元素（css_selector）：

  driver.find_element_by_css_selector("button.btn.btn-primary#YesBtn[onclick*='wlan1security_div0']").click()
  

• 第二个元素（xpath）：

  driver.find_element_by_xpath("//button[@class='btn btn-primary' and @id='YesBtn'][@onclick=\"check_security('wlan1security_div0')\"]").click()
  

Answer 3

首先，您要使用非常长的xpath，这将很难维护。您可以进一步缩小范围。

现在，您可以尝试一些xpath：

1）获取ID为YesBtn的 second 按钮（假设只有两个具有该属性的按钮）：

driver.find_element_by_xpath("(//button[@id= 'YesBtn'])[2]");

2）通过onclick属性查找：

driver.find_element_by_xpath("//button[@onclick= \'check_security(\'wlan1security_div0\')\']");

Answer 4

button1 和 HTML ：

<button class="btn btn-primary" style="width: 96px;" type="button" id="YesBtn" onclick="check_security('security_div0')">OK</button>  

XPATH：

//button[text()='OK' and @onclick="check_security('security_div0')"] 

按钮2 和 HTML ：

<button class="btn btn-primary" style="width: 96px;" type="button" id="YesBtn" onclick="check_security('wlan1security_div0')">OK</button>  

HTML：

//button[text()='OK' and @onclick="check_security('wlan1security_div0')"]

Answer 5

try:
  buttonVar = browser.find_element_by_css_selector(cssSel)
  ActionChains(browser).move_to_element(buttonVar).click(buttonVar ).perform()

except Exception as ex:
  print("button not found)

Firefox为您提供了几个可以与硒find_element或元素一起使用的选项；

1. 按f12调出检查器，
2. 使用左上角的“选择项目”图标选择要查看的项目。
3. 这将在检查器中突出显示该项目的文本，然后您可以右键单击以打开一个菜单，从中选择“复制”，其中至少有2个find_element选项，css_selecor和xpath。

我个人不喜欢xpath。 它们有时工作时间长且不规则，但任何适合您的风格。就我而言，css_selector可以正常工作。