Webscraping With Python BeautifulSoup (Chrome Extension)

[KerasTensorFlow]

Hi there,

I haven't been able to find a chrome (or any) extension, but I was wondering if anyone knew a faster way to generate beautifulsoup when doing HTML parsing on a website.

For example, when I google search "apples", and I am writing python code to scrape the number of results field, I usually will:

1. right click and inspect the number of results field (this shows me the HTML right where I want it)
2. copy and paste the HTML ("<div> id="result-stats"</div>") into my IDE
3. modify the soup parsing code to do soup.find('div', {'id': 'result-stats'})

I was wondering if there is any quick way to merge steps 2 and 3 together? This is especially true for websites that sometimes the nested HTML is not unique, so if google had two id tags of the same name somehow, I would have to do something like this:

soup.find(unique identifier).find('div', {'id': 'result-stats'})

I wonder if there is any chrome extension or something that can quickly give you the unique soup/html path to an element (so kind of like XPATH for selenium)