![]() ![]() For example, the following call to the method “findAll()” lets us search for all occurrences of a specific tag. The BeautifulSoup object is designed specifically to allow for easy searching of the HTML for the tags we want. The tag indicates a data (non-header) cellīecause we typically want to pull data from the cells of a table, web scraping sports data mostly boils down to searching for the tags and pulling the data from that cell. To appreciate the power of the BeautifulSoup object, we first need to understand a little bit about the structure of tables in HTML. It can be embarrassing to reveal your style. ![]() (For many non-computer scientists, showing code you write publicly is akin to reading your diary aloud. The first step in our code is creating the BeautifulSoup object the code to do so is shown below. For that, we’ll use the requests Python library. The first step, though, is to ask for a website to send the HTML over to you so that you can begin to work with it. The Python package called BeautifulSoup gives developers a way to efficiently search through the ‘soup’ of different tags in a page’s HTML to find the data you want. Basics of BeautifulSoup for Web Scraping Sports Data ![]() This is more friendly to the host server. For example, any time I request data from sports-reference inside of a loop, I include a line of code that forces my script to pause for one second in between requests. Generally speaking, don’t reproduce the data and claim it as your own and don’t use your scripts to send many, many requests to the server in a short period of time. For example, sports-reference explicitly prohibits writing web scraping sports data “ …in a manner that adversely impacts site performance or access“. Therefore, anything you see can be scraped.īefore turning to specifics and Python code showing how to do this with the BeautifulSoup package, we want to include a word of warning, While in general it is perfectly legal to pull data from a website for your own purposes, web scraping sports data can get into some gray territory. Anything that shows up on the screen can be found in the source code. Thus, web scraping sports data boils down to downloading the HTML, looking for the relevant table rows and features, and extracting the data. For example the ‘104 indicates that the visitor points column should have the entry “104”. That is, everything you see on the screen is delivered to your browser in HTML.įor example, the HTML code on the right contains most of the necessary information to render the first row of the table on the left. The browser’s job is to translate the source HTML code (together with something we don’t need to care about called ‘CSS’) into a visual medium. When you open a website, the server sends the raw HTML (shown on the right) to your browser. ![]()
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