def get_release_schedule()

in gcpdiag/queries/gke.py [0:0]

• 52 lines of code
• 18 McCabe index (conditional complexity)

def get_release_schedule() -> Dict:
  """Extract the release schedule for gke clusters

  Returns:
    A dictionary of release schedule.
  """
  page_url = 'https://cloud.google.com/kubernetes-engine/docs/release-schedule'
  release_data = {}
  # estimate first month of the quarter
  quarter_dates = {'Q1': '1', 'Q2': '4', 'Q3': '7', 'Q4': '10'}
  try:
    table = web.fetch_and_extract_table(page_url,
                                        tag='table',
                                        class_name='gke-release-schedule')

    # Function to parse a date string or return None for 'N/A'
    def parse_date(date_str) -> Optional[datetime.date]:
      p = r'(?P<year>\d{4})-(?:(?P<quarter>Q[1-4])|(?P<month>[0-9]{1,2}))(?:-(?P<day>[0-9]{1,2}))?'
      match = re.search(p, date_str)
      # Handle incomplete dates in 'YYYY-MM' form
      if match and match.group('month') and not match.group('day'):
        return datetime.date.fromisoformat(f'{date_str}-15')
      # Handle quarter year (for example, 2025-Q3) approximations that are updated when known.
      # https://cloud.google.com/kubernetes-engine/docs/release-schedule.md#fn6
      if match and match.group('quarter') and not match.group('day'):
        date_str = f"{match.group('year')}-{quarter_dates[match.group('quarter')]}-01"
        return datetime.date.fromisoformat(date_str)
      if match and match.group('year') and match.group('month') and match.group(
          'day'):
        return datetime.date.fromisoformat(date_str)
      # anything less like N/A return None
      return None

    def find_date_str_in_td(e):
      """recursively find a date string in a td"""
      if isinstance(e, str):
        return e
      if isinstance(e, bs4.element.Tag):
        return find_date_str_in_td(e.next)
      return None

    # Find all table rows within tbody
    rows = table.find('tbody').find_all('tr')

    # Iterate over each row and extract the data
    for row in rows:
      # Extract all the columns (td elements)
      cols = row.find_all('td')

      # Extract relevant data

      minor_version = cols[0].next.strip()
      rapid_avail = parse_date(find_date_str_in_td(cols[1].next))
      regular_avail = parse_date(find_date_str_in_td(cols[3].next))
      stable_avail = parse_date(find_date_str_in_td(cols[5].next))
      extended_avail = parse_date(find_date_str_in_td(cols[7].next))
      end_of_standard_support = parse_date(find_date_str_in_td(cols[9].next))

      # Add the extracted data into the dictionary in the desired format
      release_data[minor_version] = {
          'rapid_avail': rapid_avail,
          'regular_avail': regular_avail,
          'stable_avail': stable_avail,
          'extended_avail': extended_avail,
          'eol': end_of_standard_support,
      }
    return release_data
  except (
      requests.exceptions.RequestException,
      AttributeError,
      TypeError,
      ValueError,
      IndexError,
  ) as e:
    logging.error('Error in extracting gke release schedule: %s', e)
    return release_data