Well, the last thing we need to check for is the returned tag, you may type incorrect tag or try to scrape a tag that is not found on the scraped page, and this will return None object, so you need to check for None object. This exception is URLError, so our code will be like this: from urllib.request import urlopen We need to handle this kind of exception also.
Great, what if the server is down or you typed the domain incorrectly? Handling URL exceptions Res = BeautifulSoup(html.read(),"html5lib") It could be 404 if the page is not found or 500 if there is an internal server error, so we need to avoid script crashing by using exception handling like this: from urllib.request import urlopen Handling HTTP exceptionsįor any reason, urlopen may return an error. That means if you need to extract any HTML element, you just need to know the surrounding tags to get it as we will see later. The returned HTML is transformed into a Beautiful Soup object which has a hieratical structure. We use the urlopen library to connect to the web page we want then we read the returned HTML using the html.read() method. Take a look at this simple example we will extract the page title using Beautiful Soup: from urllib.request import urlopen
#Webscraper test how to#
Now, let’s see how to use Beautiful Soup. If it runs without errors, that means Beautiful Soup is installed successfully. To check if it’s installed or not, open your editor and type the following: from bs4 import BeautifulSoup
#Webscraper test install#
I’ll install it using pip like this: $ pip install beautifulsoup4 To install Beautiful Soup, you can use pip, or you can install it from the source. I assume that you have some background in Python basics, so let’s install our first Python scraping library, which is Beautiful Soup. All this for FREE.Ī successful SEO tool like Moz that scraps and crawls the entire web and process the data for you so you can see people’s interest and how to compete with others in your field to be on the top. You can scrape your competitor’s web pages and analyze the data and see what kind of products your competitor’s clients are happy with their responses. It is not for creating search engines only. You might wonder why I should scrape the web and I have Google? Well, we don’t reinvent the wheel here. The scraped data can be passed to a library like NLTK for further processing to understand what the page is talking about. Web scraping generally is the process of extracting data from the web you can analyze the data and extract useful information.Īlso, you can store the scraped data in a database or any kind of tabular format such as CSV, XLS, etc., so you can access that information easily.
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