What Is a Web Crawler in Python?

Web crawlers have been around since 1993, and even though many internet users aren’t aware of their existence, they play a crucial role in making the Web work.

Crawling bots are programs that constantly browse the internet web pages, looking for the freshest content. Each time you request to see a web page on Google, the world’s largest, most popular search engine, relies on web crawlers to find and display the results you requested. Crawlers provide Google with an abundant source of the latest, most up-to-date data it needs to fulfill its purpose. 

They also help organize the data on the web and can be used for a wide range of different purposes. Since they are so important, let’s talk about what a web crawler is, the most common uses, and how to build one in the Python programming language.

Introduction to web crawlers

What is a web crawler?

Since this is a fairly frequent question, here is a simple answer. A web crawler is a software tool programmed to systematically and automatically browse the web to find the most relevant web pages with the most up-to-date content. 

The largest search engines use web crawlers to keep their databases updated with the latest content. Web crawlers are also called spiders, crawling bots, and internet robots. They are designed to browse, find, download, and index the latest data from countless web pages and store it in their local repositories. 

Aside from checking the content freshness across millions of web pages, web crawlers also perform many tasks, such as discovering security issues in the structure of web pages and running tests on websites and web apps. 

They can recognize multiple data formats and bypass crawler honeypots to fetch data from top-grade websites. They also recognize various GET parameters, bypass anti-recrawling mechanisms, and make a business website more SEO-friendly by eliminating duplicate content. 

The latest, most advanced crawlers can detect even the slightest changes in data frequency and adjust their crawling strategies to avoid overloading web servers.

You can read the article here to find out more about what is a web crawler.

Common uses of web crawlers

Search engines, such as Yandex, Bing, and Google, use web crawling bots to gather all the HTML data and make more websites and web pages indexed and searchable. Businesses can benefit from the use of web crawlers as well. 

Here are a few of the most common use cases of web crawlers.


You can use web crawlers for SEO monitoring and analytics. On top of collecting the HTML information, crawlers can also collect keywords and metadata like the web page loading and response time. Search engines rely on crawlers to detect broken links and remove outdated and unresponsive web pages.

Price and competitor monitoring

Crawling e-commerce websites is an excellent way to extract top-quality data regarding product pricing and the latest pricing strategies used by your competitors. You can use them to extract data on the latest pricing strategies by periodically revisiting competitors’ product pages.

Lead generation

In the game of lead generation, data is the key factor that determines the quality of your leads. Since the only way to acquire the data you need to play the game is to get it from the web, you need a tool that can ensure quick and accurate access to the best data sources on the internet. 

That’s where web crawlers can help. They can improve your SEO and make your website more Google-friendly by ranking it higher in the search results and making it more visible to internet users.

Building a scraper in Python

The first step towards building a scraper in Python is providing a library for downloading and storing the HTML from the URL and one library for the HTML parsing to extract links. Python has its standard URLlib libraries for HTML requests and html.parser for parsing HTML. 

Start by installing the two libraries on your machine using the following command: “pip install requests bs4”. You can also use a pre-written architecture diagram to build a basic crawler in Python, define its class, and run it on your terminal.

Consider using a pre-built scraper 

Another way to build your web scraper is to use a pre-built scraper with a Python framework. One of the advantages of using a pre-built scraper is that it can handle and schedule user requests asynchronously. 

Tools like Scrapy can send multiple requests without completing the previous ones and handle concurrent requests simultaneously. The best thing about tools like Scrapy is that you can configure them according to the target website’s custom settings.

Multi-component architecture

Scrapy’s multi-component architecture allows the user to implement two different classes of web crawlers: Spider and Pipeline. Since web scraping is nothing more than a data extraction technique where you extract data from the web and store it, spiders are in charge of extracting data while pipelines load it into your storage.


Python is probably the best programming language for building both web scrapers and crawlers due to its third-party libraries for parsing HTML and downloading URLs. Since you can easily customize its web crawling framework with your custom code, you can build a crawler in Python and configure it to crawl millions of web pages without any problems.

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