![]() Output: Step 3: With the help of the prettify() function, make the indentation proper #make the indentation proper #to convert Link_text into a BeautifulSoup Object Import BeautifulSoup library from bs4 #import BautifulSoup library to pull data out of HTML and XML files Output: Step 2: In order to fetch useful information, convert Link_text (which is of string data type) into a BeautifulSoup object. Step 1: Fetch the web page and convert the HTML page into text with the help of the Python request library #import the python request library to query a website Exciting, right? Let us move ahead and get our hands dirty. We can fetch the List of Billionaires even after it gets updated for the year 2019 with the help of the same Python web scraping program. We will be scraping the Wikipedia page to fetch the List of Indian Billionaires published by Forbes in the year 2018. ![]() In this demonstration, we will be walking through our first Python web scraping project. Enroll in our Python course in Bangalore and become a Python Expert.ĭemo: A Step-by-step Guide on Python Web Scraping a Wikipedia Page Python is one of the most demanding skills right now in the market. This is why, in order to perform ethical web scraping, web scrapers need to follow some rules. Let us discuss them before scraping the web. Some of the legal cases that found web scraping to be on the wrong side of the law: Let us take a look at some of the cases where web scrapers broke the rule and try to learn from them. For example, web scraping non-public data, which is not accessible to everyone on the web, can be unethical, and also it can be an invitation to legal trouble. ![]() But, at times, it may cause legal issues, just the way any tool or technique in the world can be used for good as well as for bad. Web scraping Python services that extract publicly available data is legal. Not all web scraping acts are considered legal. The answer to it can’t be summed up in one word. Well, this is one of the most common questions that arise when it comes to web scraping (also known as data scraping). With the help of web scraping, businesses can grow their lead generation by gathering contact details of businesses or individuals. Web scraping can be used in order to build brand intelligence and monitor how customers feel about a product or a service. Web scraping Python can help study the service or product pricing of the competitors to stay ahead in the market. Market Researchīefore launching a product or service, companies can study the market in advance with the help of web scraping. Web scraping Python can fulfill this requirement. Data Scienceįor learning Data Science, we need large amounts of data. Let us discuss for what business scenarios web scraping can be used. But, how do we collect data in order to make use of it? Some of the industrial applications of web scraping: We all agree to the fact that data has become a commodity in the 21 st century, data-driven technologies have experienced a significant rise, and there is an abundance of data generated from different sources on a daily basis. ![]() Now that we are familiar with what web scraping in Python is, let us discuss why to perform web scraping using python or for what business scenarios Python web scraping is useful.
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