search
HomeBackend DevelopmentPython TutorialHow to use Mozilla Firefox in Scrapy to solve the problem of scanning QR code to log in?

For crawlers to crawl websites that require login, verification code or scan code login is a very troublesome problem. Scrapy is a very easy-to-use crawler framework in Python, but when processing verification codes or scanning QR codes to log in, some special measures need to be taken. As a common browser, Mozilla Firefox provides a solution that can help us solve this problem.

The core module of Scrapy is twisted, which only supports asynchronous requests, but some websites need to use cookies and sessions to stay logged in, so we need to use Mozilla Firefox to handle these problems.

First, we need to install the Mozilla Firefox browser and the corresponding Firefox driver in order to use it in Python. The installation command is as follows:

pip install selenium

Then, we need to add some settings to the crawler's settings.py file in order to use the Firefox browser to scan the QR code to log in. The following is a sample setting:

DOWNLOADER_MIDDLEWARES = {
'scrapy.downloadermiddlewares.cookies.CookiesMiddleware':700,
'scrapy_selenium.SeleniumMiddleware':800,
}

SELENIUM_DRIVER_NAME = 'firefox'
SELENIUM_DRIVER_EXECUTABLE_PATH = which('geckodriver')
SELENIUM_BROWSER_EXECUTABLE_PATH = '/usr/bin/firefox'

We can set it according to our own operating system and Firefox installation path.

Next, we need to create a custom Scrapy Spider class to use the Firefox browser in it. In this class, we need to set some options for the Firefox browser, as shown below:

from selenium import webdriver
from scrapy.selector import Selector
from scrapy.spiders import CrawlSpider
from scrapy.http import Request

class MySpider(CrawlSpider):
   name = 'myspider'

   def __init__(self):
      self.driver = webdriver.Firefox(executable_path='geckodriver', firefox_binary='/usr/bin/firefox')
      self.driver.set_window_size(1400, 700)
      self.driver.set_page_load_timeout(30)
      self.driver.set_script_timeout(30)

   def parse(self, response):
      # 网站首页处理代码
      pass

In this custom Spider class, we use the selenium.webdriver.Firefox class to create a Firefox browser control device object. The Firefox browser controller object is used to open the home page of the website and can also perform other operations as needed.

For websites that require scanning QR codes to log in, we can use the Firefox browser to identify the QR code on the page and wait for the scanning result of the QR code. We can use Selenium to simulate user behavior in Python to scan the QR code and log in to the website. The complete code scanning login code is as follows:

def parse(self, response):
   self.driver.get(response.url)
   # 等待页面加载完成
   time.sleep(5)
   # 寻找二维码及其位置
   frame = self.driver.find_element_by_xpath('//*[@class="login-qr-code iframe-wrap"]//iframe')
   self.driver.switch_to.frame(frame)
   qr_code = self.driver.find_element_by_xpath('//*[@id="login-qr-code"]/img')
   position = qr_code.location
   size = qr_code.size

   while True:
      # 判断是否已经扫描了二维码,
      # 如果扫描了,登录,并跳出循环
      try:
         result = self.driver.find_element_by_xpath('//*[@class="login-qr-code-close"]')
         result.click()
         break
      except:
         pass

      # 如果没有扫描,等待并继续寻找
      time.sleep(5)


   # 登录后处理的代码
   pass

In the above code, we first use the self.driver.get() method to open the homepage of the website, and then use the find_element_by_xpath() method to find the QR code element. Get its position and size. Then use a while loop to wait for the QR code scanning result. If it has been scanned, click the close button on the QR code and jump out of the loop. If there is no scan, wait 5 seconds and continue searching.

When the QR code scanning results are available, we can execute our own login logic. The specific processing method depends on the actual situation of the website.

In short, when using Scrapy for crawler development, if we encounter a website that requires login, and the website uses a verification code or scan code to log in, we can use the above method to solve this problem. Using Selenium and Firefox browsers, we can simulate user operations, handle QR code login issues, and obtain the required data.

The above is the detailed content of How to use Mozilla Firefox in Scrapy to solve the problem of scanning QR code to log in?. For more information, please follow other related articles on the PHP Chinese website!

Statement
The content of this article is voluntarily contributed by netizens, and the copyright belongs to the original author. This site does not assume corresponding legal responsibility. If you find any content suspected of plagiarism or infringement, please contact admin@php.cn
Python vs. C  : Learning Curves and Ease of UsePython vs. C : Learning Curves and Ease of UseApr 19, 2025 am 12:20 AM

Python is easier to learn and use, while C is more powerful but complex. 1. Python syntax is concise and suitable for beginners. Dynamic typing and automatic memory management make it easy to use, but may cause runtime errors. 2.C provides low-level control and advanced features, suitable for high-performance applications, but has a high learning threshold and requires manual memory and type safety management.

Python vs. C  : Memory Management and ControlPython vs. C : Memory Management and ControlApr 19, 2025 am 12:17 AM

Python and C have significant differences in memory management and control. 1. Python uses automatic memory management, based on reference counting and garbage collection, simplifying the work of programmers. 2.C requires manual management of memory, providing more control but increasing complexity and error risk. Which language to choose should be based on project requirements and team technology stack.

Python for Scientific Computing: A Detailed LookPython for Scientific Computing: A Detailed LookApr 19, 2025 am 12:15 AM

Python's applications in scientific computing include data analysis, machine learning, numerical simulation and visualization. 1.Numpy provides efficient multi-dimensional arrays and mathematical functions. 2. SciPy extends Numpy functionality and provides optimization and linear algebra tools. 3. Pandas is used for data processing and analysis. 4.Matplotlib is used to generate various graphs and visual results.

Python and C  : Finding the Right ToolPython and C : Finding the Right ToolApr 19, 2025 am 12:04 AM

Whether to choose Python or C depends on project requirements: 1) Python is suitable for rapid development, data science, and scripting because of its concise syntax and rich libraries; 2) C is suitable for scenarios that require high performance and underlying control, such as system programming and game development, because of its compilation and manual memory management.

Python for Data Science and Machine LearningPython for Data Science and Machine LearningApr 19, 2025 am 12:02 AM

Python is widely used in data science and machine learning, mainly relying on its simplicity and a powerful library ecosystem. 1) Pandas is used for data processing and analysis, 2) Numpy provides efficient numerical calculations, and 3) Scikit-learn is used for machine learning model construction and optimization, these libraries make Python an ideal tool for data science and machine learning.

Learning Python: Is 2 Hours of Daily Study Sufficient?Learning Python: Is 2 Hours of Daily Study Sufficient?Apr 18, 2025 am 12:22 AM

Is it enough to learn Python for two hours a day? It depends on your goals and learning methods. 1) Develop a clear learning plan, 2) Select appropriate learning resources and methods, 3) Practice and review and consolidate hands-on practice and review and consolidate, and you can gradually master the basic knowledge and advanced functions of Python during this period.

Python for Web Development: Key ApplicationsPython for Web Development: Key ApplicationsApr 18, 2025 am 12:20 AM

Key applications of Python in web development include the use of Django and Flask frameworks, API development, data analysis and visualization, machine learning and AI, and performance optimization. 1. Django and Flask framework: Django is suitable for rapid development of complex applications, and Flask is suitable for small or highly customized projects. 2. API development: Use Flask or DjangoRESTFramework to build RESTfulAPI. 3. Data analysis and visualization: Use Python to process data and display it through the web interface. 4. Machine Learning and AI: Python is used to build intelligent web applications. 5. Performance optimization: optimized through asynchronous programming, caching and code

Python vs. C  : Exploring Performance and EfficiencyPython vs. C : Exploring Performance and EfficiencyApr 18, 2025 am 12:20 AM

Python is better than C in development efficiency, but C is higher in execution performance. 1. Python's concise syntax and rich libraries improve development efficiency. 2.C's compilation-type characteristics and hardware control improve execution performance. When making a choice, you need to weigh the development speed and execution efficiency based on project needs.

See all articles

Hot AI Tools

Undresser.AI Undress

Undresser.AI Undress

AI-powered app for creating realistic nude photos

AI Clothes Remover

AI Clothes Remover

Online AI tool for removing clothes from photos.

Undress AI Tool

Undress AI Tool

Undress images for free

Clothoff.io

Clothoff.io

AI clothes remover

Video Face Swap

Video Face Swap

Swap faces in any video effortlessly with our completely free AI face swap tool!

Hot Tools

MinGW - Minimalist GNU for Windows

MinGW - Minimalist GNU for Windows

This project is in the process of being migrated to osdn.net/projects/mingw, you can continue to follow us there. MinGW: A native Windows port of the GNU Compiler Collection (GCC), freely distributable import libraries and header files for building native Windows applications; includes extensions to the MSVC runtime to support C99 functionality. All MinGW software can run on 64-bit Windows platforms.

Dreamweaver Mac version

Dreamweaver Mac version

Visual web development tools

Safe Exam Browser

Safe Exam Browser

Safe Exam Browser is a secure browser environment for taking online exams securely. This software turns any computer into a secure workstation. It controls access to any utility and prevents students from using unauthorized resources.

SublimeText3 Mac version

SublimeText3 Mac version

God-level code editing software (SublimeText3)

ZendStudio 13.5.1 Mac

ZendStudio 13.5.1 Mac

Powerful PHP integrated development environment