How to Build Web scraping bot in Python


How to Build Web scraping bot in Python

In this article, we are going to see how to build a web scraping bot in Python.

Web Scraping is a process of extracting data from websites. A Bot is a piece of code that will automate our task. Therefore, A web scraping bot is a program that will automatically scrape a website for data, based on our requirements.

Module needed

    : Beautiful Soup(bs4) is a Python library for pulling data out of HTML and XML files. This module does not come built-in with Python. To install this type the below command in the terminal.
    : Request allows you to send HTTP/1.1 requests extremely easily. This module also does not come built-in with Python. To install this type the below command in the terminal.
    : Selenium is one of the most popular automation testing tools. It can be used to automate browsers like Chrome, Firefox, Safari, etc.

Method 1: Using Selenium

We need to install a chrome driver to automate using selenium, our task is to create a bot that will be continuously scraping the google news website and display all the headlines every 10mins.

Stepwise implementation:

Step 1: First we will import some required modules.

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Step 2: The next step is to open the required website.

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Output:

Step 3: Extracting the news title from the webpage, to extract a specific part of the page, we need its XPath, which can be accessed by right-clicking on the required element and selecting Inspect in the dropdown bar.

After clicking Inspect a window appears. From there, we have to copy the elements full XPath to access it:

Note: You might not always get the exact element that you want by inspecting (depends on the structure of the website), so you may have to surf the HTML code for a while to get the exact element you want. And now, just copy that path and paste that into your code. After running all these lines of code, you will get the title of the first heading printed on your terminal.

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Output:

‘Attack on Afghan territory’: Taliban on US airstrike that killed 2 ISIS-K men

Step 4: Now, the target is to get the X_Paths of all the headlines present.

One way is that we can copy all the XPaths of all the headlines (about 6 headlines will be there in google news every time) and we can fetch all those, but that method is not suited if there are a large number of things to be scrapped. So, the elegant way is to find the pattern of the XPaths of the titles which will make our tasks way easier and efficient. Below are the XPaths of all the headlines on the website, and let’s figure out the pattern.

/html/body/c-wiz/div/div[2]/div[2]/div/main/c-wiz/div[1]/div[3]/div/div/article/h3/a

/html/body/c-wiz/div/div[2]/div[2]/div/main/c-wiz/div[1]/div[4]/div/div/article/h3/a

/html/body/c-wiz/div/div[2]/div[2]/div/main/c-wiz/div[1]/div[5]/div/div/article/h3/a

/html/body/c-wiz/div/div[2]/div[2]/div/main/c-wiz/div[1]/div[6]/div/div/article/h3/a

/html/body/c-wiz/div/div[2]/div[2]/div/main/c-wiz/div[1]/div[7]/div/div/article/h3/a

/html/body/c-wiz/div/div[2]/div[2]/div/main/c-wiz/div[1]/div[8]/div/div/article/h3/a

So, by seeing these XPath’s, we can see that only the 5th div is changing (bolded ones). So based upon this, we can generate the XPaths of all the headlines. We will get all the titles from the page by accessing them with their XPath. So to extract all these, we have the code as


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