Scrape tables and text from public website

I need python code for extracting tables and text from specific web pages. I will provide the web pages in a zip file. For each html page, there will be multiple output files: - For each table within the html: o Identify name of table, use this as name of below two output files o Table_<name>.csv : the table extracted in csv format o Table_<name>.json : the table extracted in json format - All text in the html page to be extracted in json format without the tables such that o SectionName : is based on the name within table of contents o SectionText : is based on the text without the tables, page numbers within the section o Example : [ { “SectionName” : <name of section from table of contents>, “SectionText” : <text within the section without tables and page numbers>} ] o Output file name : [login to view URL] For the project to successfully complete, I would need following: - Python code that generates above output files. Code must use popular html parsing libraries like BeautifulSoup etc and should be independent of the specific html file being looked at. - All above outputs to be provided back as zip file Examples of html pages here : [login to view URL] [login to view URL] For the selected candidate, I will provide a larger set of these saved and zipped htmls which are to be used as inputs