Detailed explanation of python3 Baidu index crawling example-Python Tutorial-php.cn

This article mainly introduces python3 Baidu index crawling. The editor thinks it is quite good. Now I will share it with you and give it as a reference. Let’s follow the editor to have a look.

Catch the Baidu index, and then use image recognition to get the index

Foreword:

Tufu once said that the Baidu index is difficult to grasp. On Taobao, it costs 20 yuan per unit. Keywords:

Detailed explanation of python3 Baidu index crawling example

How could someone be frightened by someone with such a big mouth, so it took me about 2 and a half days to complete it. I despise Tufu

There are many installed libraries:

谷歌图像识别tesseract-ocr

pip3 install pillow

pip3 install pyocr

selenium2.45

Chrome47.0.2526.106 m or Firebox32.0.1

chromedriver.exe

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You need to log in to enter the Baidu Index. The login account and password are written in the text account:

Detailed explanation of python3 Baidu index crawling example

The universal login code is as follows:

# 打开浏览器
def openbrowser():
  global browser

  # http://www.php.cn/
  url = "https://passport.baidu.com/v2/?login&tpl=mn&u=http%3A%2F%2Fwww.baidu.com%2F"
  # 打开谷歌浏览器
  # Firefox()
  # Chrome()
  browser = webdriver.Chrome()
  # 输入网址
  browser.get(url)
  # 打开浏览器时间
  # print("等待10秒打开浏览器...")
  # time.sleep(10)

  # 找到id="TANGRAM__PSP_3__userName"的对话框
  # 清空输入框
  browser.find_element_by_id("TANGRAM__PSP_3__userName").clear()
  browser.find_element_by_id("TANGRAM__PSP_3__password").clear()

  # 输入账号密码
  # 输入账号密码
  account = []
  try:
    fileaccount = open("../baidu/account.txt")
    accounts = fileaccount.readlines()
    for acc in accounts:
      account.append(acc.strip())
    fileaccount.close()
  except Exception as err:
    print(err)
    input("请正确在account.txt里面写入账号密码")
    exit()
  browser.find_element_by_id("TANGRAM__PSP_3__userName").send_keys(account[0])
  browser.find_element_by_id("TANGRAM__PSP_3__password").send_keys(account[1])

  # 点击登陆登陆
  # id="TANGRAM__PSP_3__submit"
  browser.find_element_by_id("TANGRAM__PSP_3__submit").click()

  # 等待登陆10秒
  # print(&#39;等待登陆10秒...&#39;)
  # time.sleep(10)
  print("等待网址加载完毕...")

  select = input("请观察浏览器网站是否已经登陆(y/n)：")
  while 1:
    if select == "y" or select == "Y":
      print("登陆成功！")
      print("准备打开新的窗口...")
      # time.sleep(1)
      # browser.quit()
      break

    elif select == "n" or select == "N":
      selectno = input("账号密码错误请按0，验证码出现请按1...")
      # 账号密码错误则重新输入
      if selectno == "0":

        # 找到id="TANGRAM__PSP_3__userName"的对话框
        # 清空输入框
        browser.find_element_by_id("TANGRAM__PSP_3__userName").clear()
        browser.find_element_by_id("TANGRAM__PSP_3__password").clear()

        # 输入账号密码
        account = []
        try:
          fileaccount = open("../baidu/account.txt")
          accounts = fileaccount.readlines()
          for acc in accounts:
            account.append(acc.strip())
          fileaccount.close()
        except Exception as err:
          print(err)
          input("请正确在account.txt里面写入账号密码")
          exit()

        browser.find_element_by_id("TANGRAM__PSP_3__userName").send_keys(account[0])
        browser.find_element_by_id("TANGRAM__PSP_3__password").send_keys(account[1])
        # 点击登陆sign in
        # id="TANGRAM__PSP_3__submit"
        browser.find_element_by_id("TANGRAM__PSP_3__submit").click()

      elif selectno == "1":
        # 验证码的id为id="ap_captcha_guess"的对话框
        input("请在浏览器中输入验证码并登陆...")
        select = input("请观察浏览器网站是否已经登陆(y/n)：")

    else:
      print("请输入“y”或者“n”！")
      select = input("请观察浏览器网站是否已经登陆(y/n)：")

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Detailed explanation of python3 Baidu index crawling example

After logging in, you need to open a new window, that is, open the Baidu Index and switch windows. Use selenium:

# 新开一个窗口，通过执行js来新开一个窗口
js = &#39;window.open("http://index.baidu.com");&#39;
browser.execute_script(js)
# 新窗口句柄切换，进入百度指数
# 获得当前打开所有窗口的句柄handles
# handles为一个数组
handles = browser.window_handles
# print(handles)
# 切换到当前最新打开的窗口
browser.switch_to_window(handles[-1])

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Clear the input box and construct the number of click days:

# 清空输入框
browser.find_element_by_id("schword").clear()
# 写入需要搜索的百度指数
browser.find_element_by_id("schword").send_keys(keyword)
# 点击搜索
# <input type="submit" value="" id="searchWords" onclick="searchDemoWords()">
browser.find_element_by_id("searchWords").click()
time.sleep(2)
# 最大化窗口
browser.maximize_window()
# 构造天数
sel = int(input("查询7天请按0，30天请按1，90天请按2，半年请按3："))
day = 0
if sel == 0:
  day = 7
elif sel == 1:
  day = 30
elif sel == 2:
  day = 90
elif sel == 3:
  day = 180
sel = &#39;//a[@rel="&#39; + str(day) + &#39;"]&#39;
browser.find_element_by_xpath(sel).click()
# 太快了
time.sleep(2)

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The number of days is here:

Detailed explanation of python3 Baidu index crawling example

Find the graphics box:

xoyelement = browser.find_elements_by_css_selector("#trend rect")[2]

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The graphics box is:

Detailed explanation of python3 Baidu index crawling example

Construct offsets based on different coordinate points:

Detailed explanation of python3 Baidu index crawling example

Select the coordinates of 7 days to observe:

The abscissa of one point is 1031.66666

The abscissa of the second point is 1234

Detailed explanation of python3 Baidu index crawling example

##So the distance between the two coordinates is 7 days The difference is: 202.33, other days are similar

Use selenium library to simulate mouse sliding suspension:

from selenium.webdriver.common.action_chains import ActionChains
ActionChains(browser).move_to_element_with_offset(xoyelement,x_0,y_0).perform()

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But this is sure The point is pointed out at this position:

Detailed explanation of python3 Baidu index crawling example , which is the upper left corner of the rectangle. The js will not be loaded here to display the pop-up box, so the abscissa + 1:

x_0 = 1
y_0 = 0

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Write a cycle based on the number of days and let the abscissa accumulate:

# 按照选择的天数循环
for i in range(day):
  # 构造规则
  if day == 7:
    x_0 = x_0 + 202.33
  elif day == 30:
    x_0 = x_0 + 41.68
  elif day == 90:
    x_0 = x_0 + 13.64
  elif day == 180:
    x_0 = x_0 + 6.78

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A box will pop up when the mouse moves horizontally. Find this box in the URL:

Detailed explanation of python3 Baidu index crawling example Selenium automatically recognizes...:

# <p class="imgtxt" style="margin-left:-117px;"></p>
imgelement = browser.find_element_by_xpath(&#39;//p[@id="viewbox"]&#39;)

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And determine the size and position of this box:

# 找到图片坐标
locations = imgelement.location
print(locations)
# 找到图片大小
sizes = imgelement.size
print(sizes)
# 构造指数的位置
rangle = (int(locations[&#39;x&#39;]), int(locations[&#39;y&#39;]), int(locations[&#39;x&#39;] + sizes[&#39;width&#39;]),
     int(locations[&#39;y&#39;] + sizes[&#39;height&#39;]))

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The intercepted graphic is:

Detailed explanation of python3 Baidu index crawling example
The following idea is:

1. Take a screenshot of the entire screen

2. Open the screenshot and use the coordinate range obtained above to crop it

But the final crop is the black frame above. The effect I want is:

Detailed explanation of python3 Baidu index crawling example So I need to calculate the range, but I am lazy and ignore the length of the search term, so I directly write violently:

# 构造指数的位置
rangle = (int(locations[&#39;x&#39;] + sizes[&#39;width&#39;]/3), int(locations[&#39;y&#39;] + sizes[&#39;height&#39;]/2), int(locations[&#39;x&#39;] + sizes[&#39;width&#39;]*2/3),
     int(locations[&#39;y&#39;] + sizes[&#39;height&#39;]))

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这个写法最终不太好，最起码要对keyword的长度进行判断，长度过长会导致截图坐标出现偏差，反正我知道怎么做，就是不写出来给你们看！

后面的完整代码是：

# <p class="imgtxt" style="margin-left:-117px;"></p>
imgelement = browser.find_element_by_xpath(&#39;//p[@id="viewbox"]&#39;)
# 找到图片坐标
locations = imgelement.location
print(locations)
# 找到图片大小
sizes = imgelement.size
print(sizes)
# 构造指数的位置
rangle = (int(locations[&#39;x&#39;] + sizes[&#39;width&#39;]/3), int(locations[&#39;y&#39;] + sizes[&#39;height&#39;]/2), int(locations[&#39;x&#39;] + sizes[&#39;width&#39;]*2/3),
     int(locations[&#39;y&#39;] + sizes[&#39;height&#39;]))
# 截取当前浏览器
path = "../baidu/" + str(num)
browser.save_screenshot(str(path) + ".png")
# 打开截图切割
img = Image.open(str(path) + ".png")
jpg = img.crop(rangle)
jpg.save(str(path) + ".jpg")

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但是后面发现裁剪的图片太小，识别精度太低，所以需要对图片进行扩大：

# 将图片放大一倍
# 原图大小73.29
jpgzoom = Image.open(str(path) + ".jpg")
(x, y) = jpgzoom.size
x_s = 146
y_s = 58
out = jpgzoom.resize((x_s, y_s), Image.ANTIALIAS)
out.save(path + &#39;zoom.jpg&#39;, &#39;png&#39;, quality=95)

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原图大小请右键->属性->详细信息查看，我的是长73像素，宽29像素

最后就是图像识别

# 图像识别
index = []
image = Image.open(str(path) + "zoom.jpg")
code = pytesseract.image_to_string(image)
if code:
  index.append(code)

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最后效果图：

Detailed explanation of python3 Baidu index crawling example

以上就是本文的全部内容，希望对大家的学习有所帮助，也希望大家多多支持PHP中文网。

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