new_contents: #
  # htmlTableParser.py
  #
  # Example of parsing a simple HTML table into a list of rows, and optionally into a little database
  #
  # Copyright 2019, Paul McGuire
  #
  
  import pyparsing as pp
  import urllib.request
  
  
  # define basic HTML tags, and compose into a Table
  table, table_end = pp.makeHTMLTags('table')
  thead, thead_end = pp.makeHTMLTags('thead')
  tbody, tbody_end = pp.makeHTMLTags('tbody')
  tr, tr_end = pp.makeHTMLTags('tr')
  th, th_end = pp.makeHTMLTags('th')
  td, td_end = pp.makeHTMLTags('td')
  a, a_end = pp.makeHTMLTags('a')
  
  # method to strip HTML tags from a string - will be used to clean up content of table cells
  strip_html = (pp.anyOpenTag | pp.anyCloseTag).suppress().transformString
  
  # expression for parsing <a href="url">text</a> links, returning a (text, url) tuple
  link = pp.Group(a + pp.SkipTo(a_end)('text') + a_end.suppress())
  link.addParseAction(lambda t: (t[0].text, t[0].href))
  
  # method to create table rows of header and data tags
  def table_row(start_tag, end_tag):
      body = pp.SkipTo(end_tag)
      body.addParseAction(pp.tokenMap(str.strip),
                          pp.tokenMap(strip_html))
      row = pp.Group(tr.suppress()
                     + pp.ZeroOrMore(start_tag.suppress()
                                     + body
                                     + end_tag.suppress())
                     + tr_end.suppress())
      return row
  
  th_row = table_row(th, th_end)
  td_row = table_row(td, td_end)
  
  # define expression for overall table - may vary slightly for different pages
  html_table = table + tbody + pp.Optional(th_row('headers')) + pp.ZeroOrMore(td_row)('rows') + tbody_end + table_end
  
  
  # read in a web page containing an interesting HTML table
  with urllib.request.urlopen("https://en.wikipedia.org/wiki/List_of_tz_database_time_zones") as page:
      page_html = page.read().decode()
  
  tz_table = html_table.searchString(page_html)[0]
  
  # convert rows to dicts
  rows = [dict(zip(tz_table.headers, row)) for row in tz_table.rows]
  
  # make a dict keyed by TZ database name
  tz_db = {row['TZ database name']: row for row in rows}
  
  from pprint import pprint
  pprint(tz_db['America/Chicago'])
  
subject: Add example showing scraping/parsing of an HTML table into a Python dict