#!/usr/bin/python3

import sys
import pandas as pd
import numpy as np
import os

# infile = 'wa.csv'
infile = sys.argv[1]

f = open(infile)
l= f.readlines()
h= l[4]
maxPossible=l[6]
f.close()

# clean up of headers
h=h.strip()
h = h.replace('"', '')
headers = h.split(',')
headers[0]='FullName'
headers[1]='UserName'
headers[2]='SID'
headers[3]='TotalPcnt'
headers[4]='TotalScore'

d = pd.read_csv(infile, skiprows=[0,1,2,3,4,5,7,8], header=None, names=headers)
d.loc[0, 'FullName']='MaxScore'
d.loc[0, 'UserName']='MaxScore'

# cleanup
c = d.columns
c=c.drop(['FullName', 'UserName', 'SID'])
index = d[c] == 'ND'
d[index] = np.nan
index = d[c] == 'NS'
d[index] = np.nan
d['UserName'].replace('@wm$', '', regex=True, inplace=True)
d['UserName'].replace('@email.wm.edu$', '@wm.edu', regex=True, inplace=True)

d.to_csv('WebAssign.csv')

# now import to sqlite3

os.popen('rm -f WebAssign.db')
p = os.popen('printf ".mode csv\n.import \"WebAssign.csv\" export_table\n.q" | sqlite3 WebAssign.db')
p.close()