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#!/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)
# hand tuned fixes
d["UserName"].replace(
"phanng@hotmail.com@tj.va$", "kphan@wm.edu", regex=True, inplace=True
)
d["UserName"].replace(
"chipkd2001@gmail.com$", "ckdangerio@wm.edu", regex=True, inplace=True
)
d["UserName"].replace(
"eliasarivera@live.com@schs.va$", "earivera@wm.edu", regex=True, inplace=True
)
d.to_csv("WebAssign.csv", index=False)
# 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()
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