Recently, with the development of Internet crawler technology, more and more companies and individuals have begun to use crawlers to obtain website information and help analyze business data, competitive product analysis, etc. In actual crawler development, it is often necessary to quickly generate a simple crawler code to quickly implement data collection. This article will introduce the introductory practice of implementing crawlers using PHP and Selenium, and provide a library that automatically generates crawler examples.
Selenium is a tool for web application testing. Selenium test scripts can be run directly on the browser to simulate user operations, such as Open web pages, click, type, etc. Selenium provides drivers in multiple languages, including Java, Python, Ruby, PHP, etc., which you can choose according to your own programming language preferences.
In practice, we first need to configure the following environment and tools:
The first is the installation of the PHP environment. The installation method is different for each operating system, so I won’t go into details here. After installing PHP, we need to install Composer, a PHP package manager that can quickly install PHP extensions and class libraries.
Selenium provides a variety of drivers, including ChromeDriver, FirefoxDriver, etc. Here we take ChromeDriver as an example. ChromeDriver is the WebDriver implementation of the Chrome browser and corresponds to the browser version one-to-one. First, you need to install the Chrome browser, check the Chrome browser version, and then go to the ChromeDriver official website to download the corresponding version of the driver.
After installing the necessary software, we can start to implement a simple crawler. Suppose we need to crawl product information on an e-commerce platform, including product name and price. Take Taobao as an example:
First, install Selenium and ChromeDriver in cmd or terminal:
composer require facebook/webdriver:dev-master
Then write a PHP script:
<?php require_once 'vendor/autoload.php'; use FacebookWebDriverRemoteRemoteWebDriver; use FacebookWebDriverWebDriverBy; // 配置ChromeDriver $host = 'http://localhost:9515'; $capabilities = array(FacebookWebDriverRemoteWebDriverCapabilityType::BROWSER_NAME => 'chrome'); $driver = RemoteWebDriver::create($host, $capabilities); // 打开网页 $driver->get('https://www.taobao.com'); // 输入搜索关键字 $input = $driver->findElement(WebDriverBy::name('q')); $input->click(); $input->sendKeys('电视机'); // 点击搜索按钮 $button = $driver->findElement(WebDriverBy::cssSelector('.btn-search')); $button->click(); // 获取商品名称和价格 $items = $driver->findElements(WebDriverBy::cssSelector('.item')); foreach ($items as $item) { $name = $item->findElement(WebDriverBy::cssSelector('.title'))->getText(); $price = $item->findElement(WebDriverBy::cssSelector('.price'))->getText(); echo $name . ' ' . $price . PHP_EOL; } // 退出ChromeDriver $driver->quit();
The logic of this script is very simple, First configure ChromeDriver and open the web page that needs to be crawled, and then find and process the required information based on the selector of the page element.
The above is just the most basic crawler practice. If you need to crawl information from other websites, you need to modify the code according to the specific situation. For common e-commerce websites like Taobao and JD.com, they often already have a certain page structure and elements, so you can try to generate the corresponding crawler code through automation.
Since we want to automatically generate a crawler example, we need a set of input and output, where the input is the website to be crawled and the output is the crawler code. Therefore, we can use end-to-end learning to map the website and crawler code using machine learning models.
Specifically, we can collect a large number of e-commerce websites and corresponding crawler codes, annotate the websites (mark the specific information and elements to be crawled), and then use the neural network model to train the data. The trained model can automatically generate corresponding crawler code based on the input website.
In the process of automatically generating crawler examples, many skills are involved, including data crawling, data annotation, neural network model training, etc. Therefore, we can use the platform provided by AI2 Notebook (https://github.com/GuiZhiHuai/AI2) to implement it based on our own needs and skills.
This article introduces the introductory practice of using PHP and Selenium to implement a simple crawler, and provides ideas and methods for automatically generating crawler examples. If you are interested in crawler development and AI technology, you can explore it in depth in practice, and I believe there will be more interesting discoveries and applications.
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