Python Web Scraping

The process of drawing out data from the web using bots is called web scraping. This process will extract the HTML code lying beneath along with the stored database. Web scraping is a completely different process than screen scraping as screen scraping just extracts the data as pixels present on the screen. The only thing one should be very particular about is doing web scraping using ethical ways. Web scraping can be good as well as bad, however, if used in a good way then web scraping is very helpful in getting data from the internet. The most real-time example of web scraping is the google search engine.

Python Web Scraping

As we are aware, python is a multi-purpose language. The tools in python have the ability to build a feasible web scraper that won't just extract data but will do so much more. Web scraping using python can support a number of processes such as data extraction, data parsing, and data visualization. These processes are however difficult to conduct if done using some other language.

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Uses of Web Scraping

There are endless uses of web scraping, whether we talk about business use or personal use. The tools associated with Web Scraping Software can list out a number of pages within an internet site and simply motorize the monotonous work of copying-pasting the data manually. The data derived from web scraping is downloaded in the form of a spreadsheet, mainly in a table format.

There are some areas where web scraping is very helpful. Let's discuss this in the section below:

Price Comparison: 

There are a few websites these days that help a customer in comparing the prices of the items, ditching the old traditional method of doing it manually. Customers can now search on the web and find the best price for the required services without compromising the quality.

Email Address Gathering:

Using web scraping tools, people are now able to export emails in the form of an excel sheet easily. This is done simply by selecting the required lead sources carefully which will form a high-quality email list instantly.

Social Media Scraping: 

There are some special bots designed to scrape data from social media. The bots help in browsing various social media websites and platforms. Hence they extract the required information as they are commanded to gather.

Research and Development:

Web scraping can be used for research in the areas where data needs to be extracted from the websites for some research-based project. Before the development process, research is a very important part of the process in order to move ahead. Hence web scraping plays an important role in research and development.

Job Listings:

Web scraping for job search and postings is very essential to gather a huge number of job postings from all over the world. This is done by extracting feeds from different websites online and that is displayed on a job board created for various job postings under one platform. These, therefore, help the job finders to crawl and find this data from these sourced websites containing all the related data.

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Is Python Web scraping Legal

A number of multinational companies do scrapping from the web for the extraction of data which is required to undergo various important decisions in the company. Web scraping will not just allow them to extract the wise data but will also help in certain fields such as investment opportunities, development of products, solutions delivery, and market research.

Web scraping is therefore not 100% legal to work with, however, a person has to follow certain ethics to do web scraping. There are a set of rules one needs to follow while extracting the data from the web. Also, the person should be well aware of the data he is trying to extract. An informed decision has to be made whether that data being scraped is public or personal. For example, if a person has a personal profile on social media or says Linkedin, that information is illegal to extract or use further.

Below is some set of rules which define that data is public and can be used: 

  • The person who has put in the data has mentioned that this data is not personal and can be used further anywhere.
  • When a person does not need to create any personal account to access the data. Any kind of login activity is the personal data of an individual.
  • There are certain websites that ask for permission and make the data available to the user. The user needs to be careful before clicking yes on such websites which take in your personal information.

Reasons for Web scraping

Let us understand the reasons for web scraping through an example. Let’s assume a person is a surfer and he is looking for jobs both online as well as offline. He is not interested in random jobs but will have complete dedication and a full mindset, he is waiting for his golden chance that rolls his way to a successful career. Then, he finds a website that is well known for offering jobs, especially the type of jobs he is looking for. Unfortunately, he notices that a new job has come in suddenly and the website is not providing any notification regarding emails. He is checking his email every day regarding the job he applied for, but this whole activity is very frustrating as well as time-consuming. This is certainly not the kind one wants to wake up to.

Here comes the reason for web scraping now where the technology world offers certain different ways to satisfy the surfer. He does not need to check the website for jobs every day now, he can automate his job search using python in all the parts where he has searched before. Web scraping automation is not only the solution for speeding up the process of data collection but once the surfer writes code, he is able to get all the information he might want from all over the internet.

However, when we try to fetch this same information manually, for example looking at daily newspapers for jobs makes it very time-consuming for a person. Even without automated web scraping, a user will spend most of his time exploring, scrolling, and finding data where he will require huge amounts of data on the internet to go through. Hence, web scraping manually is also very time-consuming and an average option when one saves effort and has productivity.

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Challenges for Web scraping

Over the years we see that the internet has grown greatly over a number of sources. We are now able to combine so many independent technologies together, including their styles and data. But we also face some challenges while working with web scraping.

Here is a list of a few challenges one might face while scraping the web:

Accessing Bot:

The most important thing one needs to understand before scraping is if he is allowed to do it or not. There are cases under robots.txt where one needs to seek permission for web scraping by explaining the need and purpose of doing it. If there is a disagreement, the user can still switch to an alternative website that might have similar data or information available.

Web Page Structures:

As we are aware that most web pages are dependent on HTML. However, a lot of web designers might have their way of designing the structure of their pages which makes this field completely divergent as there is no set of rules to fix the web structure. There has to be a proper scraper that will scrape data in case the user needs to extract it from different websites. Especially, when the websites regularly update their data for improving the experience of the user or even for adding upgraded features leads to changes in web page structures.

IP BLocking:

This is a very common method for stopping scrapers from accessing data on the internet. This generally takes place when a web page detects requests which are high in number. This leads to either totally banning the IP or restricting the access which will in turn break down the process of scraping. A few IP services for a proxy such as Luminati are essentially integrated with automated web scraping which helps in saving people from any kind of blocking.


CAPTCHA stands for Completely Automated Public Turing test to tell Computers and Humans Apart. This term is useful in separating users who intend to scrape tools. This is done by designing images that are very easy to identify by humans, however web scrapers fail to detect the right images in the process and get caught. Although there are technologies that may overcome the CAPTCHA identification process, there still lies a few CAPTCHA solvers also in the form of bots.

Honeypot Traps:

This is actually a form of the trap that is placed on the website for trapping web scrapers. This can be in the form of links that might not be visible to humans but to scrapers. In case a scraper falls into this set trap, it gets blocked as the website catches the IP address.

Slow Loading Speed:

There are websites that do not respond fast or sometimes even do not load on receiving the access requests. In that case, the user has to wait for the website to load the required web page till the website recovers. However, scraping might break up as the scraper won’t understand how to deal with this kind of emergency at that particular time.

There will definitely be a number more challenges for web scraping if we predict this in the future. However, there is a fact when it comes to web scraping which is: that the more you treat the websites nicely, the nicer they are to you.

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In this article, we have understood the term web scraping along with the uses of web scraping. This process is not legal as it is, so the article will help you in understanding how to treat the websites better before trying to extract data from them. We have also discussed the reasons why people feel the need to do web scraping along with the challenges that come with it.

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As a content writer at HKR trainings, I deliver content on various technologies. I hold my graduation degree in Information technology. I am passionate about helping people understand technology-related content through my easily digestible content. My writings include Data Science, Machine Learning, Artificial Intelligence, Python, Salesforce, Servicenow and etc.

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