Measure DCU's contributions to Ireland's score on open.kattis.com

kattis_dcu.py

#!/usr/bin/python3

# adapted from code at https://github.com/iandioch/ceres/

import json
from urllib.request import urlopen, Request
from bs4 import BeautifulSoup

def is_dcu(c):
    return c == 'Dublin City University'

def load_page(url):
    q = Request(url)
    q.add_header('User-Agent', 'Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.11 (KHTML, like Gecko) Firefox')
    q.add_header('Accept', 'text/html,application/xhtml+xml,applicationxml;q=0.9,*/*;q=0.8')
    q.add_header('Accept-Encoding', 'none')
    q.add_header('Accept-Language', 'en-IE,en,en-US')
    q.add_header('Connection', 'keep-alive')
    return urlopen(q).read()

def get_user_data(page):
    soup = BeautifulSoup(page, 'html.parser')
    data = {}
    table = soup.find('table')
    rows = table.find_all('tr')
    data['global_rank'] = number_to_position(int(rows[1].find_all('td')[0].string))
    data['score'] = (rows[1].find_all('td')[1].string)
    return data

def get_rank_data(page):
    soup = BeautifulSoup(page, 'html.parser')
    tables = soup.find_all('table')
    score_table = tables[0]
    ireland_tot = float(score_table.find_all('tr')[1].find_all('td')[1].string)
    individual_table = tables[2]
    rows = individual_table.find_all('tr')
    data = []
    for row in rows[1:]:
        parts = row.find_all('td')
        print(parts)
        pos = int(parts[0].string)
        name = parts[1].find('a').string
        college = None
        college_link = parts[2].find('a')
        if college_link is not None:
            college = college_link['title']
        score = float(parts[3].string)
        data.append((name, pos, college, score))
    return ireland_tot, data

def mult(i):
    return (0.8)**(i)

if __name__ == '__main__':
    ireland_total, irish_data = get_rank_data(load_page('https://open.kattis.com/countries/IRL'))
    dcu_data = [(n, p, c, s) for n, p, c, s in irish_data if is_dcu(c)]
    dcu_tot = 0
    print('Rank\tScore\t% Added\t# Added\tCumulative Tot\tName')
    for n, p, c, s in dcu_data:
        m = 0.2*mult(p-1)
        d = m*s
        dcu_tot += d
        print('#{}\t{}\t{:4.1f}%\t{:.2f}\t({:6.2f})\t{}'.format(p, s, 100*m, d, dcu_tot, n))
    print('DCU Total:\t{:.2f}'.format(dcu_tot))
    print('Ireland Total:\t{:.2f}'.format(ireland_total))
    print('DCU Percent:\t{:.4f}'.format(100*dcu_tot/ireland_total))