Today we are going to see how we can scrape Most Active Stocks data using Python and BeautifulSoup in a simple and elegant manner.
The aim of this article is to get you started on a real-world problem solving while keeping it super simple so you get familiar and get practical results as fast as possible.
So the first thing we need is to make sure we have Python 3 installed. If not, you can just get Python 3 and get it installed before you proceed.
Then you can install beautiful soup with:
We will also need the libraries requests, lxml and soupsieve to fetch data, break it down to XML, and to use CSS selectors. Install them using...
Once installed open an editor and type in...
Now let's go to the Yahoo Most Actice Stocks page and inspect the data we can get.
This is how it looks:
Back to our code now... let's try and get this data by pretending we are a browser like this...
Save this as yahoo_stocks_bs.py.
If you run it...
You will see the whole HTML page
Now, let's use CSS selectors to get to the data we want... To do that let's go back to Chrome and open the inspect tool.
We notice that all the individual rows of data are contained in a with the class 'simpTblRow'. We can get BeautifulSoup to select that data like this.
This prints all the content in each of the rows.
We now can pick out classes inside these rows that contain the data we want. The symbol is in the element with the attribute aria-label with the value Symbol..
If you run it it will print out all the symbols...
Bingo!! we got the symbols...
Now with the same process, we get the other data like Name, price, change, change percentage, Market Cap, Volume, etc...
When we run it it will print out every detail we want like this...
We even added a separator to show where each symbol data ends. You can now pass this data into an array or save it to CSV and do whatever you want.
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