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#!/usr/bin/python3
import sys
import pandas as pd
import numpy as np
import os
import sqlite3
# infile = 'gb.db'
infile = sys.argv[1]
con = sqlite3.connect(infile)
#dIn=pd.read_sql("Select * from 'GradesTable' where GroupName='student'", con)
dIn=pd.read_sql("Select * from 'GradesTable'", con)
dOut = dIn.copy()
# replacing user names in accordance with BlackBoard
dOut['UserName'] = dOut['UserName'].str.replace('@.*$', '', regex=True)
dOut.rename(columns={'UserName':'Username'}, inplace=True)
# exclude inforows
dOut = dOut.loc[ dOut['GroupName'].isin(['student']) ]
# remove unneeded info cols
infoCol=['FirstName', 'LastName', 'GroupName', 'UserHiddenColums', 'UserHiddenGroups', 'UserHiddenGradeCategories', 'SectionNum', 'IdNum']
dOut = dOut.drop(infoCol, axis=1)
# drop non gradable columns
cCat = (dIn['UserName'] == '_Col_Category_')
colToDrop = []
for c in dOut.columns:
if c == 'Username':
continue
category = dIn[cCat][c][0]
if category not in ['HomeWork', 'MidTerm', 'FinalExam', 'weighted_column']:
colToDrop.append(c)
dOut = dOut.drop(colToDrop, axis=1)
dOut.to_csv('BlackBoard.csv', index=False)
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