How to remove content in nested tags with BeautifulSoup?

Question

How to remove content in nested tags with BeautifulSoup? These posts showed the reverse to retrieve the content in nested tags: How to get contents of nested ta

Answer 1

Here is my simple method, soup.body.clear() or soup.tag.clear()

let's say you want to clear the content in

and add a new pandas dataframe; later you can use this clear method to easily update your tables in an html file for your webpage instead of flask/django:

    import pandas as pd
    import bs4

I want to convert a 1.2million row .csv into a DataFrame, then into a HTML table, and then add it to my webpage's html syntax. Later I want to easily update the data whenever the csv gets updated by simply switching a variable

    bizcsv = read_csv("business.csv")
    dframe = pd.DataFrame(bizcsv)
    dfhtml = dframe.to_html #convert DataFrame to table, HTML format
    dfhtml_update = dfhtml_html.strip(', ')
    """use dfhtml_update later to update your table without the  tags,
    the  is easy for BS to select & clear!"""

    #A small function to unescape (< to <) the tags back into HTML format
    def unescape(s):
        s = s.replace("<", "<")
        s = s.replace(">", ">")
        # this has to be last:
        s = s.replace("&", "&")
        return s

    with open("page.html") as page:  #return to here when updating
        txt = page.read()
        soup = bs4.BeautifulSoup(txt, features="lxml")
        soup.body.append(dfhtml) #adds table to 
        with open("page.html", "w") as outf:
            outf.write(unescape(str(soup))) #writes to page.html

    """lets say you want to make seamless table updates to your 
    webpage instead of using flask or django x_x; return to with open function"""
    soup.table.clear()  #clears everything in 
    soup.table.append(dfhtml_update)
    with open("page.html", "w") as outf:
        outf.write(unescape(str(soup))) 

I'm a newbie, but after tons of searching I just combined a bunch of fundamental teachings from the documentation...Kind of bloated, but so is working with literally billions of cells of data. This works for me