Python implements page login verification and verification code identification function analysis for headless browser collection applications

Python implements page login verification and verification code identification function analysis for headless browser collection applications

With the continuous development of Internet technology, more and more applications Page login verification and verification code identification functions are adopted to improve security. When crawling and collecting data from these applications, we also need to solve these problems. This article will introduce how to use Python to implement a headless browser to handle page login verification and verification code identification for smooth data collection.

1. Introduction to headless browser

Headless browser is a browser that does not have a visual interface and is operated through programming. It can simulate human operating behaviors, including opening web pages, filling out forms, clicking buttons, etc., thereby realizing automated operations on web pages. Common headless browsers include Selenium and Puppeteer.

2. Installation and configuration of Selenium library

Selenium is a commonly used library for automated web testing. We can use it to implement page login verification and verification code recognition in crawlers. Function. First, you need to install the Selenium library, which can be installed using the pip command.

pip install selenium

Next, you need to download the corresponding browser driver. Selenium needs to interact with the browser through the browser driver. You can select the corresponding driver according to the browser you are using. For example, Chrome browser requires downloading ChromeDriver.

3. Page login verification processing

1. Import library

from selenium import webdriver

2. Create browser object

browser = webdriver.Chrome()

3. Open the login page

browser.get("https://example.com/login ")

4. Enter username and password

username_input = browser.find_element_by_id("username")
password_input = browser.find_element_by_id("password")

username_input.send_keys("your_username")
password_input.send_keys("your_password")

5. Click the login button

login_button = browser.find_element_by_css_selector(" input[type='submit']")
login_button.click()

6. Get the page content after login

page_content = browser.page_source

The above code uses the webdriver module of the Selenium library to create a Chrome browser object, then opens a login page, enters the username and password, and clicks the login button. Finally, the page content after login is obtained and can be further crawled and processed.

4. Verification code identification processing

Some applications will add verification codes in order to increase the security of login. At this time, we need to identify the verification code. Below is an example of simple verification code recognition implemented in Python.

1. Import library

import pytesseract
from PIL import Image

2. Load verification code image

image = Image.open("captcha.png")

3. Preprocessing image

image = image.convert('L')
image = image .point(lambda x: 0 if x

4. Perform verification code identification

code = pytesseract.image_to_string(image)

The above code uses the pytesseract library, which is an OCR (Optical Character Recognition, optical character recognition) tool that can recognize text in images into strings. Before recognition, we need to load the verification code image and preprocess the image, such as converting to grayscale, binarizing, etc., in order to improve the accuracy of recognition.

5. Complete sample code

The following is a complete sample code that uses a headless browser to collect application page login verification and verification code identification functions.

from selenium import webdriver
import pytesseract
from PIL import Image

# 创建浏览器对象
browser = webdriver.Chrome()

# 打开登录页面
browser.get("https://example.com/login")

# 输入用户名和密码
username_input = browser.find_element_by_id("username")
password_input = browser.find_element_by_id("password")
username_input.send_keys("your_username")
password_input.send_keys("your_password")

# 点击登录按钮
login_button = browser.find_element_by_css_selector("input[type='submit']")
login_button.click()

# 加载验证码图片
captcha_image = browser.find_element_by_css_selector(".captcha img")
captcha_image.screenshot("captcha.png")

# 预处理验证码图片
image = Image.open("captcha.png")
image = image.convert('L')
image = image.point(lambda x: 0 if x < 200 else 255)

# 进行验证码识别
code = pytesseract.image_to_string(image)
print("验证码识别结果：" + code)

# 输入验证码
captcha_input = browser.find_element_by_id("captcha")
captcha_input.send_keys(code)

# 点击验证码提交按钮
submit_button = browser.find_element_by_css_selector("input[name='captcha_submit']")
submit_button.click()

# 获取登录后的页面内容
page_content = browser.page_source
print(page_content)

# 关闭浏览器
browser.quit()

6. Summary

This article introduces how to use Python’s Selenium library and pytesseract library to implement page login verification and verification code identification functions for headless browser collection applications. Through the operation of a headless browser, we can simulate human behavior and realize automated operations on the login page. The verification code recognition function can help us overcome the verification codes added in some applications, so as to smoothly collect data. Through studying this article, I believe readers can handle these issues more flexibly and apply them to their own projects.

The above is the detailed content of Python implements page login verification and verification code identification function analysis for headless browser collection applications. For more information, please follow other related articles on the PHP Chinese website!