DEV Community

Cover image for Crawling Google Search Results - Part 1: Getting Started
Sam Zhang
Sam Zhang

Posted on • Edited on • Originally published at samzhangjy.now.sh

Crawling Google Search Results - Part 1: Getting Started

#python #tutorial

Crawling websites are always fun. Have you ever thought about crawling Google search results? Well, in this tutorial, you'll create a dead-simple web spider to crawl Google's search results using Python. I assume that you know the basics about Python, BeautifulSoup and requests.

WARNING: Don't ever use this spider to scrape lots of data. As of Google provides a public API that allows you to call 100 times for free, your IP will be banned if Google noticed the unusual traffic from your computer. This spider is built only for learning purposes, and it shouldn't be used in real projects. So keep that in mind, and we'll get started.

Getting Ready

First of all, install BeautifulSoup and requests using pip. I'll just skip that here 'cause I guess you guys know how to install them. Leave a comment if you are having trouble with installation.

Analyzing the Web Page

Search Google for something, for example, Python, and right-click to view the source code:

Google web results' source code

It's really a mess. Let's format it and remove the script tags and the style tags:

Formatted source code

Wow, still 2000 lines of code! Let's see what's really important.

Important Things

Search for Welcome to Python.org (the first result when searching Python):

search result 1

Then, search for Python (programming language) (the second result):

search result 2

We can see that the two results are styled by the class rc. Great, now we've found the important class name - let's move on.

Notice that most of the class names in Google are generated randomly by a script. Never analyze these class names: your work might be wasted after you refresh the page!

Going Further

So now we've got the result container, let's work on the details. Take a look at the result container, and you can see that the link is right in an a element inside a div styled with the class r:

result link

And the title in h3:

result title

...and finally the description in a span with class st and surrounded by two divs. The outer one is styled by the class s:

result description

Great! Now we've got the structure of the web page, and let's get to code!

Let's Code

Open your favorite code editor (I'm using VSCode), and open the folder you just created with the dependencies you just installed at the beginning of this tutorial. Create main.py and import the dependencies we needed:

# Import dependencies
from bs4 import BeautifulSoup
import requests
Enter fullscreen mode Exit fullscreen mode

And let's create a class to put all of our code in it:

class GoogleSpider(object):
    def __init__(self):
        """Crawl Google search results

        This class is used to crawl Google's search results using requests and BeautifulSoup.
        """
        super().__init__()

    def __get_source(self, url: str) -> requests.Response:
        """Get the web page's source code

        Args:
            url (str): The URL to crawl

        Returns:
            requests.Response: The response from URL
        """
        pass

    def search(self, query: str) -> list:
        """Search Google

        Args:
            query (str): The query to search for

        Returns:
            list: The search results
        """
        pass
Enter fullscreen mode Exit fullscreen mode

First, let's get the web page source. Take a look at the URL at your browser's address bar: there's lots of strange code that humans can't understand, right? Let's take them out and only leave the necessary ones:

https://www.google.com/search?q=Python
Enter fullscreen mode Exit fullscreen mode

If you visit it, you can see that the page is the same than you just visited! Alright, let's see what's in the URL.

Analyzing the URL

We can see that the URL above only has one query param: q. You can see it like the query you are going to search. But, there's a problem: when you enter special chars, like +, %, (, ), and so on, Google won't understand them. We need to quote them to the form that websites can understand. To quote them, we need to use the function quote from urllib.parse:

# Import dependencies
from bs4 import BeautifulSoup
import requests
from urllib.parse import quote
# ...
Enter fullscreen mode Exit fullscreen mode

Great, now we are ready to crawl the webpage!

Crawling the Web Page

It's pretty simple, you just need to call get() method from requests:

class GoogleSpider(object):
    # ...

    def __get_source(self, url: str) -> requests.Response:
        """Get the web page's source code

        Args:
            url (str): The URL to crawl

        Returns:
            requests.Response: The response from URL
        """
        return requests.get(url)

    # ...
Enter fullscreen mode Exit fullscreen mode

Let's test it:

# ...
class GoogleSpider(object):
    # ...

    def search(self, query: str) -> list:
        """Search Google

        Args:
            query (str): The query to search for

        Returns:
            list: The search results
        """
        return self.__get_source('https://www.google.com/search?q=%s' % quote(query))


if __name__ == '__main__':
    print(GoogleSpider().search('Python'))
Enter fullscreen mode Exit fullscreen mode

After you run the program, you'll likely be seeing the message below:

<Response [200]>
Enter fullscreen mode Exit fullscreen mode

It looks normal, right? But, when you look at its source code:

print(GoogleSpider().search('Python').text)
Enter fullscreen mode Exit fullscreen mode

You'll see that all of the class names are randomly generated! Don't worry, it's all because of one thing: the headers.

Configuring Headers

We need to define headers first. But, let's talk about headers now rather than coding. User-Agent headers are a special type of header that tells the website who requested this request. You can think like it's a name of the request sender. By default, requests will use python-requests/x.x.x, where as x.x.x is your requests version. A browser will send the User-Agent like this:

Mozilla/5.0 (Macintosh; Intel Mac OS X 10_14_6) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/84.0.4147.89 Safari/537.36
Enter fullscreen mode Exit fullscreen mode

The UA above was sent by a Google Chrome browser on macOS 10.14. So, if we pretend that we are the browser, using the UA, we can easily go pass this "gate".

Alright, then let's get coding!

We need to define the headers as I said above. Let's define it in the __init__ method:

class GoogleSpider(object):
    def __init__(self):
        """Crawl Google search results

        This class is used to crawl Google's search results using requests and BeautifulSoup.
        """
        super().__init__()
        self.headers = {
            'User-Agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10.14; rv:79.0) Gecko/20100101 Firefox/79.0',
            'Host': 'www.google.com',
            'Referer': 'https://www.google.com/'
        }

    # ...
Enter fullscreen mode Exit fullscreen mode

PS: I've added a few other headers to make us more "browser-like".

Then, we'll use the header to crawl Google:

class GoogleSpider(object):
    # ...

    def __get_source(self, url: str) -> requests.Response:
        """Get the web page's source code

        Args:
            url (str): The URL to crawl

        Returns:
            requests.Response: The response from URL
        """
        return requests.get(url, headers=self.headers)

    # ...
Enter fullscreen mode Exit fullscreen mode

Now you run the program again, you'll see the normal source code. Next, we'll start the most important part of this spider: analyze the source code.

Using BeautifulSoup To Analyze the Source

Since I assume that you know BeautifulSoup basics, let's dive in and start coding.

First of all, we need to define a variable to store the response, instead of returning them:

class GoogleSpider(object):
    # ...

    def search(self, query: str) -> list:
        """Search Google

        Args:
            query (str): The query to search for

        Returns:
            list: The search results
        """
        # Get response
        response = self.__get_source('https://www.google.com/search?q=%s' % quote(query))
Enter fullscreen mode Exit fullscreen mode

OK, then we'll initialize BS 4:

# Initialize BeautifulSoup
soup = BeautifulSoup(response.text, 'html.parser')
Enter fullscreen mode Exit fullscreen mode

Then, we'll have to locate the result containers using soup.findAll():

# Get the result containers
result_containers = soup.findAll('div', class_='rc')
Enter fullscreen mode Exit fullscreen mode

Finally, loop through every result and get the details:

# Final results list
results = []
# Loop through every container
for container in result_containers:
    # Result title
    title = container.find('h3').text
    # Result URL
    url = container.find('a')['href']
    # Result description
    des = container.find('span', class_='st').text
    results.append({
        'title': title,
        'url': url,
        'des': des
    })
Enter fullscreen mode Exit fullscreen mode

At last, return the results:

return results
Enter fullscreen mode Exit fullscreen mode

You can now run the program to see Google's search results. To search Google for different queries, you need to change the query param to the query you wanted to search for.

Full Code

The full code for this tutorial is below.

# Import dependencies
from bs4 import BeautifulSoup
import requests
from urllib.parse import quote
from pprint import pprint


class GoogleSpider(object):
    def __init__(self):
        """Crawl Google search results

        This class is used to crawl Google's search results using requests and BeautifulSoup.
        """
        super().__init__()
        self.headers = {
            'User-Agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10.14; rv:79.0) Gecko/20100101 Firefox/79.0',
            'Host': 'www.google.com',
            'Referer': 'https://www.google.com/'
        }

    def __get_source(self, url: str) -> requests.Response:
        """Get the web page's source code

        Args:
            url (str): The URL to crawl

        Returns:
            requests.Response: The response from URL
        """
        return requests.get(url, headers=self.headers)

    def search(self, query: str) -> list:
        """Search Google

        Args:
            query (str): The query to search for

        Returns:
            list: The search results
        """
        # Get response
        response = self.__get_source('https://www.google.com/search?q=%s' % quote(query))
        # Initialize BeautifulSoup
        soup = BeautifulSoup(response.text, 'html.parser')
        # Get the result containers
        result_containers = soup.findAll('div', class_='rc')
        # Final results list
        results = []
        # Loop through every container
        for container in result_containers:
            # Result title
            title = container.find('h3').text
            # Result URL
            url = container.find('a')['href']
            # Result description
            des = container.find('span', class_='st').text
            results.append({
                'title': title,
                'url': url,
                'des': des
            })
        return results


if __name__ == '__main__':
    pprint(GoogleSpider().search(input('Search for what? ')))
Enter fullscreen mode Exit fullscreen mode

Conclusion

Of course, I know that this is really simple: it can't crawl video results, news results, picture results, and so on. But, it is a great template for learning web scraping in Python. Hope you enjoy this tutorial, and leave a comment if you are having trouble with anything in this tutorial.

Top comments (3)

Collapse
 
cannuhlar profile image
Can Nuhlar • • Edited

This seems like a good educational post but keep that in mind; crawling Google results are against Google's TOS and your IP will get blacklisted in no time. They provide a free API for querying but only for 100 queries per day if you exceed this amount then you have to pay for it.

Collapse
 
samzhangjy profile image
Sam Zhang •

Yes, I know. This is just for fun and I'm certainly not going to use it for crawling lots of information. I'll add this to the post later, and thank you!

Collapse
 
baweja_media_1fd4226087b3 profile image
Baweja Media •

Great article! Crawling Google Search Results is crucial for understanding SEO. It’s the first step to optimizing website visibility. Looking forward to Part 2 for more insights on advanced techniques. Understanding crawling is fundamental for anyone serious about improving their online presence. For more valuable resources and services similar to our discussion, explore bawejamedia.com/

Read next

leandroveiga profile image

Mastering Error Handling in .NET 8: Strategies for Minimal APIs and Controllers

Leandro Veiga -

mshsayket profile image

How to Install Bootstrap 5 in Laravel 11 with Vite?

Saddam Hossain -

muash10 profile image

Using Stable Diffusion in AWS Bedrock to Generate Images

Muhammed Ashraf -

linediconsine profile image

Quick and Dirty Guide to Running a Local LLM and Making API Requests

Marco -