Semalt Expert – Beginner's Guide To Web Scrapping In Python
Web scraping is referred to as a software technique that is used to extract information from various websites. The primary focus of the method is to transform the unstructured data (HTML format) into structured data (spreadsheet or database). There are various ways of using web scrapping, but the common and simple method is by using Python. This is because Python is rich in ecosystem as it has a "BeautifulSoup library" which helps in the task of extracting information.
Over the years, there has been a great increase in the demand for web scrapping as it has proven to be more efficient to many. There are other several ways in which a person can be able to extract web information such as the use of APIs in websites like Twitter, Google and Facebook but this is not a sure method as there are websites which do not provide IPS.
Libraries required for web scrapping
Python is one of the most preferred sources in scrapper web as it allows a person to be able to get many libraries which can perform one function and it is also intuitive and easy to manage. The two most commonly used types of Python module in scrapping data include Urllib2 and BeautifulSoup. Urllib2 is a Python module that can be used to fetch URLs. On the other hand, BeautifulSoup is a tool that is used to pull information such as tables and graphs from web pages.
Scrapping a web page using BeautifulSoup
BeautifulSoup is one of the most important scraper web tools. In order to be able to scrap a web page using BeautifulSoup, there are various steps which one should follow. They include:
1. Import the necessary libraries – in this, one is required to import the libraries that are required in order to get the information that they need
2. Use function "prettify" to look at nested structure of HTML page – this is an essential step as it helps one to know the tags that are available
3. Work with HTML tag- some of these tags include the soup tag
4. Find the right table- finding the right table is important as one will be able to get the correct data.
5. Extract the information to Data Frame- this is the final step and in this, one is able to get the results that they desire.
In a similar way, BeautifulSoup can also be used to perform other various types of web scrapping depending on the preferences of a person.
There are those who think that they can use regular expression instead of scrapper web such as BeautifulSoup and get similar results. This is not possible because there are many differences between BeautifulSoup and regular expressions and their end results are also very different. For example, BeautifulSoup codes tend to be more robust than those written with regular expressions.
Therefore, using web scrapping is a very efficient method as one can be able to get the correct results